Prevalence of cardiovascular diseases in Punjab, Pakistan: a cross-sectional study

May Measurement Month 2018: an analysis of blood pressure screening results from Pakistan. Eur Heart J Suppl 2022;24:F31-F33. [PMID: 36225274 PMCID: PMC9547515 DOI: 10.1093/eurheartjsupp/suac034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

The May Measurement Month (MMM) screening campaigns comprise an opportunistic assessment of the arterial blood pressure (BP) of Pakistani adults (≥18 years old) and evaluate the level of awareness and spectrum of the problem of hypertension and the associated risk factors. The prospective study was carried out in May 2018 in multiple medical screening camps at hospitals, pharmacies, and public areas with the help of local health care workers under ethical guidelines. The volunteers took BP measurements using OMRON digital BP devices, in a seated position, and three successive readings were noted after 5 min rest. The mean values of the second and third readings were attained. Data were analysed centrally by the MMM project management team and multiple imputations were performed, where BP readings were missing. Hypertension was defined as a systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg, or in those taking antihypertensive medication. This study included 25 076 participants, of whom 14 726 (58.7%) were hypertensive. Among all hypertensives, only 11 681 were aware of their hypertension status. After imputation, age and gender standardization, mean systolic and diastolic BP were 129.8 mmHg and 82.9 mmHg, respectively. MMM17 data revealed that 55.2% of those screened were hypertensive in Pakistan, while in 2018 the proportion rose slightly to 58.7%. The prevalence of hypertension among those screened for MMM in Pakistan was high in both years. Although most patients with hypertension were treated, the majority remained uncontrolled. Further efforts to improve awareness and control are needed.

Early Diagnosis of Coronary Artery Disease by Inflammatory Biomarkers of Atherosclerosis in Patients with Angina

Early diagnosis of coronary artery disease (CAD) in patients with chest pain is a challenge. Currently diagnosis of CAD is confirmed by coronary angiography, which is invasive and not easily available in developing countries. Therefore, it is imperative to establish noninvasive biomarker for early diagnosis of CAD in patients with angina and determine the diagnostic accuracy of inflammatory biomarkers of atherosclerosis in comparison to angiography and correlate with severity of CAD in patients with angina. Diagnostic accuracy study was carried out in tertiary care hospitals, Rawalpindi, Pakistan. Total of 58 patients aged 55.24 ± 11.61 years, with chest pain and troponin-I -ve, having coronary artery stenosis ≥50% were included as cases of CAD and 55 subjects having stenosis <50% were included as controls. Nuclear factor kappa-B (NF-κB), tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and high-sensitivity C-reactive protein (hs-CRP) were analyzed on immunoassay analyzers. The receiver operating characteristic curve analysis revealed significant (P < 0.05) high area under curve (95% confidence interval) with sensitivity and specificity of NF-κB 0.76 (0.65-0.85), 73% and 65%; TNF-α 0.72 (0.61-0.81), 71% and 69%; IL-6 0.62 (0.52-0.71), 64% and 53% and hs-CRP 0.62 (0.52-0.71), and 53% and 56% in CAD patients compared to controls. There was significant positive correlation between NF-κB (r = 0.44), TNF-α (r = 0.37), IL-6 (r = 0.23), and hs-CRP (r = 0.23) with severity of CAD by Gensini score. The inflammatory biomarkers, especially NF-κB and TNF-α, have highest diagnostic accuracy and indicate severity of atherosclerosis in patients with angina. These markers may be used as noninvasive biomarkers to exclude healthy individuals before undergoing angiography.

Unhealthy Dietary Habits and Obesity: The Major Risk Factors Beyond Non-Communicable Diseases in the Eastern Mediterranean Region

There are 22 countries in the Eastern Mediterranean Region (EMR) expanding from Morocco in the west to Pakistan and Afghanistan in the east, containing a population of 725,721 million in 2020. In the previous 30 years, the illness burden in the EMR has transmitted from communicable diseases to non-communicable diseases such as diabetes, cardiovascular diseases, and cancer. In 2019, cardiovascular mortality in the EMR was mostly attributed to ischemic heart disease, the first reason for mortality in 19 countries in the region. Stroke was the second reason for death in nine countries followed by diabetes, which was ranked as the second reason for death in two countries. The prominent nutrition-related NCDs risk factors in EMR include obesity, hypertension, high fasting plasma glucose, and upregulated unhealthy diet consumption. Most of the EMR population are unaware of their NCDs risk factor status. These risk factors, even if treated, are often poorly controlled, therefore, inhibiting their existence by changing the lifestyle to proper dietary habits and sufficient physical activity is mandatory. In this review, the epidemiology and nutrition-related risk factors of NCDs in the EMR will be discussed and illustrated, aiming to scale up action and support decision-makers in implementing cost effective strategies to address obesity and NCDs prevention and management in the region.

Development of Nonlaboratory-Based Risk Prediction Models for Cardiovascular Diseases Using Conventional and Machine Learning Approaches

Criticism of the implementation of existing risk prediction models (RPMs) for cardiovascular diseases (CVDs) in new populations motivates researchers to develop regional models. The predominant usage of laboratory features in these RPMs is also causing reproducibility issues in low–middle-income countries (LMICs). Further, conventional logistic regression analysis (LRA) does not consider non-linear associations and interaction terms in developing these RPMs, which might oversimplify the phenomenon. This study aims to develop alternative machine learning (ML)-based RPMs that may perform better at predicting CVD status using nonlaboratory features in comparison to conventional RPMs. The data was based on a case–control study conducted at the Punjab Institute of Cardiology, Pakistan. Data from 460 subjects, aged between 30 and 76 years, with (1:1) gender-based matching, was collected. We tested various ML models to identify the best model/models considering LRA as a baseline RPM. An artificial neural network and a linear support vector machine outperformed the conventional RPM in the majority of performance matrices. The predictive accuracies of the best performed ML-based RPMs were between 80.86 and 81.09% and were found to be higher than 79.56% for the baseline RPM. The discriminating capabilities of the ML-based RPMs were also comparable to baseline RPMs. Further, ML-based RPMs identified substantially different orders of features as compared to baseline RPM. This study concludes that nonlaboratory feature-based RPMs can be a good choice for early risk assessment of CVDs in LMICs. ML-based RPMs can identify better order of features as compared to the conventional approach, which subsequently provided models with improved prognostic capabilities.

Therapeutic Effects and Safe Uses of Plant-Derived Polyphenolic Compounds in Cardiovascular Diseases: A Review

Polyphenols have long been recognized as health-promoting entities, including beneficial effects on cardiovascular disease, but their reputation has been boosted recently following a number of encouraging clinical studies in multiple chronic pathologies, that seem to validate efficacy. Health benefits of polyphenols have been linked to their well-established powerful antioxidant activity. This review aims to provide comprehensive and up-to-date knowledge on the current therapeutic status of polyphenols having sufficient heed towards the treatment of cardiovascular diseases. Furthermore, data about the safety profile of highly efficacious polyphenols has also been investigated to further enhance their role in cardiac abnormalities. Evidence is presented to support the action of phenolic derivatives against cardiovascular pathologies by following receptors and signaling pathways which ultimately cause changes in endogenous antioxidant, antiplatelet, vasodilatory, and anti-inflammatory activities. In addition, in vitro antioxidant and pre-clinical and clinical experiments on anti-inflammatory as well as immunomodulatory attributes of polyphenols have revealed their role as cardioprotective agents. However, an obvious shortage of in vivo studies related to dose selection and toxicity of polyphenols makes these compounds a suitable target for clinical investigations. Further studies are needed for the development of safe and potent herbal products against cardiovascular diseases. The novelty of this review is to provide comprehensive knowledge on polyphenols safety and their health claims. It will help researchers to identify those moieties which likely exert protective and therapeutic effects towards cardiovascular diseases.

Potential drug-drug interactions in patients with cardiovascular diseases: findings from a prospective observational study

Background

Patients with cardiovascular diseases (CVD) are at high risk of experiencing drug–drug interactions (DDIs). The objective of this study was to evaluate the frequency, level and risk factors associated with potential-DDIs (pDDIs) in hospitalized CVD patients at cardiology departments of two tertiary care hospitals in Quetta, Pakistan.

Methods

In the current prospective observational study, a total of 300 eligible CVD inpatients were evaluated for pDDIs using Lexicomp Interact®. The pDDIs were classified into class A (no known interaction); B (no action needed); C (monitor therapy: it is documented that the benefits of an interaction outweigh the risk, appropriately monitor therapy in order to avoid potential adverse outcomes); D (consider therapy modification: it is documented that proper actions must be taken to reduce the toxicity resulting from an interaction); X (avoid combination: the risk of an interaction outweighs the benefits and are usually contraindicated). Multivariate binary logistic regression analysis was used to find factors associated with the presence of Class-D and/or X pDDIs. A p-value < 0.05 was considered statistically significant.

Results

With a median of 8.50 pDDIs per patient, all patients (100%) had ≥ 1 pDDIs. Out of total 2787 pDDIs observed, 74.06% (n = 2064) were of moderate and (n = 483) 17.33% of major severity. Class C pDDIs were most common (n = 1971, 70.72%) followed by D (n = 582, 20.88%), B (n = 204, 7.32%) and X (n = 30, 1.08%). Suffering from cardiovascular diseases other than myocardial infarction (OR 0.053, p-value < 0.001) and receiving > 12 drugs (OR 4.187, p-value = 0.009) had statistical significant association with the presence of class D and/or X pDDIs.

Conclusion

In the current study, pDDIs were highly prevalent. The inclusion of DDI screening tools, availability of clinical pharmacists and paying special attention to the high-risk patients may reduce the frequency of pDDIs at the study sites.

Assessment of utility values and QALYs after primary PCI with DP-Xience and BP-Biomatrix stents

BACKGROUND

Primary percutaneous coronary intervention (PPCI) is the recommended treatment in ST elevated myocardial infarction (STEMI). The determination of Quality of life (QoL) for various options of coronary revascularization is important for establishment of a comprehensive care plan. Studies of QoL in interventional cardiology are scarce. Our study has compared utility scores and quality adjusted life year (QALY) of 2nd and 3rd generation drug eluting stents (DES).

METHODS

An observational cohort study was conducted to evaluate QoL and QALY using EQ-5D-5L questionnaire. Patients undergoing PPCI between July-Dec 2019 were evaluated after completion of one year of procedure.

RESULTS

Total 334 patients were evaluated, study population consisted of a greater number of males (87.13%) than females. Mean utility value was more in 3rd G Biomatrix stents; 0.829 ± 0.11 than 2nd G Xience stents; 0.794 ± 0.11 (p < 0.05). Visual analogue scale (VAS) value was also high in 3rd G DES (81.84 ± 8.29) as compared to 2nd G DES (77.81 ± 9.01); p< 0.05. A significant association was found between utility scores/VAS and age, DM, HTN, Current smoking, family history and CAD diagnosis. There was a gain of 0.035 QALY with the use of Biomatrix DES.

CONCLUSION

Health related quality of life (HRQOL) is a leading support in the decision making of therapeutic interventions. Our study has found that Biodegradable polymer (BP) Biomatrix DES are superior to the Durable polymer (DP) Xience DES having better QoL and QALY.

Nonclinical Features in Predictive Modeling of Cardiovascular Diseases: A Machine Learning Approach

BACKGROUND

In the broader healthcare domain, the prediction bears more value than an explanation considering the cost of delays in its services. There are various risk prediction models for cardiovascular diseases (CVDs) in the literature for early risk assessment. However, the substantial increase in CVDs-related mortality is challenging global health systems, especially in developing countries. This situation allows researchers to improve CVDs prediction models using new features and risk computing methods. This study aims to assess nonclinical features that can be easily available in any healthcare systems, in predicting CVDs using advanced and flexible machine learning (ML) algorithms.

METHODS

A gender-matched case-control study was conducted in the largest public sector cardiac hospital of Pakistan, and the data of 460 subjects were collected. The dataset comprised of eight nonclinical features. Four supervised ML algorithms were used to train and test the models to predict the CVDs status by considering traditional logistic regression (LR) as the baseline model. The models were validated through the train-test split (70:30) and tenfold cross-validation approaches.

RESULTS

Random forest (RF), a nonlinear ML algorithm, performed better than other ML algorithms and LR. The area under the curve (AUC) of RF was 0.851 and 0.853 in the train-test split and tenfold cross-validation approach, respectively. The nonclinical features yielded an admissible accuracy (minimum 71%) through the LR and ML models, exhibiting its predictive capability in risk estimation.

CONCLUSION

The satisfactory performance of nonclinical features reveals that these features and flexible computational methodologies can reinforce the existing risk prediction models for better healthcare services.

Predictors of Health-Related Quality-of-Life Status Among Elderly Patients With Cardiovascular Diseases

OBJECTIVES

Quality of life is an important patient-reported outcome in the care of older patients with chronic diseases owing to aging-associated limited physical activity and poor health status. The current study aimed to evaluate health-related quality of life and its predictors among elderly cardiac outpatients.

METHODS

A descriptive, nonexperimental, cross-sectional study was carried out from May 2018 to October 2018 in outpatient departments of a tertiary-care hospital. The population under study were patients aged ≥65 years with at least 1 cardiovascular condition. The EQ-5D-3L (Euro QOL) and Barthel index were used to measure the quality of life and performance of activities of daily living, respectively. Linear regression analysis was performed by using SPSS version 21.

RESULTS

Of a total of 386 patients, 198 patients (51.3%) reported impairment in the mobility domain, and 70.5% (n = 272) of patients indicated impairment in the depression domain. Mann-Whitney tests revealed EQ-5D scores, and visual analogue scale scores significantly differed by hospital admissions (P = .001), fall history (P < 0.001), and activities of daily living (P < .001). Kruskal-Wallis analysis revealed that EQ-5D index value and visual analogue scale score were significantly lower among patients who had comorbidities and who were exposed to polypharmacy (5-9 medications) (P < .001). In multivariate linear regression analysis, self-reported health (P = .006) and performance of activities of daily living (P < .001) were reported as influencing factors on health-related quality of life.

CONCLUSION

Findings indicated poor quality of life among older patients with cardiovascular diseaese or heart diseases in Pakistan. Measures should be taken to improve patients' perception and to enhance awareness regarding the importance of doing daily living activities as a predictor of good quality of life.

Prevalence of Cardiac Risk Factors and Attitude toward Self-Risk Assessment among Cardiac Care Givers

Objective:

Aim of this survey was to assess the prevalence of cardiovascular diseases (CVD) risk factors and attitude toward self-risk assessment among cardiac care physicians (who did not have CVD history), at a tertiary care cardiac center in Pakistan.

Design:

In this survey we included cardiac care givers who had a minimum of 1 year of working experience in a cardiac care center.

Participants:

Participants with self-reported history of established diagnosis of CVD were excluded. Face-to-face interviews were conducted with the help of a structured questionnaire which consisted of demographic information, data regarding established CVD risk factors, self-awareness, and attitude toward CVD risk assessment.

Results:

A total of 126 participants were interviewed, out of which 20.6% (26) were females and mean age was 36.1±7.6 years. The most prevalent CVD risk factor was family history of CVD (33.3%) followed by smoking (14.3%) and 23.8% had body mass index of ≥27.5 kg/m². Around 23% of the participants did not know their cholesterol levels, similarly more than 74% were not aware of their high-density lipoproteins levels. More than 76% had never assessed their CVD risk and more than 37% don’t know or don’t have any opinion about their own CVD risk.

Conclusions:

The present study reveals low prevalence of conventional cardiac risk factors and marginally higher tendency of modifiable risk factors, such as smoking and obesity, among the cardiac physicians. A large proportion of these cardiac physicians have not yet assessed their CVD risk.

Effect of Dietary Supplementation of Bioactive Peptides on Antioxidant Potential of Broiler Breast Meat and Physicochemical Characteristics of Nuggets

Poultry meat is generally exposed to quality deterioration due to lipid oxidation during storage. Oxidative stability of meat can be increased by feed supplementation. Aim of the current study was to investigate the effect of dietary supplementation of fish waste derived bioactive peptides on antioxidant potential of broiler breast meat and physico-chemical characteristics and quality parameters of nuggets prepared from breast meat. 180 broiler birds (six groups of 30 birds) were purchased. Each group was given different concentrations of bioactive peptides i.e. 0, 50, 100, 150, 200, and 250 mg/kg feed. After completion of six weeks birds were slaughtered and breast meat was stored at -18°C for six months. Nuggets were prepared and stored at -18°C for 45 days. Meat samples were analyzed for antioxidant activity [total phenolic contents (TPC), DPPH• scavenging activity, and ferric reducing antioxidant power] and lipid oxidation assay at regular intervals of 1, 2, 3, 4, 5, and 6 months while nuggets were analyzed for quality (pH, color, texture and water holding capacity) parameters after regular interval of 15 days. A significant (p<0.05) effect of feed supplementation was observed on antioxidant status such as TPC, DPPH• scavenging activity, and FRAP of broiler breast meat. Dietary interventions of bioactive peptides significantly (p<0.05) delayed lipid oxidation of breast meat than control. All the quality parameters were also significantly affected due to dietary bioactive peptides and storage duration. Thus, dietary interventions of bioactive peptides can increase the antioxidant and shelf stability of broiler breast meat and nuggets.