Cardiac and Renal Comorbidities in Aging People Living With HIV.

Contemporary World Health Organization data indicates that ≈39 million people are living with the human immunodeficiency virus. Of these, 24 million have been reported to have successfully accessed combination antiretroviral therapy. In 1996, the World Health Organization endorsed the widespread use of combination antiretroviral therapy, transforming human immunodeficiency virus infection from being a life-threatening disease to a chronic illness characterized by multiple comorbidities. The increased access to combination antiretroviral therapy has translated to people living with human immunodeficiency virus (PLWH) no longer having a reduced life expectancy. Although aging as a biological process increases exposure to oxidative stress and subsequent systemic inflammation, this effect is likely enhanced in PLWH as they age. This narrative review engages the intricate interplay between human immunodeficiency virus associated chronic inflammation, combination antiretroviral therapy, and cardiac and renal comorbidities development in aging PLWH. We examine the evolving demographic profile of PLWH, emphasizing the increasing prevalence of aging individuals within this population. A central focus of the review discusses the pathophysiological mechanisms that underpin the heightened susceptibility of PLWH to renal and cardiac diseases as they age.

The genetic basis for adult-onset idiopathic dilated cardiomyopathy in people of African descent.

Cardiomyopathies are a heterogeneous group of cardiac muscle disorders that result in dilated, hypertrophic, or restrictive pathophysiological entities. Dilated cardiomyopathy (DCM) is the most common form in sub-Saharan Africa (SSA). However, population-specific research studies reporting the actual burden of DCM in this region are still lacking. Also, little is known about the genetic basis of DCM in this population, and genetic testing is still not readily accessible. This review describes the common pathogenic genes implicated in DCM globally and discusses the evidence-based management of patients with DCM. We also present a summary of studies describing genes implicated or associated with DCM in patients residing in SSA.

Machine learning and statistical methods for predicting mortality in heart failure.

Heart failure is a debilitating clinical syndrome associated with increased morbidity, mortality, and frequent hospitalization, leading to increased healthcare budget utilization. Despite the exponential growth in the introduction of pharmacological agents and medical devices that improve survival, many heart failure patients, particularly those with a left ventricular ejection fraction less than 40%, still experience persistent clinical symptoms that lead to an overall decreased quality of life. Clinical risk prediction is one of the strategies that has been implemented for the selection of high-risk patients and for guiding therapy. However, most risk predictive models have not been well-integrated into the clinical setting. This is partly due to inherent limitations, such as creating risk predicting models using static clinical data that does not consider the dynamic nature of heart failure. Another limiting factor preventing clinicians from utilizing risk prediction models is the lack of insight into how predictive models are built. This review article focuses on describing how predictive models for risk-stratification of patients with heart failure are built.

The Use of Metabolomes in Risk Stratification of Heart Failure Patients: Protocol for a Scoping Review.

BACKGROUND: Heart failure (HF) is a significant health problem that is often associated with major morbidity and mortality. Metabolic abnormalities occur in HF and may be used to identify individuals at risk of developing the condition. Furthermore, these metabolic changes may play a role in the pathogenesis and progression of HF. Despite this knowledge, the utility of metabolic changes in diagnosis, management, prognosis, and therapy for patients with chronic HF has not been systematically reviewed. OBJECTIVE: This scoping review aims to systematically appraise the literature on metabolic changes in patients with HF, describe the role of these changes in pathogenesis, progression, and care, and identify knowledge gaps to inform future research. METHODS: This review will be conducted using a strategy based on previous reports, the JBI Manual for Evidence Synthesis, and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR) guidelines. A comprehensive search of electronic databases (Medline, EBSCOhost, Scopus, and Web of Science) will be conducted using keywords related to HF, myocardial failure, metabolomes, metabonomics, and analytical chemistry techniques. The search will include original peer-reviewed research papers (clinical studies conducted on humans and systematic reviews with or without a meta-analysis) published between January 2010 and September 2023. Studies that include patients with HF younger than 18 years or those not published in English will be excluded. Two authors (UGA and MB) will screen the titles and abstracts independently and perform a full-text screen of the relevant and eligible papers. Relevant data will be extracted and synthesized, and a third author or group will be consulted to resolve discrepancies. RESULTS: This scoping review will span from January 2010 to September 2023, and the results will be published in a peer-reviewed, open-access journal as a scoping review in 2024. The presentation of the findings will use the PRISMA-ScR flow diagram and descriptive and narrative formats, including tables and graphical displays, to provide a comprehensive overview of the extracted data. CONCLUSIONS: This review aims to collect and analyze the available evidence on metabolic changes in patients with HF, aiming to enhance our current understanding of this topic. Additionally, this review will identify the most commonly used and suitable sample, analytical method, and specific metabolomes to facilitate standardization, reproducibility of results, and application in the diagnosis, treatment, and risk stratification of patients with HF. Finally, it is hoped that this review's outcomes will inspire further research into the metabolomes of patients with HF in low- and middle-income countries. TRIAL REGISTRATION: Open Science Framework; https://osf.io/sp6xj. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/53905.

HbA1c control in type 2 diabetes mellitus patients with coronary artery disease: a retrospective study in a tertiary hospital in South Africa.

Background: Type 2 diabetes mellitus (T2DM) patients with coronary artery disease (CAD) have an increased risk of recurrent cardiovascular events. These patients require optimal glucose control to prevent the progression of atherosclerotic cardiovascular disease (ASCVD). Contemporary guidelines recommend an HbA1c ≤7% to mitigate this risk. The aim of this study was to evaluate HbA1c control in T2DM patients with angiographically proven ASCVD. Methods: We conducted a cross-sectional, retrospective study on consecutive T2DM patients with acute and chronic coronary syndromes managed in a tertiary academic hospital in South Africa. Glycaemic control was assessed by evaluating the glycated haemoglobin (HbA1c) level measured at index presentation with acute and chronic coronary syndromes and during the most recent follow-up visit. Results: The study population comprised 262 T2DM patients with a mean age of 61.3 ± 10.4 years. At index presentation, 110 (42.0%) T2DM patients presented with ST-segment elevation myocardial infarction, 69 (26.3%) had non-ST-segment elevation myocardial infarction, 43 (16.4%) had unstable angina, and 40 (15.3%) had stable angina. After a median duration of 16.5 months (IQR: 7-29), 28.7% of the study participants had an HbA1c ≤7%. On multivariable logistic regression analysis, females were less likely to have poor glycaemic control (HbA1c above 7%) [odds ratio (OR): 0.42, 95% confidence interval (CI): 0.19-0.95, p=0.038]. Also, T2DM patients prescribed metformin monotherapy (OR: 0.34, 95% CI: 0.14-0.82, p=0.017) and patients with ST-segment depression on the electrocardiogram (OR: 0.39, 95% CI: 0.16-0.96, p=0.041) were less likely to have poor glycaemic control. Conclusion: After a median duration of 16.5 months, only 28.7% of T2DM patients with CAD had an HbA1c ≤7%. This finding underscores the substantial unmet need for optimal diabetes control in this very high-risk group.

In-Hospital Mortality Outcomes of ST-Segment Elevation Myocardial Infarction: A Cross-Sectional Study from a Tertiary Academic Hospital in Johannesburg, South Africa.

In sub-Saharan Africa, the burden of atherosclerotic cardiovascular disease (ASCVD) is increasing. This study aimed to describe the clinical characteristics of patients with ST-segment elevation myocardial infarction (STEMI) and estimate the in-hospital all-cause mortality rate. We conducted a cross-sectional retrospective single-centre study of STEMI patients who underwent diagnostic coronary angiography with or without percutaneous coronary intervention (PCI) between January 2015 and December 2019. We compared demographic and clinical parameters between survivors and non-survivors with descriptive statistics. Univariable and multivariable logistic regression analyses were performed to determine the predictors of all-cause mortality. The study population consisted of 677 patients with a mean age of 55.5 ± 11.3 years. The in-hospital all-cause mortality rate was 6.2% [95% confidence interval (CI): 4.5-8.3%]. Risk factors for ASCVD included smoking (56.1%), hypertension (52.8%), dyslipidemia (40.0%), and a family history of coronary artery disease (32.7%). A pharmaco-invasive management strategy (treatment with thrombolytic therapy and PCI) was implemented in 36.5% of patients and reduced all-cause mortality risk (OR: 0.16; CI: 0.04-0.71, p = 0.015). The in-hospital all-cause mortality rate in STEMI patients was 6.2%, and a pharmaco-invasive management strategy proved to be an effective approach.

Cardiovascular Magnetic Resonance Imaging Findings in Africans with Idiopathic Dilated Cardiomyopathy.

In sub-Saharan Africa, idiopathic dilated cardiomyopathy (IDCM) is a common yet poorly investigated cause of heart failure. Cardiovascular magnetic resonance (CMR) imaging is the gold standard for tissue characterisation and volumetric quantification. In this paper, we present CMR findings obtained from a cohort of patients with IDCM in Southern Africa suspected of having a genetic cause of cardiomyopathy. A total of 78 IDCM study participants were referred for CMR imaging. The participants had a median left ventricular ejection fraction of 24% [interquartile range, (IQR): 18-34]. Late gadolinium enhancement (LGE) was visualised in 43 (55.1%) participants and localised in the midwall in 28 (65.0%) participants. At the time of enrolment into the study, non-survivors had a higher median left ventricular end diastolic wall mass index of 89.4 g/m2 (IQR: 74.5-100.6) vs. 73.6 g/m2 (IQR: 51.9-84.7), p = 0.025 and a higher median right ventricular end-systolic volume index of 86 mL/m2 (IQR:74-105) vs. 41 mL/m2 (IQR: 30-71), p < 0.001. After one year, 14 participants (17.9%) died. The hazard ratio for the risk of death in patients with evidence of LGE from CMR imaging was 0.435 (95% CI: 0.259-0.731; p = 0.002). Midwall enhancement was the most common pattern, visualised in 65% of participants. Prospective, adequately powered, and multi-centre studies across sub-Saharan Africa are required to determine the prognostic significance of CMR imaging parameters such as late gadolinium enhancement, extracellular volume fraction, and strain patterns in an African IDCM cohort.

Clinical characteristics and one-year all-cause mortality outcomes in Africans with dilated cardiomyopathy.

AIMS: Dilated cardiomyopathy (DCM) is a common cause of heart failure in sub-Saharan Africa (SSA). The affected individuals present with new-onset heart failure with reduced ejection fraction and no identifiable primary or secondary aetiology. We aim to describe the clinical characteristics of participants with heart failure of unknown origin. METHODS: We screened 161 participants with heart failure of unknown origin and prospectively excluded primary and secondary causes of DCM. All study participants were subjected to laboratory biochemical testing, echocardiography, cardiovascular magnetic resonance (CMR) imaging and invasive coronary angiography. RESULTS: The study comprised 93 participants with a mean age of 47.5 SD 13.1 years. Forty-six (56.1%) participants had evidence of late gadolinium enhancement (LGE) on imaging, and LGE was visualised in the mid wall in 28 (61.0%) of these participants. After a median duration of 13.4 months [interquartile range (IQR): 8.8-28.9 months], 18 (19%) participants died. Non-survivors had a higher median left atrial volume index (44.9 mL/m2 (IQR: 34.4-58.7) compared to survivors [32.9 mL/m2 (IQR: 24.5-47.0), p = 0.017)]. The rate of all-cause rehospitalisation was 29.3%, of which 17 of the 22 re-hospitalisations were heart failure related. CONCLUSION: Dilated cardiomyopathy in Africans primarily affects young males. In our cohort, this disease was associated with an all-cause mortality of 19% in one year. In SSA, large multicenter studies are required to investigate this disease's pathogenesis and outcomes.

Predicting in-hospital all-cause mortality in heart failure using machine learning.

Background: The age of onset and causes of heart failure differ between high-income and low-and-middle-income countries (LMIC). Heart failure patients in LMIC also experience a higher mortality rate. Innovative ways that can risk stratify heart failure patients in this region are needed. The aim of this study was to demonstrate the utility of machine learning in predicting all-cause mortality in heart failure patients hospitalised in a tertiary academic centre. Methods: Six supervised machine learning algorithms were trained to predict in-hospital all-cause mortality using data from 500 consecutive heart failure patients with a left ventricular ejection fraction (LVEF) less than 50%. Results: The mean age was 55.2 ± 16.8 years. There were 271 (54.2%) males, and the mean LVEF was 29 ± 9.2%. The median duration of hospitalisation was 7 days (interquartile range: 4-11), and it did not differ between patients discharged alive and those who died. After a prediction window of 4 years (interquartile range: 2-6), 84 (16.8%) patients died before discharge from the hospital. The area under the receiver operating characteristic curve was 0.82, 0.78, 0.77, 0.76, 0.75, and 0.62 for random forest, logistic regression, support vector machines (SVM), extreme gradient boosting, multilayer perceptron (MLP), and decision trees, and the accuracy during the test phase was 88, 87, 86, 82, 78, and 76% for random forest, MLP, SVM, extreme gradient boosting, decision trees, and logistic regression. The support vector machines were the best performing algorithm, and furosemide, beta-blockers, spironolactone, early diastolic murmur, and a parasternal heave had a positive coefficient with the target feature, whereas coronary artery disease, potassium, oedema grade, ischaemic cardiomyopathy, and right bundle branch block on electrocardiogram had negative coefficients. Conclusion: Despite a small sample size, supervised machine learning algorithms successfully predicted all-cause mortality with modest accuracy. The SVM model will be externally validated using data from multiple cardiology centres in South Africa before developing a uniquely African risk prediction tool that can potentially transform heart failure management through precision medicine.

New Biomarkers and Their Potential Role in Heart Failure Treatment Optimisation-An African Perspective.

Heart failure is a clinical syndrome resulting from various cardiovascular diseases of different aetiologies and pathophysiology. These varying pathologies involve several complex mechanisms that lead to the activation of the neurohumoral system, inflammation, angiogenesis, apoptosis, fibrosis, and eventually adverse cardiac remodelling associated with a progressive decline in cardiac function. Once a diagnosis is made, the cardiac function has a gradual decline characterised by multiple hospital admissions. It is therefore imperative to identify patients at different stages of the heart failure continuum to better risk stratify and initiate optimal management strategies. Biomarkers may play a role in the diagnosis, prognostication, and monitoring response to treatment. This review discusses the epidemiology of heart failure and biomarkers commonly used in clinical practice such as natriuretic peptides and cardiac troponins. In addition, we provide a brief overview of novel biomarkers and genetic coding and non-coding biomarkers used in the management of patients with heart failure. We also discuss barriers that hinder the clinical application of novel biomarkers. Finally, we appraise the value of polygenic risk scoring, focusing on sub-Saharan Africa.

Extensive triple vessel coronary artery disease in a young male with juvenile idiopathic arthritis.

The risk of cardiovascular disease in patients with chronic inflammatory joint conditions is substantially increased compared to the general population. We present a case of a 27-year-old male with a chronic history of juvenile idiopathic arthritis (JIA) who presented with denovo acutely decompensated chronic heart failure. He had no traditional risk factors for atherosclerotic cardiovascular disease (ASCVD). However, during his workup for dilated cardiomyopathy, he was found to have extensive triple vessel disease on coronary artery angiography, and this was subsequently thought to be the most likely aetiology for the dilated cardiomyopathy despite being of young age. The chronic JIA was identified as the principal risk factor for the ischaemic cardiomyopathy. Clinicians treating patients with rheumatological conditions should routinely screen for ASCVD, despite the absence of traditional cardiovascular risk factors.

Predicting mortality and hospitalization in heart failure using machine learning: A systematic literature review.

OBJECTIVE: The partnership between humans and machines can enhance clinical decisions accuracy, leading to improved patient outcomes. Despite this, the application of machine learning techniques in the healthcare sector, particularly in guiding heart failure patient management, remains unpopular. This systematic review aims to identify factors restricting the integration of machine learning derived risk scores into clinical practice when treating adults with acute and chronic heart failure. METHODS: Four academic research databases and Google Scholar were searched to identify original research studies where heart failure patient data was used to build models predicting all-cause mortality, cardiac death, all-cause and heart failure-related hospitalization. RESULTS: Thirty studies met the inclusion criteria. The selected studies' sample size ranged between 71 and 716 790 patients, and the median age was 72.1 (interquartile range: 61.1-76.8) years. The minimum and maximum area under the receiver operating characteristic curve (AUC) for models predicting mortality were 0.48 and 0.92, respectively. Models predicting hospitalization had an AUC of 0.47 to 0.84. Nineteen studies (63%) used logistic regression, 53% random forests, and 37% of studies used decision trees to build predictive models. None of the models were built or externally validated using data originating from Africa or the Middle-East. CONCLUSIONS: The variation in the aetiologies of heart failure, limited access to structured health data, distrust in machine learning techniques among clinicians and the modest accuracy of existing predictive models are some of the factors precluding the widespread use of machine learning derived risk calculators.

Perioperative outcomes of coronary artery bypass graft surgery in Johannesburg, South Africa.

BACKGROUND: The perioperative complications in patients with coronary artery disease undergoing coronary artery bypass graft (CABG) surgery have been reported predominantly from developed countries, with a paucity of data from sub-Saharan Africa. We aim to report on the clinical characteristics and perioperative complications in patients with obstructive coronary artery disease, managed with CABG surgery at a tertiary academic hospital in Johannesburg, South Africa. METHODS: We retrospectively reviewed data from adult patients who underwent CABG surgery during a 17-year period (January 2000 - December 2017). Data was collected from the cardiothoracic surgery department's pre- and postoperative reports, the cardiology department's medical records, and anaesthesiology's intra-operative reports. We collected demographic, biochemical, clinical, surgical, echocardiographic, and angiographic data. Outcomes data collected included perioperative complications and mortality. RESULTS: We analysed 1218 consecutive patient records. The study cohort consisted of 951 (78.1%) males, and the mean age was 60.1 ± 10.1 years. During the study period, 137 (11.2%) patients demised with cardiac and sepsis-related causes of death accounting for 49.6 and 37.2%, respectively. Other perioperative complications included excessive bleeding in 222 (18.2%), prolonged ventilation (exceeding 48 h) in 139 (11.4%), and sternal sepsis in 125 (10.3%). On univariate logistic regression analysis, advanced age, a lower left ventricular ejection fraction, smoking, increased cardiopulmonary bypass (CPB) time, and a higher European System for Cardiac Operative Risk Evaluation (EuroSCORE) II were all significantly associated with mortality. The EuroSCORE II [OR: 0.15 95%CI: 0.09-0.22; p = 0.000], and prolonged CPB time [OR: 0.01 CI: 0.00-0.02; p = 0.000] were independent predictors of in-hospital all-cause mortality. CONCLUSIONS: In our study, the crude perioperative mortality rate was 11.2%. Our mortality rate was significantly higher than the mortality rates reported in other developed and developing countries. To better understand the factors driving this high mortality rate, a prospective outcomes registry has been initiated, and this promises to inform on our contemporary mortality and morbidity outcomes.

The prevalence of depression, stress and anxiety symptoms in patients with chronic heart failure.

BACKGROUND: Mental health illnesses are associated with frequent hospitalisation and an increased risk of all-cause mortality. Despite the high prevalence of depression in patients with chronic heart failure (CHF), there is a paucity of data on this subject from low and middle-income countries (LMIC). The aim of this study was to determine the prevalence of depression, anxiety, and stress symptoms in patients attending a dedicated CHF clinic. METHODS: A prospective study was conducted at an outpatient heart failure clinic in a tertiary academic centre. The study participants completed a Depression, Anxiety and Stress (DASS-21) questionnaire to screen for the presence and severity of depression, anxiety and stress symptoms. Furthermore, the Minnesota Living with Heart Failure Questionnaire (MLHFQ) was completed and used to evaluate the impact of CHF on health-related quality of life (QoL). Descriptive statistics were used to describe patients' characteristics and logistic regression analysis to identify predictors of symptoms of depression. RESULTS: The study population comprised of 103 patients, predominantly female (62.1%) with a median age of 53 (interquartile range 38-61) years. Symptoms of depression were reported by 52.4%, with 11.6% reporting symptoms suggestive of extremely severe depression. Anxiety was diagnosed in 53.4% of patients and extremely severe anxiety was reported by 18.4% of patients. Fifty patients were classified as stressed, and only 7.7% had extremely severe stress. More than half of the patients (54.4%) were in New York Heart Association functional class I. The mean left ventricular ejection fraction in the entire cohort was 30% (SD = ± 11.1%). In the multivariable logistic regression model, the MLHFQ score [odds ratio (OR) 1.04, 95% CI:1.02-1.06, p = 0.001] and the six-minute walk test [OR 0.99, 95% CI: 0.98-0.99, p = 0.014] were identified as independent predictors of depression. CONCLUSION: Depression and anxiety symptoms were found in over half of patients attending the CHF clinic. We recommend that mental health screening should be routinely performed in patients with CHF. Prospective, adequately powered, multicentre studies from LMIC investigating the impact of depression, anxiety and stress on CHF outcomes such as health-related QoL, hospitalisation and mortality are required.

Contemporary Neuroprotection Strategies during Cardiac Surgery: State of the Art Review.

Open-heart surgery is the leading cause of neuronal injury in the perioperative state, with some patients complicating with cerebrovascular accidents and delirium. Neurological fallout places an immense burden on the psychological well-being of the person affected, their family, and the healthcare system. Several randomised control trials (RCTs) have attempted to identify therapeutic and interventional strategies that reduce the morbidity and mortality rate in patients that experience perioperative neurological complications. However, there is still no consensus on the best strategy that yields improved patient outcomes, such that standardised neuroprotection protocols do not exist in a significant number of anaesthesia departments. This review aims to discuss contemporary evidence for preventing and managing risk factors for neuronal injury, mechanisms of injury, and neuroprotection interventions that lead to improved patient outcomes. Furthermore, a summary of existing RCTs and large observational studies are examined to determine which strategies are supported by science and which lack definitive evidence. We have established that the overall evidence for pharmacological neuroprotection is weak. Most neuroprotective strategies are based on animal studies, which cannot be fully extrapolated to the human population, and there is still no consensus on the optimal neuroprotective strategies for patients undergoing cardiac surgery. Large multicenter studies using universal standardised neurological fallout definitions are still required to evaluate the beneficial effects of the existing neuroprotective techniques.

Perceptions of patients and medical students towards each other in the setting of patient care-a South African perspective.

INTRODUCTION: South Africa urgently needs more doctors. We examined perceptions of patients and students to provide evidence for optimum student-patient ratios and substantiate solutions for this dilemma. METHODS: We interviewed 118 patients and invited 120 students to complete a self-administered questionnaire from four specialities in an academic hospital in Johannesburg. RESULTS: The total sample size was 238 participants. A total of 91/118 (77%) patients and 78/120 (65%) students were female. Almost all the patients had some level of education, with most patients having received at least a secondary education (71/120). More than half of the students (69/120) were final year students. A third (41/118) of the patients were unaware they were admitted to a teaching hospital. Half of the patients (60/118) thought they had the right to refuse interaction with students. Patients and students preferred smaller groups of between 1-3 and 4-8 students at a bedside tutorial (p < 0.001), although patients preferred smaller groups (1-3) compared with the students (4-8). Majority of patients said they never refused consent to students, while a third of students reported at least up to three patients refusing consent to be examined. The most frequent reason cited by students for refusal of consent by patients was the exposure to excessive numbers of students and healthcare professionals. CONCLUSION: Medical schools should consider patient safeguards while responding to the country's need for more doctors. The Medical Council and medical schools need to draw up professional guidelines on patient-student interactions, including the role of patients in this setting.

Fluorine-18 fluorodeoxyglucose positron emission tomography in assessing myocardial viability in a tertiary academic centre in Johannesburg, South Africa: a pilot study.

BACKGROUND: Positron emission tomography detects patients with myocardial contractile dysfunction secondary to ischaemic heart disease who may benefit from coronary revascularisation. METHODS: We reviewed technetium-99m sestamibi singlephoton emission computed tomography (SPECT) and fluorine-18 fluorodeoxyglucose (F18-FDG) positron emission tomography (PET) data from 236 patients imaged between January 2009 and June 2015. The patients were grouped into three groups: no evidence of viability, viability 1-10% and viability > 10%. RESULTS: Viability exceeding 10% was evident in 55% of the patients. On multivariate analysis, aspirin intake [OR: 1.92; 95% CI: 1.08-3.41; p = 0.026] and hypertension [OR: 1.89; 95% CI: 1.07-3.33; p = 0.029] were clinical factors associated with the presence of myocardial viability. CONCLUSION: Our study demonstrated that F18-FDG PET was able to identify 55% of patients with ischaemic heart disease with viability in more than 10% of the total myocardium when using a 17-segment model.

Periprocedural myocardial infarction during percutaneous coronary intervention in an academic tertiary centre in Johannesburg.

BACKGROUND: Percutaneous coronary intervention (PCI) is effective therapy for significant atherosclerotic coronary artery disease. Despite medical and technological advances in PCI, periprocedural myocardial infarction (PMI) remains a common complication. The frequency and factors associated with PMI have been well investigated in the developed world, yet there is a paucity of data from the developing world, especially Sub-Saharan Africa. METHODS: We prospectively enrolled 153 adult patients undergoing PCI at the Charlotte Maxeke Johannesburg Academic Hospital from the 1st of February 2014 to 31st October 2014. Periprocedural Creatinine Kinase-MB and hs-Troponin I were routinely measured before PCI and at 16-24h post-procedure. The third universal definition of myocardial infarction was used to define a PMI event. RESULTS: 152 participants met the inclusion criteria and were analysed for PMI. 70.4% participants were male. The mean age was 58.8 (SD 10.9) years old. Sixteen (10.5%) participants fulfilled the criteria for PMI. Side branch pinching with preserved TIMI III flow was noted in 62.5% of PMI cases. Duration of procedure (P=0.007), right coronary artery intervention (p=0.042) and total stent length (p=0.045) were independently associated with PMI. CONCLUSION: PMI occurred in 10.5% of cases undergoing PCI. This is consistent with the prevalence of PMI internationally. Larger multicentre studies are required in our demographic region to further define relevant predictors and outcomes associated with PMI.