*Article* **Study of Hybrid Modification with Humic Acids of Environmentally Safe Biodegradable Hydrogel Films Based on Hydroxypropyl Methylcellulose**

**Denis Miroshnichenko 1,\* , Katerina Lebedeva 2 , Anna Cherkashina 2 , Vladimir Lebedev 2 , Oleksandr Tsereniuk 3 and Natalia Krygina 3**

**Abstract:** The possibility of increasing the complexity of the operational properties of environmentally safe biodegradable polymer hydrogel materials based on hydroxypropyl methylcellulose due to modification by humic acids from lignite is considered. As a result of this research, environmentally safe hybrid hydrogel films with antibacterial properties were received. In the framework of physicochemical studies, it was determined by IR spectroscopy that hydroxypropyl methylcellulose modified with humic acids hybridmaterials are received by the mechanism of matrix synthesis, which is accompanied by hydroxypropyl methylcellulose crosslinking through multipoint interaction with the carboxyl group of humic acids. Regularities in terms of changes in water absorption, gelation time, and mold emergence time regarding the environmentally safe biodegradable polymer hydrogel materials based on hydroxypropyl methylcellulose depending on the humic acid content were revealed. It was established that the optimal humic acid content in environmentally safe biodegradable hydrogel films with bactericidal properties based on hydroxypropyl methylcellulose is 15% by mass. It was also established that the hybrid modification of hydroxypropyl methylcellulose with humic acids allows them to preserve their biodegradation properties while giving them antibacterial properties. The environmentally safe biodegradable hydrogel films with bactericidal properties based on hydroxypropyl methylcellulose and humic acids are superior in their operational characteristics to known similar biodegradable hydrogel films based on natural biopolymers.

**Keywords:** environmentally safe; biodegradable; hydrogel films; hydroxypropyl methylcellulose; bactericidal properties; humic acids; hybrid; modification


*4.4. Clustering and CH Selection*

Next, we discuss how to form appropriate clusters and select the optimal CH. The proposed clustering and CH selection algorithm is described in Algorithm 2. When the number of clusters is *K*, let N*k* be the set of nodes in cluster *k* ∈ {1, 2, ··· , *K*}. Without loss of generality, we denote *ik* as the CH in cluster *k*, where ∃*ik* ∈ N*k*, and *jk* as a sensor node in the cluster *k*, where ∀*jk* ∈ N*k* \ {*ik*}. The proposed algorithm is based on the well-known K-means clustering algorithm [45]. Thus, the initial *K* clusters are determined using the K-means algorithm, and the initial CH in each cluster is determined to be the node closest to the centroid of each cluster. Consequently, the initial cluster and CH are determined by only the distance among sensor nodes without considering the distance between the sensor node and the HAP. However, this distance directly affects the amount of energy harvested, so it is necessary to modify the basic process of the K-means algorithm to make it suitable for the proposed ENO scheme.

The proposed algorithm mainly consists of two parts, similarly to the K-means algorithm. Firstly, each node reselects the best cluster among the predetermined clusters. After calculating *Rik j* and *Rik* for each CH *ik*, node *j* selects the cluster that provides the highest *Rik j* among the clusters satisfying *Rik j* > *Rik* . This step is included so that SWIPT can be performed without decreasing the rate of the predetermined clusters. Thereafter, the best CH is reselected in each cluster. For all nodes in each cluster ∀*ik* ∈ {N*k*}, the rate of cluster *k*, *R*swipt *k* , is calculated using Equation (12). Then, the best CH, *i* ∗ *k* , is determined as

$$\begin{aligned} i\_k^\* &= \underset{i\_k}{\arg\max} \mathcal{R}\_k^{\text{swlpt}} \\ &= \underset{i\_k}{\arg\max} \min \left[ \min\_{j\_k \in \mathcal{N}\_k} \{ \min\_{l\_k}, \left\{ \mathcal{R}\_{l\_k j\_k}^{\text{swlpt}} \right\}, \mathcal{R}\_{l\_k}^{\text{swlpt}} \right] \end{aligned} \tag{20}$$

where *i* ∗ *k* can be found by exhaustive searching with a complexity of *O*(|N*k*|). This clustering and CH selection algorithm is repeated until all of the cluster sets and CHs are no longer changed. The computational complexity of this algorithm is given by *O*(*N*2) because it is based on k-means algorithm, which has a time complexity of *O*(*n*2) where *n* is the input data size [45].

**Algorithm 2:** Clustering and CH selection **Ensure:** N*k* is the set of nodes in cluster *k* ∈ {1, 2, ··· , *K*} *ik* is the CH in the cluster *k*, ∃*ik* ∈ N*k jk* is a sensor node in the cluster *k*, ∀*jk* ∈ N*k* \ {*ik*} 1: Initialize N*k* and *ik* ← K-means algorithm [45] 2: **repeat** 3: /\* Select the best cluster in the network \*/ 4: **for** *each node j* ∈ {N1 ∪···∪N*K*} **do** 5: **for** *each CH ik* **do** 6: Determine *Rik j* from Equation (3) 7: Determine *Rik* from Equation (5) 8: **end for** 9: **if** ∃*ik* ∈ {*ik*|*Rik j* > *Rik*} = ∅ **then** 10: *j*'s cluster ← arg*k* max{*Rik j*} for ∃*ik* ∈ {*ik*|*Rik j* > *Rik*} 11: **else** 12: *j*'s cluster ← arg*k* max{*Rik j*} for ∀*ik* 13: **end if** 14: **end for** 15: /\* Select the best CH in each cluster \*/ 16: **for** *each cluster k* **do** 17: **for** *each node ik* ∈ {N*k*} **do** 18: Calculate *R*swipt *k* from Equation (12) 19: **end for** 20: CH *i* ∗ *k* ← arg*ik* max{*R*swipt *k* } from Equation (20) 21: **end for** 22: **until** ∀N*k and* ∀*ik are no longer changed*


**Abstract**

Geothermal energy technology has successfully provided a means of generating stable base load electricity for many years. However, implementation has been spatially limited to rare high quality traditional resources possessing the combination of a shallow high heat flow anomaly and an aquifer with sufficient permeability and fluid recharge. Enhanced Geother‐ mal Systems (EGS) technology has been proposed as a potential solution to enable addition‐ al energy production from the much more common non-traditional resources. To advance this technology development, a heated true triaxial load cell with a high pressure fluid injec‐ tion system has been developed to simulate an EGS system from stimulation to production. This apparatus is capable of loading a 30x30x30 cm3 rock sample with independent princi‐ pal stresses up to 13 MPa while simultaneously providing heating up to 180 ºC. Multiple ori‐ entated boreholes of 5 to 10 mm diameter may be drilled into the sample while at reservoir conditions. This allows for simulation of borehole damage as well as injector-producer schemes. Dual 70 MPa syringe pumps set to flow rates between 10 nL/min and 60 mL/min injecting into a partially cased borehole allow for fully contained fracturing treatments. A six sensor acoustic emission (AE) array is used for geometric fracture location estimation during intercept borehole drilling operations. Hydraulic pressure sensors and a thermocouple array allow for additional monitoring and data collection as relevant to computer model valida‐ tion as well as field test comparisons. The results of the scale model hydraulic fracturing tests demonstrate the functionality of the equipment while also providing some novel data on the propagation and flow characteristics of hydraulic fractures. Fully characterized test sample materials used in the scale model tests include generic cement grout, custom high

© 2013 Frash et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

performance concrete, granite, and acrylic. Fracturing fluids used include water, brine, and Valvoline® DuraBlend® SAE 80W90 oil.

**Keywords:** Enhanced Geothermal Systems (EGS), true triaxial device, hydraulic fracturing, scale model testing, acoustic emissions


*3.3. Independent Variables*

Based on the motivation in the literature review section, we use three dimensions, further splitting them into six independent variables portraying corporate governance characteristics of a firm (see Table 1). The independent variables were calculated mostly based on their formulas in previous studies.

For capturing the ownership concentration, variable MAJORITY is used, which indicates in a binary form, whether there is a majority owner (i.e., having more than 50% of the shares) present. According to the Estonian regulation, an owner having more than 50% has the power to decide upon most of the actions in a firm, thus the usage of that threshold is well-motivated with legislation. Another variable for the concentration dimension is managerial ownership. To portray managerial ownership, the variable BOARDOWNER is used, which is a ratio of shares owned by the board members to the total shares. Thus, this variable directly portrays the overlap between the two levels of corporate governance (i.e., owners and board members). It must be emphasized, that the Estonian SMEs are subject to a two-level corporate governance system, in which the board is subordinate to owners directly, while the board members are legally responsible for all firm's activities.

For the demographic diversity dimension, the manager's age is portrayed with MANAGERAGE, which is calculated as the biological age of the oldest board member. Although in previous studies the mean age of board members has been used as well, it does not suit herewith, as we intend to capture the life experience available on the board, not the average experience. Furthermore, as a large proportion of firms have single-person boards, the usage of mean age would not be a suitable option. The context of gender is captured with the presence of a woman on the board (reflected with a binary variable WOMAN obtaining 1 on that occasion and 0 otherwise). In studies focusing on larger firms, a gender proportion has been used, but that option is not suitable in the case of SMEs, of which the overwhelming majority have only one or two individuals on the board.

#### **Table 1.** Variables in the analysis.

Source: own elaboration. Note: for robustness tests, BINARYDELAY is recoded to account for mild and severe violators (see also Sections 3.2 and 3.4).

For the experience dimension, business ties are portrayed with the variable TIES, which reflects the number of board memberships in other firms the board members of the firms under question hold. Thus, this variable reflects the scope of ongoing business experience outside the firm under question. Managerial tenure is captured with the variable TENURE, which reflects the time in years the longest-serving board member has been on their position. TENURE could also be used as a ratio of the time the longest-serving board member has been on their position to the firm's age. Still, such a ratio would easily lead to overestimating firm-specific experience in the case of (very) young firms. Finally, the control variable reflecting board size is captured by BOARDSIZE, which reflects the number of board members in the firm.


**9. Special population**

### **9.1 Obesity**

Anticoagulant dosing of obese patients with PE remains to be an area that has not been well studied [71]. The bulk of the data comes from pharmacokinetic/ pharmacodynamic (PK/PD) studies and subgroup analyses of premarketing trials comparing obese patients to patients with normal body weight [29, 32, 71, 72]. Furthermore, warfarin appears to have the most robust data available in this population. Warfarin pharmacokinetics have been compared in various studies of obese patients with a BMI > 30 and 40 kg/m2 to normal body weight subjects. These studies found that obesity was associated with a greater delay and dosage to achieve a therapeutic INR. Data associated with the risk of bleeding, however, have been conflicting, indicating that obesity may or may not increase the risk [71]. While warfarin has the most robust data in this population, the usage of warfarin appears to be on the decline [71].

Dabigatran is a direct thrombin inhibitor that sets it apart from other DOACs. Subgroup analyses of Phase 3 trials for VTE (RE-LY) and atrial fibrillation (RECOVER) suggested no significant differences in the efficacy and safety outcomes of obese patients in comparison with those with lower body weights [29, 32]. In contrast, treatment failures have been documented in morbidly obese patients using standard doses. The authors reported that standard doses failed to achieve "therapeutic levels," suggesting a higher volume of distribution (Vd) and a higher clearance [27, 28].

The factor X inhibitors, rivaroxaban, apixaban, and edoxaban also have some data in obese populations. Rivaroxaban was evaluated in a small PK/PD study involving a heterogeneous group of subjects including those in the obese range (>120 kg). The half-life, Vd, and clearance declined slightly with increasing body weight. The authors felt the declines were not clinically relevant [30]. A separate PK/PD analysis using pooled data from the phase ll EINSTEIN DVT and ODIXa-DVT trials reported similar findings. These studies enrolled some patients with BMIs >35 kg/m2 and found clinical benefits comparable across all weight groups [36]. The authors of this analysis also concluded that standard doses should be sufficient to treat obese patients; however, a review questioned whether the data were robust enough to draw that conclusion [36, 72].

In the apixaban's phase 1 PK/PD study, the pharmacokinetic data were somewhat different compared to those for rivaroxaban. The overall Vd was higher in subjects >120 kg or BMI > 30 kg/m2 than normal body weight subjects. The half-life declined almost proportionately to the increase in Vd (27% ↓ vs. 24% ↑ for half-life and Vd, respectively). Peak level and area under the plasma drug concentration-time curve (AUC) were also reduced in the higher body weight subjects. The authors concluded the differences were unlikely to be of clinical significance [47]. The phase 3 trials, ARISTOTLE and AMPLIFY, contained a significant proportion of patients with body weights >100 kg and BMIs above 30 kg/m2 . Subgroup analyses found no differences in efficacy; however, more bleeding episodes were reported in the ARISTOTLE trial. Whether the increase in hemorrhagic complications between these trials was due to age, renal clearance, or other patient-specific factors is unclear [48–50].

Edoxaban has less data than other DOACs. Phase 3 Hokusai-VTE enrolled a large group of patients >100 kg. There was no difference in efficacy and safety compared to groups with other weights [51].

A recent international retrospective study of LMWHs examined dosing in obesity regarding capped (<18,000 IU/d) and uncapped dosages (>18,000 IU/d). The data were obtained from the RIETE Registry, a large prospective case series of patients with VTE. LMWHs included enoxaparin, dalteparin, and tinzaparin. The authors reported that the results may be subject to selection bias despite attempts to control for potential confounders in multivariable analysis. Nevertheless, they found that after adjustment for multiple potential confounders, patients with obesity (>100 kg or BMI >30 kg/m2 ) who received capped doses were at a lower risk of having the composite outcome of VTE recurrences, major bleeding, or all-cause death at 15 and 90 days. Bleeding was also reduced with capped dosages [52].

A recent retrospective study of UFH for acute venous thromboembolism (VTE) compared three body mass index (BMI) cohorts: (i) non-obese (less than 30 kg/m2 ), (ii) obese (30 to 39.9 kg/m2 ), and (iii) morbid obesity (⩾40 kg/m2 ). The dosing employed was based on actual body weight. The median times to therapeutic aPTT were reported as 16.4, 16.6, and 17.1 h in each of the three cohorts [53].

Obese patients on warfarin may require a higher dose or more time to achieve a therapeutic INR. Bleeding risk may or may not be greater. Available data for DOACs other than dabigatran suggested usual doses may not negatively impact efficacy in obese patients. Apixaban studies reported conflicting results on bleeding risk. However, there are probably insufficient data for DOACs to suggest that usual doses would be adequate in the subgroup of morbidly obese patients. Obese patients with capped doses of LMWHs may have better efficacy and safety outcomes. Capped dosages are conditionally recommended in the 2018 American Society of Hematology guidelines [54].

### **9.2 Renal dysfunction**

Anticoagulants have been evaluated in CKD and ESKD patients in various PK/PD and clinical efficacy trials [55]. The PK/PD of warfarin in CKD and ESKD is not completely understood [55, 56]. Official dosing guidelines do not recommend an alteration of dose [55]. Warfarin is extensively metabolized by the cytochrome P450 type 2C9 (CYP2C9) enzyme [73]. Although not removed by dialysis, there are no data evaluating whether this procedure alters its pharmacokinetics and pharmacodynamics [55]. One study comparing individuals with a GFR of 30–59 mL/min and healthy controls reported a shorter half-life and increased clearance. Other data showed that CKD, especially GFRs <30 mL/min per 1.73 m2 or ESKD, complicates warfarin therapy [58, 59]. These data reported that lower doses were required to maintain therapeutic INR with greater fluctuations in INR values and higher risks of major bleeding events for any given INR value. A recent meta-analysis of ESKD patients with atrial fibrillation found that warfarin had no benefit in reducing ischemic stroke incidence. The authors concluded that the drug appeared to be associated with a significantly higher risk of hemorrhagic stroke but no increased risk of other types of major bleeding. They also found no change in mortality [71, 74]. How all these data apply to other indications such as PE is unknown.

The various DOACS have also been evaluated in renal disease. A small study of dabigatran using reduced doses (150 mg daily for CKD and 50 mg daily for ESKD) examined the effect of CKD and ESKD on pharmacokinetic parameters. Subjects with a creatinine clearance <30 mL/min demonstrated a 6.5-time increase in the AUC with a doubling of the half-life compared to normal controls [75].

Rivaroxaban has somewhat conflicting data in CKD and ESKD. In a phase 3 trial subgroup analysis of the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF), the authors reported that reduced renal function (creatinine clearances <80 mL/min) had no impact on rivaroxaban's effectiveness and safety [76]. In contrast, a PK/PD study comparing dialysis patients to normal controls reported a 56% increase in AUC when 15 mg doses

were administered after dialysis [77]. The AUC was decreased by only 5% when administered pre-dialysis suggesting dialysis is ineffective in clearing the drug [77]. Another PK/PD study comparing three ranges of renal insufficiency to normal controls reported AUCs of 1.4-, 1.5-, and 1.6-fold higher in cases of creatinine clearance concentrations of 50–80, 30–50, and < 30 mL/min, respectively [78].

Pharmacokinetic data for apixaban appear similar to those of rivaroxaban, except that the incremental upsurges in AUC are somewhat lower in magnitude. A small PK/PD study using a 5 mg dose in ESKD patients and normal controls found a 36% increase in AUC in the ESKD group compared to controls. The apixaban dose was administered pre-dialysis [79]. Another small PK/PD study used a single 10 mg dose and compared subjects with varying degrees of CKD to normal controls [8]. Compare to the controls, the AUCs increased by 16%, 29%, and 38% in the CKD cohorts with creatinine clearances of 50–80, 30–50, and < 30 mL/min, respectively. The mean half-life was only slightly increased in the total CKD population (17 h) compared to the controls (15 h) [79]. The overall results for both studies were not unexpected, as apixaban is metabolized more extensively and demonstrates less unchanged renal elimination than other DOACs [1]. Again, the drug appears to be poorly dialyzable [55].

Edoxaban was evaluated in a small PK/PD study comparing CKD subjects to normal controls. The data, available as an abstract only, showed that the mean AUCs increased by 32%, 74%, and 72% with creatinine clearances of 50–80, 30–50, and < 30 mL/min (not on dialysis), respectively [55]. The mean AUC for subjects on peritoneal dialysis was 93% [55]. Similar to other Factor Xa inhibitors, edoxaban is poorly cleared by hemodialysis [80].

Probably, the best data for LMWH come from a subgroup analysis of the ExTRACT TIMI 25 trial. This study compared a 1 mg/kg per day dose of enoxaparin to UFH in ST-elevation myocardial infarction (STEMI) patients with CrCLs less than 30 mL. There was no significant difference in mortality or recurrent MI (33 vs. 37.7%) and in bleeding risk (5.7 vs. 2.8%) for enoxaparin and UFH, respectively. Mortality increased for both drugs as renal function declined [81].

UFH is rapidly eliminated by the reticular endothelial system and, to a lesser extent, the kidney. However, the degree to which the RES functions in this role varies from person to person. Nevertheless, lower doses in VTE treatment are recommended to reduce bleeding risk. An advantage for UFH over enoxaparin is the ability to reverse the former easier with protamine [11, 82].

All DOACs increase AUC with the magnitude inversely proportional to renal function. These drugs may be the anticoagulants of choice for stages 1, 2, and 3 CKD [83]. Some sources recommend apixaban as an alternative to warfarin in selected patients with ESKD [55]. Warfarin, although predominately metabolized in the liver, may require a lower dose to reach a therapeutic INR. Historically, it is the oral anticoagulant of choice in ESKD [11, 82]. However, how does warfarin's potential lack of benefit in ESKD patients with AF apply to PE? Are LMWHs better than UFH? Both were associated with similar mortality increases in STEMI patients with declining kidney function. Should these data also apply to renal failure patients and PE?

### **9.3 Liver dysfunction**

Patients with cirrhosis typically have elevated INR and aPTT. As a result, there have been misconceptions that these patients are "autoanticoagulated." However, patients with liver disease may have a substantially increased risk of VTE (RR 1.74 (95% CI, 1.54–1.95) for liver cirrhosis and 1.87 (95% CI, 1.73–2.03) for noncirrhotic liver disease) [83]. A meta-analysis in patients with the liver disease found

**Table 3.**

*FDA recommendations of DOACs in liver dysfunction.*

the incidence of PE from nine studies to be 0.28% (95% CI 0.13–0.49%) and the prevalence of PE from two studies to be 0.36% (95% CI 0.13–0.7%) [84].

Determining the ideal anticoagulant to use after a PE in a patient with liver cirrhosis may be challenging. Warfarin can be safely used in patients with liver dysfunction. Elevations in baseline INR due to liver disease, however, may lead to unclear INR targets during warfarin therapy [85, 86]. LMWHs have a good safety profile with liver dysfunction; however, subcutaneous administration may limit compliance, and lower anti-Xa levels in liver dysfunction limit efficacy monitoring [87, 88]. Finally, there are a lack of data on using DOACs in patients with liver disease. Clinical trials with DOACs excluded patients with liver disease as most DOACs are predominantly cleared hepatically (apixaban 75%, rivaroxaban 65%, edoxaban 50%, and dabigatran 20%) [73, 89]. Therefore, dosing recommendations are derived from pharmacokinetic studies (**Table 3**).

Regardless of which anticoagulant is chosen, the risk of bleeding should be thoroughly evaluated. In patients with liver disease, bleeding can be due to varices, portal hypertensive gastropathy, peptic ulcer disease, and arteriovenous malformations. A small, 45-patient cohort study, comparing DOACs to warfarin/LMWH found no difference in thrombotic events. Still, there were significantly fewer major bleeding episodes in the DOAC group (1 patient [4%] vs. 5 patients [28%], *p* = 0.03) [90].

### **9.4 Cancer patients**

Cancer patients have a five- to sevenfold increased risk for VTE within the first year of diagnosis [91]. Additionally, VTE is considered an independent predictor of mortality in these patients [92, 93]. The pathophysiological and epidemiological association between PE and cancer is well established. For decades, LMWHs were considered a first-line therapy for cancer-associated PEs, as knowledge of the efficacy and safety of DOACs in cancer patients was lacking [77, 94, 95]. Since then, four large randomized control trials have been published comparing DOACs with LMWH that have highlighted the utilization of most DOACs for the treatment of PEs [77, 81, 96, 97].

The Hokusai VTE Cancer trial randomized 1050 cancer patients with acute VTE to either edoxaban, an oral direct factor Xa inhibitor, or dalteparin, an LMWH. The trial found that edoxaban was non-inferior to dalteparin for the primary outcome of recurrent VTE or major bleeding during a follow-up period of 12 months (95% confidence interval 0.70 to 1.36; *p* = 0.006) [98]. There was a lower rate of VTE, however, nonsignificant risk difference of −3.4 (−7.0 to 0.2), but the major bleeding rate was significantly higher (risk difference of 2.9 (0.1 to 5.6)) [98]. A nonsignificant lower VTE rate was seen, but the major bleeding rate was significantly higher in the edoxaban group. Major bleeding events were frequently observed in the subgroup with upper gastrointestinal tract neoplasms [98].

SELECT-D randomized 406 patients with cancer and acute VTE to oral rivaroxaban, a factor, or dalteparin for a treatment duration of 6 months [99]. SELECT-D was a 6-month open-label, pilot, randomized control study that compared rivaroxaban 15 mg BID for 3 weeks then 20 mg once daily to dalteparin (200 IU/kg once daily for 1 month, then 150 IU/kg once daily) in patients with VTE and solid or hematologic cancers [99]. The trial found that the VTE recurrence rate was 4% with rivaroxaban and 11% with dalteparin (HR 0.43, 95% CI 0.19 to 0.99) [99]. Major bleeding occurred in 4% with dalteparin and 6% with rivaroxaban (HR 1.83, 95% CI 0.68 to 4.96) and clinically relevant, nonmajor bleeding occurred in 4% with dalteparin and 13% with rivaroxaban (HR 3.76, 95% 1.63 to 8.69) [99].

CARAVAGGIO was an open-label, non-inferior study that randomized 1170 patients to apixaban (10 mg twice daily for 7 days, then 5 mg twice daily) or dalteparin (200 IU/kg once daily for 1 month, then 150 IU/kg once daily) for 6 months of treatment [100]. The trial resulted in a VTE recurrence rate of 5.6% with apixaban and 7.9% with dalteparin (risk difference − 2.3%; HR 0.63, 95% CI 0.37 to 1.07, *p* < 0.001) [100]. Additionally, major bleeding occurred in 3.8% in the apixaban group versus 4% in the dalteparin group (risk difference − 0.2%; HR 0.82, 95% CI 0.4 to 1.69, *p* = 0.60) [100].

Given that these oral agents have shown efficacy and provide a more convenient medication dosage form, we have already begun to see a shift in the way PEs are treated in cancer patients [77, 81, 96, 97]. However, since many of these studies have excluded patients with GI tumors or a history of GI bleeding, it is still recommended to continue using LMWH in these patients due to the higher GI bleeding risk seen with DOACs [77, 81, 96, 97]. If a DOAC is to be utilized, the choice of which oral anticoagulant to be used in a cancer patient should be made on an individual basis with considerations of drug interactions with chemotherapy agents and the type of cancer.

### **9.5 Pregnancy**

UFH and LMWH remain the only currently available choices for the safe management of VTE including PE during pregnancy and puerperium. UFH provides the least exposure to the fetus and risk to the mother, since it does not cross the placenta, is not distributed into breast milk, and the dose is easily titrated [101]. LMWHs have a similar safety profile as UFH for the fetus since they also do not cross the placenta. Concerns about distribution into breast milk have been raised [101, 102]. Most studies have not demonstrated that the LMWH levels in breast milk are high enough to cause coagulopathy when using standard prophylaxis doses. Further studies are needed for a complete safety profile.

The ability to easily monitor aPPT levels for UFH and anti-Xa levels for LMWHs provides clinicians with the ability to maintain therapeutic concentrations throughout pregnancy. Therapeutic-level monitoring provides safety and efficacy for both the fetus and the mother, since changes in the drug volume of distribution and clearance progressively increase throughout pregnancy [23, 101, 103–105]. Additionally, UFH and LMWH have short half-lives, allowing for anticoagulation to be maintained within 24 h of delivery and permitting the safe use of neuroaxial anesthesia if needed [102, 106]. Restarting LMWH within 6 h postdelivery in patients without bleeding concerns has been shown to be safe. Anticoagulation should be maintained during puerperium [101]. Thromboprophylaxis for future pregnancies with UFH or LMWH is recommended for women at risk [107, 108].

The safety profile and pharmacokinetics of DOACs currently do not favor their use during pregnancy or puerperium, since they cross the placenta and distribute into breast milk [101, 109]. The use of DOACs may be considered in women who are not or are no longer breastfeeding. The inability to readily monitor DOAC levels limits the clinician's ability to maintain therapeutic levels throughout pregnancy and puerperium due to the pharmacokinetic changes listed above. Maintaining a safe and therapeutic efficacious anticoagulation regimen up to and through the time of delivery requires a multidisciplinary effort and needs to be closely coordinated [101, 102, 106].

### **9.6 Elderly**

The risk of thromboembolic disease, including PE, increases with age [110–112]. The trauma to the vascular endothelium caused by a thromboembolic event places the patient at a higher risk of recurrence, requiring prolonged anticoagulation [110, 113]. Comorbidities accompanying aging, especially cardiovascular and pulmonary disease, add to the complexity of treatment of thromboembolic disease [114]. The increased risk for bleeding further complicates the safe management of an acute venous thromboembolic event, and prolonged anticoagulation is required to prevent future events [4].

PE in elderly patients may not present with the typical symptoms seen in younger patients, making early diagnosis more challenging in this population. Several studies have found syncope to be the most frequent presenting symptom in elderly patients, versus pleuritic chest pain in a younger population [115–117]. Early pharmacotherapy intervention is critical to prevent further thrombus formation, regardless of the patient's age [110].

Recommendations for initial treatment for PE in a stable patient regardless of the prognosis include DOACs (apixaban or rivaroxaban) or initial LMWH, followed with dabigatran or edoxaban. LMWH or UFH and warfarin may be preferred in patients with reduced renal function (CrCL <30 mL/min) [118].

Stable patients with a good prognosis may be managed in an outpatient setting. The current recommendations for stable patients with a poor prognosis require hospitalization [118]. A thorough medication history is important prior to starting a DOAC due to the potential drug–drug interactions seen with this class of anticoagulants. P-glycoprotein inhibitors or CYP3A4 inhibitors or inducers should be avoided, since they can alter the plasma of DOACs [118]. The unstable patient requires hospitalization and may be a candidate for thrombolytic therapy, preferably by catheter-directed thrombolysis [118].

### **9.7 COVID-19 patients**

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from Wuhan, Hubei province, China, in December 2019 has adversely impacted the world. Among the several complications related to SARS-CoV-2 is VTE [119], a systematic review of 3487 COVID-19 patients from 30 studies demonstrated VTE incidence to be 26%, 12% for PE with or without DVT, and 14% for DVT alone.

The etiology of PE in COVID-19 is secondary to the well-known VTE risk factors, with indirect aspects of the severity of illness and direct effects of SARS-CoV2 viral infection. These patients are at VTE risk due to the recurrent use of intravascular access devices, sedation, and vasopressors, within the intensive care unit (ICU) setting. These factors promote stasis. Respiratory failure, hypoxia, comorbidities, multi-organ failure, obesity, and prolonged immobility are other elements. Additional confounding factors include a history of VTE and or neoplasm, sepsis, surgery, trauma, or stroke [120, 121].

COVID-19 is associated with a profound early response of proinflammatory cytokines. This may result in a cytokine storm, increased risk of vascular hyperpermeability, multi-organ failure, and death [122, 123]. While thrombin's primary role is to accelerate clot formation *via* platelet activation and the conversion of fibrinogen to fibrin, thrombin equally exerts multiple cellular effects. It could further enhance inflammation through proteinase-activated receptors (PARs). Thrombin production is highly regulated *via* negative feedback mechanisms and physiological anticoagulants, such as the protein C system, antithrombin III, and tissue factor pathway inhibitor [124]. These three control mechanisms may become impaired throughout the inflammatory process, resulting in decreased anticoagulant concentrations secondary to reduced production and increased consumption. This impaired procoagulant– anticoagulant equilibrium results in disseminated intravascular coagulation (DIC), microthrombosis, multi-organ failure, and elevated d-dimer levels [91, 125, 126]. Hypercoagulable state, endothelial dysfunction, injury, and viral-induced procoagulant effect all also play an immense role in COVID-19-associated PE [127–129].

Both LMWH and UFH are recommended for VTE prophylaxis and PE treatment in COVID-19 patients. The recommended dose of the LMWH enoxaparin for VTE prophylaxis is 40 mg (4000 IU) daily. An intermediate dose of LMWH enoxaparin 40 mg subcutaneously every 12 h is recommended in the critically ill, the obese, and those patients with multiple VTE risk factors. A UFH dose of 5000 IU Q8H is recommended for VTE prophylaxis, and doses of up to 7500 IU have been employed in critically ill patients [98–100, 130, 131]. DOACs are recommended in stable patients and in the post-acute phase of PE and outpatient settings when the benefits from their use outweigh the risks. Renal function monitoring with dosage modifications is recommended when LMWH, UFH, and DOACs are employed. Additionally, Anti-Xa monitoring is recommended in patients requiring the therapeutic anticoagulation with LMWH, UFH, and DOAC therapy. DOAC plasma level monitoring is also recommended [101, 131]. Therapeutic anticoagulation should always be considered first; thrombolytic therapy is recommended in patients who go to develop sub-massive or massive PE. An inferior vena cava filter may be employed in at-risk patients; extracorporeal membrane oxygenator (ECMO) is an option, in conjunction with surgical embolectomy or catheter-directed management [1, 102, 103]. Several weeks of therapy is recommended with LMWH or DOACs, post-hospitalization for COVID-19 patients [132].

### **10. Conclusions**

PE is a medical emergency that affects thousands of Americans each year. Thousands of Americans die from this condition annually. The therapy for PE has evolved over the years. Traditional therapies such as UFH, VKA, and warfarin are being abandoned by clinicians in favor of LMWH and DOACs. Reversal agents such as 4-factor prothrombin complex concentrate, andaxanet alfa, and the monoclonal antibody idarucizumab have allowed clinicians to push the boundaries of PE management with confidence, particularly in the outpatient setting. Special populations, such as obese, renal dysfunction, liver impairment, cancer, pregnancy, and COVID-19 patients with PE, pose a tremendous therapeutic burden and challenge to clinicians. Despite these challenges, tremendous progress has been made, with demonstrated improved patient outcomes in PE treatment over the last three decades.

### **Conflict of interest**

The authors declare no conflict of interest.

*Anticoagulants in the Management of Pulmonary Embolism DOI: http://dx.doi.org/10.5772/intechopen.100471*


**Author details**

Edward Collins Vacek S.J. Loyola University New Orleans, Louisiana, United States of America

\*Address all correspondence to<EMAIL_ADDRESS>
© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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[5] "Natural Family Planning," Origins: CNS Documentary Service 20 no. 31, January 10, 1991, 508, no. 6. Speech given on 14 December 1991, http:// www.vatican.va/holy\_father/john\_paul\_ ii/speeches/1990/december/documents/ hf\_jp-ii\_spe\_19901214\_fertilita\_it.html.

[6] John Paul II, "Message of his Holiness Pope John Paul II to the Director of the Centre for Research and Study on the Natural Regulation of Fertility," February 27, 1998, http://www. vatican.va/holy\_father/john\_paul\_ii/ speeches/1998/february/documents/hf\_ jp-ii\_spe\_19980227\_fertilidade\_en.html.

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**3.3.2 Chitosan**

Chitosan [poly-\_(1-4)-d-glucosamine], a cationic polysaccharide, is obtained by alkaline deacetylation of chitin, the principal exoskeletal component in crustaceans. As the combination of properties of chitosan such as water binding capacity, fat binding capacity, bioactivity, biodegradability, nontoxicity, biocompatibility, acceleration of wound healing and antifungal activity, chitosan and its modified analogs have shown many applications in medicine, cosmetics, agriculture, biochemical separation systems, biomaterials and drug controlled release systems. There are also many studies showing that chitin and chitosan accelerated wound healing in many clinical cases and some types of chitin remedies have already been marketed in Japan. Chitin and chitosan was used in the forms of filament, powder, granule, sponge, and composite with cotton or polyester in most studies. (Yang & Lin, 2004)

Chitosan obtained from the shells of crabs, shrimps and other crustaceans, chitosan is a nontoxic, biodegradable and biocompatible natural polymer, and has long been used as a biopolymer and natural material in the pharmaceutical, medical, papermaking and food processing industries. Because of its polycationic nature, chitosan possesses a good antibacterial property against various bacteria and fungi through ionic interaction at a cell surface, which eventually kills the cell. Previous studies have shown that its antimicrobial activity is influenced by molecular weight (Mw), degree of deacetylation, temperature, pH and cations in solution. Because chitosan is one of the safest and most effective antibacterial agents, it has been widely applied for cotton and other textile antibacterial finishes. (Ye et al, 2005)

Fig. 8. The bacterila counting test for silver coated wool with S.aureus

Chitosan [poly-\_(1-4)-d-glucosamine], a cationic polysaccharide, is obtained by alkaline deacetylation of chitin, the principal exoskeletal component in crustaceans. As the combination of properties of chitosan such as water binding capacity, fat binding capacity, bioactivity, biodegradability, nontoxicity, biocompatibility, acceleration of wound healing and antifungal activity, chitosan and its modified analogs have shown many applications in medicine, cosmetics, agriculture, biochemical separation systems, biomaterials and drug controlled release systems. There are also many studies showing that chitin and chitosan accelerated wound healing in many clinical cases and some types of chitin remedies have already been marketed in Japan. Chitin and chitosan was used in the forms of filament, powder, granule, sponge, and composite with cotton or polyester in most studies. (Yang &

Chitosan obtained from the shells of crabs, shrimps and other crustaceans, chitosan is a nontoxic, biodegradable and biocompatible natural polymer, and has long been used as a biopolymer and natural material in the pharmaceutical, medical, papermaking and food processing industries. Because of its polycationic nature, chitosan possesses a good antibacterial property against various bacteria and fungi through ionic interaction at a cell surface, which eventually kills the cell. Previous studies have shown that its antimicrobial activity is influenced by molecular weight (Mw), degree of deacetylation, temperature, pH and cations in solution. Because chitosan is one of the safest and most effective antibacterial agents, it has been widely applied for cotton and other textile antibacterial finishes. (Ye et al,

**3.3.2 Chitosan**

Lin, 2004)

2005)

It comprises copolymers of glucosamine and N-acetyl glucosamine and has a combination of many unique properties, such as non-toxicity, biocompatibility and biodegradability. Chitosan has got wide application in textile dyeing and finishing as a substitute for the various chemicals used in textile processing . It has been used as a pretreatment agent in dyeing of cotton, in textile printing, wool dyeing and shrink proofing and in durable press finish. (Gupta & Haile, 2007; Knill et al, 2004; Fan et al, 2006)

It is known that chitosan derivatives with quaternary ammonium groups possess high efficacy against bacteria and fungi. It is now widely accepted that the target site of these cationic polymers is the cytoplasmic membrane of bacterial cells. (Ignatova et al, 2007; Ignatova et al, 2006)

Chitosan-based core-shell particle, with chitosan as the shell and a soft polymer as the core, has been designed as a novel antibacterial coating for textiles by Ye et al. The core-shell particles were synthesized via a graft copolymerization of n-butyl acrylate from chitosan in aqueous solution. Properties of the particles, including composition, particle size and distribution, surface charge as well as morphology, were characterized. The treatment of cotton with poly(n-butyl acrylate) (PBA)-chitosan particles confers the fabric with excellent antibacterial property. It is well recognized that chitosan has good antimicrobial activity, especially against the growth of Staphylococcus aureus (S. aureus). Figure 9 shows the result of treated and untreated specimens. As expected, the untreated fabric gave a negligible antibacterial activity of less than 5% while all finished cotton showed over 99% bacterial reduction.

Thus chemical modification of the chitosan through the graft copolymerization does not affect its antimicrobial property**. (**Ye et al, 2005) Also the TEM images of core-shell particles are shown in Figure 10.

Fig. 9. Comparison of bacterial reduction before and after coating cotton fabrics with chitosan-PBA particles or chitosan solution (after 1 h shaking).

Antibacterial Agents in Textile Industry 401

Despite the long list of requirements, a variety of chemical finishes have been used to produce textiles with demonstrable antimicrobial properties. These products can be divided into two types based on the mode of attack on microbes. One type consists of chemicals that can be considered to operate by a controlled-release mechanism. The antimicrobial is slowly released from a reservoir either on the fabric surface or in the interior of the fibre. This 'leaching' type of antimicrobial can be very effective against microbes on the fibre surface or in the surrounding environment. However, eventually the reservoir will be depleted and the finish will no longer be effective. In addition, the antimicrobial that is released to the environment may interfere with other desirable microbes, such as those present in waste treatment facilities. The second type of antimicrobial finish consists of molecules that are chemically bound to fibre surfaces. These products can control only those microbes that are present on the fibre surface, not in the surrounding environment. 'Bound' antimicrobials, because of their attachment to the fibre, can potentially be abraded away or become deactivated and lose long term durability. Antimicrobial finishes that control the growth and spread of microbes are more properly called biostats, i.e. bacteriostats, fungistats. Products that actually kill microbes are biocides, i.e. bacteriocides, fungicides. This distinction is important when dealing with governmental

**4. Mechanisms of antimicrobial finishes**

regulations, since biocides are strongly controlled.

Fig. 11. Controlled release antimicrobials

Fig. 10. TEM micrographs of chitosan-PBA particles stained for an appropriate period with 2% PTA solution. (A) Well-defined core-shell particles that consist of PBA cores and chitosan shells; (B) soft PBA-chitosan particles, which deform easily when in contact with each other.

Several mechanisms were proposed for the antimicrobial activity by chitosan:


**3. Analysis of the repetitive component of the genome**

### **3.1. Assembly of olive repetitive sequences**

Some of the biggest technical challenges in sequencing eukaryotic genomes are caused by repetitive DNA (Alkan et al., 2011): that is, sequences that are similar or identical to sequences elsewhere in the genome.

The first step in characterizing and sequencing large genomes has to be a genome survey, from which important information about common repeat sequences can be obtained. NGS data are particularly suitable to identify sequences present in many copies per genome, by assembling reads according to their sequence.

Olive Tree Genomic 137

1000 copies (Macas et al., 2007). Hence, we decided to proceed to the final assembly of Illumina reads after having splitted the sequence read datasets into subpackages of different

In a first assembly, we assembled the complete pool of Illumina reads using CLC-BIO and subsequently CAP3 assembler. In other experiments, the pool of Illumina reads was splitted into 8, 16, 32, 250, or 500 subpackages and assembled separately (indicated as split 1, 2, 3, 4, and 5, respectively); for each splitting, the resulting contigs were assembled on their turn

All supercontigs were then mapped with all Illumina 75 nt long reads (Table 1). It can be observed that major splittings allow to recover the most redundant supercontigs, that are not found in the lower splittings, because of their too large coverage and, hence, the occurrence of multi-reads. Due to the different redundancy observed in the different

0 0 1.309 x 44336 235.6 19.61 6.07 243

1 4 0.327 x 78983 200.5 19.96 6.01 201

2 8 0.163 x 50698 204.2 31.72 9.56 204

3 32 0.041 x 22749 252.3 68.58 14.35 265

4 244 0.005 x 14748 240.6 218.57 74.42 258

5 489 0.003 x 11819 223.6 212.77 67.99 239

**Table 1.** Characteristics of supercontig sets obtained by CLC Bio Workbench and CAP3 assembly after

Concerning 454 sequence reads, we did not proceed to such a subdivision, estimating that the superior length of reads compared to that of Illumina ones allowed to recover also highly repeated sequences. In fact, in longer sequences, the occurrence of multi-reads is

All Illumina- and 454-derived supercontigs and contigs longer than 80 nt were masked against an in-house made database of chloroplast and mitochondrial sequences using RepeatMasker, and organellar sequences were removed. Then, a final assembly was performed, using CAP3, among all datasets, i.e. six Illumina datasets (split 0-5) and one 454 dataset. The resulting whole genome dataset included 238,914 supercontigs, with mean

Mean length Mean nr. of mapped reads

Average coverage N50

Nr. of assembled supercontigs

genome coverages.

Split Nr. of

subpackages

different splitting of Illumina reads.

length of 667.9 nt and N50 = 1.331.

naturally reduced.

using CAP3 assembler obtaining 210,063 supercontigs.

Subpackage coverage

subpackages, we decided to use all supercontigs in the final assembly.

The olive genome is largely uncharacterized, despite the growing importance of this tree as oil crop. Concerning repeated sequences, the most characterized are tandem repeats belonging to 4 families, isolated from genomic libraries and, in some instances, localized by cytological hybridization on olive chromosomes (Katsiotis et al., 1998; Minelli et al., 2000; Lorite et al., 2001; Contento et al., 2002). Also putative retrotransposon fragments have been isolated and sequenced (Stergiou et al., 2002; Natali et al., 2007), but a comprehensive picture of RE landscape in the olive genome is still lacking.

We have performed a deep analysis of the repetitive component of olive genome, using NGS techniques (454 and Illumina). We have used around 25 million Illumina paired-end reads of 75 nt, corresponding to 1.8 billion nt and a 1.3 x coverage, and around 8 million 454 single reads, with mean read length of 407 nt, corresponding to a total of 3.3 billion nt and a 2.3 x coverage.

This large amount of sequencing data cannot be sufficient for whole genome assembly, but it enables representative sampling of elements present in a genome in multiple copies. Moreover, the proportion of individual sequences in the reads reflects their genomic abundance, thus providing a simple and reliable means for quantification of repetitive elements (Macas et al., 2007).

In our experiments, we performed de novo repeat identification and reconstruction by direct assembly of the reads. Due to the relatively low genome coverage of the sequencing, most of the contigs that are obtained do not represent specific genomic loci; instead, they are probably composed of reads derived from multiple copies of repetitive elements, thus representing consensus sequences of genomic repeats (Novak et al., 2010). Even though the exact form of this consensus does not necessarily occur in the genome, this representation of repetitive elements has been shown to be sufficiently accurate to enable amplification of the full length repetitive elements using PCR (Swaminathan et al., 2007).

We assembled Illumina and 454 sequence reads by overlapping DNA sequence fragments using CLC-BIO and CAP3 as aligners. In spite of recent progresses, a major challenge remains when reads map to multiple locations, i.e. with multi-reads. The occurrence of multi-reads is strongly dependent on the read length: they are most common in the Illumina sequence packages, and less common in 454 sequence packages, in which sequence length is rapidly growing to lengths similar to those achieved by classical Sanger sequencing, though at higher costs than Illumina.

The sequencing coverage affects heavily the possibility to recover repeated sequences. Obviously, the larger is the coverage, the higher is the possibility that multi-reads are not resolved and discarded. For example, it has been demonstrated, in pea, that a very low coverage (0.008 ×) of the genome allows to obtain repetitive sequences present with at least 1000 copies (Macas et al., 2007). Hence, we decided to proceed to the final assembly of Illumina reads after having splitted the sequence read datasets into subpackages of different genome coverages.

136 Olive Germplasm – The Olive Cultivation, Table Olive and Olive Oil Industry in Italy

picture of RE landscape in the olive genome is still lacking.

assembling reads according to their sequence.

2.3 x coverage.

elements (Macas et al., 2007).

at higher costs than Illumina.

The first step in characterizing and sequencing large genomes has to be a genome survey, from which important information about common repeat sequences can be obtained. NGS data are particularly suitable to identify sequences present in many copies per genome, by

The olive genome is largely uncharacterized, despite the growing importance of this tree as oil crop. Concerning repeated sequences, the most characterized are tandem repeats belonging to 4 families, isolated from genomic libraries and, in some instances, localized by cytological hybridization on olive chromosomes (Katsiotis et al., 1998; Minelli et al., 2000; Lorite et al., 2001; Contento et al., 2002). Also putative retrotransposon fragments have been isolated and sequenced (Stergiou et al., 2002; Natali et al., 2007), but a comprehensive

We have performed a deep analysis of the repetitive component of olive genome, using NGS techniques (454 and Illumina). We have used around 25 million Illumina paired-end reads of 75 nt, corresponding to 1.8 billion nt and a 1.3 x coverage, and around 8 million 454 single reads, with mean read length of 407 nt, corresponding to a total of 3.3 billion nt and a

This large amount of sequencing data cannot be sufficient for whole genome assembly, but it enables representative sampling of elements present in a genome in multiple copies. Moreover, the proportion of individual sequences in the reads reflects their genomic abundance, thus providing a simple and reliable means for quantification of repetitive

In our experiments, we performed de novo repeat identification and reconstruction by direct assembly of the reads. Due to the relatively low genome coverage of the sequencing, most of the contigs that are obtained do not represent specific genomic loci; instead, they are probably composed of reads derived from multiple copies of repetitive elements, thus representing consensus sequences of genomic repeats (Novak et al., 2010). Even though the exact form of this consensus does not necessarily occur in the genome, this representation of repetitive elements has been shown to be sufficiently accurate to enable amplification of the

We assembled Illumina and 454 sequence reads by overlapping DNA sequence fragments using CLC-BIO and CAP3 as aligners. In spite of recent progresses, a major challenge remains when reads map to multiple locations, i.e. with multi-reads. The occurrence of multi-reads is strongly dependent on the read length: they are most common in the Illumina sequence packages, and less common in 454 sequence packages, in which sequence length is rapidly growing to lengths similar to those achieved by classical Sanger sequencing, though

The sequencing coverage affects heavily the possibility to recover repeated sequences. Obviously, the larger is the coverage, the higher is the possibility that multi-reads are not resolved and discarded. For example, it has been demonstrated, in pea, that a very low coverage (0.008 ×) of the genome allows to obtain repetitive sequences present with at least

full length repetitive elements using PCR (Swaminathan et al., 2007).

In a first assembly, we assembled the complete pool of Illumina reads using CLC-BIO and subsequently CAP3 assembler. In other experiments, the pool of Illumina reads was splitted into 8, 16, 32, 250, or 500 subpackages and assembled separately (indicated as split 1, 2, 3, 4, and 5, respectively); for each splitting, the resulting contigs were assembled on their turn using CAP3 assembler obtaining 210,063 supercontigs.

All supercontigs were then mapped with all Illumina 75 nt long reads (Table 1). It can be observed that major splittings allow to recover the most redundant supercontigs, that are not found in the lower splittings, because of their too large coverage and, hence, the occurrence of multi-reads. Due to the different redundancy observed in the different subpackages, we decided to use all supercontigs in the final assembly.

**Table 1.** Characteristics of supercontig sets obtained by CLC Bio Workbench and CAP3 assembly after different splitting of Illumina reads.

Concerning 454 sequence reads, we did not proceed to such a subdivision, estimating that the superior length of reads compared to that of Illumina ones allowed to recover also highly repeated sequences. In fact, in longer sequences, the occurrence of multi-reads is naturally reduced.

All Illumina- and 454-derived supercontigs and contigs longer than 80 nt were masked against an in-house made database of chloroplast and mitochondrial sequences using RepeatMasker, and organellar sequences were removed. Then, a final assembly was performed, using CAP3, among all datasets, i.e. six Illumina datasets (split 0-5) and one 454 dataset. The resulting whole genome dataset included 238,914 supercontigs, with mean length of 667.9 nt and N50 = 1.331.


**5. Conclusions**

In this research work, a field study was carried out on the cooling energy performance of an existing, operating ventilation system under the operation of an air-to-air rotary heat wheel and direct expansion cooling coil, connected to a variable refrigerant volume outdoor unit. The major findings obtained from the study can be summarized as follows:

1. The operation of the heat wheel has a significant cooling energy saving impact on the electric energy consumption of the outdoor unit. Comparing the measured ventilation system with an air handling unit without a heat wheel operation, the cooling energy consumption is 25.1% higher;

2. Based on the measurements, the real sensible effectiveness and the CO2 cross-contamination of the heat wheel are not in accordance with the design assumptions for the cooling period;

3. The sensible effectiveness of the heat wheel performed 4.7% higher than the data (74.9%) given in the technical data book of the producer;

4. Having completed the measurements for the whole cooling period, the amount of CO2 cross-contamination in the heat wheel was much higher (with 16.4% relative average and 30.1% maximum values) than predicted during the designing phase.

Future work will focus on heating and annual energy performance investigations by conducting further field studies on the system. Moreover, simulation model development will also be considered for an annual energy consumption investigation of the existing ventilation system and model validation is planned based on data given by an annual field study. The long-term goal is to develop a simulation model which is suitable for determination of the energy consumption of ventilation systems in the design phase with a high accuracy.

**Funding:** The sensors, instruments, and transducers were financially supported and installed, and BMS software for data recording was made for this research work, by the national Intherm Ltd. In addition, the research project was financially supported by the National Research, Development and Innovation O ffice from the NRDI Fund [grant number: NKFIH PD\_18 127907], the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, Budapest, Hungary. Moreover, the research reported in this paper has been supported by the National Research, Development and Innovation Fund (TUDFO/51757/2019-ITM, Thematic Excellence Program), as well as the Higher Education Excellence Program of the Ministry of Human Capacities in the frame of Artificial Intelligence research area of Budapest University of Technology and Economics (BME FIKP-MI).

**Acknowledgments:** The author wishes to thank Árpád Nagy and Gyula Szabó from the group of Intherm Ltd., as well as Balázs Zuggó and Noémi Bálint from the group of Daikin Hungary Ltd., for providing their professional technical and practical knowledge for the research background of this research. Moreover, special thanks go to Laith Al-Hyari for his contribution in simple data saving.

**Conflicts of Interest:** The author declares no conflicts of interest.


*Article* **Analysis of Physeal Fractures from the United States National Trauma Data Bank**

**Joseph R. Fuchs 1,2, Romie F. Gibly 1,3 , Christopher B. Erickson 1,4, Stacey M. Thomas 1 , Nancy Hadley Miller 1,5 and Karin A. Payne 1,6,\***

**Abstract:** Background: Pediatric long-bone physeal fractures can lead to growth deformities. Previous studies have reported that physeal fractures make up 18–30% of total fractures. This study aimed to characterize physeal fractures with respect to sex, age, anatomic location, and Salter–Harris (SH) classification from a current multicenter national database. Methods: A retrospective cohort study was performed using the 2016 United States National Trauma Data Bank (NTDB). Patients ≤ 18 years of age with a fracture of the humerus, radius, ulna, femur, tibia, or fibula were included. Results: The NTDB captured 132,018 patients and 58,015 total fractures. Physeal fractures made up 5.7% (3291) of all long-bone fractures, with males accounting for 71.0% (2338). Lower extremity physeal injuries comprised 58.6% (1929) of all physeal fractures. The most common site of physeal injury was the tibia comprising 31.8% (1047), 73.9% (774) of which were distal tibia fractures. Physeal fractures were greatest at 11 years of age for females and 14 years of age for males. Most fractures were SH Type II fractures. Discussion and Conclusions: Our analysis indicates that 5.7% of pediatric long-bone fractures involved the physis, with the distal tibia being the most common. These findings suggest a lower incidence of physeal fractures than previous studies and warrant further investigation.

**Keywords:** physeal; physis; fracture; trauma; long-bone fractures in children

## **1. Introduction**

It is estimated that 18% to 30% of all pediatric fractures involve the physis, a cartilaginous area at the ends of long bones [1,2]. Physeal fractures are of particular concern as they can lead to partial or complete physeal arrest, resulting in angular deformities or limb-length discrepancy. Understanding the epidemiology of physeal injuries is important for the early identification of these injuries, as late presentation can result in complex deformities that can lead to greater challenges in achieving good clinical results [3,4].

Previous epidemiology studies looking at sex differences have indicated that a predominance of physeal injuries occur in males [1–3]. The distribution of anatomic locations of physeal fractures for long bones of the appendicular skeleton has been explored as well, with most fractures occurring in the upper extremities, especially of the radius [1,3,5]. This observation has led to outcomes research analyzing the treatment of these fractures, such as outcomes based on body habitus [6]. Fractures that involve the physis are classified according to the Salter–Harris (SH) classification system, which grades fractures according

**Citation:** Fuchs, J.R.; Gibly, R.F.; Erickson, C.B.; Thomas, S.M.; Hadley Miller, N.; Payne, K.A. Analysis of Physeal Fractures from the United States National Trauma Data Bank. *Children* **2022**, *9*, 914. https://doi.org/10.3390/ children9060914

Academic Editor: Johannes Mayr

Received: 14 May 2022 Accepted: 16 June 2022 Published: 18 June 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

to the involvement of the physis, metaphysis, and epiphysis (Figure 1). Past studies have shown that SH Type II fractures are the most common type of physeal injury [1–3]. ing to the involvement of the physis, metaphysis, and epiphysis (Figure 1). Past studies have shown that SH Type II fractures are the most common type of physeal injury [1–3].

as outcomes based on body habitus [6]. Fractures that involve the physis are classified according to the Salter–Harris (SH) classification system, which grades fractures accord-

*Children* **2022**, *9*, x FOR PEER REVIEW 2 of 10

**Figure 1.** Salter–Harris Classification of pediatric physeal fractures. The five fracture types are **Figure 1.** Salter–Harris Classification of pediatric physeal fractures. The five fracture types are shown with the fracture line represented by a dotted line.

shown with the fracture line represented by a dotted line. Additional studies have analyzed trends in physeal fractures such as age and sex predominance for specific long bones and anatomic locations [7–12]. Few, however, have compared all physeal fractures and identified which anatomic locations are at a higher risk for injury [1–3]. Comparison of all long-bone fractures to physeal fractures according to age and sex has also rarely been studied [1]. While most of these studies have focused on populations from a single institution, a larger-scale study was conducted in Olmstead County, MN, between 1979–1988 [3]. This study indicated that physeal injuries peak between the ages of 12–14 years. Since that time, motor vehicle technology and sports intensity have evolved, potentially altering the prevalence and severity of physeal injuries [13]. This has been explored in previous work that has analyzed the epidemiology of pediatric fractures based on age, type, and anatomic location at a single institution over time [14]. Additional studies have analyzed trends in physeal fractures such as age and sex predominance for specific long bones and anatomic locations [7–12]. Few, however, have compared all physeal fractures and identified which anatomic locations are at a higher risk for injury [1–3]. Comparison of all long-bone fractures to physeal fractures according to age and sex has also rarely been studied [1]. While most of these studies have focused on populations from a single institution, a larger-scale study was conducted in Olmstead County, MN, between 1979–1988 [3]. This study indicated that physeal injuries peak between the ages of 12–14 years. Since that time, motor vehicle technology and sports intensity have evolved, potentially altering the prevalence and severity of physeal injuries [13]. This has been explored in previous work that has analyzed the epidemiology of pediatric fractures based on age, type, and anatomic location at a single institution over time [14]. However, analyzing a more recent and larger dataset from multiple institutions could provide a better representation of the current epidemiology of physeal fractures.

However, analyzing a more recent and larger dataset from multiple institutions could provide a better representation of the current epidemiology of physeal fractures. The aim of this study was to analyze trends of pediatric long-bone fractures from a current United States multicenter national database to better characterize both physeal The aim of this study was to analyze trends of pediatric long-bone fractures from a current United States multicenter national database to better characterize both physeal and nonphyseal fractures with respect to sex, age, anatomic location, and SH classification.

#### and nonphyseal fractures with respect to sex, age, anatomic location, and SH classifica-**2. Materials and Methods**

tion. **2. Materials and Methods**  Following approval from the Institutional Review Board (COMIRB 20-0020), a retrospective cohort study was performed using the American College of Surgeons (ACS) United States National Trauma Data Bank (NTDB). The NTDB consists of patient demographics, ICD-10 codes for all injuries presenting within 14 days of occurrence, trauma center designation, and population treated [15]. The NTDB is the largest aggregation of Following approval from the Institutional Review Board (COMIRB 20-0020), a retrospective cohort study was performed using the American College of Surgeons (ACS) United States National Trauma Data Bank (NTDB). The NTDB consists of patient demographics, ICD-10 codes for all injuries presenting within 14 days of occurrence, trauma center designation, and population treated [15]. The NTDB is the largest aggregation of U.S. trauma registry data and was designed to establish a national standard for trauma data [16]. The NTDB has been utilized to study the epidemiology of adult patients with hip fractures and spinal injury in pediatric populations [17,18]. The ACS utilizes the National Trauma Data Standard and validates data annually to ensure incomplete and nonsensical data are not included [19].

The data, volunteered from over 740 institutions in the United States and Puerto Rico, are comprised of approximately two hundred Level I, II, III or IV trauma centers each and 36 Level I or II pediatric-only centers. Using the 2016 version of the NTDB, data given in CSV files were loaded into Microsoft Access. In the NTDB each patient is coded with a unique inclusion key and ICD-10 diagnosis code, along with demographic data. ICD-10 diagnosis codes based on the clinical presentation and incorporating clinical data are coded by the trauma registrar or data abstractor at each institution. This allowed patients ≤ 18 years to be identified. From those, records with ICD-10 diagnosis codes for long-bone fractures of the humerus, radius, ulna, femur, tibia, or fibula (S42, S49, S52, S59, S72, S79, S82, S89) were selected (Figure 2). Within the ICD-10 diagnosis codes for long-bone fractures are more specific codes for physeal injuries and SH Type classification [20]. These were utilized to categorize long-bone fractures more specifically into nonphyseal fractures or physeal fractures (excluding slipped capital femoral epiphysis). All physeal ICD-10 codes for each long bone were included. Physeal fractures were further categorized using the SH classification, when available (Figure 2). The detailed ICD-10 codes also allowed for an anatomic location such as the proximal and distal end of bones to be differentiated. For example, S49.0 codes for "physeal fracture of upper end of humerus" and S49.1 codes for "physeal fracture of lower end of humerus". The range of ICD-10 diagnosis codes analyzed ensured that all long-bone fractures were included in the study, with further granularity for anatomic location and physeal involvement based on more specific coding. Once the dataset was generated, data were analyzed based on sex, age, anatomic location, and fracture type for long-bone fractures. Age groups (0–4, 5–8, 9–12, and 13–18 years) were utilized to organize the data. These groups were determined based on groups utilized in previous studies and to highlight common ages for physeal injuries as described in the literature [2,3]. are comprised of approximately two hundred Level I, II, III or IV trauma centers each and 36 Level I or II pediatric-only centers. Using the 2016 version of the NTDB, data given in CSV files were loaded into Microsoft Access. In the NTDB each patient is coded with a unique inclusion key and ICD-10 diagnosis code, along with demographic data. ICD-10 diagnosis codes based on the clinical presentation and incorporating clinical data are coded by the trauma registrar or data abstractor at each institution. This allowed patients ≤ 18 years to be identified. From those, records with ICD-10 diagnosis codes for long-bone fractures of the humerus, radius, ulna, femur, tibia, or fibula (S42, S49, S52, S59, S72, S79, S82, S89) were selected (Figure 2). Within the ICD-10 diagnosis codes for long-bone fractures are more specific codes for physeal injuries and SH Type classification [20]. These were utilized to categorize long-bone fractures more specifically into nonphyseal fractures or physeal fractures (excluding slipped capital femoral epiphysis). All physeal ICD-10 codes for each long bone were included. Physeal fractures were further categorized using the SH classification, when available (Figure 2). The detailed ICD-10 codes also allowed for an anatomic location such as the proximal and distal end of bones to be differentiated. For example, S49.0 codes for "physeal fracture of upper end of humerus" and S49.1 codes for "physeal fracture of lower end of humerus". The range of ICD-10 diagnosis codes analyzed ensured that all long-bone fractures were included in the study, with further granularity for anatomic location and physeal involvement based on more specific coding. Once the dataset was generated, data were analyzed based on sex, age, anatomic location, and fracture type for long-bone fractures. Age groups (0–4, 5–8, 9–12, and 13–18 years) were utilized to organize the data. These groups were determined based on groups utilized in previous studies and to highlight common ages for physeal injuries as described in the literature [2,3].

U.S. trauma registry data and was designed to establish a national standard for trauma data [16]. The NTDB has been utilized to study the epidemiology of adult patients with hip fractures and spinal injury in pediatric populations [17,18]. The ACS utilizes the National Trauma Data Standard and validates data annually to ensure incomplete and non-

The data, volunteered from over 740 institutions in the United States and Puerto Rico,

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sensical data are not included [19].

**Figure 2. Figure 2.** Flowchart of inclusion criteria using data from the NTDB. Flowchart of inclusion criteria using data from the NTDB.

#### **3. Results**

The 2016 version of the NTDB consisted of entries for 968,665 patients. Of those, 132,018 patients were identified to be ≤18 years. 42,429 of those patients had at least one long-bone fracture code associated with their entry, resulting in a total of 58,015 fractures (Figure 2).

When analyzing all long-bone fractures, regardless of physeal involvement, males accounted for 65.6% (38,053) of long bone fractures while females comprised 34.4% (19,962). The total long-bone fracture data were then categorized into nonphyseal or physeal fractures. Nonphyseal fractures comprised 94.3% (54,724) of the long-bone fractures included in this study, and males accounted for 65.3% (35,715) of all nonphyseal fractures. Fractures involving the physis made up 5.7% (3291) of the total fractures reported in this study (6.1% in males and 4.8% in females). Males accounted for 71.0% (2338) of all physeal fractures. While SH classification information was not available for all fractures, 67.9% (2236) of the overall physeal fractures were associated with an SH class by ICD-10 coding (Figure 2). The 2016 version of the NTDB consisted of entries for 968,665 patients. Of those, 132,018 patients were identified to be ≤18 years. 42,429 of those patients had at least one long-bone fracture code associated with their entry, resulting in a total of 58,015 fractures (Figure 2). When analyzing all long-bone fractures, regardless of physeal involvement, males accounted for 65.6% (38,053) of long bone fractures while females comprised 34.4% (19,962). The total long-bone fracture data were then categorized into nonphyseal or physeal fractures. Nonphyseal fractures comprised 94.3% (54,724) of the long-bone fractures included in this study, and males accounted for 65.3% (35,715) of all nonphyseal fractures. Fractures involving the physis made up 5.7% (3291) of the total fractures reported in this study (6.1% in males and 4.8% in females). Males accounted for 71.0% (2338) of all physeal fractures. While SH classification information was not available for all fractures, 67.9%

Nonphyseal fractures for each age by sex show a relative peak at the ages of 5–6 years for both males and females (Figure 3). Another peak appears for males at 13–14 years of age which is not seen for females. The distribution of nonphyseal fractures according to long bone and separated by age is represented for males in Table 1 and females in Table 2. Upper extremity nonphyseal injuries accounted for 56.6% (20,206) of all nonphyseal fractures in males and 65.6% (12,476) in females. Nonphyseal fractures occurred most frequently in the humerus, followed by the femur, radius, ulna, and tibia which all had similar occurrences. Nonphyseal fractures to the fibula occurred less frequently. (2236) of the overall physeal fractures were associated with an SH class by ICD-10 coding (Figure 2). Nonphyseal fractures for each age by sex show a relative peak at the ages of 5–6 years for both males and females (Figure 3). Another peak appears for males at 13–14 years of age which is not seen for females. The distribution of nonphyseal fractures according to long bone and separated by age is represented for males in Table 1 and females in Table 2. Upper extremity nonphyseal injuries accounted for 56.6% (20,206) of all nonphyseal fractures in males and 65.6% (12,476) in females. Nonphyseal fractures occurred most frequently in the humerus, followed by the femur, radius, ulna, and tibia which all had similar occurrences. Nonphyseal fractures to the fibula occurred less frequently.

**Table 1.** Nonphyseal fractures for males according to age and long bone. N = 35,715.

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**3. Results**

**Tibia Fibula Humerus Radius Ulna Table 1.** Nonphyseal fractures for males according to age and long bone. N = 35,715.

**Table 2.** Nonphyseal fractures for females according to age and long bone. N = 19,009.

The number of physeal fractures at each age for males and females is shown in Figure 4. A peak occurs around the age of 11 for females and at the age of 14 for males. The number of physeal fractures is much higher for males than females after 10 years of age. The number and percentage of physeal fractures according to age, long bone, and proximal or distal location is shown for males in Table 3 and females in Table 4. In males, the largest percentage of physeal fractures were observed in the distal tibia and distal radius in the 13–18 age group (Table 3). Females also had the greatest number of physeal fractures in these locations, but they mostly occurred in the 9–12 age group (Table 4). **Total** 2776 (14.6) 2350 (12.4) 1407 (7.4) 6825 (35.9) 2929 (15.4) 2722 (14.3) The number of physeal fractures at each age for males and females is shown in Figure 4. A peak occurs around the age of 11 for females and at the age of 14 for males. The number of physeal fractures is much higher for males than females after 10 years of age. The number and percentage of physeal fractures according to age, long bone, and proximal or distal location is shown for males in Table 3 and females in Table 4. In males, the largest percentage of physeal fractures were observed in the distal tibia and distal radius in the 13–18 age group (Table 3). Females also had the greatest number of physeal fractures in these locations, but they mostly occurred in the 9–12 age group (Table 4).

**Humerus n (%)**

**Radius n (%)**

**Ulna n (%)**

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**Tibia n (%)**  **Fibula n (%)**

0–4 858 (4.5) 341 (1.8) 127 (0.7) 2076 (10.9) 315 (1.7) 352 (1.9) 5–8 497 (2.6) 353 (1.9) 206 (1.1) 3308 (17.4) 1059 (5.6) 990 (5.2) 9–12 422 (2.2) 501 (2.6) 313 (1.6) 888 (4.7) 903 (4.8) 784 (4.1) 13–18 999 (5.3) 1155 (6.1) 761 (4.0) 553 (2.9) 652 (3.4) 596 (3.1)

**Age Femur n (%)**

**Figure 4.** Number of physeal fractures at each age for females (blue) and males (red). **Figure 4.** Number of physeal fractures at each age for females (blue) and males (red).

**Table 3.** Physeal fractures for males according to age, long bone, and location (proximal or distal).

N = 2338. **Bone n (%) Table 3.** Physeal fractures for males according to age, long bone, and location (proximal or distal). N = 2338.

P = proximal, D = distal.

**Table 4.** Physeal fractures for females according to age, long bone, and location (proximal or distal). N = 953.

P = proximal, D = distal.

The breakdown of all physeal fractures by bone and further separated by proximal or distal location, sex, and age can be seen in Figure 5. Lower extremity fractures comprised 58.6% (1929/3291) of physeal injuries. The most common long bone with physeal injury was the tibia, accounting for 31.8% (1047/3291) of all physeal fractures. Of these fractures, the distal tibia was predominantly injured, accounting for 71.0% (534/752) and 81.4% (240/295) of tibial physeal fractures for males and females, respectively. In females, tibial physeal fractures occurred most often between the ages of 9–12 years, while for males,

13–18 years made up the largest share. The second most common site of physeal fracture for both males and females was the radius. Similar to the tibia, the distal end of the bone was more highly affected than the proximal end. A physeal fracture affecting the distal radius occurred in 95.7% (605/632) and 90.3% (214/237) of total physeal fractures of the radius for males and females, respectively. Physeal fractures of the radius occurred most frequently for females from the ages of 9–12 and for males from ages 13–18. males, 13–18 years made up the largest share. The second most common site of physeal fracture for both males and females was the radius. Similar to the tibia, the distal end of the bone was more highly affected than the proximal end. A physeal fracture affecting the distal radius occurred in 95.7% (605/632) and 90.3% (214/237) of total physeal fractures of the radius for males and females, respectively. Physeal fractures of the radius occurred most frequently for females from the ages of 9–12 and for males from ages 13–18.

The breakdown of all physeal fractures by bone and further separated by proximal or distal location, sex, and age can be seen in Figure 5. Lower extremity fractures comprised 58.6% (1929/3291) of physeal injuries. The most common long bone with physeal injury was the tibia, accounting for 31.8% (1047/3291) of all physeal fractures. Of these fractures, the distal tibia was predominantly injured, accounting for 71.0% (534/752) and 81.4% (240/295) of tibial physeal fractures for males and females, respectively. In females, tibial physeal fractures occurred most often between the ages of 9–12 years, while for

**Table 4.** Physeal fractures for females according to age, long bone, and location (proximal or distal).

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**Bone n (%) Femur Tibia Fibula Humerus Radius Ulna Age P D P D P D P D P D P D**  0–4 7 (0.7) 17 (1.8) 16 (1.7) 14 (1.5) 4 (0.4) 8 (0.8) 6 (0.6) 18 (1.9) 0 (0.0) 18 (1.9) 0 (0.0) 4 (0.4) 5–8 2 (0.2) 26 (2.7) 8 (0.8) 24 (2.5) 6 (0.6) 14 (1.5) 7 (0.7) 32 (3.4) 12 (1.3) 68 (7.1) 0 (0.0) 18 (1.9) 9–12 34 (3.6) 45 (4.7) 13 (1.4) 144 (15.1) 2 (0.2) 14 (1.5) 8 (0.8) 11 (1.2) 8 (0.8) 88 (9.2) 0 (0.0) 24 (2.5) 13–18 12 (1.3) 39 (4.1) 18 (1.9) 58 (6.1) 2 (0.2) 46 (4.8) 8 (0.8) 4 (0.4) 3 (0.3) 40 (4.2) 0 (0.0) 3 (0.3)

N = 953.

P = proximal, D = distal.

**Figure 5.** The number of physeal fractures for the femur, tibia, fibula, humerus, radius, and ulna, separated by sex, anatomic location (proximal and distal), and age group.

The SH classification was available for 2236 physeal fractures and analysis of these data indicated that SH class II fractures were the most common physeal fractures, comprising 69.0% (1543) of fractures (Table 5). SH class I, III, and IV each made up less than 12% of physeal fractures.

**Table 5.** Salter–Harris classification of physeal injuries based on long bone. N = 2236.

#### **4. Discussion**

Previous epidemiology studies of physeal fractures have largely been completed through an analysis of fractures at single academic institutions [1–3,21]. While this provides useful information, a more comprehensive view of physeal fractures can be obtained using data from the NTDB. The NTDB data come from 747 institutions, comprising 968,665 patient records from all regions of the United States. Therefore, this study is derived from a much larger and more varied sample of patients which allows for a better understanding of physeal fractures.

Males accounted for a majority of all fractures with peak nonphyseal fracture occurrence at 5–6 years and 13–14 years, which is similar to previous studies [21,22]. Studies have found that males generally account for 55–65% of all fractures, which is similar to our results [1,22]. In the case of nonphyseal fractures affecting females, previous studies have noted a peak at 11 years compared to the results of this study which demonstrated a peak at 5 and 6 years [2,21]. This inconsistency is possibly due to differences such as sports participation based on age and sex across times and in various countries [2,21].

In this study, the most affected long bone for nonphyseal fractures is the humerus. This deviates from studies that have found the radius to comprise 30–60% of nonphyseal fractures [1,2]. This is a unique finding that warrants further investigation to clearly establish this predominance and may relate to the subset of patients presenting to centers participating in the NTDB, with a potential for higher acuity of trauma.

Our analysis indicated that physeal fractures made up 5.7% of the total fractures, which is less than the rate of 18–30% found in previous studies [1–3,23]. One reason for this discrepancy could be that the sample was derived from long-bone fractures, while many previous studies included fractures of the phalanges. However, in Mann et al. the rate was 30% based solely on long-bone data [1]. Another factor that should be considered is the ages included in each study. For example, Peterson et al. utilized a sample of patients 0–21 years while Worlock et al. included patients 0–12 years [3,24]. However, when altering the age range analyzed using the NTDB data to include age ranges from 0–14 years, 0–15 years, 0–16 years, or 0–17 years, the maximum percentage of physeal fractures found is less than 7%. The NTDB is comprised of hundreds of institutions and thousands of patients which can be contrasted with most studies that were conducted at single institutions that are largely academic centers. It is possible that previous studies with smaller sample sizes may have seen higher rates of complicated injuries. It is also possible that not all physeal fractures would present at a trauma center. Therefore, the rate of physeal fractures compared to overall fractures may be lower than previously thought but further investigation is needed.

The most common age for physeal fractures was 14 years for males and 11 years for females. This has been noted in previous studies and has been attributed to the weakness of the growth plate during puberty [2]. Of physeal fractures, males accounted for 71.0%. This is consistent with studies that demonstrate a male predominance of 66–75% [1,3,23]. Lower extremity physeal injuries comprised a majority of injuries for both males and females. This is consistent with a previous study of long-bone physeal fractures which demonstrated that 54.78% of fractures were in the lower extremity [1]. In this study, the tibia was the long bone with the greatest percentage of physeal fractures, accounting for greater than 30% of injuries. The second most common long bone with physeal fractures was the radius with 26.4%. This deviates from previous studies, which found a predominance of physeal fractures of the radius, comprising 28–30% of long-bone physeal fractures [1,3]. This difference may be due to the NTBD being comprised of data from trauma centers that see higher acuity injuries compared to primary care settings, as tibial fractures result in difficulty with ambulation.

Tibial physeal fractures were more commonly fractured at the distal end than the proximal end. This is consistent with previous studies with distal injuries accounting for a majority (96%) of tibial physeal fractures [1]. This was also seen for the radius, with distal physeal fractures comprising greater than 90% of physeal injuries, consistent with previous estimates of 86.36% [1]. Therefore, distal tibial and radial injuries should

be closely followed to ensure the physis is not impacted. A recent study of SH Type II fractures of the distal tibia suggested that fracture displacement greater than 3 mm should be treated with closed reduction and casted [25]. If displacement remains greater than 3 mm, open reduction should be performed. The study found a small risk of growth arrest after closed reduction for displaced fractures. Thus, initial recognition, treatment, and follow-up of distal tibial and radial physeal fractures by a pediatric orthopedist can help avoid long-term complications such as angular deformity and limb-length discrepancy in pediatric populations.

SH Type II fractures were the dominant type of physeal injuries observed in this study, which has been a consistent pattern throughout the decades [1–3,23]. SH Types I, III, and IV each accounted for 12% or less of physeal fractures, which has been noted previously [1].

Previous studies have looked at the incidence of physeal fractures through direct retrospective analysis of radiographs [1–3,23]. The NTDB for 2016 is the first year that contains ICD-10 codes, which have many subclassifications for physeal injuries. Previously utilized ICD-9 codes did not include specifications for proximal or distal physis, an essential piece of knowledge when addressing physeal fractures of long bones. Through proper ICD-10 coding based on radiographic reads, it is possible to have a better understanding of physeal injuries that is standardized across institutions. This is beneficial for future studies as researchers can more quickly sort through data without having to analyze numerous radiographs that will not meet study inclusion criteria. A limitation of this information, however, is that the ICD-10 diagnosis codes utilized in this analysis are reliant on radiologic reads and radiographic imaging could not be independently verified. Therefore, errors in the assignment of ICD-10 codes during data entry may have impacted our results. However, the ACS validates the NTDB by not including missing or nonsensical data. Future studies should compare ICD-10 diagnosis codes to independently verified radiographic reads to determine if differences exist.

Despite the ability of the NTDB to provide an estimate for physeal injuries across hundreds of institutions within the country, there are some limitations to the data. The most important limitation is that the data are voluntarily provided by trauma centers. Therefore, there are differences in the number of patients seen at each institution, as well as the number of institutions for each region. Thus, this study does not provide a national representation of injuries. These differences do not allow for a denominator to be determined which would provide estimates of the incidence of pediatric physeal injuries nationally. However, this is a similar limitation to previous studies that describe the occurrence of physeal injuries at singular institutions.

#### **5. Conclusions**

In conclusion, we found that 5.7% of all pediatric long-bone fractures involved the physis, with the distal tibia the most common site of injury. Utilizing this knowledge physicians should be vigilant about these injuries to prevent future complications commonly seen in physeal fractures such as bony bar formation and limb-length discrepancy.

**Author Contributions:** Conceptualization, J.R.F., R.F.G., K.A.P. and N.H.M.; methodology, J.R.F., R.F.G., K.A.P. and N.H.M.; validation, J.R.F. and R.F.G.; formal analysis, J.R.F., R.F.G., C.B.E. and S.M.T.; investigation, all authors; data curation, J.R.F., R.F.G., C.B.E. and S.M.T.; writing—original draft preparation, J.R.F. and R.F.G.; writing—review, and editing, all authors; visualization, J.R.F., R.F.G., C.B.E. and S.M.T.; supervision, N.H.M. and K.A.P.; project administration, N.H.M. and K.A.P.; funding acquisition, N.H.M. and K.A.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Gates Grubstake Fund—2018 Research Award.

**Institutional Review Board Statement:** The study was approved by the Institutional Review Board of The University of Colorado (COMIRB 20-0020), approval date is June 2017.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data available upon reasonable request.

**Acknowledgments:** This study was supported by the Gates Grubstake Fund.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

## **References**


**5.4 Role for plants**

Phenolics stand of great importance to plants. Not only are they responsible for the protection of the plants against exterior hazards [20], but they are also crucial to physiology and cellular metabolism. They play a key role in sensorial traits such as the plants' color and aroma, germination of seeds and reproduction [21].


**5. Conclusions**

Interestingly, the study yielded new results regarding the age of the runners. Senior runners (45–53) showed significant higher levels of lipid peroxidation (MDA concentration) than medium (38–44) and young runners (31–37) throughout the study. A plausible explanation would be the higher body fat percentage observed in senior runners, together with the loss of muscular mass compared to younger runners (Table 1). These results are in agreement with Hattori and cols. who reported that ultramarathon runners aging less than 45 years old had lower ROS levels at all race points [51]. Again, larger series would be necessary to study the predictive value of this assay to consider if a personalized antioxidant supplementation might promote the physiological recovery after great physical efforts.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/2076-392 1/10/3/355/s1, Supplementary Table S1. Evolution of muscle strength (SJ and HG), muscle damage (LDH and CK) and acute inflammation (CRP) biomarkers.

**Author Contributions:** Conceptualization, C.G., C.H., E.C.-B. and M.M.; methodology, P.B., B.H. and C.H.; formal analysis, C.G., M.M. and C.H.; investigation, Barbara Hernando, I.M.-N. and C.H.; writing—original draft preparation, E.C.-B., C.G., C.H.; writing—M.M., P.B., C.H.; funding acquisition, C.H. and I.M.-N. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Vithas Hospitals group (https://vithas.es), Penyagolosa Trails organization (http://penyagolosatrails.com), catedra Endavant Villarreal CF de l'Esport (https://endavant.villarrealcf.es/) and the following grant code: UJI-B2019-38. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

**Institutional Review Board Statement:** The investigation was conducted in accordance with the Declaration of Helsinki and approval for the project was obtained from the research Ethics Committee of the University Jaume I of Castellon (Expedient Number CD/007/2019). This study is enrolled in the ClinicalTrails.gov database, with the code number NCT03990259 (www.clinicaltrials.gov).

**Informed Consent Statement:** Informed consent was obtained from all volunteers involved in the study.

**Data Availability Statement:** Data is contained within the article or supplementary material.

**Conflicts of Interest:** The authors declare no conflict of interest.