**Author details**

Pablo Juanes-Velasco1,2, Javier-Carabias-Sanchez2 , Rodrigo Garcia-Valiente2 , Jonatan Fernandez-García2 , Rafael Gongora2 , Maria Gonzalez-Gonzalez1,2 and Manuel Fuentes1,2\*

\*Address all correspondence to<EMAIL_ADDRESS>
1-Department of Medicine, General Cytometry Service-Nucleus, Cancer Research Center (IBMCC/CSIC/USAL/IBSAL), University of Salamanca, CSIC, IBSAL, Salamanca, Spain-

2-Proteomics Unit, Cancer Research Center, IBSAL, University of Salamanca, CSIC, Salamanca, Spain


3. Informatics solutions for monitoring and analyzing the power plants' KPIs

In order to analyze and monitor the key performance indicators, the executives of the power plants require an advanced decision support system (DSS). Our proposal consists in developing an informatics solution based on three levels architecture that involves models for data management, analytical models and interfaces (Figure 1):

The architecture components are as follows:

Figure 1. SIPAMER's architecture.

## 3.1. Level 1—data management

All data sources gathered from wind/photovoltaic power plants are extracted, transformed and loaded into a central relational database running Oracle Database 12c Edition in order to enable user access through cloud computing. The sources are heterogeneous: measuring devices for climate conditions (wind speed, direction, temperature, atmospheric pressure, and humidity), sensors for photovoltaic cells and wind turbines, SCADA API for measuring realtime parameters regarding power plant output. These sources are mapped into a relational data stage; then, the extract, transform and load (ETL) process is applied, and data are finally loaded into a relational data mart that organizes objects as dimensions and facts. This approach makes it easier the development of the analytical model with KPIs framework and enables an advanced roll-up/drill-down interfaces.

Based on the executives' requirements regarding the KPIs, we designed the main structural entities (objects) that will enable multidimensional data exploration. They will be organized as dimensions (subject entities) with descriptive attributes structured on hierarchies with multiple levels to enable typical OLAP operations: roll-up/drill-down, slicing and dicing. The data mart contains the following dimensions: DIM\_STAKEHOLDER, DIM\_POWERPLANT, DIM\_REGION, DIM\_TURBINE, DIM\_PV and DIM\_TIME.

Figure 2. Snowflake schema for the KPIs data mart.

Facts tables are objects that contain attributes like measures (metrics) and foreign keys to the dimension tables. Facts are usually numerical data that can be aggregated and analyzed by dimensions' levels. The model contains the following facts: FACT\_PV\_OUTPUT and FACT\_WIND\_OUTPUT. The objects are organized in a snowflake schema as shown in Figure 2.

The data mart allows us to design the KPIs framework in a subject-oriented and multidimensional view.

## 3.2. Level 2—models

3.1. Level 1—data management

enables an advanced roll-up/drill-down interfaces.

18 Recent Improvements of Power Plants Management and Technology

Figure 2. Snowflake schema for the KPIs data mart.

DIM\_REGION, DIM\_TURBINE, DIM\_PV and DIM\_TIME.

All data sources gathered from wind/photovoltaic power plants are extracted, transformed and loaded into a central relational database running Oracle Database 12c Edition in order to enable user access through cloud computing. The sources are heterogeneous: measuring devices for climate conditions (wind speed, direction, temperature, atmospheric pressure, and humidity), sensors for photovoltaic cells and wind turbines, SCADA API for measuring realtime parameters regarding power plant output. These sources are mapped into a relational data stage; then, the extract, transform and load (ETL) process is applied, and data are finally loaded into a relational data mart that organizes objects as dimensions and facts. This approach makes it easier the development of the analytical model with KPIs framework and

Based on the executives' requirements regarding the KPIs, we designed the main structural entities (objects) that will enable multidimensional data exploration. They will be organized as dimensions (subject entities) with descriptive attributes structured on hierarchies with multiple levels to enable typical OLAP operations: roll-up/drill-down, slicing and dicing. The data mart contains the following dimensions: DIM\_STAKEHOLDER, DIM\_POWERPLANT, This level contains models for forecasting the power plant output on short term (hourly, up to 3 days) and the KPIs analytical framework.

Forecasting models are build distinct for each type of renewable power plant, WPP and PPP due to the different influence factors that affect the power plant' operation and generation. The aim of the model is to improve predictions made and transmitted currently by the producer on short-time intervals. The deviations between forecasting and recorded production are currently about 30–35% for wind power plants and 15–20% for photovoltaic power plants [15, 16]. Minimizing these deviations will lead to lower costs for stakeholders due to the fact that imbalances are paid. The model consists in a set of experimental methods based on data mining algorithms, developed, validated and tested on WPP and PPP data sets. We developed three algorithms based on artificial neural networks (ANN): Levenberg-Marquardt algorithm (LM), Bayesian regularization algorithm (BR), and scaled conjugate gradient algorithm (SCG).

## 3.2.1. Forecasting the photovoltaic power plants' output

We identified the input parameters (irradiance, temperature, wind speed & direction, tilt, exposure) and the output (power), and for the training and validation, we used a data set that consist of 50,631 samples from every 10 minutes direct measurements in a PPP located in Romania, Giurgiu County, during January 1, 2014—December 31, 2014. Within this photovoltaic power plant are installed two types of ABB—PSV800 invertors, with 600 kW and 760 kW, 30,888 solar panels and the solar module has a rated power of 245 W with a 20-kV connection. The configuration is widely used in other PPP; therefore, the developed ANN can be easily implemented in other power plants with similar configuration.

Since solar energy presents seasonal variations related to the various climate conditions of the year, we designed the neural networks adaptable to irregular seasonal variations by changing the settings on the number of neurons in hidden layers and developed two types of ANN.

First, we designed one neural network for each of the three algorithms (LM, BR and SCG) based on the whole year data. The results were good, with an average mean squared error (MSE) of 0.19, and average for correlation coefficient, R = 0.95, with 0.9573 for LM.

Then, we consider the second option, to take into account the seasonal variations for solar energy, and we designed neural networks based on LM, BR and SCG for each month. So, we obtained 36 neural networks with a much better results than the previous case (yearly ANNs). Comparing results from the monthly data, we found that the prediction accuracy is excellent in

Figure 3. Regression between target values and the output values of the neural network SfebruaryLM.

all months, and monthly performance indicators have comparable values. The MSE is between 0.03 and 0.1, and coefficient R is between 0.997 and 0.999. For example, Figure 3 shows the correlation coefficient for the neural network SFebruaryLM developed on Levenberg-Marquardt algorithm.

By comparing the forecasting results through the development of neural networks based on the three algorithms, we found that in 69% of cases, neural networks developed with Bayesian regularization produced a better generalization than networks developed with Levenberg-Marquardt and SCG algorithms. But, in 31% of cases, the forecasting results with the highest level of accuracy have been obtained in the case of Levenberg-Marquardt algorithm.

If, in order to improve the accuracy of the forecasting model, new elements are added as input data, the LM algorithm will offer the advantage of a higher training rate compared with the BR algorithm but would have the disadvantage of an increased memory consumption. When new inputs are added and we want to obtain a high speed and performance, then the best solution is to develop the ANN based on SCG algorithm as it is faster than the other two algorithms (LM and BR) requiring low memory consumption, with the drawback that it provides a lower level of prediction accuracy.

## 3.2.2. Forecasting the wind power plants' output

all months, and monthly performance indicators have comparable values. The MSE is between 0.03 and 0.1, and coefficient R is between 0.997 and 0.999. For example, Figure 3 shows the correlation coefficient for the neural network SFebruaryLM developed on Levenberg-Marquardt

Figure 3. Regression between target values and the output values of the neural network SfebruaryLM.

20 Recent Improvements of Power Plants Management and Technology

By comparing the forecasting results through the development of neural networks based on the three algorithms, we found that in 69% of cases, neural networks developed with Bayesian regularization produced a better generalization than networks developed with Levenberg-Marquardt and SCG algorithms. But, in 31% of cases, the forecasting results with the highest

If, in order to improve the accuracy of the forecasting model, new elements are added as input data, the LM algorithm will offer the advantage of a higher training rate compared with the BR algorithm but would have the disadvantage of an increased memory consumption. When new inputs are added and we want to obtain a high speed and performance, then the best solution is to develop the ANN based on SCG algorithm as it is faster than the other two algorithms (LM and BR) requiring low memory consumption, with the drawback that it provides a lower

level of accuracy have been obtained in the case of Levenberg-Marquardt algorithm.

algorithm.

level of prediction accuracy.

We identified the input parameters (temperature, wind speed & direction at 50 m, 55 m, 75 m, 90 m, humidity, atmospheric pressure, turbine height, soil orography, slipstream effect) and the output (power). For ANN training and validation, we used a data set of 17,491 samples from hourly measurements in a WPP located in Romania, Tulcea, for 2 years (January 1, 2013– December 31, 2014). In this WPP, there are two types of wind turbines: V90 2MW/3MW IEC IA/IIA, with a height of 90 meters. These types of wind turbines are commonly used, so we can consider the data set suitable for training a generalized neural network, as described in [17].

Since wind energy presents seasonal variations over 1 year period, we design two sets of ANN based of three algorithms: Levenberg-Marquardt algorithm (LM), Bayesian regularization algorithm (BR) and scaled conjugate gradient algorithm (SCG).

First, we designed the neural network based on data set covering 2 years records for each algorithm (LM, BR and SCG). For the second solution, we take into account seasonal variations that affect wind energy and designed neural networks for each season, dividing the data into 4 sets corresponding to 4 seasons specific to Romania region. The results between the ANN trained for the whole year and the ANN trained for corresponding season are compared in Table 1.

The best approach is to develop and train the neural networks adjusted with seasonal data, due to the fact that the prediction accuracy is excellent in all seasons, and performance indicators have comparable values. Comparing the results for each algorithm (LM, BR, SCG), in most cases, neural networks based on Bayesian regularization produced a better generalization than Levenberg-Marquardt or SCG algorithms, but LM performed faster and with minimum memory consumption.

KPIs analytical framework provides methods for calculating the key performance indicators used by executives to monitor the power plants in terms of technological and business processes. For technological processes, we build the KPIs presented in Section 2 based on formulas (1) to (19). For business processes, we included commonly used KPIs as income, cost, profit/ loss, etc. The KPIs are developed directly into the facts tables, as derived measures and accessible into the interface level.

Table 1. Comparison between ANN developed for one year and ANN with seasonal adjustments.

## 3.3. Level 3—interface

The forecasting and analytical models are integrated into an online dashboard developed in Java with application development framework (ADF). The dashboard is built as a business intelligence (BI) portal with a very friendly interface and interactive charts, reports, pivot tables, maps and narrative elements that allows executives and stakeholders to easily analyze the KPIs. The dashboard contains three sections:

Figure 4. Forecast versus actual energy for WPP groups.

basis, the forecasted energy (orange line) versus actual produced energy (green line) for a WPP group. The chart displays also other 2 generation groups (grey and light blue lines) situated in the same region with the green marked group and the difference between estimated and actual values (light orange line).

• KPIs Analytics—contains analytical Business Intelligence elements (interactive charts, gauges, reports, maps, pivot tables) that enable KPI advanced analysis through dimensions' hierarchies that allows executives to compare indicators over different periods of time, regions and locations, aggregate/detailed KPIs over power plants' groups or module/turbines. For example, Figure 5 shows the average power, installed power load factor, installed power load duration and maximum power load duration for a wind power plant with two groups of 5 and 10 MW.

Figure 5. KPIs dashboard.

3.3. Level 3—interface

power plant;

the KPIs. The dashboard contains three sections:

22 Recent Improvements of Power Plants Management and Technology

estimated and actual values (light orange line).

with two groups of 5 and 10 MW.

Figure 4. Forecast versus actual energy for WPP groups.

The forecasting and analytical models are integrated into an online dashboard developed in Java with application development framework (ADF). The dashboard is built as a business intelligence (BI) portal with a very friendly interface and interactive charts, reports, pivot tables, maps and narrative elements that allows executives and stakeholders to easily analyze

• Production management—it contains reports for power plant current operations and maintenance plans, it displays the generation groups' configuration and location, real time data gathered from measuring devices, SCADA and generation groups or the entire

• Forecasting—it contains access to the forecasting models and offers reports and charts to display the estimations versus actual values for different periods of time, selected by the user. For example, Figure 4 shows a chart that displays for one day interval, on hourly

basis, the forecasted energy (orange line) versus actual produced energy (green line) for a WPP group. The chart displays also other 2 generation groups (grey and light blue lines) situated in the same region with the green marked group and the difference between

• KPIs Analytics—contains analytical Business Intelligence elements (interactive charts, gauges, reports, maps, pivot tables) that enable KPI advanced analysis through dimensions' hierarchies that allows executives to compare indicators over different periods of time, regions and locations, aggregate/detailed KPIs over power plants' groups or module/turbines. For example, Figure 5 shows the average power, installed power load factor, installed power load duration and maximum power load duration for a wind power plant The dashboard is developed in a cloud computing architecture, and it is accessible as a service, customized and configured depending on stakeholders' interest.


*2.4. Collection Data*

The Medical Subject Headings (MeSH) was applied for finding the keywords used in the present revision. The selected key words: "facial" or "face" and "bone" or "bone graft" and "reconstruction" or "biomaterial" or "biomaterials" and "marine" and "collagen" were recorded for collecting the data.


**10. Hospital admittance**

After acute care, the focus shifts towards treatment and education. By informing the patients and their parents about the dangers of alcohol consumption, the effect of hospitalization is broadened towards prevention and intervention. This will be of use during follow up at the outpatient department.

Most patients are admitted in the evening or at night (40). The next morning, they are woken on time to start a short program before being discharged from hospital. First, the pediatrician speaks both to the patient and the parents, explaining the reason for admittance and emphasizing the seriousness of the event. The patient's medical and social histories are checked and questions are asked about further alcohol use. The dangers of alcohol use are explained. This is seen as an important moment for intervention and education. Patient and parents pay more attention shortly after the incident occurred. Later on, a pedagogic

A New Approach in Adolescent Alcohol Intoxication –

**12. Tools for screening**

dependence.

was done in 72% of the patients for whom it was indicated.

So far, no standard screening method has been identified.

main goal. However, reliability is low because of self-report.

acid ethyl ester (FAEE) and ethyl glucuronide (EtG).

alcohol. It has no role in screening for alcohol use at the outpatient clinic.

Clinical Pediatric Experience and Research Combined 229

Preliminary results of the project are promising. At follow-up, 84-88 % of the patients had stopped binge drinking and 61% had stopped the consumption of alcohol. Awareness of the parents was another factor of interest; at follow up 82,5 % of the parents applied specific alcohol rules, including prohibition of alcohol under 16 years of age. Behavioral questionnaires were filled in by 89% of the study population. Neuropsychological screening

Screening for problematic alcohol use can be useful during follow up of the patients. It can be expected that questions about lifestyle are delicate, particularly during adolescence and in the direct vicinity of parents or adults. At the same time, detection of problematic alcohol use at a young age can reveal alcohol dependency and ensure a more effective intervention.

Various self-report questionnaires are available for rapid assessment of drinking behavior, such as the Alcohol Use Disorders Identification Test (AUDIT), TWEAK (Tolerance, Worried, Eye-opener, Amnesia, Cut Down), the Michigan Alcohol Screening Test, CAGE (Cut Down, Annoyed, Guilty, Eye Opener) and the Alcohol Dependence Scale. The AUDIT was developed by the World Health Organization (WHO) as a measure for alcohol consumption, dependence and alcohol-related problems. The TWEAK focuses more on tolerance. It was specifically developed for women and aims to identify possible hazardous drinking patterns. The CAGE places emphasis on behaviors consistent with alcohol

These various screening methods are rapid, non-invasive and inexpensive, but they have different outcome parameters and were developed for adults. Applicability for adolescents has been investigated and seems to support the AUDIT as the better screening method (42), due to its focus on frequency of use, quantity and frequency of binge drinking. This can be an advantage in adolescents, because here the early detection of drinking problems is the

Biological screening methods can offer more objectivity. Amongst them is the extensively used blood alcohol concentration, which is generally determined during the first care. However, this test only gives information during a short period after consumption of

Other traditional and new markers can add to the suspicion of problematic alcohol use. The more established markers of alcohol use are mean corpuscular volume (MCV), gammaglutamyltransferase (GGT), aspartate aminotransferase (AST) and alanine aminotransferase (ALT). Increased values can lead to the differential diagnose of alcohol dependency. Direct markers, which are all products of ethanol metabolism, are acetyldehyde, acetic acid, fatty

Newer biomarkers include carbohydrate-deficient transferrin (CDT), total serum sialic acid (TSA) and 5-hydroxytryptophol (5-HTOL). Transferrin is a plasma protein that carries iron through the bloodstream to the bone marrow. Transferrin is a polypeptide with two Nlinked polysaccharide chains. The chains are branched with sialic acid residues. Consuming

employee or nurse will help the adolescent to answer questions on alcohol use on a government-funded website. Parents are also referred to websites for further information.

Most of the patients leave the hospital in good clinical health within a day after admittance. After discharge, a program starts at the outpatient department of pediatrics and child psychology.


**Author details**

Carianne Johnson University of Salford, Salford, UK

\*Address all correspondence to<EMAIL_ADDRESS>
© 2023 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.


Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy: Insights from Thai Multicenter Study and Overview of the Major Guidelines

*Songkwan Silaruks, Charn Sriratanasathavorn, Petch Rawdaree, Rapeephon Kunjara-Na-Ayudhaya, Bandit Thinkhamrop and Piyamitr Sritara*

## **Abstract**

Background Since the release in Thailand in 2001 of the Third Guidelines by the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults or the Adult Treatment Panel (ATP III), there have been no nationwide studies on the proportion of dyslipidaemic patients who have achieved the low-density lipoprotein cholesterol (LDL-C) goals. The authors therefore aimed to estimate the percentage achievement of LDL-C goals based on the modified NCEP ATP III guidelines in intermediate- to high-risk patients. Methods The authors conducted a hospitalbased, cross-sectional, epidemiological survey. Patients (1240) were selected consecutively from 50 hospitals across Thailand. Patients were included if they had been treated with statins for at least 3 months. Results Two-thirds were female, and the mean age was 61.7+69.5 years. The median duration of statin treatment was 21 months. Half (633/1240) of the patients achieved the LDL-C goal levels as defined by the NCEP guidelines (51.1%, 95% CI 48.3% to 53.8%). The very highrisk group had the lowest percentage achievement (11.6%; 95% CI 1.6% to 21.6%), compared with 54.2% (95% CI 50.9% to 57.4%) for the high-risk group and 47.0% (95% CI 41.1% to 52.8%) for the moderate-risk group. More males achieved the LDL-C goals than females (55.6% vs. 48.9%; P = 0.029). Conclusions Overall, 51.1% of the patients with cardiovascular risk, on statins treatment, achieved the NCEP ATP III LDL-C goal levels.

**Keywords:** dyslipidemia, goal attainment, Thailand

## **1. Introduction**

Dyslipidemia is a major risk factor for the development of atherosclerotic disease. Therefore, lifestyle interventions and pharmacological approaches to decrease cholesterol are widely used in cardiovascular disease prevention. The introduction and widespread use of 3-hydroxy-3-methylglutaryl coenzyme A inhibitors (statins) for individuals at risk of atherosclerotic disease has been an important advance in cardiovascular care [1].

Since 1993, the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel or ATP) has periodically updated the treatment guidelines which identify LDL-C as a cause of CHD and the primary aim for diagnosis and treatment of hypercholesterolaemia [1–3].

In 2001, the recommendations were released in the Third ATP Report (NCEP ATP III) [3] which reaffirmed the risk of CHD from increased LDL-C, the benefit of LDL-C-lowering therapy and maintaining intensive treatment of patients with CHD. The report also added a call for more intensive LDL-C-lowering therapy as the primary aim for patients with a CHD risk equivalent.

There can be no doubt that better control of dyslipidemia, even in subjects whose low-density lipoprotein cholesterol level is not particularly high, has reduced overall event rates. On a background of lifestyle interventions, statins are routinely used to decrease risk along with aspirin and interventions to control hypertension and diabetes. The efficacy of statins in atherosclerotic conditions, particularly in the treatment and prevention of CHD, has been well established [4]. Large-scale, randomized, prospective trials involving patients with CHD have shown that statins reduce the clinical consequences of atherosclerosis, including cardiovascularrelated deaths, non-fatal MI and stroke, hospitalization for acute coronary syndrome and heart failure, as well as the need for coronary revascularization [5–7].

## **2. Clinical practice**

Although the guidelines have been widely available, achieving the lower LDL-C goals in practice has been suboptimal. In a US study, only 38% of 4888 patients under primary care in five regions achieved the LDL-C target levels [8]. The respective success rates were 68% and 37% in the low- and high-risk groups. Only 18% of the patients with established CHD with the highest risk of future CHD events achieved the lower LDL-C targets. Another study, based on the records of 461 patients in rural areas, covering all risk levels from four practices, found that only 54% of dyslipidaemic patients achieved the NCEP ATP III goals [9]. In 1998, a survey in Thailand assessing the achievement of LDL-C goals in high-risk patients indicated an unsatisfactorily low percentage of 39.2% [10]. The most recent nationwide survey was conducted between December 2002 and June 2003 [11]. The study involved 1921 patients from 48 hospitals across Thailand. Percentage achievements of LDL-C targets in the CHD and CHD equivalents, high-, and low-risk group were 34.6, 56.4 and 76.8%, respectively [11]. In 2004, several changes were made to the guideline, released as the Modified NCEP ATP III in that year [12]. There has, however, been no recent nationwide study in Thailand investigating the proportion of dyslipidemia patients who have achieved the updated LDL-C goals.

#### **3. Clinical practice in Thailand**

In our study [13], we conducted a hospital-based, cross-sectional, epidemiological survey and retrospective chart review, in both secondary and tertiary care across Thailand. Our study aimed to estimate the percentage of LDL-C goals achievement

**73**

*\**

*†*

**Table 1.**

*Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy…*

based on the NCEP ATP III guidelines in intermediate- to high-risk patients receiving statins for at least 3 months in clinical practice in Thailand. The data collection was conducted at the selected hospitals between March and July 2008. The primary outcome of this study was the percentage of dyslipidaemic patients on lipid-lowering therapy who had achieved their respective LDL-C target levels as defined by the

There are 95 secondary- and tertiary-care hospitals across Thailand, 50 (52.6%)

The duration of statin treatment prior to the date of the most recent lipid profile

ranged between 3 and 191 months (median 21 months), which represented the period of statin treatment at the time of assessing the treatment outcome.

The high-risk group accounted for the largest number of patients, followed by moderate- and high-risk patient types. The mean age was 61.7 ± 9.5 years, and approximately two-thirds were female. The mean age of each risk group was similar. Overall, the majority of males at risk (94%) were 45 years of age or higher. A similar percentage was seen in each risk group. For females at risk, about three-quarters were aged 55 years or older. Most common cardiovascular risks were diabetes mel-

Among the 1240 patients, 633 achieved the lower LDL-C goals as defined by the NCEP ATP III guidelines (51.1%; 95% CI 48.3% to 53.8%) (**Table 1**). The very high-risk group had the lowest achievement level at about one tenth. The achievement rate varies among regions where the highest achievement rate was 57.4% in the central area, and the lowest achievement rate was 42.6% in the eastern part of the country. On average, the very high-risk patients were about half, 49.7%, to reach

**Patient groups\* Total Achieved goals Percentage 95% CI Mean percentage†**

Very high risk 43 5 11.6 1.6 to 21.6 49.7 High risk 914 495 54.2 50.9 to 57.4 31.8 Moderate risk 283 133 47.0 41.1 to 52.8 9.9 Overall 1240 633 51.1 48.3 to 53.8 27.5

*Very high risk (LDL-C < 70 mg/dl); high risk (LDL-C < 100 mg/dl); moderate risk (LDL-C < 130 mg/dl).*

*Calculated based on the percentage difference between LDL-C level and the target goal among patients who did not*

*Percentage and 95% CIs of low-density lipoprotein cholesterol (LDL-C) achievement goals by patient group.*

 **to target**

**LDL-C**

of which were selected for the study. The number of selected hospitals in each region was proportional to the total number of eligible hospitals in each region (i.e., the North, the Northeast, the South and Central). A total of 1730 patients attending OPD clinics were screened by interviews, and 167 (9.6%) were excluded: 161 not currently treated with statin, five not consented and one not within 20–80 years of age. After the chart review was conducted, a further 323 (20.7%) cases were excluded: 216 treated <3 months before lipid profile became available, 32 lipid profile not available and 75 having not received the same statin before lipid profile

*DOI: http://dx.doi.org/10.5772/intechopen.82355*

**3.1 Number of patients and participating hospitals**

NCEP ATP III guidelines.

became available.

the LDL-C target goal.

*achieve the LDL-C target.*

litus (66.1%) and hypertension (57.6%).

**3.2 Percentage achievement of LDL-C goals for all patients**

#### *Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy… DOI: http://dx.doi.org/10.5772/intechopen.82355*

based on the NCEP ATP III guidelines in intermediate- to high-risk patients receiving statins for at least 3 months in clinical practice in Thailand. The data collection was conducted at the selected hospitals between March and July 2008. The primary outcome of this study was the percentage of dyslipidaemic patients on lipid-lowering therapy who had achieved their respective LDL-C target levels as defined by the NCEP ATP III guidelines.

## **3.1 Number of patients and participating hospitals**

*Dyslipidemia*

cardiovascular care [1].

**2. Clinical practice**

the updated LDL-C goals.

**3. Clinical practice in Thailand**

treatment of hypercholesterolaemia [1–3].

the primary aim for patients with a CHD risk equivalent.

cholesterol are widely used in cardiovascular disease prevention. The introduction and widespread use of 3-hydroxy-3-methylglutaryl coenzyme A inhibitors (statins) for individuals at risk of atherosclerotic disease has been an important advance in

Since 1993, the National Cholesterol Education Program (NCEP) Expert Panel

In 2001, the recommendations were released in the Third ATP Report (NCEP ATP III) [3] which reaffirmed the risk of CHD from increased LDL-C, the benefit of LDL-C-lowering therapy and maintaining intensive treatment of patients with CHD. The report also added a call for more intensive LDL-C-lowering therapy as

There can be no doubt that better control of dyslipidemia, even in subjects whose low-density lipoprotein cholesterol level is not particularly high, has reduced overall event rates. On a background of lifestyle interventions, statins are routinely used to decrease risk along with aspirin and interventions to control hypertension and diabetes. The efficacy of statins in atherosclerotic conditions, particularly in the treatment and prevention of CHD, has been well established [4]. Large-scale, randomized, prospective trials involving patients with CHD have shown that statins reduce the clinical consequences of atherosclerosis, including cardiovascularrelated deaths, non-fatal MI and stroke, hospitalization for acute coronary syndrome and heart failure, as well as the need for coronary revascularization [5–7].

Although the guidelines have been widely available, achieving the lower LDL-C goals in practice has been suboptimal. In a US study, only 38% of 4888 patients under primary care in five regions achieved the LDL-C target levels [8]. The respective success rates were 68% and 37% in the low- and high-risk groups. Only 18% of the patients with established CHD with the highest risk of future CHD events achieved the lower LDL-C targets. Another study, based on the records of 461 patients in rural areas, covering all risk levels from four practices, found that only 54% of dyslipidaemic patients achieved the NCEP ATP III goals [9]. In 1998, a survey in Thailand assessing the achievement of LDL-C goals in high-risk patients indicated an unsatisfactorily low percentage of 39.2% [10]. The most recent nationwide survey was conducted between December 2002 and June 2003 [11]. The study involved 1921 patients from 48 hospitals across Thailand. Percentage achievements of LDL-C targets in the CHD and CHD equivalents, high-, and low-risk group were 34.6, 56.4 and 76.8%, respectively [11]. In 2004, several changes were made to the guideline, released as the Modified NCEP ATP III in that year [12]. There has, however, been no recent nationwide study in Thailand investigating the proportion of dyslipidemia patients who have achieved

In our study [13], we conducted a hospital-based, cross-sectional, epidemiological survey and retrospective chart review, in both secondary and tertiary care across Thailand. Our study aimed to estimate the percentage of LDL-C goals achievement

on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel or ATP) has periodically updated the treatment guidelines which identify LDL-C as a cause of CHD and the primary aim for diagnosis and

**72**

There are 95 secondary- and tertiary-care hospitals across Thailand, 50 (52.6%) of which were selected for the study. The number of selected hospitals in each region was proportional to the total number of eligible hospitals in each region (i.e., the North, the Northeast, the South and Central). A total of 1730 patients attending OPD clinics were screened by interviews, and 167 (9.6%) were excluded: 161 not currently treated with statin, five not consented and one not within 20–80 years of age. After the chart review was conducted, a further 323 (20.7%) cases were excluded: 216 treated <3 months before lipid profile became available, 32 lipid profile not available and 75 having not received the same statin before lipid profile became available.

The duration of statin treatment prior to the date of the most recent lipid profile ranged between 3 and 191 months (median 21 months), which represented the period of statin treatment at the time of assessing the treatment outcome.

The high-risk group accounted for the largest number of patients, followed by moderate- and high-risk patient types. The mean age was 61.7 ± 9.5 years, and approximately two-thirds were female. The mean age of each risk group was similar. Overall, the majority of males at risk (94%) were 45 years of age or higher. A similar percentage was seen in each risk group. For females at risk, about three-quarters were aged 55 years or older. Most common cardiovascular risks were diabetes mellitus (66.1%) and hypertension (57.6%).

## **3.2 Percentage achievement of LDL-C goals for all patients**

Among the 1240 patients, 633 achieved the lower LDL-C goals as defined by the NCEP ATP III guidelines (51.1%; 95% CI 48.3% to 53.8%) (**Table 1**). The very high-risk group had the lowest achievement level at about one tenth. The achievement rate varies among regions where the highest achievement rate was 57.4% in the central area, and the lowest achievement rate was 42.6% in the eastern part of the country. On average, the very high-risk patients were about half, 49.7%, to reach the LDL-C target goal.

*\* Very high risk (LDL-C < 70 mg/dl); high risk (LDL-C < 100 mg/dl); moderate risk (LDL-C < 130 mg/dl). † Calculated based on the percentage difference between LDL-C level and the target goal among patients who did not achieve the LDL-C target.*

#### **Table 1.**

*Percentage and 95% CIs of low-density lipoprotein cholesterol (LDL-C) achievement goals by patient group.*

#### *Dyslipidemia*

Males had a statistically higher percentage achievement of the lower LDL-C goals than females (p = 0.024) (**Table 1**). The duration of statin treatment and the statin use, either alone or combined with other regimens, had a similar percentage achievement of lower LDL-C goals.

The final number of subjects included in the analysis was 1240. Initially, the calculated sample size was 1260, of which 20 (1.8%) patients had a statin treatment of <3 months. These were identified after enrolment and excluded from the analysis. This elimination did not, however, affect the study findings, that is, the percentage achievement of LDL-C goals was 52.5% when they were included, compared with 51.1% when they were excluded.

We, thus, included only patients who had been treated for at least 3 months with no maximum limit of treatment duration. The results in **Table 2** indeed suggest that the duration of statin treatment had no effect on the percentage achievement of LDL-C goals, which was about 51% for every interval of 12 months (p = 0.975).

#### **Table 2.**

*Percentage low-density lipoprotein cholesterol achievement goals by selected factors.*

**75**

*Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy…*

However, there are numerous factors which may confound the goal achievement, including statin dose, potency of statin, culture, socio-economic status, healthcare policy, concomitant medications, etc. Also, the selection bias from selected study sites, which were from diabetes and hypertension clinics even we tried to do the study in various parts of the country. This leads to a higher proportion of high-risk

Our study was based on the availability of lipid profiles of patients measured on request, as per real-life clinical practice; however, there were no significant differences between the percentage achievement of LDL-C goals among patients whose lipid profile was assessed before or after the median of 5.5 months prior to the survey date. This result might indicate that LDL-C levels were underutilized to

In our study, the percentage of lowered LDL-C according to goal levels, as defined by NCEP ATP III guidelines, among the high-cardiovascular-risk group, was 51.1% compared with 39.2% in a 1997–1998 study [10] and 34.6% in the 2002–2003 study [14]. The higher percentage found in our study could be due to various reasons: (1) we included only patients who used statins and not any other lipid-lowering agent alone; (2) there has been an increasing focus on the benefits of intensive cholesterol reduction; (3) new and more efficacious statins have been developed; (4) 95% of the patients in our study were attended by specialists who might be more likely to adhere to the guidelines; and (5) two-thirds of the patients in our study were females, who might have had a greater rate of compliance to the treatment or might have had a greater response to therapy than males, although there are few data to support this. As with other studies, our study found that the lowest percentage of achieving the recommended LDL-C target was in the very

A number of aspects of our study can be considered strengths. First, the case selection was unbiased, as it was carried out consecutively and independent of the attending physicians. Second, we covered a large number (52.6%) of secondary- and tertiary-care hospitals across the country. Third, almost all of the studied patients (99.0%) were attended by an internal medicine, specialist, particularly the very high-risk and high-risk patients. Finally, our study represented real-life, clinical settings in Thailand, so the percentage achievement of LDL-C goals may

In summary, our study demonstrated that 51.1% of patients with cardiovascular risk on statin treatment achieved the LDL-C goal levels defined by the NCEP ATP III guidelines. We suggest that patients with a high CHD risk should be targeted for more aggressive lipid-lowering management. National campaigns to increase the awareness among both physicians and patients of the importance of achieving the LDL-C goals are needed to optimize the prevention of cardiovascular events and to further reduce the burden of cardiovascular diseases. Further investigation is needed to understand the reasons for patients not achieving lower LDL-C levels.

Despite the >50% decrease in age-adjusted cardiovascular mortality over the past several decades, atherosclerotic disease is still the leading cause of morbidity and mortality. Moreover, cardiovascular disease accounts for more than half of all non-communicable diseases and has become the leading cause of death worldwide, a fact affirmed by the World Health Organization [15]. Large cohort studies dating back to the Framingham Heart Study have identified cholesterol as a modifiable risk factor, which can be treated with lifestyle and pharmacological interventions

*DOI: http://dx.doi.org/10.5772/intechopen.82355*

group than general populations.

adjust the treatment.

high-risk group [10, 14].

represent clinical practice.

**4. Clinical implications in real world practice**

#### *Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy… DOI: http://dx.doi.org/10.5772/intechopen.82355*

However, there are numerous factors which may confound the goal achievement, including statin dose, potency of statin, culture, socio-economic status, healthcare policy, concomitant medications, etc. Also, the selection bias from selected study sites, which were from diabetes and hypertension clinics even we tried to do the study in various parts of the country. This leads to a higher proportion of high-risk group than general populations.

Our study was based on the availability of lipid profiles of patients measured on request, as per real-life clinical practice; however, there were no significant differences between the percentage achievement of LDL-C goals among patients whose lipid profile was assessed before or after the median of 5.5 months prior to the survey date. This result might indicate that LDL-C levels were underutilized to adjust the treatment.

In our study, the percentage of lowered LDL-C according to goal levels, as defined by NCEP ATP III guidelines, among the high-cardiovascular-risk group, was 51.1% compared with 39.2% in a 1997–1998 study [10] and 34.6% in the 2002–2003 study [14]. The higher percentage found in our study could be due to various reasons: (1) we included only patients who used statins and not any other lipid-lowering agent alone; (2) there has been an increasing focus on the benefits of intensive cholesterol reduction; (3) new and more efficacious statins have been developed; (4) 95% of the patients in our study were attended by specialists who might be more likely to adhere to the guidelines; and (5) two-thirds of the patients in our study were females, who might have had a greater rate of compliance to the treatment or might have had a greater response to therapy than males, although there are few data to support this. As with other studies, our study found that the lowest percentage of achieving the recommended LDL-C target was in the very high-risk group [10, 14].

A number of aspects of our study can be considered strengths. First, the case selection was unbiased, as it was carried out consecutively and independent of the attending physicians. Second, we covered a large number (52.6%) of secondary- and tertiary-care hospitals across the country. Third, almost all of the studied patients (99.0%) were attended by an internal medicine, specialist, particularly the very high-risk and high-risk patients. Finally, our study represented real-life, clinical settings in Thailand, so the percentage achievement of LDL-C goals may represent clinical practice.

In summary, our study demonstrated that 51.1% of patients with cardiovascular risk on statin treatment achieved the LDL-C goal levels defined by the NCEP ATP III guidelines. We suggest that patients with a high CHD risk should be targeted for more aggressive lipid-lowering management. National campaigns to increase the awareness among both physicians and patients of the importance of achieving the LDL-C goals are needed to optimize the prevention of cardiovascular events and to further reduce the burden of cardiovascular diseases. Further investigation is needed to understand the reasons for patients not achieving lower LDL-C levels.

## **4. Clinical implications in real world practice**

Despite the >50% decrease in age-adjusted cardiovascular mortality over the past several decades, atherosclerotic disease is still the leading cause of morbidity and mortality. Moreover, cardiovascular disease accounts for more than half of all non-communicable diseases and has become the leading cause of death worldwide, a fact affirmed by the World Health Organization [15]. Large cohort studies dating back to the Framingham Heart Study have identified cholesterol as a modifiable risk factor, which can be treated with lifestyle and pharmacological interventions

*Dyslipidemia*

achievement of lower LDL-C goals.

51.1% when they were excluded.

Males had a statistically higher percentage achievement of the lower LDL-C goals than females (p = 0.024) (**Table 1**). The duration of statin treatment and the statin use, either alone or combined with other regimens, had a similar percentage

The final number of subjects included in the analysis was 1240. Initially, the calculated sample size was 1260, of which 20 (1.8%) patients had a statin treatment of <3 months. These were identified after enrolment and excluded from the analysis. This elimination did not, however, affect the study findings, that is, the percentage achievement of LDL-C goals was 52.5% when they were included, compared with

We, thus, included only patients who had been treated for at least 3 months with

no maximum limit of treatment duration. The results in **Table 2** indeed suggest that the duration of statin treatment had no effect on the percentage achievement of LDL-C goals, which was about 51% for every interval of 12 months (p = 0.975).

**Selected factors No Percentage achievement p Value** Gender 0.029

Male by age (years) at risk 0.750

Female by age (years) at risk 0.057

Duration (months) of statin treatment 0.997

Statins received 0.842

Field of expertise of attending physicians 0.360

0.598

Male 417 55.4 Female 823 48.9

≥45 394 55.6 <45 23 52.2

≥55 of age 623 50.7 <55 200 43.0

3–6 136 50.7 7–12 245 51.0 13–24 349 50.4 25–36 235 51.9 ≥37 275 51.3

Statins only 1156 51.1 Statins with other lipid-lowering drugs 84 50.0

Internal medicine 1227 51.2 Non-internal medicine 13 38.5

General 1029 51.2 Cardiologist 128 53.9 Endocrinologist, nephrologists or neurologist 67 46.3

*Percentage low-density lipoprotein cholesterol achievement goals by selected factors.*

Field of expertise of attending physicians

who were in internal medicine

**74**

**Table 2.**

[16]. Total cholesterol levels have decreased in high-income countries over the past 2 decades by 8–10% on average. Some countries with the highest levels were able to decrease levels more than this with targeted societal interventions, leading directly to dramatic decreases in event rates. As part of the United Nations declaration on non-communicable diseases, with a goal of reducing premature death by 25%, their target is a 20% relative reduction in high total cholesterol by 2025. To be truly effective, the treatment of dyslipidemia needs to be incorporated into a comprehensive plan of global risk reduction for patients at risk. This will involve lifestyle modification, policy change, and pharmacotherapy.

## **5. Similarities and differences in dyslipidemia guidelines**

New dyslipidemia guidelines were released by the European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS) in 2011 [17], the CCS in 2012 [18], the International Atherosclerosis Society [19], and the American College of Cardiology (ACC)/American Heart Association (AHA), both in 2013 [20]. All are similar in many respects, yet have some key differences that are worthy of discussion. The 2012 CCS guidelines recommended risk stratification using the total cardiovascular disease **F**ramingham **R**isk **S**core (FRS) [21], advocated the use of low-density lipoprotein cholesterol (LDL-C) thresholds for the initiation of treatment in low- and intermediate-risk subjects and expanded the phenotype of high-risk subjects to include subjects with atherosclerosis, most patients with diabetes, high-risk hypertension (per **A**nglo-**S**candinavian **C**ardiac **O**utcomes **T**rial [ASCOT] inclusion criteria) [22] and predialysis chronic kidney disease (CKD). LDL-C continues to be used as the atherogenic metric, but now non-high-density lipoprotein cholesterol (HDL-C) and apolipoprotein B (apo B) could be measured as alternatives, especially under circumstances when LDL-C calculations are known to be erroneous. When treatment is initiated, LDL-C (<2.0 mmol/L or 50% reduction) continues to be the primary target of therapy. The CCS guidelines have been harmonized with other relevant Canadian guidelines as part of the Canadian Cardiovascular Harmonization National Guidelines Endeavor (C-CHANGE) initiative [23] (**Table 3**).

The ESC/EAS guidelines was a comprehensive document that encouraged the use of the **S**ystematic **Co**ronary **R**isk **E**valuation (SCORE) total cardiovascular mortality [24].

Calibrated for high- or low-risk countries in Europe. Of note, the SCORE risk assessment is also based on the Framingham risk equation. LDL-C thresholds were suggested with non-HDL-C or apo B as alternatives. The European guidelines also recognized CKD as very high-risk equivalent. Target levels of LDL-C were recommended but unlike the CCS guidelines, the goals were different between those at very high risk (<1.8 mmol/L) compared with those at high risk (<2.5 mmol/L) or intermediate risk (<3.0 mmol/L).

The International Atherosclerosis Society panel decided to recommend lifetime cardiovascular risk based on 4 different tools depending on ethnicity. They favored non-HDL-C as the primary atherogenic metric for risk determination, with LDL-C as a secondary measure. Optimal levels were defined based on criteria from Adult Treatment Panel-III (ATP-III), but did not recommend treatment targets. The intensity of statin therapy should be adjusted according to overall lifetime risk and practitioner practice.

The ACC/AHA guidelines were the latest to be released and created the most controversy [20]. A major novel aspect of these guidelines was the recommendation to calculate risk using the newly developed Pooled Cohort Equation. This approach

**77**

*Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy…*

**Guidelines Year Major features Limitations**

2011 Comprehensive document that

2012 Risk stratification using the total

2013 Recommend lifetime cardiovascular risk based on 4 different tools depending on ethnicity. They favored non-HDL-C as the primary atherogenic metric for risk determination, with LDL-C as a secondary measure. Optimal levels were defined based on criteria from Adult Treatment Panel-III (ATP-III)

2013 Recommendation to calculate risk using the newly developed Pooled Cohort Equation. No recommendation for treating to any specific target. "Fire and

forget" approach

*Similarities and differences in dyslipidemia guidelines.*

equivalent

hypertension

encouraged the use of the Systematic Coronary Risk Evaluation (SCORE) total cardiovascular mortality 10 calibrated for high- or low-risk countries in Europe. Also recognized CKD as very high-risk

cardiovascular disease Framingham Risk Score (FRS), use of LDL-C thresholds for the initiation of treatment in low- and intermediate-risk subjects and expanded the phenotype of high-risk subjects to include subjects with atherosclerosis, most patients with diabetes, high-risk

Target levels of LDL-C were recommended but unlike the CCS guidelines, the goals were different between those at very high risk (<1.8 mmol/L) compared with those at high risk (<2.5 mmol/L) or intermediate risk (<3.0 mmol/L)

LDL-C continues to be used as the atherogenic metric, but non-highdensity lipoprotein cholesterol (HDL-C) and apolipoprotein B (apo B) could be measured as alternatives, especially under circumstances when LDL-C calculations are known to be

Not recommend treatment targets. The intensity of statin therapy should be adjusted according to overall lifetime risk and practitioner practice.

Created the most controversy. Novel aspect was the recommendation to calculate risk using the newly developed Pooled Cohort Equation. The new risk engine tended to overestimate events.

erroneous

represents a departure from the use of the FRS, used for decades. Of the 4 groups targeted for statin-based therapy, 3 were the same as the CCS guidelines. These include subjects with: (1) clinical evidence of atherosclerosis; (2) most subjects with diabetes; and (3) individuals with LDL-C ≥5.0 mmol/L. The fourth group includes subjects with a 10-year risk of total atherosclerotic events calculated using the Pooled Cohort Equation of ≥7.5% [25, 26]. There was no specific recommendation for CKD and other populations such as genetic dyslipidemia or high-risk hypertension. An additional novel aspect of these guidelines was the lack of specific targets of therapy. Although these guidelines recommend the use of high- or moderate-intensity statin regimens based on level of risk and anticipate a 50% LDL-C decrease with high-intensity statin therapy, there is no recommendation for treating to any specific target. Therefore, lipid measurements after initiation of

The new ACC/AHA guidelines were distinctly different from most previous recommendations in that they have discarded specific LDL-C (or alternative) targets when subjects are initiated with therapy. The rationale for this change was that no previous randomized trial specifically addressed whether a particular level produced

statin therapy are recommended, primarily to ensure adherence.

**6. The elimination of atherogenic lipoprotein targets**

*DOI: http://dx.doi.org/10.5772/intechopen.82355*

European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS) in 2011 [17]

Canadian

International Atherosclerosis Society

American College of Cardiology (ACC)/ American Heart Association (AHA)

[18]

[ 19]

[20]

**Table 3.**

Cardiovascular Society Guidelines (CCS) 2012 *Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy… DOI: http://dx.doi.org/10.5772/intechopen.82355*

#### **Table 3.**

*Dyslipidemia*

tion, policy change, and pharmacotherapy.

**5. Similarities and differences in dyslipidemia guidelines**

New dyslipidemia guidelines were released by the European Society of Cardiology (ESC)/European Atherosclerosis Society (EAS) in 2011 [17], the CCS in 2012 [18], the International Atherosclerosis Society [19], and the American College of Cardiology (ACC)/American Heart Association (AHA), both in 2013 [20]. All are similar in many respects, yet have some key differences that are worthy of discussion. The 2012 CCS guidelines recommended risk stratification using the total cardiovascular disease **F**ramingham **R**isk **S**core (FRS) [21], advocated the use of low-density lipoprotein cholesterol (LDL-C) thresholds for the initiation of treatment in low- and intermediate-risk subjects and expanded the phenotype of high-risk subjects to include subjects with atherosclerosis, most patients with diabetes, high-risk hypertension (per **A**nglo-**S**candinavian **C**ardiac **O**utcomes **T**rial [ASCOT] inclusion criteria) [22] and predialysis chronic kidney disease (CKD). LDL-C continues to be used as the atherogenic metric, but now non-high-density lipoprotein cholesterol (HDL-C) and apolipoprotein B (apo B) could be measured as alternatives, especially under circumstances when LDL-C calculations are known to be erroneous. When treatment is initiated, LDL-C (<2.0 mmol/L or 50% reduction) continues to be the primary target of therapy. The CCS guidelines have been harmonized with other relevant Canadian guidelines as part of the Canadian Cardiovascular Harmonization National Guidelines Endeavor (C-CHANGE) initia-

The ESC/EAS guidelines was a comprehensive document that encouraged the use of the **S**ystematic **Co**ronary **R**isk **E**valuation (SCORE) total cardiovascular

Calibrated for high- or low-risk countries in Europe. Of note, the SCORE risk assessment is also based on the Framingham risk equation. LDL-C thresholds were suggested with non-HDL-C or apo B as alternatives. The European guidelines also recognized CKD as very high-risk equivalent. Target levels of LDL-C were recommended but unlike the CCS guidelines, the goals were different between those at very high risk (<1.8 mmol/L) compared with those at high risk (<2.5 mmol/L) or

The International Atherosclerosis Society panel decided to recommend lifetime cardiovascular risk based on 4 different tools depending on ethnicity. They favored non-HDL-C as the primary atherogenic metric for risk determination, with LDL-C as a secondary measure. Optimal levels were defined based on criteria from Adult Treatment Panel-III (ATP-III), but did not recommend treatment targets. The intensity of statin therapy should be adjusted according to overall lifetime risk and

The ACC/AHA guidelines were the latest to be released and created the most controversy [20]. A major novel aspect of these guidelines was the recommendation to calculate risk using the newly developed Pooled Cohort Equation. This approach

[16]. Total cholesterol levels have decreased in high-income countries over the past 2 decades by 8–10% on average. Some countries with the highest levels were able to decrease levels more than this with targeted societal interventions, leading directly to dramatic decreases in event rates. As part of the United Nations declaration on non-communicable diseases, with a goal of reducing premature death by 25%, their target is a 20% relative reduction in high total cholesterol by 2025. To be truly effective, the treatment of dyslipidemia needs to be incorporated into a comprehensive plan of global risk reduction for patients at risk. This will involve lifestyle modifica-

**76**

tive [23] (**Table 3**).

intermediate risk (<3.0 mmol/L).

practitioner practice.

mortality [24].

*Similarities and differences in dyslipidemia guidelines.*

represents a departure from the use of the FRS, used for decades. Of the 4 groups targeted for statin-based therapy, 3 were the same as the CCS guidelines. These include subjects with: (1) clinical evidence of atherosclerosis; (2) most subjects with diabetes; and (3) individuals with LDL-C ≥5.0 mmol/L. The fourth group includes subjects with a 10-year risk of total atherosclerotic events calculated using the Pooled Cohort Equation of ≥7.5% [25, 26]. There was no specific recommendation for CKD and other populations such as genetic dyslipidemia or high-risk hypertension. An additional novel aspect of these guidelines was the lack of specific targets of therapy. Although these guidelines recommend the use of high- or moderate-intensity statin regimens based on level of risk and anticipate a 50% LDL-C decrease with high-intensity statin therapy, there is no recommendation for treating to any specific target. Therefore, lipid measurements after initiation of statin therapy are recommended, primarily to ensure adherence.

## **6. The elimination of atherogenic lipoprotein targets**

The new ACC/AHA guidelines were distinctly different from most previous recommendations in that they have discarded specific LDL-C (or alternative) targets when subjects are initiated with therapy. The rationale for this change was that no previous randomized trial specifically addressed whether a particular level produced greater event reduction. Second, by eliminating targets it was believed that primary care treatment would be more straightforward and easier to implement. Third, having targets potentially promotes combination therapy, for which there is currently no good evidence from randomized trials. This is supported by data from meta-analysis of trials of fibrate therapy, **A**therothrombosis **I**ntervention in **M**etabolic Syndrome with Low **H**DL/High triglycerides and **I**mpact on **G**lobal **H**ealth Outcomes (AIM-HIGH) and **H**eart **P**rotection **S**tudy **2**: **T**reatment of **H**DL to **R**educe the **I**ncidence of **V**ascular **E**vents (HPS2-THRIVE) [27–29].When using combination therapy one must be aware that the addition of either fibrates or niacin to statin therapy may increase the risk of myositis. The increased risk of myositis is greatest when gemfibrozil is used in combination with statins. Fenofibrate has a much more modest risk and the FDA approved the use of fenofibrate in combination with moderate doses of statins. The increased risk with niacin appears to be modest. In the AIM-HIGH trial the risk of myositis was not increased in patients on the combination of Niaspan and statin, whereas in the HPS2-Thrive trial myopathy was increased in the group treated with the combination of niacin and statin. The absolute risks of combination therapy are relatively modest if patients are carefully selected; in many patients at high risk for cardiovascular disease combination therapy may be appropriate. As with many decisions in medicine one needs to balance the benefits of therapy with the risks of therapy and determine for the individual patient the best approach. In deciding to use combination therapy a key focus is the non-HDL-C level. When the LDL is at goal but the non-HDL-C is still markedly above goal it may be appropriate to resort to combination therapy in patients at high risk.

Although this interpretation is literally correct, it fails to recognize several issues in the history of statin trials: the initial trials were as much studies of the lipid hypothesis as they were trials of statins. Thus, the first trials were in patients with the highest risk and highest cholesterol levels but at a time when only moderately potent statins were available, hence the use of the highest dose feasible. Because success was shown, and as more potent statins became available, ethical considerations mandated that research subjects had to have lower and lower risk and lower and lower cholesterol levels, again promoting use of the highest available dose. The latter was also influenced by a need to ensure simplicity in large trials and, to some extent, by marketing designed to promote drug potency differences. There are also 5 trials of higher vs. lower potency statins, which show consistent improvement in outcomes with the higher potency statin. The lowest risk cohort studied to date in the **J**ustification for the **U**se of Statins in **P**revention: An **I**ntervention **T**rial **E**valuating **R**osuvastatin (JUPITER) study reaped comparable benefit using the most potent statin currently available. Remarkably, no lower limit of achieved LDL-C beyond which benefit is accrued has yet been shown. The CCS dyslipidemia guideline primary panel reviewed these issues in early 2014 and recommended that until further evidence was available, we would continue to support the use of targets. Although it is certainly true that randomized trials have generally used a single statin dose approach, as opposed to a target LDL-C level, the epidemiology suggesting that lower levels of achieved LDL-C result in less events is rather compelling. Also, regression studies with intravascular ultrasound demonstrate a linear relationship between LDL-C and the amount of regression [30]. The crossing point for regression tends to occur at an LDL-C of around 2 mmol/L or a 50% reduction. A very recent meta-analysis used individual patient data from 8 statin trials [31]. Using a fixed dose of statin, there was a very large inter-individual variation in LDL-C reduction with statins. In addition, more than 40% of subjects did not achieve targets of <1.8 mmol/L with a fixed statin dose. Those who achieved very low levels of LDL-C had a lower event rate than those who achieved modest levels. The same trend was seen for non-HDL-C and apo B.

**79**

*Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy…*

We will be able to test the "lower is better" hypothesis at very low levels of LDL-C when the results of ongoing trials using nonstatins (e.g., inhibitors of cholesterol absorption, proprotein convertase subtisilin/kexin type 9 (PCSK9) and cholesterol ester transfer protein (CETP) are well established and widely applicable

The ACC/AHA guidelines would appear at first blush to support a "fire and forget" approach. The text and algorithms do, however, suggest that measuring LDL-C after statin initiation is reasonable to help assess compliance and to ensure achievement of an expected percentage of decrease of LDL-C. Compliance and adherence are important issues with statin therapy [32] and beyond the scope of this review, but are certainly another practical reason that the CCS guidelines panel continues to recommend targets. Additionally, the text and algorithms of the ACC/AHA guidelines promote LDL-C measurement to ensure achievement of the expected response to moderate- and high-intensity statin dose choices and, when not achieved or in the face of statin intolerance, support dose escalation or addition

The new ACC/AHA guidelines have generated considerable debate and confusion in the medical literature about the specifics of risk assessment and treatment of dyslipidemia in cardiovascular disease prevention. It is healthy to accept that there are different approaches to screening and management, because of the lack of decisive evidence in certain domains. The discussion should be used to highlight the need to address outstanding questions in the future. However, in the interim, our patients can be very well managed with existing guidelines that are updated on an ongoing basis when new knowledge is generated. A guidelines-based approach to screening, treatment, and compliance should continue to be the standard for all of our at-risk patients. In conclusion, the National Guideline campaigns to increase the awareness among both physicians and patients of the importance of achieving the LDL-C goals are needed to optimize the prevention of cardiovascular events and to further

*DOI: http://dx.doi.org/10.5772/intechopen.82355*

to practitioners.

of secondary, non-statin drugs.

reduce the burden of cardiovascular diseases.

*Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy… DOI: http://dx.doi.org/10.5772/intechopen.82355*

We will be able to test the "lower is better" hypothesis at very low levels of LDL-C when the results of ongoing trials using nonstatins (e.g., inhibitors of cholesterol absorption, proprotein convertase subtisilin/kexin type 9 (PCSK9) and cholesterol ester transfer protein (CETP) are well established and widely applicable to practitioners.

The ACC/AHA guidelines would appear at first blush to support a "fire and forget" approach. The text and algorithms do, however, suggest that measuring LDL-C after statin initiation is reasonable to help assess compliance and to ensure achievement of an expected percentage of decrease of LDL-C. Compliance and adherence are important issues with statin therapy [32] and beyond the scope of this review, but are certainly another practical reason that the CCS guidelines panel continues to recommend targets. Additionally, the text and algorithms of the ACC/AHA guidelines promote LDL-C measurement to ensure achievement of the expected response to moderate- and high-intensity statin dose choices and, when not achieved or in the face of statin intolerance, support dose escalation or addition of secondary, non-statin drugs.

The new ACC/AHA guidelines have generated considerable debate and confusion in the medical literature about the specifics of risk assessment and treatment of dyslipidemia in cardiovascular disease prevention. It is healthy to accept that there are different approaches to screening and management, because of the lack of decisive evidence in certain domains. The discussion should be used to highlight the need to address outstanding questions in the future. However, in the interim, our patients can be very well managed with existing guidelines that are updated on an ongoing basis when new knowledge is generated. A guidelines-based approach to screening, treatment, and compliance should continue to be the standard for all of our at-risk patients.

In conclusion, the National Guideline campaigns to increase the awareness among both physicians and patients of the importance of achieving the LDL-C goals are needed to optimize the prevention of cardiovascular events and to further reduce the burden of cardiovascular diseases.

*Dyslipidemia*

greater event reduction. Second, by eliminating targets it was believed that primary care treatment would be more straightforward and easier to implement. Third, having targets potentially promotes combination therapy, for which there is currently no good evidence from randomized trials. This is supported by data from meta-analysis of trials of fibrate therapy, **A**therothrombosis **I**ntervention in **M**etabolic Syndrome with Low **H**DL/High triglycerides and **I**mpact on **G**lobal **H**ealth Outcomes (AIM-HIGH) and **H**eart **P**rotection **S**tudy **2**: **T**reatment of **H**DL to **R**educe the **I**ncidence of **V**ascular **E**vents (HPS2-THRIVE) [27–29].When using combination therapy one must be aware that the addition of either fibrates or niacin to statin therapy may increase the risk of myositis. The increased risk of myositis is greatest when gemfibrozil is used in combination with statins. Fenofibrate has a much more modest risk and the FDA approved the use of fenofibrate in combination with moderate doses of statins. The increased risk with niacin appears to be modest. In the AIM-HIGH trial the risk of myositis was not increased in patients on the combination of Niaspan and statin, whereas in the HPS2-Thrive trial myopathy was increased in the group treated with the combination of niacin and statin. The absolute risks of combination therapy are relatively modest if patients are carefully selected; in many patients at high risk for cardiovascular disease combination therapy may be appropriate. As with many decisions in medicine one needs to balance the benefits of therapy with the risks of therapy and determine for the individual patient the best approach. In deciding to use combination therapy a key focus is the non-HDL-C level. When the LDL is at goal but the non-HDL-C is still markedly above goal it may be appropriate

Although this interpretation is literally correct, it fails to recognize several issues

in the history of statin trials: the initial trials were as much studies of the lipid hypothesis as they were trials of statins. Thus, the first trials were in patients with the highest risk and highest cholesterol levels but at a time when only moderately potent statins were available, hence the use of the highest dose feasible. Because success was shown, and as more potent statins became available, ethical considerations mandated that research subjects had to have lower and lower risk and lower and lower cholesterol levels, again promoting use of the highest available dose. The latter was also influenced by a need to ensure simplicity in large trials and, to some extent, by marketing designed to promote drug potency differences. There are also 5 trials of higher vs. lower potency statins, which show consistent improvement in outcomes with the higher potency statin. The lowest risk cohort studied to date in the **J**ustification for the **U**se of Statins in **P**revention: An **I**ntervention **T**rial **E**valuating **R**osuvastatin (JUPITER) study reaped comparable benefit using the most potent statin currently available. Remarkably, no lower limit of achieved LDL-C beyond which benefit is accrued has yet been shown. The CCS dyslipidemia guideline primary panel reviewed these issues in early 2014 and recommended that until further evidence was available, we would continue to support the use of targets. Although it is certainly true that randomized trials have generally used a single statin dose approach, as opposed to a target LDL-C level, the epidemiology suggesting that lower levels of achieved LDL-C result in less events is rather compelling. Also, regression studies with intravascular ultrasound demonstrate a linear relationship between LDL-C and the amount of regression [30]. The crossing point for regression tends to occur at an LDL-C of around 2 mmol/L or a 50% reduction. A very recent meta-analysis used individual patient data from 8 statin trials [31]. Using a fixed dose of statin, there was a very large inter-individual variation in LDL-C reduction with statins. In addition, more than 40% of subjects did not achieve targets of <1.8 mmol/L with a fixed statin dose. Those who achieved very low levels of LDL-C had a lower event rate than those who achieved modest levels.

to resort to combination therapy in patients at high risk.

The same trend was seen for non-HDL-C and apo B.

**78**

## **Author details**

Songkwan Silaruks1 \*, Charn Sriratanasathavorn<sup>2</sup> , Petch Rawdaree3 , Rapeephon Kunjara-Na-Ayudhaya4 , Bandit Thinkhamrop5 and Piyamitr Sritara6

1 Department of Medicine, Khon Kaen University, Khon Kaen, Thailand

2 Her Majesty's Cardiac Center, Department of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand

3 Endocrinology Unit, BMA Medical College, Vajira Hospital, Thailand

4 Vichaiyut Hospital, Thailand

5 Department of Biostatistics and Demography, Khon Kaen University, Khon Kaen, Thailand

6 Department of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand

\*Address all correspondence to<EMAIL_ADDRESS>
© 2019 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.

**81**

*Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy…*

[8] Pearson TA, Laurora I, Chu H, et al. The lipid treatment assessment project (L-TAP): A multicenter survey to evaluate the percentages of dyslipidemic patients receiving lipid-lowering therapy and achieving low-density lipoprotein cholesterol goals. Archives of Internal Medicine.

[9] Qayyum R, Chattha AA, Bhullar N, et al. Achievement of national cholesterol education program goals by patients with dyslipidemia in rural ambulatory care settings. Preventive

Cardiology. 2006;**9**:192-197

[10] Nitiyanant W, Ngamukos P, Koanantakul B. Lipid treatment

assessment project (L-TAP) in Thailand. Internal Medical Journal of Thailand.

[11] Nitiyanant Ws P, Deerochanawong C. The Lipid Treatment Assessment Project II (L-TAP II) in Thailand. L-TAP II in Thailand Free Paper and Poster presented at 15th ASEAN

Congress of Cardiology (ACC). Pattaya, Thailand: The 15th ASEAN Congress of

[12] Johnson LW, Weinstock RS. The metabolic syndrome: Concepts and controversy. Mayo Clinic Proceedings.

[13] Silaruks S, Sriratanasathavorn C, Rawdaree P, Na-Ayudhaya K, Thinkhamrop B, Sritara P. Lipidlowering therapy using statins in patients with cardiovascular risk in clinical practice in Thailand. Heart Asia.

Cardiology (ACC); 2004

2006;**81**:1615-1620

2011;**3**(1):99-103

2008;**91**:836-845

[14] Nitiyanant W, Sritara P, Deerochanawong C, et al. Lipid treatment assessment project II in Thailand (LTAP-II Thailand). Journal of the Medical Association of Thailand.

2000;**160**:459-467

2001;**17**:246-252

*DOI: http://dx.doi.org/10.5772/intechopen.82355*

[1] Anon. Summary of the second report of the national cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel II). JAMA.

[2] Anon. National cholesterol education program. Second report of the expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel II). Circulation. 1994;**89**:1333-1445.

[3] Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III). JAMA. 2001;**285**:2486-2497

[4] Anderson TJ, Mancini GB, Genest J Jr, Gregoire J, Lonn EM, Hegele RA. The new dyslipidemia guidelines: What is the debate? The Canadian Journal of Cardiology. 2015;**31**(5):605-612. DOI:

[5] Baigent C, Keech A, Kearney PM, et al. Efficacy and safety of cholesterollowering treatment: Prospective metaanalysis of data from 90,056 participants in 14 randomised trials of statins. Lancet.

2005;**366**:1267-1278. [PubMed]

1425-1435. [PubMed]

2004;**9**:269-279. [PubMed]

[6] LaRosa JC, Grundy SM, Waters DD, et al. Intensive lipid lowering with atorvastatin in patients with stable coronary disease. The New England Journal of Medicine. 2005;**352**:

[7] Rosenson R. Statins: Can the new generation make an impression? Expert Opinion on Emerging Drugs.

10.1016/j.cjca.2014.11.007

**References**

1993;**269**:3015-3023

[PubMed]

*Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy… DOI: http://dx.doi.org/10.5772/intechopen.82355*

## **References**

*Dyslipidemia*

**Author details**

Songkwan Silaruks1

Rapeephon Kunjara-Na-Ayudhaya4

University, Bangkok, Thailand

4 Vichaiyut Hospital, Thailand

**80**

Thailand

Thailand

provided the original work is properly cited.

\*Address all correspondence to<EMAIL_ADDRESS>
© 2019 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,

\*, Charn Sriratanasathavorn<sup>2</sup>

1 Department of Medicine, Khon Kaen University, Khon Kaen, Thailand

3 Endocrinology Unit, BMA Medical College, Vajira Hospital, Thailand

2 Her Majesty's Cardiac Center, Department of Medicine, Siriraj Hospital, Mahidol

5 Department of Biostatistics and Demography, Khon Kaen University, Khon Kaen,

6 Department of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok,

, Petch Rawdaree3

, Bandit Thinkhamrop5

,

and Piyamitr Sritara6

[1] Anon. Summary of the second report of the national cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel II). JAMA. 1993;**269**:3015-3023

[2] Anon. National cholesterol education program. Second report of the expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel II). Circulation. 1994;**89**:1333-1445. [PubMed]

[3] Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III). JAMA. 2001;**285**:2486-2497

[4] Anderson TJ, Mancini GB, Genest J Jr, Gregoire J, Lonn EM, Hegele RA. The new dyslipidemia guidelines: What is the debate? The Canadian Journal of Cardiology. 2015;**31**(5):605-612. DOI: 10.1016/j.cjca.2014.11.007

[5] Baigent C, Keech A, Kearney PM, et al. Efficacy and safety of cholesterollowering treatment: Prospective metaanalysis of data from 90,056 participants in 14 randomised trials of statins. Lancet. 2005;**366**:1267-1278. [PubMed]

[6] LaRosa JC, Grundy SM, Waters DD, et al. Intensive lipid lowering with atorvastatin in patients with stable coronary disease. The New England Journal of Medicine. 2005;**352**: 1425-1435. [PubMed]

[7] Rosenson R. Statins: Can the new generation make an impression? Expert Opinion on Emerging Drugs. 2004;**9**:269-279. [PubMed]

[8] Pearson TA, Laurora I, Chu H, et al. The lipid treatment assessment project (L-TAP): A multicenter survey to evaluate the percentages of dyslipidemic patients receiving lipid-lowering therapy and achieving low-density lipoprotein cholesterol goals. Archives of Internal Medicine. 2000;**160**:459-467

[9] Qayyum R, Chattha AA, Bhullar N, et al. Achievement of national cholesterol education program goals by patients with dyslipidemia in rural ambulatory care settings. Preventive Cardiology. 2006;**9**:192-197

[10] Nitiyanant W, Ngamukos P, Koanantakul B. Lipid treatment assessment project (L-TAP) in Thailand. Internal Medical Journal of Thailand. 2001;**17**:246-252

[11] Nitiyanant Ws P, Deerochanawong C. The Lipid Treatment Assessment Project II (L-TAP II) in Thailand. L-TAP II in Thailand Free Paper and Poster presented at 15th ASEAN Congress of Cardiology (ACC). Pattaya, Thailand: The 15th ASEAN Congress of Cardiology (ACC); 2004

[12] Johnson LW, Weinstock RS. The metabolic syndrome: Concepts and controversy. Mayo Clinic Proceedings. 2006;**81**:1615-1620

[13] Silaruks S, Sriratanasathavorn C, Rawdaree P, Na-Ayudhaya K, Thinkhamrop B, Sritara P. Lipidlowering therapy using statins in patients with cardiovascular risk in clinical practice in Thailand. Heart Asia. 2011;**3**(1):99-103

[14] Nitiyanant W, Sritara P, Deerochanawong C, et al. Lipid treatment assessment project II in Thailand (LTAP-II Thailand). Journal of the Medical Association of Thailand. 2008;**91**:836-845

[15] Laslett LJ, Alagona P Jr, Clark BA 3rd, et al. Journal of the American College of Cardiology. 2012;**60**:S1-S49

[16] Wilson PW, D'Agostino RB, Levy D, et al. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;**97**:1837-1847

[17] European Association for Cardiovascular Prevention and Rehabilitation, Reiner Z, Catapano AL, et al. European Heart Journal. 2011;**32**:1769-1818

[18] Anderson TJ, Gregoire J, Hegele RA, et al. 2012 update of the Canadian cardiovascular society guidelines for the diagnosis and treatment of dyslipidemia for the prevention of cardiovascular disease in the adult. The Canadian Journal of Cardiology. 2013;**29**:151-167

[19] Expert Dyslipidemia Panel of the International Atherosclerosis Society Panel members. An international atherosclerosis society position paper: Global recommendations for the management of dyslipidemia–full report. Journal of Clinical Lipidology. 2014;**8**:29-60

[20] Stone NJ, Robinson J, Lichtenstein AH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: A report of the American College of Cardiology/American Heart Association task force on practice guidelines. [erratum in 2014;63:3024- 5]. Journal of the American College of Cardiology. 2013;**63**:2889-2934

[21] D'Agostino RB Sr, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: The Framingham heart study. Circulation. 2008;**117**:743-753

[22] Sever PS, Dahlof B, Poulter NR, et al. Prevention of coronary and stroke events with atorvastatin in hypertensive patients who have

average or lower-than-average cholesterol concentrations, in the anglo-scandinavian cardiac outcomes trial–lipid lowering arm (ASCOT-LLA): A multicentre randomised controlled trial. Lancet. 2003;**361**:1149-1158

[23] Tobe SW, Stone JA, Brouwers M, et al. Harmonization of guidelines for the prevention and treatment of cardiovascular disease: The C-CHANGE initiative. CMAJ. 2011;**183**:E1135-E1150

[24] Conroy RM, Pyorala K, Fitzgerald AP, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: The SCORE project. European Heart Journal. 2003;**24**:987-1003

[25] Goff DC Jr, Lloyd-Jones DM, Bennett G, et al. Circulation. 2013;**129**(25 suppl 2):S49-S73

[26] Ridker PM, Cook Statins NR. New American guidelines for prevention of cardiovascular disease. Lancet. 2013;**382**:1762-1765

[27] AIM-HIGH Investigators, Boden WE, Probstfield JL, et al. Niacin in patients with low HDL cholesterol levels receiving intensive statin therapy. The New England Journal of Medicine. 2011;**365**:2255-2267

[28] HPS2-THRIVE Collaborative Group, Landray MJ, Haynes R, et al. The New England Journal of Medicine. 2014;**371**:203-212

[29] Cholesterol Treatment Trialists' (CTT) Collaborators, Mihaylova B, Emberson J, et al. The effects of lowering LDL cholesterol with statin therapy in people at low risk of vascular disease: Meta-analysis of individual data from 27 randomised trials. Lancet, 2012;**380**:581-590

[30] Ballantyne M, Raichlen JS, Nicholls SJ, et al. Effect of rosuvastatin therapy on coronary artery stenoses assessed by quantitative coronary

**83**

*Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy…*

*DOI: http://dx.doi.org/10.5772/intechopen.82355*

angiography: A study to evaluate the effect of rosuvastatin on intravascular

ultrasound-derived coronary atheroma burden. Circulation.

[31] Boekholdt SM, Hovingh GK, Mora S, et al. Very low levels of

[32] Ben-Yehuda AN. DeMariaLDLcholesterol targets after the ACC/AHA 2013 guidelines: Evidence that lower is better? Journal of the American College

of Cardiology. 2014;**64**:495-497

atherogenic lipoproteins and the risk for cardiovascular events: A meta-analysis of statin trials. Journal of the American College of Cardiology. 2014;**64**:485-494

2008;**117**:2458-2466

*Prevalence of Dyslipidemia and Goal Attainment with Lipid-Lowering Therapy… DOI: http://dx.doi.org/10.5772/intechopen.82355*

angiography: A study to evaluate the effect of rosuvastatin on intravascular ultrasound-derived coronary atheroma burden. Circulation. 2008;**117**:2458-2466

*Dyslipidemia*

[15] Laslett LJ, Alagona P Jr, Clark BA 3rd, et al. Journal of the American College of Cardiology. 2012;**60**:S1-S49 average or lower-than-average cholesterol concentrations, in the anglo-scandinavian cardiac outcomes trial–lipid lowering arm (ASCOT-LLA): A multicentre randomised controlled trial. Lancet. 2003;**361**:1149-1158

[23] Tobe SW, Stone JA, Brouwers M, et al. Harmonization of guidelines for the prevention and treatment of cardiovascular disease: The C-CHANGE initiative. CMAJ. 2011;**183**:E1135-E1150

[24] Conroy RM, Pyorala K, Fitzgerald AP, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: The SCORE project. European Heart

Journal. 2003;**24**:987-1003

2013;**382**:1762-1765

2011;**365**:2255-2267

2014;**371**:203-212

2012;**380**:581-590

[25] Goff DC Jr, Lloyd-Jones DM, Bennett G, et al. Circulation. 2013;**129**(25 suppl 2):S49-S73

[26] Ridker PM, Cook Statins NR. New American guidelines for prevention of cardiovascular disease. Lancet.

[27] AIM-HIGH Investigators, Boden WE, Probstfield JL, et al. Niacin in patients with low HDL cholesterol levels receiving intensive statin therapy. The New England Journal of Medicine.

[28] HPS2-THRIVE Collaborative Group, Landray MJ, Haynes R, et al. The New England Journal of Medicine.

[29] Cholesterol Treatment Trialists' (CTT) Collaborators, Mihaylova B, Emberson J, et al. The effects of lowering LDL cholesterol with statin therapy in people at low risk of vascular disease: Meta-analysis of individual data from 27 randomised trials. Lancet,

[30] Ballantyne M, Raichlen JS,

Nicholls SJ, et al. Effect of rosuvastatin therapy on coronary artery stenoses assessed by quantitative coronary

[16] Wilson PW, D'Agostino RB, Levy D, et al. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;**97**:1837-1847

[17] European Association for Cardiovascular Prevention and Rehabilitation, Reiner Z, Catapano AL, et al. European Heart Journal.

[18] Anderson TJ, Gregoire J, Hegele RA, et al. 2012 update of the Canadian cardiovascular society guidelines for the diagnosis and treatment of dyslipidemia for the prevention of cardiovascular disease in the adult. The Canadian Journal of Cardiology. 2013;**29**:151-167

[19] Expert Dyslipidemia Panel of the International Atherosclerosis Society Panel members. An international atherosclerosis society position paper: Global recommendations for the management of dyslipidemia–full report. Journal of Clinical Lipidology.

[20] Stone NJ, Robinson J, Lichtenstein AH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: A report of the American College of Cardiology/American Heart Association task force on practice guidelines. [erratum in 2014;63:3024- 5]. Journal of the American College of Cardiology. 2013;**63**:2889-2934

[21] D'Agostino RB Sr, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: The Framingham heart study. Circulation.

[22] Sever PS, Dahlof B, Poulter NR, et al. Prevention of coronary and stroke events with atorvastatin in hypertensive patients who have

2011;**32**:1769-1818

2014;**8**:29-60

2008;**117**:743-753

**82**

[31] Boekholdt SM, Hovingh GK, Mora S, et al. Very low levels of atherogenic lipoproteins and the risk for cardiovascular events: A meta-analysis of statin trials. Journal of the American College of Cardiology. 2014;**64**:485-494

[32] Ben-Yehuda AN. DeMariaLDLcholesterol targets after the ACC/AHA 2013 guidelines: Evidence that lower is better? Journal of the American College of Cardiology. 2014;**64**:495-497

**85**

**Chapter 5**

Factor

**Abstract**

postprandial lipemia.

dysfunction, hypertriglyceridemia

**1. Lipoprotein metabolism**

of lipoprotein metabolism.

Postprandial Lipemia as

Cardiovascular Disease Risk

*Neil Francis Amba and Leilani B. Mercado-Asis*

Postprandial lipemia (PPL) is characterized by prolonged and increased levels of lipids especially triglycerides (TG) and triglyceride-rich lipoprotein levels after a meal. There are an increasing number of evidence that postprandial lipemia is a significant risk factor for cardiovascular disease because of its causative role in atherosclerosis and endothelial dysfunction. This has serious implications because common dietary patterns are characterized by high fat content and meal consumption; hence, most will be in a postprandial state resulting to frequent and prolonged exposure to high lipid levels. The review will present the current evidences for the role of postprandial lipemia as a risk factor for cardiovascular disease and its association with other cardiovascular risk factors, namely, diabetes and obesity. We will also present recommendations on the diagnosis and management of

**Keywords:** postprandial lipemia, postprandial dyslipidemia, endothelial

Lipoproteins are responsible for the distribution of cholesterol and triglyceride from the intestine and liver to peripheral cells. The process of lipoprotein distribution and metabolism is highly related to energy metabolism and the feed-fast cycle. Triglycerides (TG) are synthesized from dietary free fatty acids and glycerol in enterocytes. They are assembled together with phospholipids and cholesterol with apolipoproteins, mainly apoB-48 into chylomicron particles (apo A, C, E also present). These TG-rich particles enter the plasma via the intestinal lymph. Chylomicrons are then transported to peripheral cells where the enzyme lipoprotein lipase (LPL) hydrolyses their triglyceride content, releasing free fatty acids to be used by peripheral cells. The resulting chylomicron remnants are smaller and denser and are removed in the circulation by binding of the surface apo E to the LDL receptor or LDL receptor-related protein (LRP) [1]. Please also refer to the introductory chapter of this book for detailed and illustrated review

In the liver, synthesized TGs are released to the circulation by the very lowdensity lipoprotein (VLDL) particles. VLDL particles are TG-rich and, mainly, apo B-100-containing particles (apo A, C, E also present). VLDL synthesis takes place

## **Chapter 5**