ST-Segment Elevation Myocardial Infarction (STEMI): A 10-year Review form a primary PCI capable hospital in Tanzania

ST-Segment Elevation Myocardial Infarction (STEMI): A 10-year Review form a primary PCI capable hospital in Tanzania | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article ST-Segment Elevation Myocardial Infarction (STEMI): A 10-year Review form a primary PCI capable hospital in Tanzania Nadeem kassam, Mohamed Varwani, Mzee Ngunga, Mohamed Jeilan, Mangaro Mabusi, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4514601/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Ischemic Heart Disease (IHD) is an emerging epidemic in sub-Saharan Africa (SSA). Despite the true burden underestimated in the African continent, it remains the leading cause of death among adults aged above 60 years. ST-Segment Elevation Myocardial Infarction (STEMI) is a clinically time-sensitive fatal sequela of IHD with timely reperfusion by primary Percutaneous Coronary Intervention (PCI) considered the gold standard of care. Tanzania has witnessed a gradual and continued development in the ability to provide coronary care and a simultaneous increase in risk factors associated with IHD. There is paucity of available data in the country. Methodology This single-center retrospective study was conducted at the Aga Khan Hospital Dar-es-Salaam (AKHD), Tanzania. The AKHD is one of the pioneers in establishing the first cardiac catheterization laboratory in the nation. The current study involved extracting relevant data of all patients who presented with STEMI from August 2014 to December 2023. Descriptive statistics were used to define the population. Patient’s outcomes were based on hospital survival. Binary logistic regression was run (at 95% CI and p -value < 0.05) to identify the determinants for in-hospital mortality. Results 230 patients were included in the final analysis. The cohort was predominantly male (n=192,83.5%), with a median age was 55.0 years (IQR 48.0-65.0). Most patients presented with chest pain (n=162,72.6%), with a median duration of 12.2 hours (IQR 3.0-24.0 hours). The left Anterior descending (LAD) artery was the culprit vessel in most cases (n=112,48.7%). A total of 163(70.8%) patients underwent Primary-PCI. The in-hospital mortality of the cohort was 5.7%. When survivors and non-survivors were compared, a higher percentage of non-survivors were diabetic (n=12,92.3%), hypertensive (n=12,92.3%) and having a history of cigarette smoking(n=11,84.6%) (P- value <0.05). A higher mean BMI of 36.2 (±5.7) (OR 1.46, CI 1.17– 2.10), the presence of smoking (OR 41.68, CI 2.60– 240.71), and the need for mechanical ventilation (OR 77.42, CI 1.95– 128.89) were factors associated with in-hospital mortality. Conclusion Our study results demonstrate lower in-hospital mortality for STEMI patients compared to other regional studies. Cigarette smoking, obesity and the need for mechanical ventilation were predictors of poor in-hospital outcomes. Introduction Cardiovascular disease (CVD) is an emerging epidemic in sub-Saharan Africa (SSA) and other low- to middle-income countries (LMICs) such as Tanzania( 1 ). CVD accounts for approximately 13% of all deaths in Tanzania, higher than in most African countries( 2 ). Various reports have speculated that the true burden of ischemic heart disease (IHD) is likely underestimated in the majority of African countries due to limited awareness, inadequate clinician training, and lack of resources, yet it still accounts for the single most common cause of cardiovascular mortality worldwide( 3 ). Most of the LMICs in SSA have undergone economic growth and adopted lifestyle changes in the past years that have increased the risk prevalence associated with IHD, more so in a much younger population( 4 ). This has led to an increased burden of health expenditures in most sub-Saharan region regions battling the dawn of an epidemiological transition. Understanding the trend and transformation, as well as improving measures to stem the global tide associated with CVD mortality, remains an important action frontier in these regions( 5 ). ST-Segment Elevation Myocardial Infarction (STEMI) is a clinically time-sensitive fatal sequela of ischemic heart disease (IHD)( 6 ). The treatment is timely reperfusion by percutaneous coronary intervention (PCI) or thrombolytic therapy of the culprit coronary artery ( 7 ). There has been a notable decrease in the mortality rate associated with ST-segment elevation myocardial infarction (STEMI) in resourceful HICs, mostly due to overall improvement in healthcare infrastructure and systems of care ( 8 ). This may not be true for the majority of the Sub-Saharan region. The impact of IHD remains a major public health burden due to various factors; including insufficient health care systems, lack of resources, skewed allocation of budget, high cost of treatment coupled with lack of health care professionals able to emulate its timely and ideal care( 9 ). To date, there is a paucity of available data on the state of coronary care within most LMICs in Sub-Saharan Africa. In the past decade, Tanzania has witnessed a gradual and continued development in the ability to provide coronary care in both the private and public sectors. Simultaneously, recent national trends also portray an increased magnitude of multiple risk factors associated with coronary artery disease in Tanzania. In light of the country now experiencing a shift in its health landscape, the traditional focus on infectious disease is gradually giving way to the rising burden of NCDs with cardiovascular diseases assuming a prominent role; this analysis is a timely field( 10 ). The Aga Khan Hospital Dar - es - salaam has been one of the pioneers in establishing the state-of-the-art catheterization laboratory in the nation. This study aimed to describe demographics, clinical presentation, and angiographic findings among patients presenting with STEMI at a private tertiary hospital in Tanzania, as well as patient outcomes including mortality for the past decade. Methods This single-center retrospective study was conducted at the Aga Khan Hospital Dar-es-Salaam (AKHD), Tanzania. AKHD is a private, non-profit, tertiary hospital in Tanzania. The AKHD was the first hospital in the country to have an operational 24-hour catheterization laboratory and the only hospital to date in Tanzania to be accredited by the Joint Commission International (JCI). The accreditation by JCI attests to quality patient care guided by evidenced-based practice and continuous monitoring of clinical outcomes. The AKHD is a teaching hospital for the Aga Khan University Medical College, East Africa (Dar-es-Salaam Campus). The coronary care unit (CCU) of the AKHD is a 4-bed unit able to provide level III care( 11 ). Patients admitted to the unit receive 1:1 nursing care. There is 24-hour coverage of the unit by a registered medical officer and on-call interventional cardiologist. The current study involved extracting data from charts and electronic medical records for patients who presented with STEMI from August 2014 to December 2023. Patients 18 years and older who presented with STEMI as per the third and fourth universal definitions of myocardial infarction were included in the study Field ( 12 ). Patients with incomplete medical records, duplicate medical records, alternate diagnoses such as myopericarditis, Takotsubo cardiomyopathy, and those who were transferred out or those who left against medical advice were excluded from the final analysis. The hospital's coronary care unit registry, which contains data on all patients admitted to the unit, was used to identify patients who presented with STEMI. Data collected included multiple variables such as: demographics, comorbidities and risk factors, clinical presentation, biochemical parameters, ECG changes (territory involved), coronary angiography findings (number of vessels, culprit lesion, and suspected mechanism of ACS), intervention performed, medical therapy received, the need of organ support, length of hospital stay and final hospital outcome. Patients were followed up to hospital discharge and grouped as survivors and non-survivors. Interventional cardiologists determined the cause of ACS according to previously validated methods ( 13 , 14 ) and were grouped into atherosclerotic ( 14 ), thrombotic ( 14 ), or Spontaneous coronary artery dissection( 13 , 14 ). Obstructive CAD was defined by invasive coronary angiography as a narrowing of the internal diameter > 50% stenosis of the left main stem and > 70% stenosis in a major coronary epicardial vessel( 15 ). A percentage diameter less than the mentioned above was characterized as non-obstructive coronary artery disease ( 16 ). Left Ventricular function on 2D echocardiography performed during admission was documented and confirmed by the attending cardiologist. At the AKHD, all patients are managed with either one of the following strategies: (a) Primary PCI, (b)Rescue PCI, (c) conservative management in those presenting with a fully evolved myocardial infarct, and (d)thrombolysis when Primary PCI services aren’t available. Patients who have undergone thrombolysis on or off-site generally undergo a pharmaco-invasive approach. All data, both in paper form and electronic format, was collected by the primary investigator and checked by the supervising faculty for accuracy and completeness. The collected data was incorporated into a Microsoft Excel 2010 (Redmond, WA, USA). Categorical data were reported as frequencies and proportions and compared with Pearson chi-square or Fisher’s exact tests. Continuous variables were reported as means or medians and compared with students' t-tests or the wilcoxon rank-sum test. Univariable and multivariable logistic regression analyses were used to determine the predictors of in-hospital all-cause mortality. Any variable demonstrating statistical or clinical significance in explaining ICU mortality was considered in the multivariate model. We presented the adjusted odds ratios with their 95% confidence intervals (95% CI). Statistical significance was considered at a p-value < 0.05. Analysis was performed using Stata version 17 (StataCorp Ltd., College Station, TX, USA). The study was approved by the Aga Khan University, East Africa Ethical Research Committee (AKU, EA ERC). The National Institute for Medical Research (NIMR) in Tanzania mandates the AKU, EA ERC to approve health research conducted by Tanzanian students. The hospital’s ethical committee and the AKU, EA, and ERC exempted the primary investigator from acquiring informed consent from the study participants since the study design did not affect the rights and welfare of the patients. This study was conducted in accordance with the Declaration of Helsinki. Ethical Reference number (AKU/2023/018/fb/04/02). Results We identified 351 from medical records; after careful verification and search of records, 121 patients were excluded due to missing medical records, duplication, or alternative diagnosis (High-risk NSTEMI) and staged PCI procedures entry. 230 patients were included in the final study analysis. The demographic and clinical characteristics of the patients are summarized in Table 1 . The cohort was predominantly male (n = 192,83.5%), with a median age was 55.0 years (IQR 48.0–65.0). The majority of the patients were aged between 45–60 years (n = 117,50.8%), had underlying Diabetes Mellitus(n = 131,56.9%), hypertension (n = 111,51.6%) and were on treatment with cholesterol-lowering medication before presentation (n = 160, 60.5%). Table 1 Baseline demographics of the cohort Characteristics n N = 230 1 Median Age 230 55.0 (48.0–65.0) Age Group, n (%) 60 years 79 (37.1) ETHNICTY, n (%) 230 African 80 (34.7) South Asian 101 (43.9) Other 40 (17.4) Caucasian 9 (3.9%) Sex, n (%) Female Male 230 38 (16.5) 192 (83.5) BMI (Kg/m2), Median (IQR) 230 26.5 (25.0–31.0) BMI Category Normal Overweight Obesity I Obesity II Obesity III 49(21.3) 79 (34.3) 55 (23.9) 32 (13.9) 15 (6.5) Admitting Category, n (%) Referral Self 230 85 (37.0) 135 (63) Atherosclerotic risk factors DM, n (%) HTN, n (%) Family history of Premature ASCVD, n (%) CKD/ESRD, n (%) Previous ASCVD, n (%) Smoking, n (%) On Cholesterol- lowering medication prior presentation, n (%) 131(56.9) 111(51.6) 64(29.8) 27(12.6) 52(24.2) 72(33.5) 130(60.5) 1: Median (IQR); n (%). BMI: Body Mass Index, DM: Diabetes Mellitus, HTN: Hypertension, CKD: Chronic Kidney Disease, ESRD: End Stage Renal Disease, ASCVD: Atherosclerotic Cardiovascular Disease Most patients presented with chest pain (n = 162,72.6%), with the median duration of chest pain before hospital presentation of 12.2 hours (IQR 3.0–24.0 hours). Most patients presented in Killip Class 1 (n = 125,54.3%). Anterior myocardial infarction on ECG was the most common presentation (n = 136,59.1%). A small fraction of patients underwent thrombolysis prior to intervention (n = 17,7.8%). These findings are summarized in Table 2 below. Table 2 Symptoms and presentation of the Cohort Characteristic N = 230 1 Presenting Complain, n (%) Chest Pain Cardiac arrest on presentation Dyspeptic syndrome Dyspnea Syncope 167(72.6) 4 (1.7) 12(5.2) 41(17.8) 6(2.6) Chest pain Duration, (IQR) 24 hours, n (%) 12.2 hours (IQR3.0–24.0) 39(23.1) 25(14.9) 22(13.4) 81(48.5) KILLIP, n (%) Killip I 125 (54.3) Killip II 59 (25.6) Killip III 32 (13.9) Killip IV 14 (6.1) ECG changes, n (%) Anterior - septal Inferior Anterior- lateral Anterior Inferior- lateral Lateral Complete heart block Posterior- lateral 67(29.1) 59(25.7) 41(17.8) 28(12.2) 18(7.8) 8(3.5) 5(2.2) 4(1.7) Thrombolysis, n (%) Off site On site 16 (7.8) 12(75) 4( 25 ) 1: n (%). The majority of the patients underwent a femoral puncture (n = 142,61.7%), with single vessel disease (n = 151, 65.6%) and atherosclerosis (n = 182,79.1%) as the most common finding and mechanism of obstruction. Left Anterior descending (LAD) artery was the culprit vessel in most cases (n = 112,48.7%). A total of 163(70.8%) patients underwent Primary Percutaneous intervention (PCI) Table 3 Angiographic findings and interventions Characteristics n N = 230 1 Access. n (%) Radial Femoral 230 88 (38.2) 142 (61.7) Angiographic findings, n (%) Non- Obstructive Coronary Single vessel Disease Single vessel- ISRS Single vessel - stent thrombosis Two vessel disease Triple vessel disease 230 17 (7.9) 142 (61.7) 5 (2.2) 4 (1.7) 37 (16.1) 25 (10.9) Culprit vessel, n (%) LM LAD RCA LCX N/A 230 2 (0.87) 112 (48.7) 69 ( 30 ) 32 (13.9) 17 (7.9) Intervention Done, n (%) Coronary Angiography - No Intervention Primary PCI Thrombotic Aspiration + Primary PCI POBA Primary PCI + PCI of non- IRA Rescue PCI Coronary Angiography - Referral for CABG Unsuccessful PCI 230 17 (7.4) 126 (54.7) 12 (5.2) 7 (3.04) 25 (10.9) 15 (6.5) 17 (7.4) 11 (4.8) Mechanism Atherosclerotic Thrombotic SCAD N/A 230 182 (79.1) 29 (12.6) 2 (0.87) 17 (7.4) 1: n (%). LM: Left Main, LAD: Left Anterior Descending, RCA: Right Coronary artery, LCX: Left Circumflex, PCI: Percutaneous coronary intervention, SCAD: Spontaneous Coronary Artery Dissection. The in-hospital mortality of the cohort was 5.7%. Patients who died prior to discharge were more likely to have Diabetes Mellitus (n = 12,92.3%), hypertension(n = 12,92.3%), a history of current or previous smoking (n-11,84.6%), and to be on treatment for hyperlipidemia (n = 10,76.9%) (P- value < 0.05). Additionally, an increased need for mechanical ventilation(n = 4,30.8%) and inotropes(n = 8,61.5%) was also noted amongst the non-survivors with statistical significance (P- value < 0.05). A higher BMI and delayed time to presentation was predictive of in-hospital mortality. Table 4 Comparison of Survivors and non-Survivors Characteristic Overall, N = 230 1 Survivors, N = 217 (94.3%) Non- Survivors, N = 13 (5.7%) P- Value 2 AGE, Median (IQR) 55.0 (48.0–65.0) 54.1 (48.0–65.0) 55.5 (49.0–75.0) 0.77 SEX, n (%) 0.99 Female 38 (10.7) 37 (10.9) 1 (7.7) Male 192 (89.3) 180 (89.1) 12 (92.3) Chest Pain Duration, Median (IQR) 12.0 (3.0–24.0) 10.5 (3.0–24.0) 24.0 (24.0–36.0) 0.05 BMI, Kg/m2 (IQR) 26.5 (IQR 25.0–31.0) 26.0 (IQR 25.0–31.0) 39.0 (IQR 36.0–39.0) < 0.001 DM, n (%) 131 (54.0) 119 (54.8) 12 (92.3) < 0.001 HTN, n (%) 111 (51.6) 99 (49.0) 12 (92.3) 0.002 Smoking, n (%) 72 (33.5) 61 (30.2) 11 (84.6) < 0.001 Hyperlipidemia, n (%) 130 (60.5) 120 (57.9) 10 (76.9) 0.003 Killip, n (%) < 0.001 Killip I 125 (58.1) 125 (61.9) 0 (0.0) Killip II 59 (20.5) 58 (26.7) 1 (7.7) Killip III 32 (13.0) 23 (10.9) 9 (46.2) Killip IV 14 (6.5) 11 (5.4) 3 (23.1) Angiographic Findings (%) 0.48 Non- Obstructive Coronary 17 (7.9) 17 (8.5) 0 (0.0) Single Vessel Disease 142(61) 136(62.7%) 6(46.2) Single Vessel Disease - ISRS 5 (2.3) 5 (2.5) 0 (0.0) Single Vessel Disease- Stent thrombosis 4 (1.9) 4 (2.0) 0 (0.0) Two Vessel Disease 37 (17.2) 34 (16.8) 3 (23.1) Triple Vessel Disease 25 (11.6) 21 (10.4) 4 (30.8) Culprit Vessel, n (%) 0.18 N/A 17 (7.9) 17 (8.4) 0 (0.0) LM 2 (0.9) 2 (0.9) 0 (0.0) LAD 112 (48.7) 101 (46.5) 11 (84.6) LCX 32 (13.9) 32 (14.7) 0 (0.0) RCA 69 (30.) 67 (30.1) 2 (15.4) Inotropes, n (%) 15 (7.0) 7 (3.5) 8 (61.5) < 0.001 Mechanical Ventilation, n (%) 9 (4.2) 5 (2.5) 4 (30.8) < 0.001 IABP, n (%) 3 (1.4) 1 (0.5) 2 (15.4) 0.01 LOS, Median (IQR) 2.0 (2.0–3.0) 2.0 (2.0–3.0) 2.0 (0.0–8.0) 0.74 1: Median (IQR); n (%). 2: Wilcoxon rank sum test; Fischer’s exact test; Pearson chi-squared test. BMI: Body Mass Index, DM: Diabetes Mellitus, HTN: Hypertension, LAD: Left Anterior Descending, LCX: Left Circumflex, RCA: Right Coronary artery, IABP: Intra-Aortic Balloon Pump, LOS: Length of Stay Table 5 below illustrates laboratory investigations for all patients and provides a comparison between survivors and non-survivors. A higher Low-Density Lipoprotein and Triglyceride (TG), with statistical significance (P-value < 0.05), was noted amongst the non-survivors. Table 5 Laboratory investigations and comparison of survivors and non-survivors n Overall, N = 230 1 Survivors, N = 217 (94.3%) Non- Survivors, N = 13 (5.7%) P- Value 2 Troponin T, Mean (SD) 224 1,073.6 (1,558.3) 1,045.5 (1,383.4) 1,496.4 (3,284.1) 0.46 CKMB, Mean (SD) 188 76.2 (88.3) 75.7 (87.9) 86.6 (100.1) 0.58 TC, Mean (SD), mmol/l 212 4.7 (1.1) 4.7 (1.1) 4.4 (1.1) 0.10 LDL, Mean (SD), mmol/l 212 2.8 (0.9) 2.2 (0.9) 2.8 (1.3) 0.05 HDL, Mean (SD), mmol/l 212 1.1 (0.2) 1.1 (0.2) 1.0 (0.1) 0.18 TG, Mean (SD), mmol/l 212 1.8 (0.9) 1.7 (0.9) 2.5 (1.0) 0.006 HBA1C, Mean (SD)% 91 6.3 (3.8) 6.3 (3.9) 6.7 (3.6) 0.79 CRP, Mean (SD) mg/l 126 72.4 (111.5) 70.4 (110.0) 136.4 (158.7) 0.96 BUN, Mean (SD)mmol/l 212 5.4 (2.4) 5.4 (2.4) 5.5 (2.2) 0.77 Creatinine, Mean (SD)umol/l 212 79.3 (21.4) 78.9 (19.3) 84.8 (43.9) 0.41 1: Mean, 2 Wilcoxon rank sum tests. TC: Total Cholesterol, LDL: Low Density Lipoprotein, HDL: High Density Lipoprotein, TG: Triglycerides, CRP: C- Reactive Protein, BUN: Blood Urea Nitrogen. The Median Left Ventricular Ejection Fraction (LVEF) was 50.23%, and non-survivors had a lower LVEF when compared to survivors. Only 12 patients (5.6%) of the 213 were noted to have LV thrombus on 2D echocardiography. Table 6 2D Echocardiographic findings prior hospital discharge Characteristic Overall, N = 213 1 Survivors, N = 202 Non-Survivors, N = 11 P - Value 2 LVEF, Median (IQR) 50.23% (40.1–60.2) 50.6% (45.6–61.3) 30.5% (31.5–42.5) < 0.001 LV Thrombus, n (%) 12 (5.6) 11 (7.7) 1 (16.7) 0.40 1: Median, n (%), 2 Wilcoxon rank sum tests. LV : Left Ventricle, LVEF : Left Ventricle Ejection Fraction. We could only retrieve the discharge medication of 217 patients. The majority were discharged on B-blockers (n = 163,75.1%), as seen in Table 6 below. Aspirin and Clopidogrel were the most commonly used Dual Antiplatelet Therapy (DAPT)(n = 112,51.6%) Table 7 Discharge Medications of the study population Characteristics N = 217 (100) B- Blocker, n (%) 163 (75.1) ACE-i, n (%) 67 (30.8) ARB, n (%) 61 (28.1) ARNI, n (%) 25 (11.5) MRA, n (%) 68 (31.3) SGLT.2, n (%) 44 (20.2) DAPT, n (%) Aspirin + Clopidogrel 112(51.6) Aspirin + Ticagrelor 49(22.5) Aspirin + prasugrel 13(5.9) Triple antithrombotic Therapy 36 (16.6) 1: n (%). B: Beta, ACE-I: Angiotensin converting Enzyme inhibitor, ARB: Angiotensin Receptor Blocker, ARNI: Angiotensin Receptor Neprilysin Inhibitor, MRA: Mineralocorticoid receptor Antagonist, SGLT-2: Sodium Glucose Transport 2, DAPT: Dual Anti platelet. A higher mean BMI of 36.2 (± 5.7) (OR 1.46, 95% CI 1.17– 2.10), the presence of smoking (OR 41.68, 95% CI 2.60– 240.71), and the use of mechanical ventilation (OR 77.42, 95% CI 1.95– 128.89) were factors associated with in-hospital mortality. Table 8 Factors associated with in-hospital mortality. Dependent: OUTCOME Survivors Non- Survivors OR (univariable) p-value OR (multivariable) p-value Time from chest pain to Presentation(hours) 10.5 (3.0–24.0) 24.0 (24.0–36.0) 1.03 (1.00-1.06) p = 0.069 1.04 (0.97–1.14) p = 0.235 BMI 27.8 (± 5.2) 36.2 (± 5.7) 1.24 (1.13–1.39) p < 0.001 1.46 (1.17–2.10) p = 0.006 HTN No 103 (99.0) 1 (1.0) - - Yes 99 (89.2) 12 (10.8) 12.48 (2.39-229.57) p = 0.016 6.49 (0.35-631.08) p = 0.301 Smoking No 141 (98.6) 2 (1.4) - - Yes 61 (84.7) 11 (15.3) 12.71 (3.29–83.76) p = 0.001 41.68 (2.60-240.71) p = 0.025 Inotropes No 195 (97.5) 5 (2.5) - - Yes 7 (46.7) 8 (53.3) 44.57 (12.06-185.95) p < 0.001 14.22 (0.65-650.87) p = 0.107 Mechanical Ventilation No 197 (95.6) 9 (4.4) - - Yes 5 (55.6) 4 (44.4) 17.51 (3.80–78.30) p < 0.001 77.42 (1.95-128.89) p = 0.033 IABP No 201 (94.8) 11 (5.2) - - Yes 1 (33.3) 2 (66.7) 36.55 (3.27-823.35) p = 0.004 26.47 (0.03-130.61) p = 0.570 Triglycerides Mean (SD) 1.7 (0.9) 2.5 (1.0) 1.94 (1.18–3.16) p = 0.007 3.33 (0.85–18.80) p = 0.097 BMI: Body Mass Index, HTN: Hypertension, IABP: Intra-Aortic Balloon Pump, OR : Odds Ration Discussion These data provide an overview of care for patients presenting with STEMI for approximately a decade at a private primary PCI hospital in Tanzania. To our knowledge, this is the first study in the country that systematically describes clinical characteristics, interventions, and outcomes among patients presenting with STEMI. Our results demonstrate lower in-hospital mortality for patients treated according to recommended guidelines compared to other regional studies from the Ivory Coast( 17 , 18 ), Burkina Faso( 19 ), Djibouti( 20 ), Nigeria( 21 ), and Mali( 22 ). Our morality rates are comparable to well-resourced centers in Africa( 23 – 25 ), Northern America( 26 – 30 ), and data from national registries of the European Society of Cardiology member countries( 31 , 32 ). The lower hospital mortality in our cohort may be attributed to a cohorts younger age, shorter time from onset to presentation, and a high rate of timely intervention and reperfusion strategies available at our institution. However, comparing outcomes across different cohorts may be confounded by many factors; including definitions of disease and outcomes, time to presentation, burden of underlying comorbidities, age and availability of resources and should be made with that in mind. The mean age of our cohort is lower than that of western cohorts, but comparable to that of other African series. The age range among various study populations on the African continent with STEMI has consistently been noted to be lower, with a mean age between 55 and 58 years ( 33 ). This phenomenon may be due to various genetic factors, higher incidence of various risk factors, and socioeconomic reasons. It should also be noted that our cohort is comprised of mixed ethnicity and is not representative of the native population in Tanzania. As noted in the INTERHEART Africa( 33 ) multicentric study, our results continue to highlight the burden of Hypertension, Diabetes Mellitus, Obesity, and hyperlipidemia as the main cardiovascular risk factors associated with STEMI. This analysis further highlights the epidemiological transition in the country, and underscores the importance of intensifying preventive medicine campaigns. The time from symptom onset to presentation was lower in our cohort compared to similar studies in the African continent ( 34 ). This probably reflects a selection bias, as patients presenting to a private facility tend to be from a higher socioeconomic background and education level. Our facility is also located in an easily accessible area in a major urban center, and this provides an advantage. For this reason, the vast majority of the Tanzanian population are unlikely to enjoy the privilege of timely primary PCI. Late presentation was a key factor of in- hospital mortality in our cohort. Delays in reperfusion therapy have been clearly linked to poor outcomes ( 35 ). Timely intervention and Systems of care exploring thrombolysis and referral for invasive assessment have been successfully demonstrated to provide excellent outcomes in developed world and this may be the way forward for many African healthcare systems. The lack of PCI-capable hospitals in Africa has made the comparison of angiographic data and intervention rates challenging ( 34 ). Our study results highlight high and timely reperfusion rates, comparable to rates documented in Northern America ( 36 ) and Europe ( 36 ). Large multi-center registry STEMI studies in South Africa, Ivory Coast, and Kenya have reported variable reperfusion rates ranging between 13–60%( 17 , 34 ). Numerous studies have identified low body mass index (BMI) as a predictor of poor outcomes after STEMI, with overweight and obese individuals experiencing more favorable LOS, fewer inpatient complications, and better in-hospital, 30-day, and long-term outcomes( 37 – 39 ), expanding on the concept of the “obesity paradox” which continues to remain a point of debate to date. Hypotheses that have been postulated to support the obesity paradox in STEMI patients are the higher metabolic reserve and increased development of collaterals ( 40 ). Our results are contrary to the aforementioned reports and associate a higher BMI with an increase in in-hospital mortality and this could be related to the small size of our population. The aim of the study was beyond exploring this relationship. Nonetheless, obesity in Tanzania continues to be a growing pandemic ( 42 ) and a precursor of other cardiovascular risks factors such as diabetes mellitus, hypertension, and hyperlipidemia. Obesity is also a state of chronic inflammation ( 43 ) and a factor of poor functional status( 41 ). This collective association could account for poor hospital outcomes among patients with obesity in our cohort. Nonetheless, it is important to note that the obesity paradox is still a subject of ongoing research, and not all studies agree on its existence; thus, it should not overshadow the risks associated with obesity. Our study also highlighted smoking as the main factor of in hospital mortality among patients with STEMI. Similarly, various reports have also indicated the presence of “smokers’ paradox,” suggesting favorable outcomes among smokers than non-smokers( 42 ). This association is intriguing, counterintuitive, and may be misleading because several epidemiological studies have clearly attributed smoking as an independent risk for atherosclerosis, heart failure, premature ASCVD, and death( 43 ). This paradox is largely attributed to the younger age as smokers may develop an acute myocardial infarction a decade earlier than non-smokers and thus tend to have fewer cardiovascular comorbidities( 42 ).It has also been postulated that smoking might exert protective effects and could reduce infarct size, a strong predictor of poor outcomes among patients with STEMI( 42 ), suggesting greater responsiveness to spontaneous or therapeutic thrombolysis. Furthermore, smoking activates the cytochrome system, an enzyme responsible for converting Clopidogrel, a common antiplatelet, from its prodrug to its active form, thereby increasing its antiplatelet effect (Field, ( 42 ). It is, however, crucial to understand that the harmful effects of smoking on the cardiovascular system outweigh any potential short-term advantages observed in a few studies. Just like the obesity paradox, the smoking paradox is still evolving and remains an area of discussion and ongoing research. Patients with STEMI requiring mechanical ventilation during admission or hospitalization often face a more complicated clinical course. Approximately 20% of patients with STEMI typically experience respiratory impairment due to acute heart failure ( 44 ), with prior studies indicating half of this group to require invasive mechanical ventilation during their hospital stay, forming a very high-risk subgroup ( 44 ). Our study results are parallel to published reports indicating an increase in the risk of death among those needing mechanical ventilation. Additionally, prolonged mechanical ventilation has been associated with the development of ventilator-associated pneumonia, need of inotropes, and IABP, which collectively increase the risk of in-hospital mortality( 45 ). Limitations Our study has several key limitations: this was a single-center study from a private urban teaching and referral University Hospital, so findings cannot be generalized nationwide. Single-center studies also risk institutional and patient selection bias. Furthermore, as expected, retrospective design is inclined to miss data. Nonetheless, we tried to extract as much as possible from medical records and databases available for consentient statistical analysis. Additionally, we were not able to accurately collect data or analyze specific timings related to outcomes among patients with STEMI, such as door-to-ECG timing and door-to-procedure timing, which have significant prognostication value. Conclusion We present a decade of descriptive summary of patients who presented with STEMI at a teaching university Hospital in Tanzania. Our study demonstrates a low in-hospital mortality rate of 5.7% among patients with STEMI. Cigarette smoking, obesity and the need for mechanical ventilation were predictors of poor outcomes. Large prospective, multicenter registry studies are needed to understand the magnitude of the syndrome and better highlight areas of improvement. Abbreviations ACS: Acute Coronary Syndrome SSA: Sub- Saharan Africa STEMI: ST- Elevation Myocardial Infarction NSTEMI: Non- ST Elevation Myocardial infarction LMICs: Low Middle Income Countries CVD: Cardiovascular Disease NCD: Non-Communicable Diseases CAD: Coronary Artery Disease JCI: Joint Commission International NCDR: National Cardiovascular Data Registry ACC: American College of Cardiology CCU: Coronary Care Unit AHA: American Heart Association PCI: Percutaneous Intervention ASE: American Society of Echocardiography LVEF: Left Ventricular Ejection Fraction PCI: Percutaneous Coronary Intervention Declarations Ethics Approval and consent to participate The study was presented to the section of cardiology of the Aga Khan Hospital Dar es Salaam. The study was approved by the Aga Khan University, East Africa Ethical Research Committee (AKU, EA ERC). The National Institute for Medical Research (NIMR) in Tanzania mandates the AKU, EA ERC to approve health research conducted by Tanzanian students. The hospital’s ethical committee and the AKU, EA, and ERC exempted the primary investigator from acquiring informed consent from the study participants since the study design was purely based on extracting data from the hospital registrar and did not affect the rights and welfare of the patients. This study was conducted in accordance with the Declaration of Helsinki. Reference (AKU/2023/018/fb/04/02). Consent for Publication Not applicable Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Conflict of interest The authors report no conflict on interest in this work. Funding There was no funding for this research. Author Contribution All authors made an important and substantial contribution to the conception, study design, execution, acquisition of data, analysis, interpretation and implementation. All authors equally contributed in writing, revising, and critically revising the article. All authors approved the final document to be published and agreed to be accountable for all aspects of the work. Acknowledgments We want to thank the medical records and the section of cardiology of the Aga Khan hospital, Dar -es- Salaam for their support in the successful completion of the research. References Minja NW, Nakagaayi D, Aliku T, Zhang W, Ssinabulya I, Nabaale J, et al. Cardiovascular diseases in Africa in the twenty-first century: Gaps and priorities going forward. Front Cardiovasc Med. 2022;9:1008335. Chillo P, Mashili F, Kwesigabo G, Ruggajo P, Kamuhabwa A. Developing a Sustainable Cardiovascular Disease Research Strategy in Tanzania Through Training: Leveraging From the East African Centre of Excellence in Cardiovascular Sciences Project. Front Cardiovasc Med. 2022;9:849007. Zhang L, Tong Z, Han R, Guo R, Zang S, Zhang X, et al. Global, Regional, and National Burdens of Ischemic Heart Disease Attributable to Smoking From 1990 to 2019. J Am Heart Assoc. 2023;12(3):e028193. Gaziano TA, Bitton A, Anand S, Abrahams-Gessel S, Murphy A. Growing epidemic of coronary heart disease in low- and middle-income countries. Curr Probl Cardiol. 2010;35(2):72-115. Guan C, Wu S, Xu W, Zhang J. Global, regional, and national burden of ischaemic heart disease and its trends, 1990-2019. Public Health. 2023;223:57-66. Badianyama M, Mutyaba A, Nel S, Tsabedze N. ST-segment elevation myocardial infarction heart of Charlotte one-year (STEMI HOC-1) study: a prospective study protocol. BMC Cardiovasc Disord. 2023;23(1):396. Lassen JF, Botker HE, Terkelsen CJ. Timely and optimal treatment of patients with STEMI. Nat Rev Cardiol. 2013;10(1):41-8. Li F, Luo R, Wang XT, Jia JF, Yu XY. Current situation of acute ST-segment elevation myocardial infarction in a county hospital chest pain center during an epidemic of novel coronavirus pneumonia. Open Med (Wars). 2023;18(1):20220621. Knysh VI, Ozhiganov EL, Bagirov Iu F. [Treatment and prevention of urinary tract radical rectal during radical operations for rectal cancer]. Vopr Onkol. 1982;28(9):84-90. Mayige M, Kagaruki G, Ramaiya K, Swai A. Non communicable diseases in Tanzania: a call for urgent action. Tanzan J Health Res. 2011;13(5 Suppl 1):378-86. Marshall JC, Bosco L, Adhikari NK, Connolly B, Diaz JV, Dorman T, et al. What is an intensive care unit? A report of the task force of the World Federation of Societies of Intensive and Critical Care Medicine. J Crit Care. 2017;37:270-6. Domienik-Karlowicz J, Kupczynska K, Michalski B, Kaplon-Cieslicka A, Darocha S, Dobrowolski P, et al. Fourth universal definition of myocardial infarction. Selected messages from the European Society of Cardiology document and lessons learned from the new guidelines on ST-segment elevation myocardial infarction and non-ST-segment elevation-acute coronary syndrome. Cardiol J. 2021;28(2):195-201. Hayes SN, Kim ESH, Saw J, Adlam D, Arslanian-Engoren C, Economy KE, et al. Spontaneous Coronary Artery Dissection: Current State of the Science: A Scientific Statement From the American Heart Association. Circulation. 2018;137(19):e523-e57. Tweet MS, Olin JW, Bonikowske AR, Adlam D, Hayes SN. Physical activity and exercise in patients with spontaneous coronary artery dissection and fibromuscular dysplasia. Eur Heart J. 2021;42(37):3825-8. Neglia D, Rovai D, Caselli C, Pietila M, Teresinska A, Aguade-Bruix S, et al. Detection of significant coronary artery disease by noninvasive anatomical and functional imaging. Circ Cardiovasc Imaging. 2015;8(3). Dees D, Rahimi F, Amann M, Nuhrenberg TG, Loffelhardt N, Schmitz R, et al. Prevalence and Causes of Myocardial Infarction with Non-Obstructive Coronary Arteries in a Contemporary Cohort of Patients with Suspected Myocardial Infarction. J Clin Med. 2021;10(21). Ekou A, Yao H, Kouame I, Boni RY, Ehouman E, N'Guetta R. Primary PCI in the management of STEMI in sub-Saharan Africa: insights from Abidjan Heart Institute catheterisation laboratory. Cardiovasc J Afr. 2020;31(4):201-4. Yao H, Ekou A, Hadeou A, N'Djessan JJ, Kouame I, N'Guetta R. Medium and long-term follow-up after ST-segment elevation myocardial infarction in a sub-Saharan Africa population: a prospective cohort study. BMC Cardiovasc Disord. 2019;19(1):65. Yameogo NV, Samadoulougou A, Millogo G, Kologo KJ, Kombassere K, Toguyeni BJ, et al. [Delays in the management of acute coronary syndromes with ST-ST segment elevation in Ouagadougou and factors associated with an extension of these delays: a cross-sectional study about 43 cases collected in the CHU-Yalgado Ouedraogo]. Pan Afr Med J. 2012;13:90. Maurin O, Massoure PL, de Regloix S, Topin F, Sbardella F, Lamblin G, et al. [Acute myocardial infarction in Djibouti: 2-year prospective study]. Med Sante Trop. 2012;22(3):297-301. Kolo PM, Fasae AJ, Aigbe IF, Ogunmodede JA, Omotosho AB. Changing trend in the incidence of myocardial infarction among medical admissions in Ilorin, north-central Nigeria. Niger Postgrad Med J. 2013;20(1):5-8. Beye SA, Malle KK, Wade KA, Djibo MD, Landrover RJ, Dembele D, et al. [Problems with the management of myocardial infarction at the Desegou Hospital]. Mali Med. 2011;26(3):45-7. Chamtouri I, Souissi R, Amdouni N, Jomaa W, Abdallah W, Hamda KB, et al. ST-segment Elevation Myocardial Infarction in North African Women: Results From a Twenty-year Experience. J Saudi Heart Assoc. 2022;34(3):166-74. Soufiani A, Chraibi H, Asfalou I, Ouafi NE, Hattaoui ME, Habbal R, et al. The national moroccan registry of ST-elevation myocardial infarction (MR-MI). BMC Cardiovasc Disord. 2023;23(1):419. Chetty R, Ross A. Chart review of acute myocardial infarction at a district hospital in KwaZulu-Natal, South Africa. Afr J Prim Health Care Fam Med. 2016;8(1):e1-5. McNamara RL, Kennedy KF, Cohen DJ, Diercks DB, Moscucci M, Ramee S, et al. Predicting In-Hospital Mortality in Patients With Acute Myocardial Infarction. J Am Coll Cardiol. 2016;68(6):626-35. Jollis JG, Granger CB, Zegre-Hemsey JK, Henry TD, Goyal A, Tamis-Holland JE, et al. Treatment Time and In-Hospital Mortality Among Patients With ST-Segment Elevation Myocardial Infarction, 2018-2021. JAMA. 2022;328(20):2033-40. Popa-Fotea NM, Grigore IA, Calmac L, Mihai C, Bataila V, Ploscaru V, et al. The Profile and All-Cause In-Hospital Mortality Dynamics of St-Segment Elevation Myocardial Infarction Patients during the Two Years of the COVID-19 Pandemic. J Clin Med. 2023;12(4). Hillerson D, Li S, Misumida N, Wegermann ZK, Abdel-Latif A, Ogunbayo GO, et al. Characteristics, Process Metrics, and Outcomes Among Patients With ST-Elevation Myocardial Infarction in Rural vs Urban Areas in the US: A Report From the US National Cardiovascular Data Registry. JAMA Cardiol. 2022;7(10):1016-24. Ludman P, Zeymer U, Danchin N, Kala P, Laroche C, Sadeghi M, et al. Care of patients with ST-elevation myocardial infarction: an international analysis of quality indicators in the acute coronary syndrome STEMI Registry of the EURObservational Research Programme and ACVC and EAPCI Associations of the European Society of Cardiology in 11 462 patients. Eur Heart J Acute Cardiovasc Care. 2023;12(1):22-37. Pedersen F, Butrymovich V, Kelbaek H, Wachtell K, Helqvist S, Kastrup J, et al. Short- and long-term cause of death in patients treated with primary PCI for STEMI. J Am Coll Cardiol. 2014;64(20):2101-8. Granger CB, Bates ER, Jollis JG, Antman EM, Nichol G, O'Connor RE, et al. Improving Care of STEMI in the United States 2008 to 2012. J Am Heart Assoc. 2019;8(1):e008096. Steyn K, Sliwa K, Hawken S, Commerford P, Onen C, Damasceno A, et al. Risk factors associated with myocardial infarction in Africa: the INTERHEART Africa study. Circulation. 2005;112(23):3554-61. Yao H, Ekou A, Niamkey T, Hounhoui Gan S, Kouame I, Afassinou Y, et al. Acute Coronary Syndromes in Sub-Saharan Africa: A 10-Year Systematic Review. J Am Heart Assoc. 2022;11(1):e021107. Di Pasquale G. The avoidable delay in the care of STEMI patients is still a priority issue. Int J Cardiol Heart Vasc. 2022;39:101011. Widimsky P, Wijns W, Fajadet J, de Belder M, Knot J, Aaberge L, et al. Reperfusion therapy for ST elevation acute myocardial infarction in Europe: description of the current situation in 30 countries. Eur Heart J. 2010;31(8):943-57. Liu SH, Lin YZ, Han S, Jin YZ. The obesity paradox in ST-segment elevation myocardial infarction patients: A meta-analysis. Ann Noninvasive Electrocardiol. 2023;28(2):e13022. Kim DW, Her SH, Park HW, Park MW, Chang K, Chung WS, et al. Association between body mass index and 1-year outcome after acute myocardial infarction. PLoS One. 2019;14(6):e0217525. Alhuneafat L, Jabri A, Abu Omar Y, Margaria B, Al-Abdouh A, Mhanna M, et al. Relationship Between Body Mass Index and Outcomes in Acute Myocardial Infarction. J Clin Med Res. 2022;14(11):458-65. Sasmaz H, Yilmaz MB. Coronary collaterals in obese patients: impact of metabolic syndrome. Angiology. 2009;60(2):164-8. Samper-Ternent R, Al Snih S. Obesity in Older Adults: Epidemiology and Implications for Disability and Disease. Rev Clin Gerontol. 2012;22(1):10-34. Redfors B, Furer A, Selker HP, Thiele H, Patel MR, Chen S, et al. Effect of Smoking on Outcomes of Primary PCI in Patients With STEMI. J Am Coll Cardiol. 2020;75(15):1743-54. Jee Y, Jung KJ, Lee S, Back JH, Jee SH, Cho SI. Smoking and atherosclerotic cardiovascular disease risk in young men: the Korean Life Course Health Study. BMJ Open. 2019;9(6):e024453. Kouraki K, Schneider S, Uebis R, Tebbe U, Klein HH, Janssens U, et al. Characteristics and clinical outcome of 458 patients with acute myocardial infarction requiring mechanical ventilation. Results of the BEAT registry of the ALKK-study group. Clin Res Cardiol. 2011;100(3):235-9. Ansari MI, Umair M, Taimoor L, Memon AR, Abubaker Z, Arif MS, et al. Mechanical ventilation in acute myocardial infarction: Outcomes from a prospective audit at a cardiovascular hospital in Pakistan. PLoS One. 2023;18(8):e0290399. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4514601","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":332486178,"identity":"3e75882f-14e9-4fc5-9d93-81dab945a560","order_by":0,"name":"Nadeem kassam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYBACCTjrABB/qAASzMwNxGthnHEGpIWRBC3MvG0gFgEtku3HH3/4mXNHnu9489ENvPNqo/nbgVp+VGzDqUWaJ8dMsnfbM8OZZ46l3ZDcdjx3xmHGBsaeM7dxapFjyGFj4N12mHHDjRyzG4bbjuU2ALUwM7bh0cL//PHHv9sO22+4//7bjcQ5x3LnE9IiLZFgIA20JXHDDR62GwcbanI3ENIiOeONmbTstsPJM8+kmd1sOHYgdyNQy0F8fpE4n/7449tth237jh9+dvtPTV3uvPOHDz74UYFbCzo4DCYPEK0eCOpIUTwKRsEoGAUjBAAAzs1oCOxPL0gAAAAASUVORK5CYII=","orcid":"","institution":"Aga Khan University Hospital","correspondingAuthor":true,"prefix":"","firstName":"Nadeem","middleName":"","lastName":"kassam","suffix":""},{"id":332486179,"identity":"da709040-7753-4078-93b9-438b7c557eb2","order_by":1,"name":"Mohamed Varwani","email":"","orcid":"","institution":"Aga Khan University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"","lastName":"Varwani","suffix":""},{"id":332486180,"identity":"429f9292-2442-49e5-bf2a-f64c6977f5dd","order_by":2,"name":"Mzee Ngunga","email":"","orcid":"","institution":"Aga Khan University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mzee","middleName":"","lastName":"Ngunga","suffix":""},{"id":332486181,"identity":"c3037a6a-60ec-401d-a0c6-82cd5bc2f2a3","order_by":3,"name":"Mohamed Jeilan","email":"","orcid":"","institution":"Aga Khan University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"","lastName":"Jeilan","suffix":""},{"id":332486182,"identity":"055476eb-83b6-4bd9-8a16-f15c66d26248","order_by":4,"name":"Mangaro Mabusi","email":"","orcid":"","institution":"Aga Khan Hospital Dar es Salaam","correspondingAuthor":false,"prefix":"","firstName":"Mangaro","middleName":"","lastName":"Mabusi","suffix":""},{"id":332486184,"identity":"88f2a5ab-e285-4cf8-8995-7fd36a62c38f","order_by":5,"name":"James Orwa","email":"","orcid":"","institution":"Aga Khan University Hospital","correspondingAuthor":false,"prefix":"","firstName":"James","middleName":"","lastName":"Orwa","suffix":""},{"id":332486186,"identity":"6c129961-37cf-4783-b593-465e7b3db1e8","order_by":6,"name":"Salim Surani","email":"","orcid":"","institution":"Aga Khan University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Salim","middleName":"","lastName":"Surani","suffix":""},{"id":332486188,"identity":"7568b294-388d-4c0c-b1da-777cbf9386cb","order_by":7,"name":"Robert Mvungi","email":"","orcid":"","institution":"Aga Khan Hospital Dar es Salaam","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"","lastName":"Mvungi","suffix":""},{"id":332486189,"identity":"f95ed511-fff4-47ef-acaf-88da0cd1d9d0","order_by":8,"name":"Nasiruddin Jamal","email":"","orcid":"","institution":"Aga Khan Hospital Dar es Salaam","correspondingAuthor":false,"prefix":"","firstName":"Nasiruddin","middleName":"","lastName":"Jamal","suffix":""}],"badges":[],"createdAt":"2024-06-01 17:38:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4514601/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4514601/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":64466335,"identity":"0d00bc18-8173-4ed6-a93b-a15e1b62d55c","added_by":"auto","created_at":"2024-09-13 13:46:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":982386,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4514601/v1/c323801b-fb65-435b-a37b-2c06cba3a8db.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"ST-Segment Elevation Myocardial Infarction (STEMI): A 10-year Review form a primary PCI capable hospital in Tanzania","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCardiovascular disease (CVD) is an emerging epidemic in sub-Saharan Africa (SSA) and other low- to middle-income countries (LMICs) such as Tanzania(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). CVD accounts for approximately 13% of all deaths in Tanzania, higher than in most African countries(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Various reports have speculated that the true burden of ischemic heart disease (IHD) is likely underestimated in the majority of African countries due to limited awareness, inadequate clinician training, and lack of resources, yet it still accounts for the single most common cause of cardiovascular mortality worldwide(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Most of the LMICs in SSA have undergone economic growth and adopted lifestyle changes in the past years that have increased the risk prevalence associated with IHD, more so in a much younger population(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This has led to an increased burden of health expenditures in most sub-Saharan region regions battling the dawn of an epidemiological transition. Understanding the trend and transformation, as well as improving measures to stem the global tide associated with CVD mortality, remains an important action frontier in these regions(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eST-Segment Elevation Myocardial Infarction (STEMI) is a clinically time-sensitive fatal sequela of ischemic heart disease (IHD)(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The treatment is timely reperfusion by percutaneous coronary intervention (PCI) or thrombolytic therapy of the culprit coronary artery (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). There has been a notable decrease in the mortality rate associated with ST-segment elevation myocardial infarction (STEMI) in resourceful HICs, mostly due to overall improvement in healthcare infrastructure and systems of care (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). This may not be true for the majority of the Sub-Saharan region. The impact of IHD remains a major public health burden due to various factors; including insufficient health care systems, lack of resources, skewed allocation of budget, high cost of treatment coupled with lack of health care professionals able to emulate its timely and ideal care(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo date, there is a paucity of available data on the state of coronary care within most LMICs in Sub-Saharan Africa. In the past decade, Tanzania has witnessed a gradual and continued development in the ability to provide coronary care in both the private and public sectors. Simultaneously, recent national trends also portray an increased magnitude of multiple risk factors associated with coronary artery disease in Tanzania. In light of the country now experiencing a shift in its health landscape, the traditional focus on infectious disease is gradually giving way to the rising burden of NCDs with cardiovascular diseases assuming a prominent role; this analysis is a timely field(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Aga Khan Hospital Dar - es - salaam has been one of the pioneers in establishing the state-of-the-art catheterization laboratory in the nation. This study aimed to describe demographics, clinical presentation, and angiographic findings among patients presenting with STEMI at a private tertiary hospital in Tanzania, as well as patient outcomes including mortality for the past decade.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis single-center retrospective study was conducted at the Aga Khan Hospital Dar-es-Salaam (AKHD), Tanzania. AKHD is a private, non-profit, tertiary hospital in Tanzania. The AKHD was the first hospital in the country to have an operational 24-hour catheterization laboratory and the only hospital to date in Tanzania to be accredited by the Joint Commission International (JCI). The accreditation by JCI attests to quality patient care guided by evidenced-based practice and continuous monitoring of clinical outcomes. The AKHD is a teaching hospital for the Aga Khan University Medical College, East Africa (Dar-es-Salaam Campus). The coronary care unit (CCU) of the AKHD is a 4-bed unit able to provide level III care(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Patients admitted to the unit receive 1:1 nursing care. There is 24-hour coverage of the unit by a registered medical officer and on-call interventional cardiologist.\u003c/p\u003e \u003cp\u003eThe current study involved extracting data from charts and electronic medical records for patients who presented with STEMI from August 2014 to December 2023. Patients 18 years and older who presented with STEMI as per the third and fourth universal definitions of myocardial infarction were included in the study Field (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Patients with incomplete medical records, duplicate medical records, alternate diagnoses such as myopericarditis, Takotsubo cardiomyopathy, and those who were transferred out or those who left against medical advice were excluded from the final analysis. The hospital's coronary care unit registry, which contains data on all patients admitted to the unit, was used to identify patients who presented with STEMI.\u003c/p\u003e \u003cp\u003eData collected included multiple variables such as: demographics, comorbidities and risk factors, clinical presentation, biochemical parameters, ECG changes (territory involved), coronary angiography findings (number of vessels, culprit lesion, and suspected mechanism of ACS), intervention performed, medical therapy received, the need of organ support, length of hospital stay and final hospital outcome.\u003c/p\u003e \u003cp\u003ePatients were followed up to hospital discharge and grouped as survivors and non-survivors. Interventional cardiologists determined the cause of ACS according to previously validated methods (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) and were grouped into atherosclerotic (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), thrombotic (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), or Spontaneous coronary artery dissection(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Obstructive CAD was defined by invasive coronary angiography as a narrowing of the internal diameter\u0026thinsp;\u0026gt;\u0026thinsp;50% stenosis of the left main stem and \u0026gt;\u0026thinsp;70% stenosis in a major coronary epicardial vessel(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). A percentage diameter less than the mentioned above was characterized as non-obstructive coronary artery disease (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Left Ventricular function on 2D echocardiography performed during admission was documented and confirmed by the attending cardiologist. At the AKHD, all patients are managed with either one of the following strategies: (a) Primary PCI, (b)Rescue PCI, (c) conservative management in those presenting with a fully evolved myocardial infarct, and (d)thrombolysis when Primary PCI services aren\u0026rsquo;t available. Patients who have undergone thrombolysis on or off-site generally undergo a pharmaco-invasive approach.\u003c/p\u003e \u003cp\u003eAll data, both in paper form and electronic format, was collected by the primary investigator and checked by the supervising faculty for accuracy and completeness. The collected data was incorporated into a Microsoft Excel 2010 (Redmond, WA, USA). Categorical data were reported as frequencies and proportions and compared with Pearson chi-square or Fisher\u0026rsquo;s exact tests. Continuous variables were reported as means or medians and compared with students' t-tests or the wilcoxon rank-sum test. Univariable and multivariable logistic regression analyses were used to determine the predictors of in-hospital all-cause mortality. Any variable demonstrating statistical or clinical significance in explaining ICU mortality was considered in the multivariate model. We presented the adjusted odds ratios with their 95% confidence intervals (95% CI). Statistical significance was considered at a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Analysis was performed using Stata version 17 (StataCorp Ltd., College Station, TX, USA).\u003c/p\u003e \u003cp\u003e The study was approved by the Aga Khan University, East Africa Ethical Research Committee (AKU, EA ERC). The National Institute for Medical Research (NIMR) in Tanzania mandates the AKU, EA ERC to approve health research conducted by Tanzanian students. The hospital\u0026rsquo;s ethical committee and the AKU, EA, and ERC exempted the primary investigator from acquiring informed consent from the study participants since the study design did not affect the rights and welfare of the patients. This study was conducted in accordance with the Declaration of Helsinki. Ethical Reference number (AKU/2023/018/fb/04/02).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e We identified 351 from medical records; after careful verification and search of records, 121 patients were excluded due to missing medical records, duplication, or alternative diagnosis (High-risk NSTEMI) and staged PCI procedures entry. 230 patients were included in the final study analysis.\u003c/p\u003e \u003cp\u003eThe demographic and clinical characteristics of the patients are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The cohort was predominantly male (n\u0026thinsp;=\u0026thinsp;192,83.5%), with a median age was 55.0 years (IQR 48.0\u0026ndash;65.0). The majority of the patients were aged between 45\u0026ndash;60 years (n\u0026thinsp;=\u0026thinsp;117,50.8%), had underlying Diabetes Mellitus(n\u0026thinsp;=\u0026thinsp;131,56.9%), hypertension (n\u0026thinsp;=\u0026thinsp;111,51.6%) and were on treatment with cholesterol-lowering medication before presentation (n\u0026thinsp;=\u0026thinsp;160, 60.5%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline demographics of the cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;230\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian Age\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.0 (48.0\u0026ndash;65.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge Group, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;45 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34 (16.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e117(50.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79 (37.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eETHNICTY, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfrican\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80 (34.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth Asian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e101 (43.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40 (17.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaucasian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex, n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (16.5)\u003c/p\u003e \u003cp\u003e192 (83.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (Kg/m2), Median (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.5 (25.0\u0026ndash;31.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI Category\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNormal\u003c/p\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003cp\u003eObesity I\u003c/p\u003e \u003cp\u003eObesity II\u003c/p\u003e \u003cp\u003eObesity III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49(21.3)\u003c/p\u003e \u003cp\u003e79 (34.3)\u003c/p\u003e \u003cp\u003e55 (23.9)\u003c/p\u003e \u003cp\u003e32 (13.9)\u003c/p\u003e \u003cp\u003e15 (6.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdmitting Category, n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eReferral\u003c/p\u003e \u003cp\u003eSelf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85 (37.0)\u003c/p\u003e \u003cp\u003e135 (63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAtherosclerotic risk factors\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDM, n (%)\u003c/p\u003e \u003cp\u003eHTN, n (%)\u003c/p\u003e \u003cp\u003eFamily history of Premature ASCVD, n (%)\u003c/p\u003e \u003cp\u003eCKD/ESRD, n (%)\u003c/p\u003e \u003cp\u003ePrevious ASCVD, n (%)\u003c/p\u003e \u003cp\u003eSmoking, n (%)\u003c/p\u003e \u003cp\u003eOn Cholesterol- lowering medication prior presentation, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131(56.9)\u003c/p\u003e \u003cp\u003e111(51.6)\u003c/p\u003e \u003cp\u003e64(29.8)\u003c/p\u003e \u003cp\u003e27(12.6)\u003c/p\u003e \u003cp\u003e52(24.2)\u003c/p\u003e \u003cp\u003e72(33.5)\u003c/p\u003e \u003cp\u003e130(60.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e1: Median (IQR); n (%). BMI: Body Mass Index, DM: Diabetes Mellitus, HTN: Hypertension, CKD: Chronic Kidney Disease, ESRD: End Stage Renal Disease, ASCVD: Atherosclerotic Cardiovascular Disease\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMost patients presented with chest pain (n\u0026thinsp;=\u0026thinsp;162,72.6%), with the median duration of chest pain before hospital presentation of 12.2 hours (IQR 3.0\u0026ndash;24.0 hours). Most patients presented in Killip Class 1 (n\u0026thinsp;=\u0026thinsp;125,54.3%). Anterior myocardial infarction on ECG was the most common presentation (n\u0026thinsp;=\u0026thinsp;136,59.1%). A small fraction of patients underwent thrombolysis prior to intervention (n\u0026thinsp;=\u0026thinsp;17,7.8%). These findings are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSymptoms and presentation of the Cohort\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;230\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresenting Complain, n (%)\u003c/p\u003e \u003cp\u003eChest Pain\u003c/p\u003e \u003cp\u003eCardiac arrest on presentation\u003c/p\u003e \u003cp\u003eDyspeptic syndrome\u003c/p\u003e \u003cp\u003eDyspnea\u003c/p\u003e \u003cp\u003eSyncope\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167(72.6)\u003c/p\u003e \u003cp\u003e4 (1.7)\u003c/p\u003e \u003cp\u003e12(5.2)\u003c/p\u003e \u003cp\u003e41(17.8)\u003c/p\u003e \u003cp\u003e6(2.6)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChest pain Duration, (IQR)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3 hours, \u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e3\u0026ndash;12 hours, \u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e12\u0026ndash;24 hours, \u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;24 hours, \u003cb\u003en (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.2 hours (IQR3.0\u0026ndash;24.0)\u003c/p\u003e \u003cp\u003e39(23.1)\u003c/p\u003e \u003cp\u003e25(14.9)\u003c/p\u003e \u003cp\u003e22(13.4)\u003c/p\u003e \u003cp\u003e81(48.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKILLIP, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKillip I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125 (54.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKillip II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (25.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKillip III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (13.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKillip IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (6.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eECG changes, n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAnterior - septal\u003c/p\u003e \u003cp\u003eInferior\u003c/p\u003e \u003cp\u003eAnterior- lateral\u003c/p\u003e \u003cp\u003eAnterior\u003c/p\u003e \u003cp\u003eInferior- lateral\u003c/p\u003e \u003cp\u003eLateral\u003c/p\u003e \u003cp\u003eComplete heart block\u003c/p\u003e \u003cp\u003ePosterior- lateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67(29.1)\u003c/p\u003e \u003cp\u003e59(25.7)\u003c/p\u003e \u003cp\u003e41(17.8)\u003c/p\u003e \u003cp\u003e28(12.2)\u003c/p\u003e \u003cp\u003e18(7.8)\u003c/p\u003e \u003cp\u003e8(3.5)\u003c/p\u003e \u003cp\u003e5(2.2)\u003c/p\u003e \u003cp\u003e4(1.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eThrombolysis, n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOff site\u003c/p\u003e \u003cp\u003eOn site\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (7.8)\u003c/p\u003e \u003cp\u003e12(75)\u003c/p\u003e \u003cp\u003e4(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e1: n (%).\u003c/p\u003e \u003cp\u003eThe majority of the patients underwent a femoral puncture (n\u0026thinsp;=\u0026thinsp;142,61.7%), with single vessel disease (n\u0026thinsp;=\u0026thinsp;151, 65.6%) and atherosclerosis (n\u0026thinsp;=\u0026thinsp;182,79.1%) as the most common finding and mechanism of obstruction. Left Anterior descending (LAD) artery was the culprit vessel in most cases (n\u0026thinsp;=\u0026thinsp;112,48.7%). A total of 163(70.8%) patients underwent Primary Percutaneous intervention (PCI)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAngiographic findings and interventions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;230\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAccess. n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eRadial\u003c/p\u003e \u003cp\u003eFemoral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88 (38.2)\u003c/p\u003e \u003cp\u003e142 (61.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAngiographic findings, n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNon- Obstructive Coronary\u003c/p\u003e \u003cp\u003eSingle vessel Disease\u003c/p\u003e \u003cp\u003eSingle vessel- ISRS\u003c/p\u003e \u003cp\u003eSingle vessel - stent thrombosis\u003c/p\u003e \u003cp\u003eTwo vessel disease\u003c/p\u003e \u003cp\u003eTriple vessel disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (7.9)\u003c/p\u003e \u003cp\u003e142 (61.7)\u003c/p\u003e \u003cp\u003e5 (2.2)\u003c/p\u003e \u003cp\u003e4 (1.7)\u003c/p\u003e \u003cp\u003e37 (16.1)\u003c/p\u003e \u003cp\u003e25 (10.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCulprit vessel, n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eLM\u003c/p\u003e \u003cp\u003eLAD\u003c/p\u003e \u003cp\u003eRCA\u003c/p\u003e \u003cp\u003eLCX\u003c/p\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.87)\u003c/p\u003e \u003cp\u003e112 (48.7)\u003c/p\u003e \u003cp\u003e69 (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e32 (13.9)\u003c/p\u003e \u003cp\u003e17 (7.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntervention Done, n (%)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCoronary Angiography - No Intervention\u003c/p\u003e \u003cp\u003ePrimary PCI\u003c/p\u003e \u003cp\u003eThrombotic Aspiration\u0026thinsp;+\u0026thinsp;Primary PCI\u003c/p\u003e \u003cp\u003ePOBA\u003c/p\u003e \u003cp\u003ePrimary PCI\u0026thinsp;+\u0026thinsp;PCI of non- IRA\u003c/p\u003e \u003cp\u003eRescue PCI\u003c/p\u003e \u003cp\u003eCoronary Angiography - Referral for CABG\u003c/p\u003e \u003cp\u003eUnsuccessful PCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (7.4)\u003c/p\u003e \u003cp\u003e126 (54.7)\u003c/p\u003e \u003cp\u003e12 (5.2)\u003c/p\u003e \u003cp\u003e7 (3.04)\u003c/p\u003e \u003cp\u003e25 (10.9)\u003c/p\u003e \u003cp\u003e15 (6.5)\u003c/p\u003e \u003cp\u003e17 (7.4)\u003c/p\u003e \u003cp\u003e11 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMechanism\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAtherosclerotic\u003c/p\u003e \u003cp\u003eThrombotic\u003c/p\u003e \u003cp\u003eSCAD\u003c/p\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e182 (79.1)\u003c/p\u003e \u003cp\u003e29 (12.6)\u003c/p\u003e \u003cp\u003e2 (0.87)\u003c/p\u003e \u003cp\u003e17 (7.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e1: n (%). LM: Left Main, LAD: Left Anterior Descending, RCA: Right Coronary artery, LCX: Left Circumflex, PCI: Percutaneous coronary intervention, SCAD: Spontaneous Coronary Artery Dissection.\u003c/p\u003e \u003cp\u003eThe in-hospital mortality of the cohort was 5.7%. Patients who died prior to discharge were more likely to have Diabetes Mellitus (n\u0026thinsp;=\u0026thinsp;12,92.3%), hypertension(n\u0026thinsp;=\u0026thinsp;12,92.3%), a history of current or previous smoking (n-11,84.6%), and to be on treatment for hyperlipidemia (n\u0026thinsp;=\u0026thinsp;10,76.9%) (P- value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, an increased need for mechanical ventilation(n\u0026thinsp;=\u0026thinsp;4,30.8%) and inotropes(n\u0026thinsp;=\u0026thinsp;8,61.5%) was also noted amongst the non-survivors with statistical significance (P- value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A higher BMI and delayed time to presentation was predictive of in-hospital mortality.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Survivors and non-Survivors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall, N\u0026thinsp;=\u0026thinsp;230\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvivors, N\u0026thinsp;=\u0026thinsp;217 (94.3%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon- Survivors, N\u0026thinsp;=\u0026thinsp;13\u003c/p\u003e \u003cp\u003e(5.7%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP- Value\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAGE, Median (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.0 (48.0\u0026ndash;65.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.1 (48.0\u0026ndash;65.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.5 (49.0\u0026ndash;75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEX, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e192 (89.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180 (89.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (92.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChest Pain Duration, Median (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.0 (3.0\u0026ndash;24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.5 (3.0\u0026ndash;24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.0 (24.0\u0026ndash;36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI, Kg/m2 (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.5 (IQR 25.0\u0026ndash;31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.0 (IQR 25.0\u0026ndash;31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.0 (IQR 36.0\u0026ndash;39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDM, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131 (54.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119 (54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (92.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHTN, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111 (51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99 (49.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (92.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (33.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (84.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHyperlipidemia, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130 (60.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 (57.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (76.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKillip, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKillip I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125 (58.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125 (61.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKillip II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (26.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKillip III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKillip IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAngiographic Findings (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon- Obstructive Coronary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle Vessel Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142(61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136(62.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle Vessel Disease - ISRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle Vessel Disease- Stent thrombosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwo Vessel Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (16.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriple Vessel Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCulprit Vessel, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112 (48.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101 (46.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (84.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (30.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (30.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInotropes, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMechanical Ventilation, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIABP, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLOS, Median (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0 (2.0\u0026ndash;3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0 (2.0\u0026ndash;3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0 (0.0\u0026ndash;8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e1: Median (IQR); n (%). 2: Wilcoxon rank sum test; Fischer\u0026rsquo;s exact test; Pearson chi-squared test. BMI: Body Mass Index, DM: Diabetes Mellitus, HTN: Hypertension, LAD: Left Anterior Descending, LCX: Left Circumflex, RCA: Right Coronary artery, IABP: Intra-Aortic Balloon Pump, LOS: Length of Stay\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e below illustrates laboratory investigations for all patients and provides a comparison between survivors and non-survivors. A higher Low-Density Lipoprotein and Triglyceride (TG), with statistical significance (P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05), was noted amongst the non-survivors.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLaboratory investigations and comparison of survivors and non-survivors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOverall, N\u0026thinsp;=\u0026thinsp;230\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSurvivors, N\u0026thinsp;=\u0026thinsp;217 (94.3%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNon- Survivors, N\u0026thinsp;=\u0026thinsp;13\u003c/p\u003e \u003cp\u003e(5.7%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP- Value\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTroponin T, Mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,073.6 (1,558.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,045.5 (1,383.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1,496.4 (3,284.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCKMB, Mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76.2 (88.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75.7 (87.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86.6 (100.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC, Mean (SD), mmol/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.7 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.7 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.4 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL, Mean (SD), mmol/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.8 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.2 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.8 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL, Mean (SD), mmol/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.1 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.0 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG, Mean (SD), mmol/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.8 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.7 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.5 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBA1C, Mean (SD)%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.3 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.3 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.7 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP, Mean (SD) mg/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.4 (111.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70.4 (110.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e136.4 (158.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN, Mean (SD)mmol/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.4 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.4 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.5 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine, Mean (SD)umol/l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.3 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.9 (19.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84.8 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e1: Mean, 2 Wilcoxon rank sum tests. TC: Total Cholesterol, LDL: Low Density Lipoprotein, HDL: High Density Lipoprotein, TG: Triglycerides, CRP: C- Reactive Protein, BUN: Blood Urea Nitrogen.\u003c/p\u003e \u003cp\u003eThe Median Left Ventricular Ejection Fraction (LVEF) was 50.23%, and non-survivors had a lower LVEF when compared to survivors. Only 12 patients (5.6%) of the 213 were noted to have LV thrombus on 2D echocardiography.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e2D Echocardiographic findings prior hospital discharge\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall, N\u0026thinsp;=\u0026thinsp;213\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvivors, N\u0026thinsp;=\u0026thinsp;202\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-Survivors, N\u0026thinsp;=\u0026thinsp;11\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP - Value\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF, Median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.23% (40.1\u0026ndash;60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.6% (45.6\u0026ndash;61.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.5% (31.5\u0026ndash;42.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLV Thrombus, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e1: Median, n (%), 2 Wilcoxon rank sum tests. LV : Left Ventricle, LVEF : Left Ventricle Ejection Fraction.\u003c/p\u003e \u003cp\u003eWe could only retrieve the discharge medication of 217 patients. The majority were discharged on B-blockers (n\u0026thinsp;=\u0026thinsp;163,75.1%), as seen in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e below. Aspirin and Clopidogrel were the most commonly used Dual Antiplatelet Therapy (DAPT)(n\u0026thinsp;=\u0026thinsp;112,51.6%)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDischarge Medications of the study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;217 (100)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB- Blocker, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e163 (75.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACE-i, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67 (30.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARB, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61 (28.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARNI, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25 (11.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMRA, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68 (31.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGLT.2, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44 (20.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDAPT, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u0026thinsp;+\u0026thinsp;Clopidogrel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112(51.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u0026thinsp;+\u0026thinsp;Ticagrelor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49(22.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u0026thinsp;+\u0026thinsp;prasugrel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13(5.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriple antithrombotic Therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36 (16.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e1: n (%). B: Beta, ACE-I: Angiotensin converting Enzyme inhibitor, ARB: Angiotensin Receptor Blocker, ARNI: Angiotensin Receptor Neprilysin Inhibitor, MRA: Mineralocorticoid receptor Antagonist, SGLT-2: Sodium Glucose Transport 2, DAPT: Dual Anti platelet.\u003c/p\u003e \u003cp\u003eA higher mean BMI of 36.2 (\u0026plusmn;\u0026thinsp;5.7) (OR 1.46, 95% CI 1.17\u0026ndash; 2.10), the presence of smoking (OR 41.68, 95% CI 2.60\u0026ndash; 240.71), and the use of mechanical ventilation (OR 77.42, 95% CI 1.95\u0026ndash; 128.89) were factors associated with in-hospital mortality.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with in-hospital mortality.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDependent: OUTCOME\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvivors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon- Survivors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (univariable)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOR (multivariable)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime from chest pain to Presentation(hours)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.5 (3.0\u0026ndash;24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.0 (24.0\u0026ndash;36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.03 (1.00-1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.04 (0.97\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.235\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.8 (\u0026plusmn;\u0026thinsp;5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.2 (\u0026plusmn;\u0026thinsp;5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.24 (1.13\u0026ndash;1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.46 (1.17\u0026ndash;2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e103 (99.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99 (89.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.48 (2.39-229.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.49 (0.35-631.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e141 (98.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61 (84.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11 (15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.71 (3.29\u0026ndash;83.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e41.68 (2.60-240.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInotropes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e195 (97.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (46.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (53.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.57 (12.06-185.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14.22 (0.65-650.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical Ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e197 (95.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.51 (3.80\u0026ndash;78.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e77.42 (1.95-128.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIABP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e201 (94.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.55 (3.27-823.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26.47 (0.03-130.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.570\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriglycerides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.7 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.5 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.94 (1.18\u0026ndash;3.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.33 (0.85\u0026ndash;18.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBMI: Body Mass Index, HTN: Hypertension, IABP: Intra-Aortic Balloon Pump, OR : Odds Ration\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThese data provide an overview of care for patients presenting with STEMI for approximately a decade at a private primary PCI hospital in Tanzania. To our knowledge, this is the first study in the country that systematically describes clinical characteristics, interventions, and outcomes among patients presenting with STEMI.\u003c/p\u003e \u003cp\u003eOur results demonstrate lower in-hospital mortality for patients treated according to recommended guidelines compared to other regional studies from the Ivory Coast(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), Burkina Faso(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), Djibouti(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), Nigeria(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), and Mali(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Our morality rates are comparable to well-resourced centers in Africa(\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), Northern America(\u003cspan additionalcitationids=\"CR27 CR28 CR29\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), and data from national registries of the European Society of Cardiology member countries(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). The lower hospital mortality in our cohort may be attributed to a cohorts younger age, shorter time from onset to presentation, and a high rate of timely intervention and reperfusion strategies available at our institution. However, comparing outcomes across different cohorts may be confounded by many factors; including definitions of disease and outcomes, time to presentation, burden of underlying comorbidities, age and availability of resources and should be made with that in mind.\u003c/p\u003e \u003cp\u003eThe mean age of our cohort is lower than that of western cohorts, but comparable to that of other African series. The age range among various study populations on the African continent with STEMI has consistently been noted to be lower, with a mean age between 55 and 58 years (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). This phenomenon may be due to various genetic factors, higher incidence of various risk factors, and socioeconomic reasons. It should also be noted that our cohort is comprised of mixed ethnicity and is not representative of the native population in Tanzania.\u003c/p\u003e \u003cp\u003eAs noted in the INTERHEART Africa(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) multicentric study, our results continue to highlight the burden of Hypertension, Diabetes Mellitus, Obesity, and hyperlipidemia as the main cardiovascular risk factors associated with STEMI. This analysis further highlights the epidemiological transition in the country, and underscores the importance of intensifying preventive medicine campaigns.\u003c/p\u003e \u003cp\u003eThe time from symptom onset to presentation was lower in our cohort compared to similar studies in the African continent (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). This probably reflects a selection bias, as patients presenting to a private facility tend to be from a higher socioeconomic background and education level. Our facility is also located in an easily accessible area in a major urban center, and this provides an advantage. For this reason, the vast majority of the Tanzanian population are unlikely to enjoy the privilege of timely primary PCI.\u003c/p\u003e \u003cp\u003eLate presentation was a key factor of in- hospital mortality in our cohort. Delays in reperfusion therapy have been clearly linked to poor outcomes (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Timely intervention and Systems of care exploring thrombolysis and referral for invasive assessment have been successfully demonstrated to provide excellent outcomes in developed world and this may be the way forward for many African healthcare systems.\u003c/p\u003e \u003cp\u003eThe lack of PCI-capable hospitals in Africa has made the comparison of angiographic data and intervention rates challenging (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Our study results highlight high and timely reperfusion rates, comparable to rates documented in Northern America (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) and Europe (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Large multi-center registry STEMI studies in South Africa, Ivory Coast, and Kenya have reported variable reperfusion rates ranging between 13\u0026ndash;60%(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNumerous studies have identified low body mass index (BMI) as a predictor of poor outcomes after STEMI, with overweight and obese individuals experiencing more favorable LOS, fewer inpatient complications, and better in-hospital, 30-day, and long-term outcomes(\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), expanding on the concept of the \u0026ldquo;obesity paradox\u0026rdquo; which continues to remain a point of debate to date. Hypotheses that have been postulated to support the obesity paradox in STEMI patients are the higher metabolic reserve and increased development of collaterals (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Our results are contrary to the aforementioned reports and associate a higher BMI with an increase in in-hospital mortality and this could be related to the small size of our population. The aim of the study was beyond exploring this relationship. Nonetheless, obesity in Tanzania continues to be a growing pandemic (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e) and a precursor of other cardiovascular risks factors such as diabetes mellitus, hypertension, and hyperlipidemia. Obesity is also a state of chronic inflammation (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e) and a factor of poor functional status(\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). This collective association could account for poor hospital outcomes among patients with obesity in our cohort. Nonetheless, it is important to note that the obesity paradox is still a subject of ongoing research, and not all studies agree on its existence; thus, it should not overshadow the risks associated with obesity.\u003c/p\u003e \u003cp\u003eOur study also highlighted smoking as the main factor of in hospital mortality among patients with STEMI. Similarly, various reports have also indicated the presence of \u0026ldquo;smokers\u0026rsquo; paradox,\u0026rdquo; suggesting favorable outcomes among smokers than non-smokers(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). This association is intriguing, counterintuitive, and may be misleading because several epidemiological studies have clearly attributed smoking as an independent risk for atherosclerosis, heart failure, premature ASCVD, and death(\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). This paradox is largely attributed to the younger age as smokers may develop an acute myocardial infarction a decade earlier than non-smokers and thus tend to have fewer cardiovascular comorbidities(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e).It has also been postulated that smoking might exert protective effects and could reduce infarct size, a strong predictor of poor outcomes among patients with STEMI(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), suggesting greater responsiveness to spontaneous or therapeutic thrombolysis. Furthermore, smoking activates the cytochrome system, an enzyme responsible for converting Clopidogrel, a common antiplatelet, from its prodrug to its active form, thereby increasing its antiplatelet effect (Field, (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). It is, however, crucial to understand that the harmful effects of smoking on the cardiovascular system outweigh any potential short-term advantages observed in a few studies. Just like the obesity paradox, the smoking paradox is still evolving and remains an area of discussion and ongoing research.\u003c/p\u003e \u003cp\u003ePatients with STEMI requiring mechanical ventilation during admission or hospitalization often face a more complicated clinical course. Approximately 20% of patients with STEMI typically experience respiratory impairment due to acute heart failure (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e), with prior studies indicating half of this group to require invasive mechanical ventilation during their hospital stay, forming a very high-risk subgroup (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Our study results are parallel to published reports indicating an increase in the risk of death among those needing mechanical ventilation. Additionally, prolonged mechanical ventilation has been associated with the development of ventilator-associated pneumonia, need of inotropes, and IABP, which collectively increase the risk of in-hospital mortality(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eOur study has several key limitations: this was a single-center study from a private urban teaching and referral University Hospital, so findings cannot be generalized nationwide. Single-center studies also risk institutional and patient selection bias. Furthermore, as expected, retrospective design is inclined to miss data. Nonetheless, we tried to extract as much as possible from medical records and databases available for consentient statistical analysis. Additionally, we were not able to accurately collect data or analyze specific timings related to outcomes among patients with STEMI, such as door-to-ECG timing and door-to-procedure timing, which have significant prognostication value.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWe present a decade of descriptive summary of patients who presented with STEMI at a teaching university Hospital in Tanzania. Our study demonstrates a low in-hospital mortality rate of 5.7% among patients with STEMI. Cigarette smoking, obesity and the need for mechanical ventilation were predictors of poor outcomes. Large prospective, multicenter registry studies are needed to understand the magnitude of the syndrome and better highlight areas of improvement.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cul\u003e\n \u003cli\u003eACS: Acute Coronary Syndrome\u003c/li\u003e\n \u003cli\u003eSSA: Sub- Saharan Africa\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSTEMI: ST- Elevation Myocardial Infarction\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eNSTEMI: Non- ST Elevation Myocardial infarction\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLMICs: Low Middle Income Countries\u003c/li\u003e\n \u003cli\u003eCVD: Cardiovascular Disease\u003c/li\u003e\n \u003cli\u003eNCD: Non-Communicable Diseases\u003c/li\u003e\n \u003cli\u003eCAD: Coronary Artery Disease\u003c/li\u003e\n \u003cli\u003eJCI: Joint Commission International\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eNCDR: National Cardiovascular Data Registry\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eACC: American College of Cardiology\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCCU: Coronary Care Unit\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAHA: American Heart Association\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePCI: Percutaneous Intervention\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eASE: American Society of Echocardiography\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLVEF: Left Ventricular Ejection Fraction\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePCI: Percutaneous Coronary Intervention\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and consent to participate \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was presented to the section of cardiology of the Aga Khan Hospital Dar es Salaam.\u0026nbsp;The study was approved by the Aga Khan University, East Africa Ethical Research Committee (AKU, EA ERC). The National Institute for Medical Research (NIMR) in Tanzania mandates the AKU, EA ERC to approve health research conducted by Tanzanian students. The hospital\u0026rsquo;s ethical committee and the AKU, EA, and ERC exempted the primary investigator from acquiring informed consent from the study participants since the study design was purely based on extracting data from the hospital registrar and did not affect the rights and welfare of the patients. This study was conducted in accordance with the Declaration of Helsinki. Reference (AKU/2023/018/fb/04/02).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no conflict on interest in this work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no funding for this research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors made an important and substantial contribution to the conception, study design, execution, acquisition of data, analysis, interpretation and implementation. All authors equally contributed in writing, revising, and critically revising the article. All authors approved the final document to be published and agreed to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe want to thank the medical records and the section of cardiology of the Aga Khan hospital, Dar -es- Salaam for their support in the successful completion of the research.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMinja NW, Nakagaayi D, Aliku T, Zhang W, Ssinabulya I, Nabaale J, et al. Cardiovascular diseases in Africa in the twenty-first century: Gaps and priorities going forward. Front Cardiovasc Med. 2022;9:1008335.\u003c/li\u003e\n\u003cli\u003eChillo P, Mashili F, Kwesigabo G, Ruggajo P, Kamuhabwa A. 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Angiology. 2009;60(2):164-8.\u003c/li\u003e\n\u003cli\u003eSamper-Ternent R, Al Snih S. Obesity in Older Adults: Epidemiology and Implications for Disability and Disease. Rev Clin Gerontol. 2012;22(1):10-34.\u003c/li\u003e\n\u003cli\u003eRedfors B, Furer A, Selker HP, Thiele H, Patel MR, Chen S, et al. Effect of Smoking on Outcomes of Primary PCI in Patients With STEMI. J Am Coll Cardiol. 2020;75(15):1743-54.\u003c/li\u003e\n\u003cli\u003eJee Y, Jung KJ, Lee S, Back JH, Jee SH, Cho SI. Smoking and atherosclerotic cardiovascular disease risk in young men: the Korean Life Course Health Study. BMJ Open. 2019;9(6):e024453.\u003c/li\u003e\n\u003cli\u003eKouraki K, Schneider S, Uebis R, Tebbe U, Klein HH, Janssens U, et al. Characteristics and clinical outcome of 458 patients with acute myocardial infarction requiring mechanical ventilation. Results of the BEAT registry of the ALKK-study group. Clin Res Cardiol. 2011;100(3):235-9.\u003c/li\u003e\n\u003cli\u003eAnsari MI, Umair M, Taimoor L, Memon AR, Abubaker Z, Arif MS, et al. Mechanical ventilation in acute myocardial infarction: Outcomes from a prospective audit at a cardiovascular hospital in Pakistan. PLoS One. 2023;18(8):e0290399.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4514601/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4514601/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIschemic Heart Disease (IHD) is an emerging epidemic in sub-Saharan Africa (SSA). Despite the true burden underestimated in the African continent, it remains the leading cause of death among adults aged above 60 years. ST-Segment Elevation Myocardial Infarction (STEMI) is a clinically time-sensitive fatal sequela of IHD with timely reperfusion by primary Percutaneous Coronary Intervention (PCI) considered the gold standard of care. Tanzania has witnessed a gradual and continued development in the ability to provide coronary care and a simultaneous increase in risk factors associated with IHD. There is paucity of available data in the country.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis single-center retrospective study was conducted at the Aga Khan Hospital Dar-es-Salaam (AKHD), Tanzania. The AKHD is one of the pioneers in establishing the first cardiac catheterization laboratory in the nation. The current study involved extracting relevant data of all patients who presented with STEMI from August 2014 to December 2023. Descriptive statistics were used to define the population. Patient’s outcomes were based on hospital survival. Binary logistic regression was run (at 95% CI and \u003cem\u003ep\u003c/em\u003e-value \u0026lt; 0.05) to identify the determinants for in-hospital mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e230 patients were included in the final analysis. The cohort was predominantly male (n=192,83.5%), with a median age was 55.0 years (IQR 48.0-65.0). Most patients presented with chest pain (n=162,72.6%), with a median duration of 12.2 hours (IQR 3.0-24.0 hours). The left Anterior descending (LAD) artery was the culprit vessel in most cases (n=112,48.7%). A total of 163(70.8%) patients underwent Primary-PCI. The in-hospital mortality of the cohort was 5.7%. When survivors and non-survivors were compared, a higher percentage of non-survivors were diabetic (n=12,92.3%), hypertensive (n=12,92.3%) and having a history of cigarette smoking(n=11,84.6%) (P- value \u0026lt;0.05). A higher mean BMI of 36.2 (±5.7) (OR 1.46, CI 1.17– 2.10), the presence of smoking (OR 41.68, CI 2.60– 240.71), and the need for mechanical ventilation (OR 77.42, CI 1.95– 128.89) were factors associated with in-hospital mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study results demonstrate lower in-hospital mortality for STEMI patients compared to other regional studies. Cigarette smoking, obesity and the need for mechanical ventilation were predictors of poor in-hospital outcomes.\u003c/p\u003e","manuscriptTitle":"ST-Segment Elevation Myocardial Infarction (STEMI): A 10-year Review form a primary PCI capable hospital in Tanzania","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-30 09:13:57","doi":"10.21203/rs.3.rs-4514601/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0525cee4-f195-4a83-b97d-9e5c14d17d02","owner":[],"postedDate":"July 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-13T13:38:04+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-30 09:13:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4514601","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4514601","identity":"rs-4514601","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}