*5.5.1 Antithyroid drugs*

ATD are the first choice for treatment of Graves' Disease during pregnancy. Propylthiouracil (PTU) and methimazole (MMI) are equally effective in the management of hyperthyroidism during pregnancy. Propylthiouracil and methimazole inhibit thyroid hormone synthesis by interfering with intrathyroidal iodine utilization and the iodotyrosine coupling reaction, both of which are catalyzed by thyroid peroxidase. Antithyroid drugs do not directly affect iodine uptake or hormone release by the thyroid. Because of this, the clinical and hormonal improvement is delayed for 10-14 days after their implementation in the therapeutic regimen. PTU, but not methimazole, inhibits the conversion of T4 to T3 in peripheral tissues, thus theoretically it can ensure faster alleviation of the symptoms and reaching the desired levels of FT4. In clinical practice this is not considered relevant. Comparative study showed that methimazole generally normalizes serum T4 and T3 levels faster than PTU [71]. Both antithyroid agents are well absorbed from the gastrointestinal tract. They differ in their ability to bind to proteins in circulation, with PTU being strongly protein-bound, mainly to albumin, at physiologic pH, while methimazole binding to proteins is negligible [72]. Other studies have found that both drugs readily cross the placenta [73, 74]. The serum half-lives of PTU and methimazole are 1 and 4 to 6 hours, respectively. The intrathyroidal duration of action of both drugs is longer than that. Both drugs are metabolized in the liver and their metabolites are excreted by the kidney. However, so far there are no data, that the doses used to treat hyperthyroidism generally need to be altered in patients with liver or kidney disease. This characteristic, apart from their side effects, may determine the choice of the antithyroid drug in pregnancy and lactation, since PTU crosses the placenta and breast epithelium less readily than methimazole. So it is reasonable to begin therapy with PTU because there are no reported cases of PTU-associated aplasia cutis. However, if a woman cannot tolerate PTU for any reason, experience side effects does not want to take the prescribed number of pills (PTU usually requires multiple daily dosages, whereas MMI can often be given once daily), MMI may be substituted. The initial dose rarely exceeds more than 450 mg of PTU or 30 mg of MMI daily in order to achieve the predefined levels of FT4 and TSH. The median time, usually seven to eight weeks, to normalization of the maternal FT4 index for both PTU and MMI is equal [75], but improvement in these parameters may be seen earlier at three to four weeks. This fact, makes clinically relevant to reassess maternal FT4 or total T4 at an interval of three to four weeks and to adjust ATD dosage appropriately based upon the current levels of thyroid hormones. We should keep in mind, that maternal serum TSH levels may remain suppressed for several weeks after normalization of thyroid hormone levels. So measuring TSH level is not helpful early in treatment, and may mislead us to continue with the unnecessary high dose of ATD, causing drug induced hypothyroidism and thus depriving the developing fetus from crucially important maternal T4 delivery. As was discussed above, due to the changes of the activity of Graves' Disease throughout pregnancy, determined by fluctuations of TRAbs concentrations, in the late second and third trimesters the dose of ATD can be reduced or even stopped by 32 to 34 weeks of gestation in 30% of women [76]. Of course, the

same spectrum of adverse effects related to ATD therapy in the nonpregnant state applies to use during gestation.

Both drugs are showing similar fetal outcomes, in terms of thyroid function. The risk for congenital abnormalities had been considered to be higher in MMI than in PTU.

Aplasia cutis and also other malformations have been reported in the offspring of mothers who had taken methimazole during pregnancy [67, 77]. Aplasia cutis is a congenital localized absence of skin that occurs spontaneously in approximately 1 in 2000 births [78]. Many years, the fear from the possible development of this complication had restricted the use of methimazole during pregnancy, nevertheless, there is no definitive proof that MMI is actually responsible for the condition. Additional possible congenital malformation in children exposed to MMI during the first trimester of pregnancy are choanal and esophageal atresia, minor facial abnormalities and psychomotor delay, which either isolated or associated with aplasia cutis define the so called methimazole embryopathy [67, 77].

Because there are no reports of aplasia cutis in association with PTU, this drug is preferred by some physicians. Growing data from the literature for the causative roll of PTU for acute liver injury, had limited the use of the drug only during the first trimester of the pregnancy due to its lower risk for congenital malformations. Before pregnancy and during the second and third trimester methimazole is preferred, considered to be less hepatotoxic. Pregnancy itself does not appear to alter the maternal pharmacokinetics of MMI, although serum PTU levels may be lower in the latter part of gestation compared to the first and second trimesters [71].

The treatment of Graves' Disease during pregnancy should aim to achieve normalization of FT4 and FT3 levels with strict monitoring of maternal thyroid function at an appropriate intervals. Careful surveillance of fetal development to optimize fetal outcomes is also important, and this makes the team approach with a close collaboration between endocrinologist and obstetrician crucial. Apart from monitoring the laboratory parameters, there are clinical signs of improvement, that include maternal weight gain, decrease in pulse rate and appropriate fetal growth, that should be followed up. Clinical signs and laboratory values must always be considered together when a therapeutic decision is necessary, and if for example, there is a detected lack of maternal weight gain in conjunction with mild elevations in thyroid hormone levels, the initiation of a low dose of ATD should be considered.

#### *<IP_ADDRESS> Antithyroid drugs: effect on the Fetus*

In pregnancies complicated with concomitant Graves' Disease, fetal thyroid status is influenced by two maternal factors, both of which cross the placenta: maternal ATD dosage and maternal TRAb activity. There are two potentially opposing influences on fetal thyroid function by maternal TRAb, because they can be with either stimulating or blocking effect on the developing fetal thyroid gland. Different assays for maternal TRAb exist. Some, like one of the most commonly used radioreceptor assay does not distinguish between blocking and stimulating antibodies, so their peripheral effect can be estimated only by assessing the thyroid function [79]. The currently available bioassay is the thyroid stimulating immunoglobulin (TSI), which measures the generation of cyclic adenosine monophosphate by cells that express TSH receptor when incubated with the patient's serum [66].

Because both PTU and MMI can cross the placenta and they may decrease fetal thyroid hormone production The dose–response relationship between maternal ATD dose and neonatal thyroid function is controversial, as some studies have

#### *Graves' Disease and Pregnancy DOI: http://dx.doi.org/10.5772/intechopen.97640*

reported a direct correlation [66, 69, 80] and others have not demonstrated this [64, 69, 73]. There are data showing that ATD drugs even at low daily dosages (PTU ≤ 100 mg, MMI ≤ 10 mg) at term may affect the fetal thyroid function. An elevated cord TSH level was found in 23% of babies born to such PTU-treated mothers and in 14% of those treated MMI [81]. There is an individual variability in serum PTU and MMI levels after a standard oral dose and that could partly explain the observed lack of correlation between maternal dosage and fetal thyroid function [81, 82]. Transplacental passage of maternal TRAb resulting in excessive fetal thyroid stimulation is the second factor that can influence fetal thyroid function. Usually, this becomes clinically relevant at 24 to 26 weeks, of gestation. Maternal levels reflect the degree of fetal exposure [83]. At term there is a strong correlation between maternal and cord TRAb levels with development of neonatal hyperthyroidism. Clinically relevant is to measure the maternal TRAb levels at term, because the combination of continued use of maternal ATD therapy with low maternal TRAb levels may lead to elevated serum TSH levels in approximately 50–60% of infants [80]. This shows how important is to adjust appropriately the maternal ATD dosage during pregnancy especially when maternal immune thyroid stimulation is low. In nonimmune types of thyrotoxicosis, like toxic adenoma for example, dose relationship between ATD and the risk of suppression of the fetal thyroid function is more profound, since there is no contribution of fetal thyroid stimulation by the maternal immune system. Therefore, it is not surprising that fetal thyroid status is not strictly correlated with maternal ATD dosage. Inappropriately high doses of ATD may result in development of fetal or neonatal goiter, which in the most severe cases if markedly enlarged at birth may cause respiratory distress. In the past, due to the concomitant iodide therapy and ATD, goiter occurred more frequently. The combined inhibitory effect on the fatal thyroid gland of iodide and ATD resulted in the development of goiter. One clinical approach is to perform a fetal utrasound in all women who are still taking relatively high ATD doses at 26 to 28 weeks (PTU ≥450 mg/day, MMI ≥30 mg/day) [84]. If a fetal goiter is detected this could be due to either fetal hyperthyroidism, transplacental passage of stimulating TRAbs, or to fetal hypothyroidism caused by transplacental passage of maternal ATD therapy. In both situations intrauterine growth retardation may occur. The presence of fetal tachycardia (160–180 beats per minute) and advanced fetal bone age is highly suggestive of hyperthyroidism [85, 86]. When caused by maternal ATD use, a quick resolution within two weeks after birth of the neonatal goiter is observed, reflecting the discontinuation of drug exposure [69]. Therefore, stopping maternal ATD therapy and monitoring the fetal goiter by ultrasound is advisable. Other therapeutic approach for treatment of the fetal goiter due to maternal ATD exposure includes intra-amniotic levothyroxine injections [87, 88], but because it was done concomitantly with lowering of the maternal PTU dose, it is difficult to estimate the relative importance of each factor on the resolution of the fetal goiter. The cessation of maternal ATD therapy alone may result in decrease in the fetal goiter assessed ultrasonographically [89]. Discontinuation or decreasing the dose of ATD therapy is crucial in cases where hypothyroidism is suspected because of transplacental ATD passage. Fetal goiter must be followed with sequential ultrasounds and if no reduction in size, within two to three weeks, occurs, fetal thyroid function should be determined by performing periumbilical blood sampling, and intra-amniotic levothyroxine therapy should considered if necessary. Several studies have reported no cognitive and somatic defects in development of children exposed to maternal ATD in utero [90–93] and this was so even after accounting for higher dosage or first trimester exposure. These were cross sectional studies that measured cognitive development by intelligence quotient. Therefore, it is unknown if transient, or more subtle developmental changes might have been present.

#### *5.5.2 Beta-adrenergic blockers*

Considering the relation between thyroid hormones and sympathetic nervous system, beta-adrenergic blocking agents may be used transiently to control adrenergic symptoms, while waiting for ATD therapy to decrease thyroid hormone levels. The fact, that combined use of ATD and propranolol in comparison with ATD alone was related with a higher rate of spontaneous first trimester miscarriages, although the similar levels of thyroid hormone [94], beta-blockers should be used for short period and with caution.

#### *5.5.3 Iodides*

As was previously discussed, chronic use of iodides during pregnancy has been associated with hypothyroidism and goiter in neonates, sometimes in severe cases resulting in asphyxiation because of tracheal obstruction [95]. Iodides should not be used as a first line therapy in women with Grave's because of the well-known dual effect of iodine upon the thyroid function and the risk for provocation of a latent autoimmune disorder and also for aggravation of the thyrotoxicosis increasing the iodine store in an already hyperfunctioning thyroid gland. Iodides could be used transiently if needed in preparation for thyroidectomy.

#### *5.5.4 Surgery*

Subtotal thyroidectomy for Graves' Disease is rarely considered during pregnancy. The reasons for such treatment could be the need to use high levels of ATD (PTU 450 mg/day, MMI 40 mg/day) to control the clinical symptoms and thyroid hormonal levels, if compressive symptoms due to goiter size develop or if a patient is allergic to ATD therapy or noncompliant to the therapeutic regiment. The surgery is usually performed in latter half of the second trimester. The surgery in the first trimester is relatively contraindicated, because that this is the time of the highest spontaneous abortion rate and surgery and anesthesia could possibly further increase the risk, but if clinically indicated subtotal thyroidectomy may be done in some specific cases [96].

#### *5.5.5 131I therapy*

The use of 131I therapy is completely contraindicated in pregnancy. The most vulnerable for the fetus period to 131I therapy is that after 12 weeks gestation, because at this period the fetal thyroid begins to concentrate radioiodine at higher rate than the maternal thyroid and other fetal tissues are generally more radiosensitive [97]. It is essentially important to exclude pregnancy in all women prior to radioiodine therapy. The therapeutic administration of 131I to a nursing mother is contraindicated and lactation should be stopped immediately if this occurs.

#### **5.6 Lactation**

Because the ATD present in breast milk in sufficient concentrations that can influence infant's thyroid, their use in breast-feeding women was considered contraindicated. Due to the ability of PTU to bind more tightly with protein than MMI, less amount of PTU is available in the milk. The ratio of milk to serum levels is found to be lower for PTU (0.67) [98] than for MMI (1.0) [99], moreover the amount of ingested drug secreted in breast milk is approximately six

*Graves' Disease and Pregnancy DOI: http://dx.doi.org/10.5772/intechopen.97640*

times higher for MMI than for PTU (0.14 vs. 0.025% of the ingested dose) [99]. Despite this, the fetal thyroid function assessed in newborns breast-fed by mothers treated with ATD with daily doses of PTU (50–300 mg), MMI (5–20 mg), or carbimazole (5–15 mg) for periods ranging from three weeks to eight months, remained normal, even in overtreated women with elevated serum TSH levels [100]. Data from the literature show that ATD therapy (PTU 300 mg/day, MMI 20 mg/day) may be considered relatively safe during lactation [100]. Generally, PTU would be preferred than MMI, because of its less availability in breast milk. It is wise the drug to be taken by the mother after a feeding.


**3. Decision Support Systems Development: Challenges and Trade-offs**

A number of methodologies and software applications were used to develop the decision support tools above described (Table 1). The goal always remained to provide solid, but user-friendly DSS tools. The methodology as well as the software application approach fol‐ lowed the tool development and the ultimate goal pursued and not vice versa. It was usual to combine and adapt methodologies within a particular tool development. Following is a succinct description of the most important methodologies used for the DairyMGT.info DSS tools and a discussion of the approaches used for the software applications.

### **3.1. Methodologies used for the Decision Support System Tools**

#### *3.1.1. Partial Budgeting*

Partial budgeting compares a current with an alternative technology by balancing the eco‐ nomics of 4 elements that are assessed before and after the adoption of the alternative tech‐ nology: 1) additional returns (adds), 2) reduced costs (adds), 3) returns foregone (subtracts), and 4) additional costs (subtracts) [23]. Partial budgeting could be a robust methodology when a direct change is expected from the new technology without major interaction with other system components beyond the analyzed variables. Partial budgeting is the underline methodology to assess the break-even level of using feed additives, the economic benefit of milking 3 times a day, the economic evaluation of using rbST, the assessment of corn feed‐ ing strategies, and the assessment of income over feed cost by different diets under com‐ modity price changes.

**Decision Support System Tool**

Dairy Ration Feed Additive Break-Even

Dairy Cattle

Reproductive Efficiency

Income over Feed Cost

Production and Productivity

Grouping Strategies for Feeding Lactating

Exploring Pregnancy Timing Impact on

Economic Value of Sexed Semen for Dairy

Heifer Management and Cow Replacement

Economic Analysis of Switching from 2X to 3X

DSS Program for Dairy Production and

Price Risk Management and Financial

Expansion

Assessment

LGM-Analyzer

LGM-Premium Estimator

**Underline Methodology**

Mathematical Simulation

Mathematical Simulation

FeedVal 2012 Matrix Solution Online Dairy Extension Feed Cost Evaluator Database Management Online Optigen® Evaluator Matrix Solution Online

Analysis Partial Budgeting Flash

Heifers Decision Analysis Flash/Online UW-DairyRepro\$ Decision Analysis Spreadsheet Dairy Reproductive Economic Analysis Markov Chains Online

Heifer Break-Even Enterprise Budgets Online/Spreadsheet

Heifer Replacement Decision Analysis Spreadsheet/Online The Economic Value of a Dairy Cow Markov Chains Online/Spreadsheet

Cost-Benefit of Accelerated Feeding Programs Cost Benefit Flash/Online

Milk Curve Fitter Nonlinear Optimization Installation3

Milking Partial Budgeting Flash Economic Analysis of using rbST Partial Budgeting Flash

LGM-Least Cost Optimizer Nonlinear Optimization Online

Lactation Benchmark Curves for Wisconsin Database Management Flash/Spreadsheet

Markov Chains Spreadsheet

Online

Online

Mathematical Simulation

Mathematical Simulation

**Software Application**

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155

DairyMGT: A Suite of Decision Support Systems in Dairy Farm Management

Online

Online

#### *3.1.2. Cost Benefit*

The cost benefit methodology is similar to partial budgeting but determines profitability of a new technology over longer periods of time and therefore requires the specification of a dis‐ count rate that is used to calculate a net present value [23]. The cost benefit is the underline methodology for calculating the value of adopting accelerated heifer liquid feeding pro‐ grams and is as a supporting methodology to find out the economic value of sexed semen for dairy heifers, the value of reproductive programs in adult cows, and to assess the net present value of alternative scenarios of possible dairy farm expansion or modernization.

#### *3.1.3. Decision Analysis*

The decision analysis is appropriate when probabilistic distributions are important factors in determining the final outcomes [24] as it occurs when analyzing the value of using sexed se‐ men on heifers, comparing the value of reproductive programs in adult cows, or projecting the replacement flow needed to maintain the herd size. In the first two cases, conditional probabilities were used to successively determine populations of pregnant, non-pregnant, and eligible to breed animals along with their respective expected monetary contributions. In the case of the replacement flow tool, transition probabilities are used to dynamically project the herd dynamics across time.

**3.1. Methodologies used for the Decision Support System Tools**

Partial budgeting compares a current with an alternative technology by balancing the eco‐ nomics of 4 elements that are assessed before and after the adoption of the alternative tech‐ nology: 1) additional returns (adds), 2) reduced costs (adds), 3) returns foregone (subtracts), and 4) additional costs (subtracts) [23]. Partial budgeting could be a robust methodology when a direct change is expected from the new technology without major interaction with other system components beyond the analyzed variables. Partial budgeting is the underline methodology to assess the break-even level of using feed additives, the economic benefit of milking 3 times a day, the economic evaluation of using rbST, the assessment of corn feed‐ ing strategies, and the assessment of income over feed cost by different diets under com‐

The cost benefit methodology is similar to partial budgeting but determines profitability of a new technology over longer periods of time and therefore requires the specification of a dis‐ count rate that is used to calculate a net present value [23]. The cost benefit is the underline methodology for calculating the value of adopting accelerated heifer liquid feeding pro‐ grams and is as a supporting methodology to find out the economic value of sexed semen for dairy heifers, the value of reproductive programs in adult cows, and to assess the net present value of alternative scenarios of possible dairy farm expansion or modernization.

The decision analysis is appropriate when probabilistic distributions are important factors in determining the final outcomes [24] as it occurs when analyzing the value of using sexed se‐ men on heifers, comparing the value of reproductive programs in adult cows, or projecting the replacement flow needed to maintain the herd size. In the first two cases, conditional probabilities were used to successively determine populations of pregnant, non-pregnant, and eligible to breed animals along with their respective expected monetary contributions. In the case of the replacement flow tool, transition probabilities are used to dynamically

> **Underline Methodology**

Corn Feeding Strategies Partial Budgeting Flash1 Income Over Feed Cost Partial Budgeting Flash

Income over Feed Supplement Cost Linear Programming Spreadsheet/

**Software Application**

Online2

*3.1.1. Partial Budgeting*

154 Decision Support Systems

modity price changes.

*3.1.3. Decision Analysis*

project the herd dynamics across time.

Feeding and Nutrition

**Decision Support System Tool**

*3.1.2. Cost Benefit*

tools, as these are less computationally demanding than alternative methods. Markov chains are therefore important part of the DairyMGT.info DSS tools and are the backbone structure of the tools: seasonal manure prediction, dynamic dairy farm model, reproductive economic analysis, and the economic value of a dairy cow. Markov chains are also important part of the tools dealing with expansion and modernization and the one comparing the value of dif‐

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157

Mathematical simulation and projection is a general description that encompass a group of di‐ verse and integrated empirical techniques and algorithms that have as main goal to represent observed data as it happens in real-life situations when not a single method fits this condition to satisfaction. Mathematical simulation and projection is used in most of the DairyMGT tools. However, it is a core methodology in a group of them. For example, mathematical simulation is used in the grouping tool to calculate feed nutrient requirements for every single cow in a herd; in the timing of pregnancy tool to aggregate the overall milk production and feed consump‐ tion a cow will have depending on the time of pregnancy; and in all LGM related tools to gener‐ ate thousands of replicates and calculate the statistics of net margins that will determine insurance premiums [27]. Also mathematical simulation and projection is important to predict cash flows within the expansion tool and to perform nutrient balances in tools such as dairy

Nonlinear optimization deals with finding an objective function of maximizing or minimiz‐ ing a variable within a set of simultaneous constraints, where the objective function or some of the constraints have nonlinear relationships. Nonlinear optimization adds a set of com‐ plexity to the implementation of decision support tools because it is computational demand‐ ing. However, for some applications it is required. Since finding the global maxima for nonlinear problems it is not always possible, a compromise between finding a satisfactory answer and maintain the applications as user-friendly as possible is needed. Nonlinear opti‐ mization is used in the grouping, milk curve fitter, and LGM least cost optimizer tools. For the grouping tool, a nonlinear optimization algorithm groups lactating cows according to nutritional requirements with the objective function of finding the aggregated maximum in‐ come over feed cost through recursive iterations by allocating cows to size-defined groups. In the milk curve fitter tool, the user enters farm herd milk production and a nonlinear algo‐ rithm minimizes the residual difference between the farm observed data and the predicted data adjusted to a pre-defined milk lactation function such as Wood [28] or MilkBot [29]. The results are coefficients of the defined function that best represent farm-specific lactation curves. The LGM-least cost uses a nonlinear optimization to find out the minimum premi‐ um price to a defined target guarantee net income over feed cost according to future project‐ ed commodity prices and farm specific conditions, replicating the rules governing the insurance product. The result is the least cost premium for a determined level of coverage

ferent reproductive programs for adult cows.

*3.1.7. Mathematical Simulation and Projection*

dynamic model, dairy nutrient manager, and grazing-N.

within the LGM-Dairy insurance structure [30-31].

*3.1.8. Nonlinear Optimization*

**Table 1.** Principal methodology and software application of DairyMGT.info decision support system tools.1Flash: Macromedia Flash. 2Online tools use a combination of software including HTML, PHP, JavaScript, C, CSS, and MySQL. 3Requires software installation in local machine.

#### *3.1.4. Enterprise Budgets*

Enterprise budgets are a systematic way to list returns and costs and evaluate profits from inside a specific business enterprise [25] within the dairy farm. This methodology is used to calculatethe heifer break-even by contrasting heifers' rearing costs with potential benefits. This methodology is also used, in more detail, in the tool working capital to project the cash flow of a dairy farm enterprise.

#### *3.1.5. Linear Programming*

Linear programming is a mathematical optimization algorithm to maximize or minimize a goal (e.g., maximum profit or minimum costs) within a set of constraints represented as linear relationships [26]. Linear programming is at the core of the tool income over feed supplementation cost in determining the diet composition that results in the maximum net return within a set of constraints of available feed ingredients. Linear programming is also used recursively in the dynamic dairy farm model to maximize the farm net return while minimizing nitrogen leaching.

#### *3.1.6. Markov Chains*

Markov chains are a mathematical system that undergoes transitions from one state to the next within a finite space of states as random processes. In dairy farming, Markov chains are widely used for decision-making to predict herd demographics or to project cows' probabil‐ istic life [2, 10, 12, 19-20]. Markov chains are also very useful to implement decision support tools, as these are less computationally demanding than alternative methods. Markov chains are therefore important part of the DairyMGT.info DSS tools and are the backbone structure of the tools: seasonal manure prediction, dynamic dairy farm model, reproductive economic analysis, and the economic value of a dairy cow. Markov chains are also important part of the tools dealing with expansion and modernization and the one comparing the value of dif‐ ferent reproductive programs for adult cows.

#### *3.1.7. Mathematical Simulation and Projection*

**Decision Support System Tool**

Environmental Stewardship

Dairy Nutrient Manager

3Requires software installation in local machine.

Grazing-N

156 Decision Support Systems

*3.1.4. Enterprise Budgets*

flow of a dairy farm enterprise.

while minimizing nitrogen leaching.

*3.1.5. Linear Programming*

*3.1.6. Markov Chains*

LGM-Net Guarantee Income Over Feed Cost

**Underline Methodology**

Mathematical

Mathematical

Mathematical

Wisconsin Dairy Farm Benchmarking Tool Database Management Online/Spreadsheet

Working Capital Decision Support System Enterprise Budgets Spreadsheet

Dynamic Dairy Farm Model Markov Chains Spreadsheet

Seasonal Prediction of Manure Excretion Markov Chains Spreadsheet

**Table 1.** Principal methodology and software application of DairyMGT.info decision support system tools.1Flash: Macromedia Flash. 2Online tools use a combination of software including HTML, PHP, JavaScript, C, CSS, and MySQL.

Enterprise budgets are a systematic way to list returns and costs and evaluate profits from inside a specific business enterprise [25] within the dairy farm. This methodology is used to calculatethe heifer break-even by contrasting heifers' rearing costs with potential benefits. This methodology is also used, in more detail, in the tool working capital to project the cash

Linear programming is a mathematical optimization algorithm to maximize or minimize a goal (e.g., maximum profit or minimum costs) within a set of constraints represented as linear relationships [26]. Linear programming is at the core of the tool income over feed supplementation cost in determining the diet composition that results in the maximum net return within a set of constraints of available feed ingredients. Linear programming is also used recursively in the dynamic dairy farm model to maximize the farm net return

Markov chains are a mathematical system that undergoes transitions from one state to the next within a finite space of states as random processes. In dairy farming, Markov chains are widely used for decision-making to predict herd demographics or to project cows' probabil‐ istic life [2, 10, 12, 19-20]. Markov chains are also very useful to implement decision support

Simulation Spreadsheet

Simulation Spreadsheet

Simulation Spreadsheet

LGM-Dairy Feed Equivalent Matrix Solution Online

**Software Application**

> Mathematical simulation and projection is a general description that encompass a group of di‐ verse and integrated empirical techniques and algorithms that have as main goal to represent observed data as it happens in real-life situations when not a single method fits this condition to satisfaction. Mathematical simulation and projection is used in most of the DairyMGT tools. However, it is a core methodology in a group of them. For example, mathematical simulation is used in the grouping tool to calculate feed nutrient requirements for every single cow in a herd; in the timing of pregnancy tool to aggregate the overall milk production and feed consump‐ tion a cow will have depending on the time of pregnancy; and in all LGM related tools to gener‐ ate thousands of replicates and calculate the statistics of net margins that will determine insurance premiums [27]. Also mathematical simulation and projection is important to predict cash flows within the expansion tool and to perform nutrient balances in tools such as dairy dynamic model, dairy nutrient manager, and grazing-N.

#### *3.1.8. Nonlinear Optimization*

Nonlinear optimization deals with finding an objective function of maximizing or minimiz‐ ing a variable within a set of simultaneous constraints, where the objective function or some of the constraints have nonlinear relationships. Nonlinear optimization adds a set of com‐ plexity to the implementation of decision support tools because it is computational demand‐ ing. However, for some applications it is required. Since finding the global maxima for nonlinear problems it is not always possible, a compromise between finding a satisfactory answer and maintain the applications as user-friendly as possible is needed. Nonlinear opti‐ mization is used in the grouping, milk curve fitter, and LGM least cost optimizer tools. For the grouping tool, a nonlinear optimization algorithm groups lactating cows according to nutritional requirements with the objective function of finding the aggregated maximum in‐ come over feed cost through recursive iterations by allocating cows to size-defined groups. In the milk curve fitter tool, the user enters farm herd milk production and a nonlinear algo‐ rithm minimizes the residual difference between the farm observed data and the predicted data adjusted to a pre-defined milk lactation function such as Wood [28] or MilkBot [29]. The results are coefficients of the defined function that best represent farm-specific lactation curves. The LGM-least cost uses a nonlinear optimization to find out the minimum premi‐ um price to a defined target guarantee net income over feed cost according to future project‐ ed commodity prices and farm specific conditions, replicating the rules governing the insurance product. The result is the least cost premium for a determined level of coverage within the LGM-Dairy insurance structure [30-31].

#### *3.1.9. Matrix Solution to Multiple Equations*

Matrix or algebra simultaneous equation solution is helpful in the area of nutrition and feed‐ ing to replace feed ingredients and maintain same level nutritional of the diet and same lev‐ el of feed intake. It is also useful to value feeds depending on their nutrients content. Each feed ingredient is defined in function of its nutrient contents and its market price. When the number of nutrients equals to the number of feed ingredients (same number of equations as unknowns) the result is an exact value for each nutrient and therefore the predicted value of a feed ingredient is equal to the input value as it is the case in the Optigen Evaluator tool [32]. Similar approach is used for the LGM-feed equivalent, which converts any feed ingre‐ dient into equivalents of corn and soybean meal, as it is required for LGM-Dairy insurance contracts. The tool FeedVal 2012 goes beyond and analyzes a set of user-defined matrix be‐ tween 2 and 50 ingredients and between 2 and 13 nutrients to find out the difference be‐ tween the feed ingredient market price and the estimated price based on the nutrient composition value of the ingredient.

the National Research Council model of nutrient requirement for dairy animals [34] accord‐

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According to the type of application, the methodologies used in the tool, and, most impor‐ tantly, the goal of the tool as a DSS, different software application approaches were used (Table 1). Most of the tools have been developed in different software applications with the objective of better meeting user styles and therefore capture larger audiences of users.

Spreadsheet applications are a very popular format among dairy farmers and consultants because of their familiarity with them, the possibility of using the same spreadsheet for fur‐ ther analyses, and the capacity of save and maintain a copy of it in a personal computer. Spreadsheet application was the elected method for a number of DairyMGT.info tools (Table 1). Most of the spreadsheet applications, however,required some type of Visual Basic code

Other group of tools uses Macromedia Flash as the software application. Macromedia Flash has the advantage of having a nice interactive visual interface connected with a calculator. From the point of view of the user, Flash tools are probably the easiest to use. They havethe ad‐ ditional advantage of becoming stand-alone applications and therefore of being used offline or embedded in Power Point presentations or Portable Document Format (PDF) files. One prob‐ lem with Flash applications is, however, its limited computational functionality. Flash applica‐ tions have only a set of limited mathematical functions without the possibility of using macros or combinethemwith code programming. Also Flash applications are not compatible with Ap‐ ple smart phones and tablets. Current tools that are only Flash applications within the Dai‐

Other group of tools can be classified in the general category of online tools. These use an array of different software applications. What they all have in common is that these work in any web browser and eventually in any device and in any platform including smart phones, tablets, Ap‐ ple, Linux, PC, etc. Calculations and analyses are normally performed in the DairyMGT.info web server, so the online tool is only an interface between the device of the user and the server. In general, online tools are very efficient and reliable tools that have the advantage to be al‐ ways up-to-date: users always experience the latest version of the tool. Other important ad‐ vantage is that complex processes and mathematical calculations can be managed using a combination of web code such as HTML (hyper text markup language), PHP (hypertext pre‐ processor), JavaScript (prototype-based scripting language), C (general-purpose language), CSS (style sheet language), MySQL (relational database management system), or others. An‐ other advantage of online tools is that their design layout can be very efficient and solid once the tool is deployed. A drawback for developing online tools, however, is the need of expertise in web-based code writing. Nonetheless, online tools are very efficient and probably a trend to

ryMGT.info DSS tools will eventually be converted also to be online applications.

which many of the tools of DairyMGT.info will continue to gravitate.

ing to a set of characteristics that include age, production, and live weight.

**3.2. Software Applications**

embedded into the application (macros).

#### *3.1.10. Database Management and Analysis*

Some tools require a database interface and some mechanism of querying the database to retrieve information and to perform analysis dynamically and efficiently. Databases are per‐ manently being updated. Database tools are the lactation benchmark curves and the dairy farm ratio benchmarking. The user does not update these database applications directly, but a server manager. The user queries the database and is able to compare specific farm data with a set of filtered information within the databases. Other type of database application is the feed evaluator tool that registers users in the system and allows them to enter and save their data. The users update the database and the queries retrieve real-time information any‐ time. Users can then compare their own data against to a filtered group of other farms. A different concept is portrayed in all LGM related tools for which all the data (commodity prices of milk, corn, and soybean meal from the future markets) is retrieved real-time from the official sources anytime the user performs an analysis [29]. The calculation of either LGM premiums or least cost premiums changes depending not only on the user inputs, but also based upon the time of the query. The system saves historical information, so users can also do retrospective analyses.

#### *3.1.11. External Simulation Models*

Some tools require to be integrated with more complex, fully developed and established models. That is for example the case of the Dynamic Dairy Farm Model and the Grazing-N tools. In the first case, model requires assessments of crop production (corn, soybean, pas‐ tures, etc.), which are performed by using external crop simulation models from the family of Decision Support System for Agrotechnology Transfer [33]. The dynamic dairy farm model feeds the crop simulation model with data of soils, weather, and crop management schemes and the crop simulation models return predicted biomass produced, nutrient uti‐ lization, and nitrogen leaching from the soil. The Grazing-N application is integrated with the National Research Council model of nutrient requirement for dairy animals [34] accord‐ ing to a set of characteristics that include age, production, and live weight.

#### **3.2. Software Applications**

*3.1.9. Matrix Solution to Multiple Equations*

158 Decision Support Systems

composition value of the ingredient.

also do retrospective analyses.

*3.1.11. External Simulation Models*

*3.1.10. Database Management and Analysis*

Matrix or algebra simultaneous equation solution is helpful in the area of nutrition and feed‐ ing to replace feed ingredients and maintain same level nutritional of the diet and same lev‐ el of feed intake. It is also useful to value feeds depending on their nutrients content. Each feed ingredient is defined in function of its nutrient contents and its market price. When the number of nutrients equals to the number of feed ingredients (same number of equations as unknowns) the result is an exact value for each nutrient and therefore the predicted value of a feed ingredient is equal to the input value as it is the case in the Optigen Evaluator tool [32]. Similar approach is used for the LGM-feed equivalent, which converts any feed ingre‐ dient into equivalents of corn and soybean meal, as it is required for LGM-Dairy insurance contracts. The tool FeedVal 2012 goes beyond and analyzes a set of user-defined matrix be‐ tween 2 and 50 ingredients and between 2 and 13 nutrients to find out the difference be‐ tween the feed ingredient market price and the estimated price based on the nutrient

Some tools require a database interface and some mechanism of querying the database to retrieve information and to perform analysis dynamically and efficiently. Databases are per‐ manently being updated. Database tools are the lactation benchmark curves and the dairy farm ratio benchmarking. The user does not update these database applications directly, but a server manager. The user queries the database and is able to compare specific farm data with a set of filtered information within the databases. Other type of database application is the feed evaluator tool that registers users in the system and allows them to enter and save their data. The users update the database and the queries retrieve real-time information any‐ time. Users can then compare their own data against to a filtered group of other farms. A different concept is portrayed in all LGM related tools for which all the data (commodity prices of milk, corn, and soybean meal from the future markets) is retrieved real-time from the official sources anytime the user performs an analysis [29]. The calculation of either LGM premiums or least cost premiums changes depending not only on the user inputs, but also based upon the time of the query. The system saves historical information, so users can

Some tools require to be integrated with more complex, fully developed and established models. That is for example the case of the Dynamic Dairy Farm Model and the Grazing-N tools. In the first case, model requires assessments of crop production (corn, soybean, pas‐ tures, etc.), which are performed by using external crop simulation models from the family of Decision Support System for Agrotechnology Transfer [33]. The dynamic dairy farm model feeds the crop simulation model with data of soils, weather, and crop management schemes and the crop simulation models return predicted biomass produced, nutrient uti‐ lization, and nitrogen leaching from the soil. The Grazing-N application is integrated with

According to the type of application, the methodologies used in the tool, and, most impor‐ tantly, the goal of the tool as a DSS, different software application approaches were used (Table 1). Most of the tools have been developed in different software applications with the objective of better meeting user styles and therefore capture larger audiences of users.

Spreadsheet applications are a very popular format among dairy farmers and consultants because of their familiarity with them, the possibility of using the same spreadsheet for fur‐ ther analyses, and the capacity of save and maintain a copy of it in a personal computer. Spreadsheet application was the elected method for a number of DairyMGT.info tools (Table 1). Most of the spreadsheet applications, however,required some type of Visual Basic code embedded into the application (macros).

Other group of tools uses Macromedia Flash as the software application. Macromedia Flash has the advantage of having a nice interactive visual interface connected with a calculator. From the point of view of the user, Flash tools are probably the easiest to use. They havethe ad‐ ditional advantage of becoming stand-alone applications and therefore of being used offline or embedded in Power Point presentations or Portable Document Format (PDF) files. One prob‐ lem with Flash applications is, however, its limited computational functionality. Flash applica‐ tions have only a set of limited mathematical functions without the possibility of using macros or combinethemwith code programming. Also Flash applications are not compatible with Ap‐ ple smart phones and tablets. Current tools that are only Flash applications within the Dai‐ ryMGT.info DSS tools will eventually be converted also to be online applications.

Other group of tools can be classified in the general category of online tools. These use an array of different software applications. What they all have in common is that these work in any web browser and eventually in any device and in any platform including smart phones, tablets, Ap‐ ple, Linux, PC, etc. Calculations and analyses are normally performed in the DairyMGT.info web server, so the online tool is only an interface between the device of the user and the server. In general, online tools are very efficient and reliable tools that have the advantage to be al‐ ways up-to-date: users always experience the latest version of the tool. Other important ad‐ vantage is that complex processes and mathematical calculations can be managed using a combination of web code such as HTML (hyper text markup language), PHP (hypertext pre‐ processor), JavaScript (prototype-based scripting language), C (general-purpose language), CSS (style sheet language), MySQL (relational database management system), or others. An‐ other advantage of online tools is that their design layout can be very efficient and solid once the tool is deployed. A drawback for developing online tools, however, is the need of expertise in web-based code writing. Nonetheless, online tools are very efficient and probably a trend to which many of the tools of DairyMGT.info will continue to gravitate.


**3. Complications of fistula access**

Even though complications of fistula access are far less than a graft or a catheter, they do occur and need to be addressed. Complications occur in approximately one-third of fistulas and include: aneurysms, infection, stenosis, thrombosis, steal syndrome and heart failure. These complications have historically been classified as early and late failure. The etiology of both early and late are somewhat similar because if the cause is not diagnosed early on it may progress and lead to late access failure. Fistula failure may also be classified as primary defined as a fistula which fails prior to cannulation or secondary defined as failure after a radiologic intervention such as angioplasty or stent or surgical revision.


**5. Addressing sustainability planning in research project proposals: an exemplar**

In this section, sustainability planning in research project proposal development in higher education research is exemplified. This is done to drive home forcefully the thesis of the chapter that ensuring project sustainability requires more than addressing financial sustainability alone, and that donors look at critically, scrutinize and fund proposals on the basis of how they address financial sustainability vis-à-vis other different but equally important aspects of sustainability to ensure that these projects continue to exist to deliver required impacts even after primary funding from donors recede or dry out completely. To be able to do this, excerpts from a research project proposal submitted recently in responds to an Open Call for project proposals for funding from a renowned multilateral funding agency is drawn upon for purposes of exemplification. For purposes of succinctness of presentation, the issues to be presented are dealt with under three sub-headings, namely: information about the Open Call for proposals; addressing the development challenge and impact of the proposed African Centre of Excellence for

Educational Leadership and Teacher Training (ACE-ELTT); and outlining the sustainability plan for the proposed ACE-ELTT project.3

#### **5.1 Information about the open call for proposals**

The Africa Centres of Excellence for Development Impact (ACE Impact) project is an initiative of the World Bank which is being implemented through/by the Association of African Universities (AAU) to, among other things, improve the quality, quantity and development impact of postgraduate education (defined to include Master's and PhD degrees, and short term professional level courses and training) in selected universities in Africa through regional specialization and collaboration [26]. Each ACE Impact Centre proposed for funding is expected to identify an aspect of a developmental challenge (i.e. relative its host institution and country) that can be addressed with an integrated programme of work that is achievable over the period of four and half years project duration.

The ACE Impact project consists of three components, namely: establishing new and scaling-up well-performing existing ACEs for development impact; fostering regional partnerships for emerging centres and regional scholarships; and enhancing regional project facilitation, and monitoring and evaluation. This Call for Proposals, to which our research project team responded with a project proposal, is focused on the first of three components (i.e. establishing new and scaling-up well-performing existing ACEs for development impact).

As indicated in the Guidance Notes for the Open Call for proposals [26], Component 1 aims to build and strengthen the capacity of competitively selected ACE centres based in higher education institutions across West and Central Africa. To this end, each ACE centre is expected to address a regional development challenge through: higher quality postgraduate education addressing the skills gap and tackling priority applied research questions; leading regional education networks; and delivering short-term courses. In consultation with stakeholders, the centre are to update and/or launch new postgraduate degree programmes that are accredited to meet international high-quality standards. The centres are also expected to offer curricula that ensure that their students have the demanded competences upon graduating from their degree programmes, including analytical, digital, and entrepreneurial competencies.

According to the Guidance Notes for writing up proposals attached to the Open Call [26], partnerships with national, regional and global sectoral stakeholders (i.e. private enterprise, including but not limited to, multinational, regional, national or local enterprises; Ministries and other public authorities; chambers of commerce,; trade groups and professional associations; hospitals; policymakers; and other appropriate stakeholders) and academic institutions will ensure that the ACEs focus their activities on the education and research needs to solve specific problems associated with the targeted development challenge. Centres are expected to disseminate their research findings to policymakers and companies, as well as through international peer reviewed journals. Further, each Centre, according to the guidance notes, will be required to have policies backed by specific interventions in place to: (a) increase the number of females within their student body, faculty and academic leadership; and (b) ensure the overall well-being of their student population. Under this project, the Guidance Note adds, greater emphasis will be placed

3 The research proposal described in this chapter passed all the assessment evaluations for funding, and was particularly hailed by assessors for its sustainability strategies outlined. That notwithstanding, it is instructive to concede that the project was not funded eventually owing to infrastructural lapses on the part of UCC to house the ACE-ELTT to support project activities.

#### *Addressing Sustainability Planning in Higher Education Research DOI: http://dx.doi.org/10.5772/intechopen.93589*

on ensuring ACE host institutions are incentivized to undertake several activities, including those which promote good governance; data collection and management; and regionalization of their institutions, that is, taking steps to make their institutions regionally (and ultimately globally) competitive [26].

Overall, the expected results of the proposed project include:

Thus briefly, it is against this background that the research proposal being described in the context of this chapter was developed and submitted in response to the Open Call for funding to establish ACE to address a pertinent developmental challenge facing Ghana, and by extension, West Africa and sub-Saharan Africa region as a whole.


**1. Introduction**

TV White Space is the free channel or frequency range which was already dedicated for terrestrial television transmission in one country's boundary. The channels reserved for this primary use may be found free in time and spatial variations. The availability of free channels depends on these variations. The variations on the other hand resulted from geographical difference and other parameters. These parameters are factors on which different propagation models depend. Considering different parameters, the signal of TV propagation must be represented more closely to the natural signal loss of the propagation. For this comparison, different propagation models are taken in to account which have different response for different parameters. One may be very sensitive for frequency, where the other considers mainly the terrain and the other may be more sensitive to weather. In addition to these differences in consideration of different parameters, there are some parameters to affect all the models. Frequency is one of these parameters. The propagation losses have different values of sensitivity. Different sensitivity for frequency will cause different response for differences in frequency from very-high frequency (VHF) to ultra-high frequency (UHF). The difference is also not the same for the same variation in frequency for the two frequency ranges [1]. The availability of free channels directly related to the coverage of primary digital terrestrial TV (DTT) transmission system [2–5]. The coverage of incumbent system is directly related to pathloss models which are used to represent the signal propagation of TV signals. Its area of coverage is calculated by using the minimum receivable signal by the DTT receiver which is to be modeled with precise pathloss model [6]. If the pathloss model used for this modeling is very sensitive for frequency in VHF and UHF, it shows a significant variation in coverage area which may result in difference in number of available channels. So, we must select less sensitive model. Propagation models used for modeling the DTT signal, and also for tv white space (TVWS), must be perfect in operating under VHF and UHF band. Also, they must be models which can cover long range in signal propagation, since TV signals cover long distances with small power. In this paper, related works are revised in part II. The next part focuses on coverage determination factors. In IV, system model and problem formulation are discussed. After this, results are discussed and relevant conclusion is given then.


**OPHTHALMOLOGY - CURRENT CLINICAL AND RESEARCH UPDATES**

Edited by **Pinakin Gunvant Davey**

#### **Ophthalmology - Current Clinical and Research Updates**

http://dx.doi.org/10.5772/57076 Edited by Pinakin Davey

#### **Contributors**

Pinakin Davey, Makoto Ishikawa, Takeshi Yoshitomi, Yukitoshi Izumi, De-Quan Li, Cintia de Paiva, Stephen Pflugfelder, Balwant Singh Gendeh, Vikas Tah, Walid Sharif, James Myerscough, Kamran Saha, Stephen Tuft, Muhamad Ahad, Jason Ho, Bennett McAllister, Rebecca Kammer Od, Jie Shen, Elliot Marc Kirstein, Hezheng Zhou, Artashes Arto Zilfyan, Arto Zilfyan, Aaron Seitz, Jenni Deveau, Gary Lovcik, Felicia M. Ferreri, Italo Giuffre\', Ipek Midi, Magdalena Zdybel, Barbara Pilawa, Umit Yolcu, Omer Faruk Sahin, Fatih Cakir Gundogan, Roshini Sanders, Hannah Timlin, Peizeng Yang, Patricio Pacheco

#### **© The Editor(s) and the Author(s) 2014**

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#### **Notice**

Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book.

First published in Croatia, 2014 by INTECH d.o.o. eBook (PDF) Published by IN TECH d.o.o. Place and year of publication of eBook (PDF): Rijeka, 2019. IntechOpen is the global imprint of IN TECH d.o.o. Printed in Croatia

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**5. Discussion**

38 Recent Advances in Arthroplasty

sent questionnaires capturing both self-reported WOMAC scores and surgery satisfaction scores. Poor WOMAC functional status scores (< 60) were noted to be more frequent among patients of surgeons who performed fewer than 12 TKA/year (20%), and centers performing fewer than 10 TKA/year (19%), as compared to their higher-volume counterparts (12% and 10% amongst high-volume surgeons and hospitals, respectively). These findings were

Overall, the American experience is quite unique in that across the country there is a virtual myriad of low volume centers that coexist with some of the largest and highest volume centers in the world. The current body of data indicates that despite increasing volume trends for THA and TKA, the majority of these procedures in the United States are still being performed by surgeons who perform fewer than 30/year and centers performing fewer than 100/year. Several studies have demonstrated increased complications rates, including increased risk of infection, revision, and mortality among low-volume surgeons and centers. In particular, it is evident that very low provider volumes (fewer than 10/year) are more frequently associated with increased morbidity and mortality. However, consensus on a minimum individual or institutional volume threshold for optimal patient outcomes has not been reached. The data are less conclusive with respect to the relationship between provider volumes and length of hospital stay, with early studies showing shorter stays in low-volume centers and subsequent studies the reverse. Little has been published on the financial costs of care in high versus low-

Judge et al examined the effects of hospital surgical volumes and teaching center status on the outcomes of total joint replacement between 1997 and 2002 in the United Kingdom, looking at over 280,000 hip and 211,000 knee replacements11. They used National Health Service Hospital Episode Statistics and defined hospital volume groups of <51, 51-100, 101- 250, 251-500 and >500 procedures/year. They observed a decrease in patient mortality for both hip and knee replacement as volumes increased. Training institutions also had better THA outcomes, but no such effect was observed for TKA. Lower volume centers had longer

This study demonstrated that overall, in contrast to the US, most arthroplasty surgery in England was being done in proportionally higher-volume centers. This was true for each of the six years studied. This finding is not surprising as it is easier to consolidate health care resources in a geographically smaller country. Further, over 80% of surgical services in the

Results from Canadian volume-outcome studies have been mixed. Compared to their southern neighbors, Canadians have a more centralized medical delivery system, with more limited access to surgeons. On average, Canadian surgeons perform higher volumes than their American counterparts, resulting in relatively greater average annual procedure volumes among both surgeons and institutions. For example, surgeons performing greater than 25 procedures a year in Canada account for nearly 75% of the THA and TKA surgical volume14 whereas in the US, only one third of arthroplasties are performed by those doing

consistent across the country, even after adjusting for medical comorbidities and age.

volume centers. Further such studies are needed.

**3. The English experience**

lengths of stay.

UK are publicly insured.

over 25 procedures a year6.

**4. The Canadian experience**

In summary, while the literature suggests that lower surgeon and hospital procedure volumes are associated with poorer short-term patient outcomes after TJR,1-3,6,7*,*8,10,12,14 this relationship appears to exist only when provider volumes are extremely low. The data among moderate and high volume providers is otherwise inconsistent with no clear relationship between surgeon or center experience and patient outcomes. Shorter hospital stays have also been observed among high volume surgeons and to a lesser extent among high volume centers1,10,12,14.

Provider Volumes and Surgical Outcomes in Total Hip and Knee Replacement 41

Categories

3 groups: low <40 %ile, medium 40- 80 %ile and high

Surgeon volume: Low: 1-3/yr Medium: 4-10/yr High: >10/yr Hospital volume:

Created 4 volume groups for surgeon and hospital volume

Hospital volume:

to attain approximately equal percentages in each category Surgeon volume: <15/yr, 15-29/yr, 30-59/yr and >60/yr

1-5/yr 6-10/yr 11-25/yr 26-50/yr >50/yr

>80 %ile Surgeons: Low: <2/yr Medium: 2-10/yr High: >10/yr Hospitals: Low: <16/yr Medium: 16- 65/yr High: >65/yr

Results

Low volume surgeons experienced higher rates of mortality, infection, revision operations and serious complications during initial hospital

High volume surgeons demonstrates shorter length of hospital stay High volume centers had longer average length of hospital stay Average cost per procedure higher in low

volume centers

identified

mortality

risk

outcome

Higher surgeon and hospital volumes associated with lower

Surgeons performing <15/yr category associated with

increased DVT risk and post-operative infection

No other relationship between volume and

Higher hospital volume associated with lower rates of mortality and dislocation following primary THA

Higher surgeon volume associated with lower rate of dislocation and deep hip infection Similar results for revision THA Steady trend toward better outcome associated with higher volume but no discrete volume thresholds

stay

Author Year Databases Methods Volume

Examined 7936 primary THA between 1988-1991

Examined 58,521 primary THA and 12,956 revision THA between July 1995-June 1996

Examined 50,874 primary TKA and 4636 revision TKA performed in

1997

Kreder et al1

Katz et al2

Hervey et

al3

1997 CHARS

2007 Medicare

2003 Healthcare Cost and Utilization Project Nationwide Inpatient Sample

claims data

computerized data set of Washington State Health Department

These findings raise several points for consideration. The fact that extremely low provider volumes are associated with higher complication rates supports the notion of some minimum number of procedures that surgeons and surgical centers should perform in order to optimize outcomes. However, exactly where this threshold lies is difficult to determine from published reports. The fact that Canadian studies, where individual surgeons and centers perform relatively more procedures on average, generally fail to demonstrate a link between provider volumes and adverse outcomes suggests that few Canadian providers fall below this unidentified threshold. The association between surgeon procedure volume and decreased length of hospital stay (even after adjustment for hospital volume) does seem to be a reproducible finding and may be associated with lower costs for acute hospital care. It has been hypothesized that high volume surgeons and centers have more streamlined post-operative protocols and better access to rehabilitation and other ancillary services that could act to facilitate more rapid discharge1. Further research is needed to demonstrate whether there is a cost benefit to performing joint replacements in higher volume settings.

There is a global trend toward increasing surgeon and center procedure volumes in an effort to accommodate the fast-growing needs of an aging population. This increasing demand for joint replacement surgery has lead to the introduction of practice standards and protocols for everything from intake assessments, pre-operative work-up, surgical techniques, postoperative pain management and rehabilitation, which serve to streamline the care process and have contributed to significantly lower complication rates than seen in the previous two decades. The fact that complication rates are so low makes it harder to detect significant differences in outcomes related to provider volumes and also raises the question of whether small statistical differences in complication rates are of sufficient clinical importance to warrant the closure of low-volume centers in favor of high-volume regionalized centers of excellence. While small differences in outcomes, such as mortality, are likely to be important to patients, these must be weighted against potentially competing priorities such as access to service, inconvenience, and quality of life.

Other factors that may be contributing to heterogeneity among volume-outcome study findings are differences in the data used and patients studied. Most American studies have used Medicare data. In the US, Medicare covers selected patients (including those aged 65 years). This contrasts the Canadian and British public health insurance systems, which are universal. Consequently, it is likely that US Medicare patients undergoing TJR are, on average, older than Canadian and British TJR recipients. Furthermore, the US studies' reliance on Medicare data means that many private, high-volume clinics are excluded. When such centers are included, Medicare patients typically comprise a small percentage of total clinic and surgeon volumes. Thus, relative to Canadian and British studies, the American studies may be biased toward poorer outcomes, making volume-outcome relationships potentially easier to detect.

In summary, the relationship between TJR provider volumes and patient outcomes is complex. Based on intuition, it seems logical that surgeons and institutions that perform few procedures should have higher rates of complications, given the lack of familiarity, practice and available resources, such as rehabilitation and other ancillary services. US studies support this notion. However, there is no consensus regarding the number of procedures below which adverse patient outcomes (and possibly increased costs) would justify a change in policy. Further research and debate are needed to determine whether such a threshold exists and if so, where it lies.

These findings raise several points for consideration. The fact that extremely low provider volumes are associated with higher complication rates supports the notion of some minimum number of procedures that surgeons and surgical centers should perform in order to optimize outcomes. However, exactly where this threshold lies is difficult to determine from published reports. The fact that Canadian studies, where individual surgeons and centers perform relatively more procedures on average, generally fail to demonstrate a link between provider volumes and adverse outcomes suggests that few Canadian providers fall below this unidentified threshold. The association between surgeon procedure volume and decreased length of hospital stay (even after adjustment for hospital volume) does seem to be a reproducible finding and may be associated with lower costs for acute hospital care. It has been hypothesized that high volume surgeons and centers have more streamlined post-operative protocols and better access to rehabilitation and other ancillary services that could act to facilitate more rapid discharge1. Further research is needed to demonstrate whether there is a cost benefit to

There is a global trend toward increasing surgeon and center procedure volumes in an effort to accommodate the fast-growing needs of an aging population. This increasing demand for joint replacement surgery has lead to the introduction of practice standards and protocols for everything from intake assessments, pre-operative work-up, surgical techniques, postoperative pain management and rehabilitation, which serve to streamline the care process and have contributed to significantly lower complication rates than seen in the previous two decades. The fact that complication rates are so low makes it harder to detect significant differences in outcomes related to provider volumes and also raises the question of whether small statistical differences in complication rates are of sufficient clinical importance to warrant the closure of low-volume centers in favor of high-volume regionalized centers of excellence. While small differences in outcomes, such as mortality, are likely to be important to patients, these must be weighted against potentially competing priorities such as access to

Other factors that may be contributing to heterogeneity among volume-outcome study findings are differences in the data used and patients studied. Most American studies have used Medicare data. In the US, Medicare covers selected patients (including those aged 65 years). This contrasts the Canadian and British public health insurance systems, which are universal. Consequently, it is likely that US Medicare patients undergoing TJR are, on average, older than Canadian and British TJR recipients. Furthermore, the US studies' reliance on Medicare data means that many private, high-volume clinics are excluded. When such centers are included, Medicare patients typically comprise a small percentage of total clinic and surgeon volumes. Thus, relative to Canadian and British studies, the American studies may be biased toward poorer outcomes, making volume-outcome

In summary, the relationship between TJR provider volumes and patient outcomes is complex. Based on intuition, it seems logical that surgeons and institutions that perform few procedures should have higher rates of complications, given the lack of familiarity, practice and available resources, such as rehabilitation and other ancillary services. US studies support this notion. However, there is no consensus regarding the number of procedures below which adverse patient outcomes (and possibly increased costs) would justify a change in policy. Further research and debate are needed to determine whether such a

performing joint replacements in higher volume settings.

service, inconvenience, and quality of life.

relationships potentially easier to detect.

threshold exists and if so, where it lies.

Provider Volumes and Surgical Outcomes in Total Hip and Knee Replacement 43

Hospital volume: Low (<40%ile):

Intermediate (40- 80%ile): 50/yr High (>80%ile):

Categories

Volumes stratified based on percentiles into 3 categories –

low (<40%ile), medium (40- 80%ile) and high (>80%ile) Surgeon volume: Low: <9/yr Medium: 9- 27/yr High: >27/yr

Hospital volume: Low: <42/yr Medium: 42- 107/yr High: >107/yr

Volumes stratified based on percentiles into 3

13/yr

145/yr

Examined 3645 patient with elective THA in Ontario in 1992

Examined 14,352 patients with elective TKA between 1993-1996

Examined discharge data for 222,684 primary TKA between 1991-

2001

Table 1. Summary of American TJR Volume-Outcome Studies

Author Year Databases Methods Volume

SooHoo et al8

Kreder et al12

Kreder et al10

2006 California's Office of Statewide Health Planning and Development records

1998 Canadian

Institute for Health Information (CIHI) Hospital Discharge Abstracts and Ontario Health Insurance Plan (OHIP) Physician Service Claims

2003 CIHI Hospital Discharge Abstracts and Ontario Health Insurance Plan

No difference in pain or level of satisfaction

Low volume hospitals had higher mortality in 90 days post discharge and higher 90-day readmission rate for infection, pulmonary embolism and thrombophlebitis

Results

No difference in complication rate between low and high volume categories Patients of high volume surgeons had shorter length of hospital stay with lowest volume group averaging 2.4 days longer in hospital than highest volume

group

Hospital volume not related to length of stay

No effect of provider volume on infection or

Low volume groups (both surgeon and center) had longer

mortality

Examined 78,745 primary TKA performed between January and August 2000

Examined 76,627 primary THR between July 1995 and June

Examined functional status of 932 patients who underwent primary TKA

1996

Katz et al5

Losina et al6

Katz et al7

2004 Medicare

2003 Medicare

2006 Medicare

claims data

claims data

claims data

<85/yr, 85-149/yr 150-249/yr and >250/yr No clear

definition of low versus high volume

Surgeon volume: 1-12/yr, 13-25/yr, 26-50/yr and >50/yr

Highest volume centers had lower risk of pneumonia, dealth, PE acute MI and infection when compared to lowest volume centers Highest volume surgeons compared to lowest volume surgeons had lower risks of pneumonia and any adverse outcome

Only looked at rate of early failure requiring revision surgery Patients of low volume surgeons more likely to need revision THA compared to high volume surgeons Strongest association within first 18 months suggesting technical cause as mechanism of

early failure

failure rates

centers

motion

independently associated with lower

Higher hospital volume

Patients of low volume surgeons and centers were 2X as likely to report poor functional score compared to high volume surgeons and

Lowest volume group 2X as likely to have decreased range of

Hospital volume: 1-25/yr, 26- 100/yr, 101- 200/yr and >200/yr No clear

definition of low versus high volume

Surgeon volume: Low: <12/yr Hospital volume:

Surgeon volume: Low: <6/yr Hospital volume: Low: <25/yr

1-25/yr 26-50/yr 51-100/yr >100/yr

Table 1. Summary of American TJR Volume-Outcome Studies

Provider Volumes and Surgical Outcomes in Total Hip and Knee Replacement 45

Gawande, A. (2003). Complications: a surgeon's notes on an imperfect science. Metropolitan

Hagen, T.P., Vaughan-Sarrazin, M., & Cram, P. (2010). Relation between hospital

older:retrospective analysis of US Medicare data. *Br Medical J*. Pp. 340:c165. Hervey, S.I., Purves, H.R., Guller, U., Toth, A.P., Vail, T.P., & Pietrobon, R. (2003). Provider

Judge, A., Chard, J., Learmonth, I., & Dieppe, P. (2006). The effects of surgical volumes and

Katz, J.N., Losina, E., Barrett, J., Phillips, C.B., Mahomed, N.N., Lew, R., Guadagnoli, E.,

Katz, J.N., Barrett, J., Mahomed, N.N., Baron, J.A., Wright, J., & Losina, E. (2004). Association

Katz, J.N., Mahomed, N.N., Baron, J.A., Barrett, J.A., Fossel, A.H., Creel, A.H., Wright, J.,

Kreder, H.J., Deyo, R.A., Koepsell T., Swiontkowski, M.F., & Kreuter, W. (1997).

Kreder, H.J., Williams, J.I., Jaglal, S., Hu, R., Axcell, T., & Stephen, D. (1998). Are

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**6. References**

Books.

Table 2. Summary of Canadian TJR Volume-Outcome Studies


*5.3. Groupings and Suggestions*

We applied Ward's method to perform cluster analysis using the standardized scores for six criteria associated with villa development and the net ratio of vacant lots, the ratio of villa lots having areas ranging between 300 and 400 m2, the ratio of villa lots having areas ranging between 1000 and 1400 m2, the average land price, the total area of vacant lots, the distance between a mosque and a park, and the total road length (Figures 14–16). The 103 target areas were categorized into six groups (Figure 17). The characteristics and recommendations for reducing the net ratio of vacant lots are presented below.

**Figure 14.** Scatter diagram (1).

### 1. Group A (26 sites)

The neighborhoods included in this group evidence the following characteristics: (1) the areas of a few lots range between 300 and 400 m2; (2) the total area of vacant lots is relatively large; (3) land prices are high; and (4) the road lengths are short compared with those of other groups. Because of the relatively large total area of vacant lots, it is necessary to delineate existing lots with areas ranging between 300 and 400 m2 along with increasing road length for improving the street environment and reducing the ratio of vacant lots. In addition, increasing the number of parks to respond to the increase in population density is recommended, thereby increasing the possibility of consumers being able to purchase lots.

**Figure 15.** Scatter diagram (2).

**Figure 16.** Scatter diagram (3).

#### 2. Group B (38 sites)

The neighborhoods included in this group share the following characteristics: (1) a certain number of villas have been built in lots with areas ranging between 300 and 400 m2; (2) a few vacant areas are present; (3) the total street length is substantial; and (4) there is a short distance between the mosque and park. As the majority of lots within this group have already been developed, there are no further recommendations or changes needed.


*2.6. Fatty Acid Composition*

A sub-sample of 60 steaks (*n* = 30 steaks closest to the mean marbling score of each treatment) were selected to evaluate fatty acid profile using direct FAME synthesis. Steaks were thawed slightly and external fat, epimysial connective tissue, and additional muscles were trimmed from the longissimus muscle. Samples were minced, immersed in liquid nitrogen, and powdered for 15 s using a Waring commercial blender (Waring Products Division, Model 51BL32, Landcaster, PA, USA). Duplicate 1 g samples were weighed and processed to generate FAMEs according to procedures of O'Fallon et al. [19]. Fatty acids were identified through comparison with retention times of an authentic fatty acid standard mixture (GLC-463, Nu-Check Prep Inc., Elysian, MN, USA). Quantities were computed as mg/g of raw wet tissue through an internal standard calibration method where C13:0 served as the internal standard. Final contents were then summed and %, g/100 g total fatty acids was produced after summing all fatty acids.