In hospital mortality and associated factors among patients admitted with myocardial infarction at public referral hospitals, Bahir Dar, Ethiopia, 2023. A multicenter three years, retrospective cross-sectional study

In hospital mortality and associated factors among patients admitted with myocardial infarction at public referral hospitals, Bahir Dar, Ethiopia, 2023. A multicenter three years, retrospective cross-sectional study | 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 Article In hospital mortality and associated factors among patients admitted with myocardial infarction at public referral hospitals, Bahir Dar, Ethiopia, 2023. A multicenter three years, retrospective cross-sectional study Tadele Demilew, Yihealem Yabebal, Wubet Hunegnaw, Yeshambel Agumas, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5325801/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 : The prevalence of ischemic heart disease is increasing in Sub Saharan Africa countries, but adequate data are lacking regarding the in hospital mortality and associated factors. Objective: To assess the magnitude of in hospital mortality due to myocardial infarction and associated factors among hospitalized patients at two public referral hospitals, Bahir Dar, Ethiopia, 2023. Methods : Institution based retrospective cross-sectional study was conducted, using sample size of 317, among patients who were hospitalized between November 2020 to December 2023 due myocardial infarction in two public referral hospitals at Bahir Dar, Ethiopia. Pre-developed check list were used to extract data from the medical registry. Data were entered using Epidata Manager Version 4.6 and analyzed using SPSS version 27. Multivariate logistic regression analysis was used, considering with a p-value of <0.05 as statically significant, with a 95% confidence interval. Result . The in-hospital mortality rate was 21.5% (95% CI: 16.6, 25.9). Age greater than 65 (AOR 6.85, 95% CI 1.58-29.71), presence of diabetes mellitus (AOR 7.02; 95% CI 2.47-19.91), high level of serum troponin (AOR=9.98; 95% CI: 4.06-24.53), elevated serum creatinine (AOR=4.21, 95% CI-1.47-12.08), higher Killip class (AOR-15.52, 95% CI: 5.19-46.46),and STEMI (AOR=5.75; 95% CI-1.66-19.87) were factors associated with in hospital mortality due MI. Conclusion and recommendation : The in-hospital mortality due MI was found to be high and it was associated with advanced age, high Killip class, STEMI, high serum troponin, diabetes mellitus and high serum creatinine. Addressing these major factors and effective preventive tools are required to reduce this burden. Health sciences/Cardiology Health sciences/Diseases Health sciences/Medical research Cardiovascular disease Myocardial infarction Mortality Sub Sahara Africa Background Myocardial infarction (MI) is the death of myocardial cells due to prolonged interruption of blood flow. It is a syndrome with a diagnostic criterion, having combination of symptoms, electrocardiographic changes, and elevated cardiac biomarkers at least one value above the 99th percentile from the reference range. The presence of myocardial ischemia can be demonstrated by new ischemic ECG findings and imaging evidence of loss of viable myocardium or new regional wall motion abnormality. An occluding thrombus may also be seen by angiography or autopsy [1]. Globally ischemic heart disease (IHD) is the leading cause of morbidity and mortality affecting 126.5 million people in 2017 [2]. In developed countries, acute coronary syndrome (ACS) related mortality has reduced in the last decades. However, the mortality trend is increasing in African countries [3]. In Africa, ACS incidence and mortality is rising due to an increase in cardiovascular risk factors including hypertension, diabetes and ageing of population [4]. Additionally, most of the hospitals provide low quality care due to limited resources such as lack of fibrinolytic medication, catheterization center and adequately trained physician [5]. This problem is very grave in the rural areas of Africa [6]. In a meta-analysis conducted in Africa, which included 29 studies and 11,788 participants, the overall estimated in-hospital death rate was 22%. The death rate was higher in those who were treated in referral hospitals (24%) compared to those who were treated in cardiac centers (14%) [7]. There are various factors presumed to affect the in-hospital mortality of myocardial infarction. But, the association of these factors with the fatality of MI is variable in different studies. Some of the factors include; the time of presentation of patients from onset of illness, the type of MI, the availability of invasive interventions, age of patients, gender, area of residency, and presence of comorbidities and post MI complication [8–14]. Despite the increase in morbidity and mortality due MI in Sub Sahara African countries, the in-hospital mortality and factors associated with it was not studied well using large sample size. In addition, this study conducted in setting where there are no invasive cardiac interventions including fibrinolytics and PCI. METHODS AND MATERIALS Study area and study period The study was conducted at two public referral hospitals, Tibebe Ghion Specialized Hospital (TGSH) and Felege Hiwot Comprehensive Specialized Referral Hospital (FHCSRH), of Bahir Dar city, Ethiopia. These hospitals are located in Bahir Dar city Amhara region, 578km from the capital city, Addis Ababa. Both are tertiary-level teaching and referral hospitals that serve as the referral center for more than 15 district hospitals in the area, catering to a total catchment of 7 million people. Each hospital has more than 500 beds and offers health services to patients with various diseases in the outpatient and inpatient departments. The cardiac unit provides clinical service including, thrice a week trans-thoracic echocardiography session by cardiologist and it provides diagnostic tests and treatments for cardiac patients. ECG and cardiac biomarkers, such as highly sensitive cardiac troponin (hs-cTn), lipid panel, liver and renal function test, serum electrolyte and random blood sugar. The cardiac clinic has 03 rooms and currently there are 06 nurses and 9 physician including medical residents, internist, 04 cardiologists and 01 interventional cardiologist who are working there. However, both hospitals don’t provide fibrinolytics and invasive procedure including PCI and CABG. The study was conducted among MI patients who were admitted to the two public referral hospitals of Bahir Dar between November 2020and December 2023 GC. Study design and population Institution based retrospective cross-sectional study was conducted from November 2023 to December 2023 at FHCSRH and TGSH, Bahir Dar, Ethiopia. The study populations were all MI patients who were admitted to TGSH & FHCSRH during November 2020 to December 2023. All patients who were above 18 years old and had clinical, cardiac troponin, ECG, and echocardiography evidence of MI by cardiologist were included in the study. Patients without proper ECG and echocardiography (not done & interpreted by cardiologist), those with advanced malignancy and cirrhosis and those with incomplete medical record were excluded from this study. Sample size and sampling procedure The sample size was calculated using the single population proportion formula with the following assumptions: a confidence level of 95%, a 5% margin of error, and a prevalence of 27.4 % from a previous study [9]. With these assumptions the sample size was calculated to be 306 and adding 10% for incomplete data the total sample size was 337. There were 450 patients who were admitted to the two public hospitals between November 2020 and December 2023 and all eligible patients, only 317 patients found to be eligible, were included in this study. Study variables The dependent variable was the presence of in hospital mortality due MI. The independent variables include Socio-demographic variables (age, gender, area of residence, time of arrival of patients to hospital since symptom onset, presenting complaint), comorbidities (diabetes, hypertension, dyslipidemia, alcohol, smoking), clinical factors (STEMI, NSTEMI, killip class), type of management (aspirin (ASA), clopidogrel, beta blocker, unfractionated heparin (UFH), ACE inhibitors, statin, diuretics, thrombolytic, PCI). Data collection procedure The registration books at TGSH and FHCSRH emergency, medical ward and medical ICU were revised to get the hospital chart numbers of MI patients who were admitted during November 2020 to December 2023. After getting their chart numbers, patient charts were retrieved from record and documentation office. These data were accessed and data were collected at documentation office from November 2023 to December 2023. Medical information was collected from patients’ medical records by a trained medical doctor under close supervision by the principal investigator using pretested questionnaire. From the medical record socio-demographic, clinical, laboratory and imaging data were obtained. Data processing and analysis The data were entered into EPI data version 4.6 and then transferred to SPSS 27.0 statistical packages for analysis. Data cleaning was conducted before performing the descriptive analysis. The baseline characteristics are presented as numbers and percentages. The findings were summarized in tables and figures. All statistical tests were performed using two-sided tests at the 0.05 level of significance. Odds ratio with 95 % confidence intervals and associated p-values were computed to assess the presence and degree of association between dependent and independent variables. Variables with p values < 0.25 in the bivariate analysis were transferred to multivariate analysis and entered hierarchically to fit the logistic regression model. Statistically significant associations were determined based on the adjusted odds ratio (AOR) with its 95% CI and the P-value <0.05. Hosner-Lemeshow test was used to assess model fitness and multicollinearity test was conducted to check the absence of correlation between independent variables. Operational definitions For the purpose of this study myocardial infarction was defined as detection of a rise and/or fall of high-sensitivity cardiac troponin (hs-cTn) with at least one value above the 99th percentile and with at least one of the following: symptoms of acute myocardial ischemia, new ischemic electrocardiographic (ECG) changes, development of pathological Q waves and Imaging evidence of new loss of viable myocardium or new regional wall motion abnormality in a pattern consistent with an ischemic etiology[1]. Sgarbossa criteria: an ECG criterion used to diagnose acute myocardial infarction in patient with previous LBBB and has 3 criteria: ST segment elevation of 1 mm or more that was in the same direction (concordant) as the QRS complex in any lead-score 5, ST segment depression of 1 mm or more in any lead from V1 to V3-score 3, and ST segment elevation of 1 mm or more that was discordant with the QRS complex (that is associated with a QS or RS complex) score 2 [15]. KILLIP class: Killip class of the patient at the time of hospital admission based on physical examination: Class 1: no evidence of heart failure, Class 2: findings consistent with mild to moderate heart failure (S3 gallop, lung rales < half way up the posterior lung fields, jugular venous distension), Class 3: overt pulmonary edema, Class 4: cardiogenic shock [16]. In-hospital mortality: patients who died during their hospital stay due MI. Conventional cardiovascular risk factors: refer to smoking, hypertension, diabetes and dyslipidemia. Cigarette smoking: smoked more than 100 cigarettes in their life-time [17]. Alcohol drinking: consumption of more than 3 standard drinks daily (for males) or 2 standard drinks daily (for females) [18]. RESULTS Sociodemographic and clinical characteristics A total of 317 patients were included in this study. As depicted in table 1, most of the participants were males (226, 71.3%), from urban areas (200, 63.1%). The mean age of participants was 61.24 years [SD ± 11.90 years]. More than a quarter of patients i.e., 87 (27.4%) were aged above 65 years. The average time of arrival since symptom onset was 3.18 days [SD ± 2.42 days]. Cardiac pain is the most common presenting complaint accounting for 70.3% (223) while possibly cardiac pain and likely non cardiac pain constitute 28.1% (89) and 1.6% (5) of cases respectively. The average duration of hospitalization was 6.62 days [SD ± 3.25 days]. The maximum hospital stay was 3 weeks. Among comorbidities, hypertension was the most common comorbidity accounting for 38.6 % (122), followed by DM 23.7% (75). Among DM patients, 87% of them had poor glycemic control. Other comorbidities included dyslipidemia (13.7%), alcohol (9.8%), smoking (5.4%) and family history of MI (1.6%). Table 1. Socio-demographic variables of MI patients in TGSH and FHCSRH, Bahir Dar, Ethiopia, 2023. Category Variables Outcome No Death Death N % N % Age in years less than 55 years 59 23.7% 6 8.8% 55 to 65 years 137 55.0% 28 41.2% greater than 65 years 53 21.3% 34 50.0% Gender Male 183 73.5% 43 63.2% Female 66 26.5% 25 36.8% Area of residence Urban 160 64.3% 40 58.8% Rural 89 35.7% 28 41.2% Presenting complaint Cardiac pain 185 74.3% 38 55.9% Possibly cardiac pain 59 23.7% 30 44.1% Likely non cardiac pain 5 2.0% 0 0.0% Time since symptom onset in hours less than 12 hrs 111 44.6% 26 38.2% 12 to 48 hrs 109 43.8% 35 51.5% greater than 48 hrs 29 11.6% 7 10.3% Previous history of MI Yes 8 3.2% 3 4.4% No 239 96.8% 65 95.6% Family history of MI Yes 5 2.0% 0 0.0% No 244 98.0% 68 100.0% DM Yes 42 16.9% 33 48.5% No 207 83.1% 35 51.5% Hypertension Yes 101 40.6% 21 31.3% No 148 59.4% 46 68.7% Dyslipidaemia Yes 33 13.4% 10 14.7% No 214 86.6% 58 85.3% Alcoholic Yes 23 9.3% 8 11.8% No 225 90.7% 60 88.2% Smoking Yes 13 5.2% 4 6.0% No 235 94.8% 63 94.0% DM: Diabetes Mellitus, MI: Myocardial Infarction Laboratory and imaging parameters All the patients were in cardiac ICU on continuous ECG monitoring throughout their hospital stay and the majority of patients (66.2%, 210) have STEMI whereas 107 (33.8%) patients have NSTEMI. As depicted in table 2, Killip classes I and II categories of MI combined constitute 59.6% of all patients. The remaining 40.4% of patients have Killip classes III and IV combined. Cardiac highly sensitive troponin was measured in all patients at admission and 21.1% of patients had serum troponin levels above 5000 ng/ml. Urinalysis is done for 261(82.33%) of cases and 49(18.8%) of them have proteinuria. Serum total cholesterol was done in 119 patients and 90 (75.6%) of them have elevated total cholesterol. Serum triglyceride level was determined in 129(39.4%) of patients and 105 (84%) of them have hypertriglyceridemia. Likewise, serum HDL level was analyzed for 117 patients and 36(30.8%) of them have reduced level of HDL. LDL was also done for 131 patients and 71(54.2%) of them have elevated levels of LDL. The level of serum creatinine of patients was determined in 98% of patients and 44 (13.9%) of them had elevated serum creatinine. Echocardiographic assessment of left ventricular function was done in 98% of patients and 71.1% of them have reduced ejection fraction while 28.9% have preserved ejection fraction. Table 2. Laboratory, imaging and Killip class of MI patients in TGSH and FHCSRH, Bahir Dar, Ethiopia, 2023 Category Variables Outcome No Death Death Number % Number % ECG STEMI 148 59.4% 62 91.2% NSTEMI 101 40.6% 6 8.8% Cardiac troponin in ng/ml < 5000 227 91.2% 20 29.4% ≥5000 22 8.8% 48 70.6% Serum creatinine in mg/dl Normal 231 92.8% 42 61.8% Elevated 18 7.2% 26 38.2% Urinalysis Proteinuria 35 17.1% 14 25.0% No Proteinuria 170 82.9% 42 75.0% Total cholesterol in mg/dl < 200 78 77.2% 12 66.7% ≥200 23 22.8% 6 33.3% Triglyceride in mg/dl < 150 87 81.3% 18 100.0% ≥150 20 18.7% 0 0.0% LDL-C in mg/dl < 100 62 55.4% 9 47.4% ≥100 50 44.6% 10 52.6% HDL-C in mg/dl < 40 32 31.4% 4 26.7% ≥40 70 68.6% 11 73.3% LV Ejection fraction Reduced 166 66.9% 55 87.3% Preserved 82 33.1% 8 12.7% Killip class class I and II 177 71.1% 12 17.6% class III and IV 72 28.9% 56 82.4% ECG: Electrocardiography, HDL-C: High Density Lipid-Cholesterol, LDL-C: Low Density Lipid-Cholesterol, LV: Left Ventricle Medications parameters The available medications in the set up for guideline directed treatment of MI is given in majority of patients with the exception of reperfusion therapies i.e., both fibrinolytics and PCI which were not available in the study setting and study period. Dual anti platelets (ASA and clopidogrel) were given for 99.4% of patients. As depicted in table 3, ASA, anticoagulant and statins were provided for all patients (100%). Beta blockers were given for 92.4 % and ACEi for 41%. Mineralocorticoid receptor antagonists and diuretics were given for 7.3% and 55.5% of patients respectively. The provision of diuretics was dependent on the presence of heart failure and its severity as per Killip class while the others were mainly dependent on the presence or absence of contra indications for the specific medication. Table 3. Medications provided to MI patients of TGSH and FHCSRH Bahir Dar, Ethiopia, 2023. Medications Outcome No Death Death N % N % Clopidogrel Yes 245 98.4% 66 97.1% No 4 1.6% 2 2.9% Beta blocker Yes 238 95.6% 55 80.9% No 11 4.4% 13 19.1% ACEi/ARBS Yes 117 47.0% 13 19.1% No 132 53.0% 55 80.9% Mineralocorticoid receptor antagonist Yes 21 8.5% 2 3.0% No 226 91.5% 64 97.0% Diuretic Yes 116 46.6% 60 88.2% No 133 53.4% 8 11.8% ACEi: Angiotensin Converting Enzyme inhibitor, ARBS: Angiotensin Receptor Blocker In hospital mortality and post MI complications The overall in hospital mortality of MI patients was 21.5% (95% CI: 16.6, 25.9 ) . As depicted in table 4, cardiogenic shock is the most common cause of death accounting for 73.5% of the total deaths. Fatal arrhythmias account for the second most common immediate cause of death which occurs in 17(25%) of deaths. Thromboembolism is the presumed cause of death in 1 patient. From survivors of myocardial infarction, the most common sequel was persistent left ventricular dysfunction (LV dysfunction) which occurred in 74% of patients, depicted in table 5. Left ventricular thrombus and non-fatal thromboembolism occurred in 6.9% and 5.7% of patients respectively. Other associated post MI sequels on top of the listed ones include diastolic dysfunction, post MI pericarditis with pericardial effusion and left ventricular aneurysms. Table 4. Immediate causes of death among MI patients in TGSH and FHCSRH, Bahir Dar, Ethiopia, 2023. Death Percent of Cases N % Immediate causes of death Arrhythmia 17 25.0% 25.0% Cardiogenic shock 50 73.5% 73.5% Thromboembolism 1 1.5% 1.5% Total 68 100.0% 100.0% Table 5. Post MI complications of patients in TGSH and FHCSRH, Bahir Dar, Ethiopia, 2023 No death Number Percent (%) Post MI Sequels Persistent LV dysfunction 194 74.0% Mitral regurgitation 31 11.8% LV thrombus 18 6.9% Non-fatal thromboembolism 15 5.7% Re-infarction 4 1.5% Total 262 100.0% LV: Left Ventricle, MI: Myocardial Infarction Factors associated with in hospital mortality in MI The association between independent and dependent variable, in hospital mortality was assessed using both univariable and multivariable logistic regression. On univariable logistic regression LVEF, age, diabetes, MI type, Hs-cTn level, serum creatinin and Killip class found to be associated with in hospital mortality due MI. All the factors associate with p value of 65years (p=0.01), diabetes presence (p=5000ng/ml (p=<0.001), elevated serum creatinin (p=0.007) and Killip class III and IV were found to be statically significant independent factors of in hospital mortality due MI with p value of <0.05 as depicted in the table 6. Those who aged above 65 years were 6.8 time more likely to have in hospital mortality due MI compared to those who age <55 years (AOR=6.85, 95% CI: 1.58-29.71, p=0.01). Similarly, those with STEMI were 5.7 time more likely to have in hospital mortality due MI compared to NSTEMI (AOR=5.75, 95% CI: 1.66-19.87, P=0.006). In addition, those who had high serum creatinin were 4.2 times more likely to have in hospital mortality due MI compared to those who had low serum creatinin (AOR=4.21, 95%CI 1.47-12.08, p=0.007) Participants with serum troponin level > 5000 ng/ml had 9.9 time more likely to have in hospital mortality due MI compared to those who had <5000ng/ml (AOR= 9.98, 95% CI 4.06-24.53, p=<0.001). Further more patients with diabetes were 7 times more likely to have in patient mortality due MI compared to non diabetic patients (AOR=7.02, 95% CI 2.47-19.91, p=<0.001). Finally participants with Killip class III and IV were 15 time more likely to have in hospital mortality compared to those who with Killip class I and II (AOR=15.52, 95%CI 5.19-46.46, p=<0.001). DISCUSSION The in-hospital mortality of myocardial infarction in this study was 21.5% (95% CI: 16.6, 25.9). This prevalence is similar outcome compared to other previously conducted studies in Kenya (20.0%), Nigeria (21.4%), Egypt (19.6%) and a meta-analysis in Africa (22%)[7, 19-21]. This study has showed a higher in hospital mortality compared to other previous studies conducted in Egypt (1.8%), Sweden (4%), Portugal (6.9%) and Israel (10.4%)[22-24]. The main reason for this difference was most of the patient present late and the setting has no setup for intervention including PCI, thrombolytic and CABG which will significantly affect the outcome. In contrast this study has a lower in hospital mortality compared to previous studies conducted in Senegal (28.0%), Tunisia (71.6%) and Mali (100%) [25-27]. The possible reason for this variation was difference in sample size and patient characteristics, particularly type of MI representation. Those who age >65 years were more likely to have in hospital mortality due MI compared to those aged <55 years. This result is in line with studies conducted previously [28, 29]. Elderly patients are more likely to have comorbidity including diabetes, heart failure, prior MI [30]. Table 6.Bivariate and multivariate logistic regression analyses of factors associated with in hospital mortality in MI at TGSH & FHCSRH, Bahir Dar, Ethiopia, 2023. Categor y Variable s Death due M I Bivariate analysis Multivariate analysi s No deat h N (%) Death N (% ) COR(95% CI ) AOR(95%CI ) P valu e Age in years 65 59(23.7%) 137(55%) 53(21.3%) 6(8.8%) 28(41.2%) 34(50%) 1.00 2.01(0.79-5.10) 6.30(2.45-16.21) 1.00 2.01(0.79-5.10) 6.85(1.58-29.71) - 0.13 0.01 * Diabetes Presence Yes No 42(16.9%) 207(83.1%) 33(48.5%) 35(51.5%) 4.64(2.60-8.29) 1.00 7.02(2.47-19.91) 1.00 <0.001 * - MI type STEMI NSTEMI 148(59.4%) 101(40.6%) 62(91.2%) 6(8.8%) 7.05(2.93-16.92) 1.00 5.75(1.66-19.87) 1.00 0.006 * - Hs-cTn (ng/ml) < 5000 ≥ 5000 226(90.8%) 23(9.2%) 24(35.3%) 44(64.7%) 1.00 18.01(9.34-34.74) 1.00 9.98(4.06-24.53) - <0.001 * LVEF Reduced Preserved 166(66.9%) 82(33.1%) 55(87.3%) 8(12.7%) 3.39(1.54-7.46) 1.00 1.07(0.31-3.70) 1.00 0.90 - Serum creatinin Normal Elevated 231(92.8%) 18(7.2%) 42(61.8%) 26(38.2%) 1.00 7.94(4.00-15.76) 1.00 4.21(1.47-12.08) - 0.007 * Killip class Class I to II Class III to IV 177(71.1%) 72(28.9%) 12(17.6%) 56(82.4%) 1.00 11.47(5.80-22.66) 1.00 15.52(5.19-46.46) - <0.001 * *Statically significant, AOR: Adjusted Odds Ratio, CI: Confidence Interval, COR: Crude Odds Ratio, LVEF: Left Ventricular Ejection Fraction D iscussion The in-hospital mortality of myocardial infarction in this study was 21.5% (95% CI: 16.6, 25.9). This prevalence is comparable to other previously conducted studies in Kenya (20.0%), Cote D'ivoire (20.7%), Egypt (19.6%) and a meta-analysis in Africa (22%) [7, 19-21]. This study has showed a higher in hospital mortality compared to other previous studies conducted in Egypt (1.8%), Sweden (4%), Portugal (6.9%) and Israel (10.4%) [22-24]. The main reason for this difference was most of the patient present late and the setting has no setup for intervention including PCI, thrombolytic and CABG which will significantly affect the outcome. In contrast, this study has a lower in hospital mortality compared to previous studies conducted in Senegal (28.0%), Tunisia (71.6%) and Mali (100%) [25-27]. The possible reason for this variation was the difference in sample size and patient characteristics, particularly type of MI representation. Those who age >65 years were more likely to have in hospital mortality due MI compared to those age <55 years. This result is in line with studies conducted previously [28, 29]. Elderly patients are more likely to have comorbidity including diabetes, heart failure and prior MI [30]. Diabetes patients were more likely to have in hospital mortality due MI compared to non-diabetic patients. Similar outcome has been seen in other studies [13, 31]. The possible explanation may be diabetes patients are more likely to have more comorbidity and complication [32]. Patients diagnosed with STEMI were more likely to have in hospital mortality compared to NSTEMI. This result is in line with a meta-analysis conducted in Ethiopia [33]. However, the CZECH-2 registry in central European country study showed that the rate of mortality was higher in patients with NSTEMI (8.4% for NSTEMI patients, 7.3% for STEMI patients) [34]. The observed difference may be due to majority of the participant in our study had STEMI (66.2%). Participants who had high serum cardiac troponin level had high in hospital mortality due MI compared to those who had low serum cardiac troponin level. Similar outcome has been seen in the GUSTO-IIa trail (Global Use of Strategies to Open Occluded Coronary Arteries in Acute Coronary Syndromes) [35, 36]. The level of troponin was higher in this study compared to the GUSTO-IIa study. This may be due to the provision of reperfusion and early arrival of patients in GUSTO-IIa in contrast to no reperfusion and delayed arrival of patients in this study. This study also dictates that patients with acute renal injury had higher in-hospital mortality due MI compared to those with no renal failure. This result is in line with previous studies conducted [12, 14]. The increased mortality in patients with renal failure may indicate the severity of MI as a component of multi-organ failure. It may also signify the presence of reduced dosage or complete preclusion of some medications due to contraindications from renal failure [14]. Participants with Killip class III and IV were associated with a higher in-hospital mortality compared to Killip classes I and II. Similar association was seen in previous studies [37-39]. The possible explanation could be patients with a higher Killip class had more likely to have severe form of MI and more complication [14]. Strength and limitations of this study To our knowledge this study is the first study to assess the in hospital mortality of MI at Amhara region, Ethiopia. Another strength of this study is, it comprises a relatively large sample size compared to other Sub Sahara African country studies. However, this study was a retrospective study and patients long term outcome were not studied. Conclusions and recommendations Despite an attempt made by Ethiopian minster of health to reduce cardiovascular related mortality, the in-hospital mortality of myocardial infarction in Bahir Dar public referral hospitals was 21.5% (95% CI: 16.6-25.9 ) . Age above 65, presence of diabetes mellitus, STEMI, higher levels of cardiac troponin, Killip class III or IV and having elevated serum creatinine were significant factors associated with increased in hospital mortality due MI. Much efforts have to be made to solve the factors associated with in hospital mortality due MI. Particularly, greater attention has to be given for elderly, those with comorbidity including diabetes mellitus and acute kidney injury. In addition, early intervention is required for those with STEMI, high serum troponin and high Killip class. Further research is needed with a larger sample size and cohort study to ensure representativeness and investigate the association between in hospital mortality due MI and factors that affects it. Abbreviations ACEi=Angiotensin Converting Enzyme inhibitor, ACS=Acute Coronary Syndrome , AMI=Acute Myocardial Infarction, ASA=Aspirin, CVD=Cardiovascular Disease, DM=Diabetes Mellitus, ECG=Electrocardiography, FHCSRH=Felege Hiwot Comprehensive Specialized Referral Hospital, HDL=High Density Lipoprotein, HTN=Hypertension, IHD= Ischemic Heart Disease, LDL=Low Density Lipoprotein, LV=Left Ventricle, MI=Myocardial Infarction, PCI=Percutaneous Coronary Intervention, NSTEMI=Non ST Elevation Myocardial Infarction, SSA=Sub Saharan Africa, STEMI=ST Elevation Myocardial Infarction, TGSH=Tibebe Ghion Specialized Hospital, UFH=Unfractionated Heparin Declarations Ethical considerations This study was conducted according to the declaration of Helsinki. Ethical clearance was approved by the Research Ethical Review Board of Collage of Medicine and Health Science, Bahir Dar University (Protocol number 807/2023) and informed written consent was taken from all participants. Patient data confidentiality was respected at all levels, including chart retrieving and data analysis, which was handled by the investigators. Consent for publication Not applicable. Clinical trial number Not applicable. Data availability The datasets used and/or analyzed during the current study are not publicly available due to sensitivity issues but are available from the corresponding author upon reasonable request via email. Competing interests The authors declare that they have no competing interests. Funding This work was funded by Bahir Dar University. The funder has no role in research design, data collection, result writing and manuscript preparation. Authors' contributions TD conceived, designed the research protocol and edited the manuscript. WH and YA approved the proposal. YY drafted, wrote and edited the manuscript. AK, BB and AG participated in the literature review, and quality assessment. All the authors have read and approved the final manuscript. Acknowledgments We would like to thank study participants. In addition, we would thank Bahir Dar University and data collectors. References Thygesen K, A.J., Jaffe AS, Chaitman BR, Bax JJ, Morrow DA, et al. Fourth Universal Definition of Myocardial Infarction (2018). Journal of the American College of Cardiology. 2018;72(18):2231-64. Dai H, M.A., Maor E, et al. Global, regional, and national burden of ischaemic heart disease and its attributable risk factors, 1990–2017: results from the Global Burden of Disease Study 2017. Eur Hear J – Qual Care Clin Outcomes 2020; 0: 1–11. Sanchis-Gomar F, P.-Q.C., Leischik R, et al. Epidemiology of coronary heart disease and acute coronary syndrome. Ann Transl Med 2016; 4(13): 256. Alsheikh-Ali AA, O.M., Raal FJ, et al. Cardiovascular risk factor burden in Africa and the Middle East: the Africa Middle East cardiovascular epidemiological (ACE) study. PLoS One 2014; 9(8): e102830. Kannan VC, T.A., Sawe HR, et al. Emergency care systems in Africa: a focus on quality. Afr J Emerg Med 2020; 10: S65–S72. Thompson SC, N.L., Katzenellenbogen J, et al. Challenges in managing acute cardiovascular diseases and follow up care in rural areas: a narrative review. Int J Environ Res Public Health 2019; 16(24): 5126. Adem F, Abdi S, Amare F, Mohammed MA. In-hospital mortality from acute coronary syndrome in Africa: a systematic review and meta-analysis. SAGE Open Med. 2023 Jan 17;11:20503121221143646. doi: 10.1177/20503121221143646. PMID: 36685798; PMCID: PMC9850135. Desta DM, N.T., Hailu A, et al. Treatment outcome of acute coronary syndrome patients admitted to ayder comprehensive specialized hospital, mekelle, Ethiopia; a retrospective cross sectional study. PLoS One 2020; 15(2): 1–17. Bogale K, Mekonnen D, Nedi T, Woldu MA. Treatment Outcomes of Patients with Acute Coronary Syndrome Admitted to Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia. Clin Med Insights Cardiol. 2019 Apr 17;13:1179546819839417. doi: 10.1177/1179546819839417. PMID: 31024218; PMCID: PMC6472164. Fanta K, D.F., Asefa ET, et al. Management and 30-day mortality of acute coronary syndrome in a resource-limited setting: insight from Ethiopia. a prospective cohort study. Front Cardiovasc Med. 2021;8:707700. doi:10.3389/fcvm.2021.707700. Armstrong, P.W., et al., Acute Coronary Syndromes in the GUSTO-IIb Trial. Circulation, 1998. 98(18): p. 1860-1868. Marinsek, M., D. Šuran, and A. Sinkovic, Factors of Hospital Mortality in Men and Women with ST-Elevation Myocardial Infarction – An Observational, Retrospective, Single Centre Study. International Journal of General Medicine, 2023. 16(null): p. 5955-5968. Schmitt, V.H., et al., Impact of diabetes mellitus on mortality rates and outcomes in myocardial infarction. Diabetes & Metabolism, 2021. 47(4): p. 101211. Wang, C., et al., Risk factors for acute kidney injury in patients with acute myocardial infarction. Chin Med J (Engl), 2019. 132(14): p. 1660-1665. Walker G. Calculated decisions: sgarbossa criteria for myocardial infarction in left bundle branch block. Emerg Med Pract . 2021;23(Suppl 1):2. Killip T, Kimball JT. Treatment of myocardial infarction in a coronary care unit. A two year experience with 250 patients. Am j Cardiol . 1967;20(4):457–464. doi:10.1016/0002-9149(67)90023-9 Charatcharoenwitthaya P, K.K., Aekplakorn W. Cigarette smoking increased risk of overall mortality in patients with non-alcoholic fatty liver disease: a nationwide population-based cohort study. Front Med. 2020;7:604919. doi:10.3389/fmed.2020.604919. Zhang C, Q.Y., Chen Q, et al. Alcohol intake and risk of stroke: a dose-response meta-analysis of prospective studies. Int J Cardiol. 2014;174 (3):669–677. doi:10.1016/j.ijcard.2014.04.225. Bashandy M, Abd Elgalil H, Abou Elhassan H. Epidemiological and clinical profile of acute coronary syndrome of Egyptian patients admitted to the Coronary Care Unit, Al-Azhar University Hospital, New Damietta. Sci J Al-Azhar Med Fac Girls 2019; 3(3): 625. 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;20:5–8. Shavadia J, Yonga G, Otieno H. A prospective review of acute coronary syndromes in an urban hospital in sub-Saharan Africa. Cardiovasc J Afr. 2012 Jul;23(6):318-21. doi: 10.5830/CVJA-2012-002. PMID: 22836154; PMCID: PMC3734739. Comendeiro-Maaløe M, E.n.R.F., Thygesen LC, Mateus C, Merlo J,Bernal-Delgado E, et al. (2020) Acknowledging the role of patient heterogeneity in hospital outcome reporting: Mortality after acute myocardial infarction in five European countries. PLoS ONE 15(2): e0228425. https://doi.org/10.1371/journal.pone.0228425. Orvin K, E.A., Goldenberg I, et al. Outcome of contemporary acute coronary syndrome complicated by ventricular tachyarrhythmias. Europace 2016; 18(2): 219–226. Shaheen S, W.A., Mokarab M, et al. Presentation, management, and outcomes of STEMI in Egypt: results from the European Society of Cardiology Registry on ST elevation myocardial infarction. Egypt Heart J 2020; 72: 35. Ekou A, Y.H., Kouamé I, et al. Primary PCI in the management of STEMI in sub-Saharan Africa: insights from Abidjan Heart Institute catheterisation laboratory. Cardiovasc J Afr 2020; 31(4): 201–204. Addad F, M.A., Gouider J, et al. Management of patients with acute ST-elevation myocardial infarction: results of the FAST-MI Tunisia registry. PLoS One 2019; 14(2): 1–11. Sangarre Z, T.A., Doumbia IS, et al. Evaluation of thrombolysis in the management of St-Elevation Myocardial Infarction (STEMI) in isolated cardiology unit. Cardiol Vasc Res 2017; 1(1): 1–4. Zorbozan O, C.A., Acar N, et al. Predictors of mortality in ST-elevation MI patients. A prospective study. Medicine. 2018;97(9):e0065. doi:10.1097/MD.0000000000010065. Kanič V, V.M., Tapajner A, Sinkovic A. Sex-related 30-day and long-term mortality in acute myocardial infarction patients treated with percutaneous coronary intervention. J Women’s Health. 2017;26(4):374–379. doi:10.1089/jwh.2016.5957. Bugiardini R, R.B., Cenko E, et al. Delayed Care and Mortality Among Women and Men With Myocardial Infarction. J Am Heart Assoc. 2017;6:e005968. Rohani C, J.H., Mortazavi Y, Esbakian B, Gholinia H. Mortality in patients with myocardial infarction and potential risk factors: A five-year data analysis. ARYA Atheroscler 2022; 18: 2427. Alabas OA, H.M., Dondo TB, Rutherford MJ, Timmis AD, Batin PD, et al. Long-term excess mortality associated with diabetes following acute myocardial infarction: A population-based cohort study. J Epidemiol Community Health 2017; 71(1): and 25-32. Kebede, B., et al., Acute coronary syndrome and its treatment outcomes in Ethiopia: a systematic review and meta-analysis. Journal of Pharmaceutical Policy and Practice, 2023. 16(1): p. 98. Tousek P, T.F., Horak D, Cervinka P, Rokyta R, Pesl L, Jarkovsky J, Widimsky P, CZECH-2 Investigators. The incidence and outcomes of acute coronary syndromes in a central European country: results of the CZECH-2 registry. Int J Cardiol. 2014;173(2):204–8. Ohman EM, A.P., Christenson RH, et al. Cardiac troponin T levels fo risk stratification in acute myocardial ischemia. GUSTO IIA Investigators. N Engl J Med 1996;335:1333-41. Newby LK, C.R., Ohman EM, et al. Value of serial troponin T measures for early and late risk stratification in patients with acute coronary syndromes. The GUSTO-IIa Investigators. Circulation 1998;98:1853-9. Hashmi K A, A.F., Ahmed O, et al. (December 21, 2020) Risk Assessment of Patients After ST-Segment Elevation Myocardial Infarction by Killip Classification: An Institutional Experience. Cureus 12(12): e12209. DOI 10.7759/cureus.12209. Parakh K, T.B., Bhat U, Fauerbach JA, Bush DE, Ziegelstein RC: Long-term significance of Killip class and left ventricular systolic dysfunction. Am J Med. 2008, 121:1015-8. 10.1016/j.amjmed.2008.06.020. Mello BH, O.G., Ramos RF, et al.: Validation of the Killip-Kimball classification and late mortality after acute myocardial infarction. Arq Bras Cardiol. 2014, 103:107-17. 10.5935/abc.20140091. Additional Declarations No competing interests reported. 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A multicenter three years, retrospective cross-sectional study","fulltext":[{"header":"Background","content":"\u003cp\u003eMyocardial infarction (MI) is the death of myocardial cells due to prolonged interruption of blood flow. It is a syndrome with a diagnostic criterion, having combination of symptoms, electrocardiographic changes, and elevated cardiac biomarkers at least one value above the 99th percentile from the reference range. The presence of myocardial ischemia can be demonstrated by new ischemic ECG findings and imaging evidence of loss of viable myocardium or new regional wall motion abnormality. An occluding thrombus may also be seen by angiography or autopsy [1].\u003c/p\u003e \u003cp\u003eGlobally ischemic heart disease (IHD) is the leading cause of morbidity and mortality affecting 126.5\u0026nbsp;million people in 2017 [2]. In developed countries, acute coronary syndrome (ACS) related mortality has reduced in the last decades. However, the mortality trend is increasing in African countries [3].\u003c/p\u003e \u003cp\u003eIn Africa, ACS incidence and mortality is rising due to an increase in cardiovascular risk factors including hypertension, diabetes and ageing of population [4]. Additionally, most of the hospitals provide low quality care due to limited resources such as lack of fibrinolytic medication, catheterization center and adequately trained physician [5]. This problem is very grave in the rural areas of Africa [6].\u003c/p\u003e \u003cp\u003eIn a meta-analysis conducted in Africa, which included 29 studies and 11,788 participants, the overall estimated in-hospital death rate was 22%. The death rate was higher in those who were treated in referral hospitals (24%) compared to those who were treated in cardiac centers (14%) [7].\u003c/p\u003e \u003cp\u003eThere are various factors presumed to affect the in-hospital mortality of myocardial infarction. But, the association of these factors with the fatality of MI is variable in different studies. Some of the factors include; the time of presentation of patients from onset of illness, the type of MI, the availability of invasive interventions, age of patients, gender, area of residency, and presence of comorbidities and post MI complication [8\u0026ndash;14].\u003c/p\u003e \u003cp\u003eDespite the increase in morbidity and mortality due MI in Sub Sahara African countries, the in-hospital mortality and factors associated with it was not studied well using large sample size. In addition, this study conducted in setting where there are no invasive cardiac interventions including fibrinolytics and PCI.\u003c/p\u003e"},{"header":"METHODS AND MATERIALS","content":"\u003cp\u003e\u003cstrong\u003eStudy area and study period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted at two public referral hospitals, Tibebe Ghion Specialized Hospital (TGSH) and Felege Hiwot Comprehensive Specialized Referral Hospital (FHCSRH), of Bahir Dar city, Ethiopia. These hospitals are located in Bahir Dar city Amhara region, 578km from the capital city, Addis Ababa. Both are tertiary-level teaching and referral hospitals that serve as the referral center for more than 15 district hospitals in the area, catering to a total catchment of 7 million people. Each hospital has more than 500 beds and offers health services to patients with various diseases in the outpatient and inpatient departments.\u003c/p\u003e\n\u003cp\u003eThe cardiac unit provides clinical service including, thrice a week trans-thoracic echocardiography session by cardiologist and it provides diagnostic tests and treatments for cardiac patients. ECG and cardiac biomarkers, such as highly sensitive cardiac troponin (hs-cTn), lipid panel, liver and renal function test, serum electrolyte and random blood sugar. The cardiac clinic has 03 rooms and currently there are 06 nurses and 9 physician including medical residents, internist, 04 cardiologists and 01 interventional cardiologist who are working there. However, both hospitals don\u0026rsquo;t provide fibrinolytics and invasive procedure including PCI and CABG. The study was conducted among MI patients who were admitted to the two public referral hospitals of Bahir Dar between November 2020and December\u0026nbsp;2023 GC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy design and population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstitution based retrospective cross-sectional study was conducted from November 2023 to December 2023 at FHCSRH and TGSH, Bahir Dar, Ethiopia. The study populations were all MI patients who were admitted to TGSH \u0026amp; FHCSRH during November 2020 to December 2023.\u003c/p\u003e\n\u003cp\u003eAll patients who were above 18 years old and had clinical, cardiac troponin, ECG, and echocardiography evidence of MI by cardiologist were included in the study. Patients without proper ECG and echocardiography (not done \u0026amp; interpreted by cardiologist), those with advanced malignancy and cirrhosis and those with incomplete medical record were excluded from this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size and sampling procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size was calculated using the single population proportion formula with the following assumptions: a confidence level of 95%, a 5% margin of error, and a prevalence of 27.4 % from a previous study [9]. \u0026nbsp; With these assumptions the sample size was calculated to be 306\u0026nbsp;and adding 10% for incomplete data the total sample size was 337. There were 450 patients who were admitted to the two public hospitals between November 2020 and December 2023 and all eligible patients, only 317 patients found to be eligible, were included in this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dependent variable was the presence of in hospital mortality due MI. The independent variables include Socio-demographic variables (age, gender, area of residence, time of arrival of patients to hospital since symptom onset, presenting complaint), comorbidities (diabetes, hypertension, dyslipidemia, alcohol, smoking), clinical factors (STEMI, NSTEMI, killip class), type of management (aspirin (ASA), clopidogrel, beta blocker, unfractionated heparin (UFH), ACE inhibitors, statin, diuretics, thrombolytic, PCI).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe registration books at TGSH and FHCSRH emergency, medical ward and medical ICU were revised to get the hospital chart numbers of MI patients who were admitted during November 2020 to December 2023. After getting their chart numbers, patient charts were retrieved from record and documentation office. These data were accessed and data were collected at documentation office from November 2023 to December 2023. Medical information was collected from patients\u0026rsquo; medical records by a trained medical doctor under close supervision by the principal investigator using pretested questionnaire. From the medical record socio-demographic, clinical, laboratory and imaging data were obtained.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eData processing and analysis\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe data were entered into EPI data version 4.6 and then transferred to SPSS 27.0 statistical packages for analysis. Data cleaning was conducted before performing the descriptive analysis. The baseline characteristics are presented as numbers and percentages. The findings were summarized in tables and figures. All statistical tests were performed using two-sided tests at the 0.05 level of significance. Odds ratio with 95 % confidence intervals and associated p-values were computed to assess the presence and degree of association between dependent and independent variables.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVariables with p values \u0026lt; 0.25 in the bivariate analysis were transferred to multivariate analysis and entered hierarchically to fit the logistic regression model. Statistically significant associations were determined based on the adjusted odds ratio (AOR) with its 95% CI and the P-value \u0026lt;0.05. Hosner-Lemeshow test was used to assess model fitness and multicollinearity test was conducted to check the absence of correlation between independent variables.\u003c/p\u003e\n\u003ch2\u003eOperational definitions\u003c/h2\u003e\n\u003cp\u003eFor the purpose of this study\u0026nbsp;myocardial infarction was defined as detection of a rise and/or fall of high-sensitivity cardiac troponin (hs-cTn) with at least one value above the 99th percentile and with at least one of the following: symptoms of acute myocardial ischemia, new ischemic electrocardiographic (ECG) changes, development of pathological Q waves and Imaging evidence of new loss of viable myocardium or new regional wall motion abnormality in a pattern consistent with an ischemic etiology[1].\u003c/p\u003e\n\u003cp\u003eSgarbossa criteria: an ECG criterion used to diagnose acute myocardial infarction in patient with previous LBBB and has 3 criteria: ST segment elevation of 1 mm or more that was in the same direction (concordant) as the QRS complex in any lead-score 5, ST segment depression of 1 mm or more in any lead from V1 to V3-score 3, and ST segment elevation of 1 mm or more that was discordant with the QRS complex (that is associated with a QS or RS complex) score 2 [15].\u003c/p\u003e\n\u003cp\u003eKILLIP class: Killip class of the patient at the time of hospital admission based on physical examination: Class 1: no evidence of heart failure, Class 2: findings consistent with mild to moderate heart failure (S3 gallop, lung rales \u0026lt; half way up the posterior lung fields, jugular venous distension), Class 3: overt pulmonary edema, Class 4: cardiogenic shock [16].\u003c/p\u003e\n\u003cp\u003eIn-hospital mortality: patients who died during their hospital stay due MI.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConventional cardiovascular risk factors: refer to smoking, hypertension, diabetes and dyslipidemia.\u003c/p\u003e\n\u003cp\u003eCigarette smoking: smoked more than 100 cigarettes in their life-time [17].\u003c/p\u003e\n\u003cp\u003eAlcohol drinking: consumption of more than 3 standard drinks daily (for males) or 2 standard drinks daily (for females) [18].\u0026nbsp;\u003c/p\u003e"},{"header":"RESULTS","content":"\u003ch2\u003e\u003cstrong\u003eSociodemographic and clinical characteristics\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA total of 317 patients were included in this study. As depicted in table 1, most of the participants were males (226, 71.3%), from urban areas (200, 63.1%). The mean age of participants was 61.24 years\u0026nbsp;[SD \u0026plusmn; 11.90 years]. More than a quarter of patients i.e., 87 (27.4%) were aged above 65 years. The average time of arrival since symptom onset was 3.18 days\u0026nbsp;[SD \u0026plusmn; 2.42 days].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCardiac pain is the most common presenting complaint accounting for 70.3% (223) while possibly cardiac pain and likely non cardiac pain constitute 28.1% (89) and 1.6% (5) of cases respectively. The average duration of hospitalization was 6.62 days\u0026nbsp;[SD \u0026plusmn; 3.25 days]. The maximum hospital stay was 3 weeks.\u003c/p\u003e\n\u003cp\u003eAmong comorbidities, hypertension was the most common comorbidity accounting for 38.6 % (122), followed by DM 23.7% (75). Among DM patients, 87% of them had poor glycemic control. Other comorbidities included dyslipidemia (13.7%), alcohol (9.8%), smoking (5.4%) and family history of MI (1.6%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1. Socio-demographic variables of MI patients in TGSH and FHCSRH, Bahir Dar, Ethiopia, 2023.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"587\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" valign=\"top\" style=\"width: 275px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCategory \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Variables \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 313px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Outcome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No Death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Death\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026nbsp;%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eAge in years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eless than 55 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e23.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e8.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e55 to 65 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e55.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e41.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003egreater than 65 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e21.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e73.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e63.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e26.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e36.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eArea of residence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e64.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e58.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e35.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e41.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003ePresenting complaint\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eCardiac pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e74.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e55.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003ePossibly cardiac pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e23.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e44.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eLikely non cardiac pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eTime since symptom onset in hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eless than 12 hrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e44.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e38.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003e12 to 48 hrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e43.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e51.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003egreater than 48 hrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e11.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e10.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003ePrevious history of MI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e3.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e4.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e96.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e95.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eFamily history of MI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e2.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e98.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e16.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e48.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e83.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e51.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e40.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e31.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e59.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e68.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eDyslipidaemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e13.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e14.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e86.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e85.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eAlcoholic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e9.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e11.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e90.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e88.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 126px;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e5.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e6.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e94.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e94.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDM: Diabetes Mellitus, MI: Myocardial Infarction\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eLaboratory and imaging parameters\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAll the patients were in cardiac ICU on continuous ECG monitoring throughout their hospital stay and the majority of patients (66.2%, 210) have STEMI whereas 107 (33.8%) patients have NSTEMI. As depicted in table 2, Killip classes I and II categories of MI combined constitute 59.6% of all patients. The remaining 40.4% of patients have Killip classes III and IV combined.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCardiac highly sensitive troponin was measured in all patients at admission and 21.1% of patients had serum troponin levels above 5000 ng/ml. Urinalysis is done for 261(82.33%) of cases and 49(18.8%) of them have proteinuria.\u003c/p\u003e\n\u003cp\u003eSerum total cholesterol was done in 119 patients and 90 (75.6%) of them have elevated total cholesterol. Serum triglyceride level was determined in 129(39.4%) of patients and 105 (84%) of them have hypertriglyceridemia. Likewise, serum HDL level was analyzed for 117 patients and 36(30.8%) of them have reduced level of HDL. LDL was also done for 131 patients and 71(54.2%) of them have elevated levels of LDL.\u003c/p\u003e\n\u003cp\u003eThe level of serum creatinine of patients was determined in 98% of patients and 44 (13.9%) of them had elevated serum creatinine. Echocardiographic assessment of left ventricular function was done in 98% of patients and 71.1% of them have reduced ejection fraction while 28.9% have preserved ejection fraction.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. \u0026nbsp;Laboratory, imaging and Killip class of MI patients in TGSH and FHCSRH, Bahir Dar, Ethiopia, 2023\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"574\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" valign=\"top\" style=\"width: 301px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCategory \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eNo Death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eDeath\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eECG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eSTEMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e59.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e91.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eNSTEMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e40.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e8.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eCardiac troponin in ng/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026lt; 5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e91.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e29.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026ge;5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e8.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e70.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eSerum creatinine in mg/dl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e92.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e61.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eElevated\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e7.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e38.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eUrinalysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eProteinuria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e17.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e25.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eNo Proteinuria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e82.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e75.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eTotal cholesterol in mg/dl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026lt; 200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e77.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e66.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026ge;200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e22.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e33.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eTriglyceride in mg/dl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026lt; 150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e81.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026ge;150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e18.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eLDL-C in mg/dl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026lt; 100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e55.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e47.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026ge;100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e44.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e52.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eHDL-C in mg/dl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026lt; 40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e31.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e26.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026ge;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e68.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e73.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eLV Ejection fraction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eReduced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e66.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e87.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003ePreserved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e33.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e12.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eKillip class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eclass I and II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e71.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e17.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eclass III and IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e28.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e82.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eECG: Electrocardiography, HDL-C: High Density Lipid-Cholesterol, LDL-C: Low Density Lipid-Cholesterol, LV: Left Ventricle\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eMedications parameters\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe available medications in the set up for guideline directed treatment of MI is given in majority of patients with the exception of reperfusion therapies i.e., both fibrinolytics and PCI which were not available in the study setting and study period. Dual anti platelets (ASA and clopidogrel) were given for 99.4% of patients. As depicted in table 3, ASA, anticoagulant and statins were provided for all patients (100%). Beta blockers were given for 92.4 % and ACEi for 41%. Mineralocorticoid receptor antagonists and diuretics were given for 7.3% and 55.5% of patients respectively. The provision of diuretics was dependent on the presence of heart failure and its severity as per Killip class while the others were mainly dependent on the presence or absence of contra indications for the specific medication.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3. Medications provided to MI patients of TGSH and FHCSRH Bahir Dar, Ethiopia, 2023.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"528\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMedications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 315px;\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eNo Death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eDeath\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eClopidogrel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e98.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e97.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eBeta blocker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e95.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e80.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e4.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e19.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eACEi/ARBS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e47.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e19.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e53.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e80.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eMineralocorticoid receptor antagonist\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e8.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e3.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e91.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e97.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eDiuretic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e46.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e88.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e53.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e11.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eACEi: Angiotensin Converting Enzyme inhibitor, ARBS: Angiotensin Receptor Blocker\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eIn hospital mortality and post MI complications\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe overall in hospital mortality of MI patients was 21.5% (95% CI: 16.6, 25.9\u003cstrong\u003e)\u003c/strong\u003e. As depicted in table 4, cardiogenic shock is the most common cause of death accounting for 73.5% of the total deaths. Fatal arrhythmias account for the second most common immediate cause of death which occurs in 17(25%) of deaths. Thromboembolism is the presumed cause of death in 1 patient.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFrom survivors of myocardial infarction, the most common sequel was persistent left ventricular dysfunction (LV dysfunction) which occurred in 74% of patients, depicted in table 5. Left ventricular thrombus and non-fatal thromboembolism occurred in 6.9% and 5.7% of patients respectively. Other associated post MI sequels on top of the listed ones include diastolic dysfunction, post MI pericarditis with pericardial effusion and left ventricular aneurysms. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4. Immediate causes of death among MI patients in TGSH and FHCSRH, Bahir Dar, Ethiopia, 2023.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"552\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003eDeath\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003ePercent of Cases\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eImmediate causes of death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eArrhythmia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e25.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e25.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eCardiogenic shock\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e73.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e73.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eThromboembolism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e1.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 291px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 5. Post MI complications of patients in TGSH and FHCSRH, Bahir Dar, Ethiopia, 2023\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"546\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 354px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 191px;\"\u003e\n \u003cp\u003eNo death\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003ePercent (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003ePost MI Sequels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003ePersistent LV dysfunction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e74.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eMitral regurgitation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e11.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eLV thrombus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e6.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eNon-fatal thromboembolism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e5.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eRe-infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 354px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eLV: Left Ventricle, MI: Myocardial Infarction\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eFactors associated with in hospital mortality in MI\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe association between independent and dependent variable, in hospital mortality was assessed using both univariable and multivariable logistic regression. On univariable logistic regression LVEF, age, diabetes, MI type, Hs-cTn level, serum creatinin and Killip class \u0026nbsp;found to be associated with in hospital mortality due MI.\u003c/p\u003e\n\u003cp\u003eAll the factors associate with p value of \u0026lt;0.25 were included in the multivariable logistic regression analysis and resulted age \u0026gt;65years (p=0.01), diabetes presence (p=\u0026lt;0.001), STEMI(p=0.006), Hs-cTn \u0026gt;5000ng/ml (p=\u0026lt;0.001), elevated serum creatinin (p=0.007) and Killip class III and IV were found to be statically significant independent factors of in hospital mortality due MI with p value of \u0026lt;0.05 as depicted in the table 6.\u003c/p\u003e\n\u003cp\u003eThose who aged above 65 years were 6.8 time more likely to have in hospital mortality due MI compared to those who age \u0026lt;55 years (AOR=6.85, 95% CI: 1.58-29.71, p=0.01). Similarly, those with STEMI were 5.7 time more likely to have in hospital mortality due MI compared to NSTEMI\u0026nbsp;(AOR=5.75, 95% CI:\u0026nbsp;1.66-19.87, P=0.006).\u0026nbsp;In addition, those who had high serum creatinin were 4.2 times more likely to have in hospital mortality due MI compared to those who had low serum creatinin (AOR=4.21, 95%CI 1.47-12.08, p=0.007)\u003c/p\u003e\n\u003cp\u003eParticipants with serum troponin level \u0026gt; 5000 ng/ml had 9.9 time more likely to have in hospital mortality due MI compared to those who had \u0026lt;5000ng/ml (AOR= 9.98, 95% CI 4.06-24.53, p=\u0026lt;0.001). Further more patients with diabetes were 7 times more likely to have in patient mortality due MI compared to non diabetic patients (AOR=7.02, 95% CI 2.47-19.91, p=\u0026lt;0.001). Finally participants with Killip class III and IV were 15 time more likely to have in hospital mortality compared to those who with Killip class I and II (AOR=15.52, 95%CI 5.19-46.46, p=\u0026lt;0.001).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe in-hospital mortality of myocardial infarction in this study was 21.5% (95% CI: 16.6, 25.9). This prevalence is similar outcome compared to other previously conducted studies in Kenya (20.0%), Nigeria (21.4%), Egypt (19.6%) and a meta-analysis in Africa (22%)[7, 19-21].\u003c/p\u003e\n\u003cp\u003eThis study has showed a higher in hospital mortality compared to other previous studies conducted in Egypt (1.8%), Sweden (4%), Portugal (6.9%) and Israel (10.4%)[22-24]. The main reason for this difference was most of the patient present late and the setting has no setup for intervention including PCI, thrombolytic and CABG which will significantly affect the outcome. In contrast this study has a lower in hospital mortality compared to previous studies conducted in Senegal (28.0%), Tunisia (71.6%) and Mali (100%) [25-27]. The possible reason for this variation was difference in sample size and patient characteristics, particularly type of MI representation.\u003c/p\u003e\n\u003cp\u003eThose who age \u0026gt;65 years were more likely to have in hospital mortality due MI compared to those aged \u0026lt;55 years. This result is in line with studies conducted previously [28, 29]. Elderly patients are more likely to have comorbidity including diabetes, heart failure, prior MI [30].\u003c/p\u003e\n\u003cp\u003eTable 6.Bivariate and multivariate logistic regression analyses of factors associated with in hospital mortality in MI at TGSH \u0026amp; FHCSRH, Bahir Dar, Ethiopia, 2023.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"739\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategor\u003c/strong\u003e\u003cstrong\u003ey\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Variable\u003c/strong\u003e\u003cstrong\u003es\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Death due M\u003c/strong\u003e\u003cstrong\u003eI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 354px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBivariate analysis \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Multivariate analysi\u003c/strong\u003e\u003cstrong\u003es\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;No deat\u003c/strong\u003e\u003cstrong\u003eh\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; N (%)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Death\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;N (%\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOR(95% CI\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAOR(95%CI\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;P valu\u003c/strong\u003e\u003cstrong\u003ee\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eAge in years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026lt;55\u003c/p\u003e\n \u003cp\u003e55-65\u003c/p\u003e\n \u003cp\u003e\u0026gt;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e59(23.7%)\u003c/p\u003e\n \u003cp\u003e137(55%)\u003c/p\u003e\n \u003cp\u003e53(21.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e6(8.8%)\u003c/p\u003e\n \u003cp\u003e28(41.2%)\u003c/p\u003e\n \u003cp\u003e34(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e2.01(0.79-5.10)\u003c/p\u003e\n \u003cp\u003e6.30(2.45-16.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e2.01(0.79-5.10)\u003c/p\u003e\n \u003cp\u003e6.85(1.58-29.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;-\u003c/p\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eDiabetes Presence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e42(16.9%)\u003c/p\u003e\n \u003cp\u003e207(83.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e33(48.5%)\u003c/p\u003e\n \u003cp\u003e35(51.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e4.64(2.60-8.29)\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e7.02(2.47-19.91)\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eMI type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eSTEMI\u003c/p\u003e\n \u003cp\u003eNSTEMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e148(59.4%)\u003c/p\u003e\n \u003cp\u003e101(40.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e62(91.2%)\u003c/p\u003e\n \u003cp\u003e6(8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e7.05(2.93-16.92)\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e5.75(1.66-19.87)\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eHs-cTn (ng/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026lt; 5000\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026ge; 5000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e226(90.8%)\u003c/p\u003e\n \u003cp\u003e23(9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e24(35.3%)\u003c/p\u003e\n \u003cp\u003e44(64.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e18.01(9.34-34.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e9.98(4.06-24.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;-\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eLVEF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eReduced\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePreserved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e166(66.9%)\u003c/p\u003e\n \u003cp\u003e82(33.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e55(87.3%)\u003c/p\u003e\n \u003cp\u003e8(12.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3.39(1.54-7.46)\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e1.07(0.31-3.70)\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eSerum creatinin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eNormal \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eElevated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e231(92.8%)\u003c/p\u003e\n \u003cp\u003e18(7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e42(61.8%)\u003c/p\u003e\n \u003cp\u003e26(38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e7.94(4.00-15.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e4.21(1.47-12.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;-\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eKillip class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eClass I to II\u003c/p\u003e\n \u003cp\u003eClass III to IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e177(71.1%)\u003c/p\u003e\n \u003cp\u003e72(28.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e12(17.6%)\u003c/p\u003e\n \u003cp\u003e56(82.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e11.47(5.80-22.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e15.52(5.19-46.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;-\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Statically significant, AOR: Adjusted Odds Ratio, CI: Confidence Interval, COR: Crude Odds Ratio, LVEF: Left Ventricular Ejection Fraction\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eD\u003c/strong\u003e\u003cstrong\u003eiscussion\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe in-hospital mortality of myocardial infarction in this study was 21.5% (95% CI: 16.6, 25.9). This prevalence is comparable to other previously conducted studies in Kenya (20.0%), Cote D\u0026apos;ivoire (20.7%), Egypt (19.6%) and a meta-analysis in Africa (22%) [7, 19-21].\u003c/p\u003e\n\u003cp\u003eThis study has showed a higher in hospital mortality compared to other previous studies conducted in Egypt (1.8%), Sweden (4%), Portugal (6.9%) and Israel (10.4%) [22-24]. The main reason for this difference was most of the patient present late and the setting has no setup for intervention including PCI, thrombolytic and CABG which will significantly affect the outcome. In contrast, this study has a lower in hospital mortality compared to previous studies conducted in Senegal (28.0%), Tunisia (71.6%) and Mali (100%) [25-27]. The possible reason for this variation was the difference in sample size and patient characteristics, particularly type of MI representation.\u003c/p\u003e\n\u003cp\u003eThose who age \u0026gt;65 years were more likely to have in hospital mortality due MI compared to those age \u0026lt;55 years. This result is in line with studies conducted previously [28, 29]. Elderly patients are more likely to have comorbidity including diabetes, heart failure and prior MI [30].\u003c/p\u003e\n\u003cp\u003eDiabetes patients were more likely to have in hospital mortality due MI compared to non-diabetic patients. Similar outcome has been seen in other studies [13, 31]. The possible explanation may be diabetes patients are more likely to have more comorbidity and complication [32].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePatients diagnosed with STEMI were more likely to have in hospital mortality compared to NSTEMI. This result is in line with a meta-analysis conducted in Ethiopia [33]. However, the CZECH-2 registry in central European country study showed that the rate of mortality was higher in patients with NSTEMI (8.4% for NSTEMI patients, 7.3% for STEMI patients) [34]. The observed difference may be due to majority of the participant in our study had STEMI (66.2%).\u003c/p\u003e\n\u003cp\u003eParticipants who had high serum cardiac troponin level had high in hospital mortality due MI compared to those who had low serum cardiac troponin level. Similar outcome has been seen in the GUSTO-IIa trail (Global Use of Strategies to Open Occluded Coronary Arteries in Acute Coronary Syndromes) [35, 36]. The level of troponin was higher in this study compared to the GUSTO-IIa study. This may be due to the provision of reperfusion and early arrival of patients in GUSTO-IIa in contrast to no reperfusion and delayed arrival of patients in this study.\u003c/p\u003e\n\u003cp\u003eThis study also dictates that patients with acute renal injury had higher in-hospital mortality due MI compared to those with no renal failure. This result is in line with previous studies conducted [12, 14].\u0026nbsp;The increased mortality in patients with renal failure may indicate the severity of MI as a component of multi-organ failure. It may also signify the presence of reduced dosage or complete preclusion of some medications due to contraindications from renal failure [14].\u003c/p\u003e\n\u003cp\u003eParticipants with Killip class III and IV were associated with a higher in-hospital mortality compared to Killip classes I and II. Similar association was seen in previous studies [37-39]. The possible explanation could be patients with a higher Killip class had more likely to have severe form of MI and more complication [14].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrength and limitations of this study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo our knowledge this study is the first study to assess the in hospital mortality of MI at Amhara region, Ethiopia. Another strength of this study is, it comprises a relatively large sample size compared to other Sub Sahara African country studies. However, this study was a retrospective study and patients long term outcome were not studied.\u003c/p\u003e"},{"header":"Conclusions and recommendations","content":"\u003cp\u003eDespite an attempt made by Ethiopian minster of health to reduce cardiovascular related mortality, the in-hospital mortality of myocardial infarction in Bahir Dar public referral hospitals was 21.5% (95% CI: 16.6-25.9\u003cstrong\u003e)\u003c/strong\u003e. Age above 65, presence of diabetes mellitus, STEMI, higher levels of cardiac troponin, Killip class III or IV and having elevated serum creatinine were\u0026nbsp;significant factors\u0026nbsp;associated with increased in hospital mortality due MI.\u003c/p\u003e\n\u003cp\u003eMuch efforts have to be made to solve the factors associated with in hospital mortality due MI. Particularly, greater attention has to be given for elderly, those with comorbidity including diabetes mellitus and acute kidney injury. In addition, early intervention is required for those with STEMI, high serum troponin and high Killip class.\u003c/p\u003e\n\u003cp\u003eFurther research is needed with a larger sample size and cohort study to ensure representativeness and investigate the association between in hospital mortality due MI and factors that affects it.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACEi=Angiotensin Converting Enzyme inhibitor, ACS=Acute Coronary Syndrome , AMI=Acute Myocardial Infarction, ASA=Aspirin, CVD=Cardiovascular Disease, DM=Diabetes Mellitus, ECG=Electrocardiography, FHCSRH=Felege Hiwot Comprehensive Specialized Referral Hospital, HDL=High Density Lipoprotein, HTN=Hypertension, IHD= Ischemic Heart Disease, LDL=Low Density Lipoprotein, LV=Left Ventricle, MI=Myocardial Infarction, PCI=Percutaneous Coronary Intervention, NSTEMI=Non ST Elevation Myocardial Infarction, SSA=Sub Saharan Africa, STEMI=ST Elevation Myocardial Infarction, TGSH=Tibebe Ghion Specialized Hospital, UFH=Unfractionated Heparin\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted according to the declaration of Helsinki. Ethical clearance was approved by the Research Ethical Review Board of Collage of Medicine and Health Science, Bahir Dar University (Protocol number 807/2023) and informed written consent was taken from all participants. Patient data confidentiality was respected at all levels, including chart retrieving and data analysis, which was handled by the investigators.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are not publicly available due to sensitivity issues but are available from the corresponding author upon reasonable request via email.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by Bahir Dar University. The funder has no role in research design, data collection, result writing and manuscript preparation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTD conceived, designed the research protocol and edited the manuscript. WH and YA approved the proposal. YY drafted, wrote and edited the manuscript. AK, BB and AG participated in the literature review, and quality assessment. All the authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank study participants. In addition, we would thank Bahir Dar University and data collectors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eThygesen K, A.J., Jaffe AS, Chaitman BR, Bax JJ, Morrow DA, et al. Fourth Universal Definition of Myocardial Infarction (2018). 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International Journal of General Medicine, 2023. 16(null): p. 5955-5968.\u003c/li\u003e\n\u003cli\u003eSchmitt, V.H., et al., Impact of diabetes mellitus on mortality rates and outcomes in myocardial infarction. Diabetes \u0026amp; Metabolism, 2021. 47(4): p. 101211.\u003c/li\u003e\n\u003cli\u003eWang, C., et al., Risk factors for acute kidney injury in patients with acute myocardial infarction. Chin Med J (Engl), 2019. 132(14): p. 1660-1665.\u003c/li\u003e\n\u003cli\u003eWalker G. Calculated decisions: sgarbossa criteria for myocardial infarction in left bundle branch block. \u003cem\u003eEmerg Med Pract\u003c/em\u003e. 2021;23(Suppl 1):2.\u003c/li\u003e\n\u003cli\u003eKillip T, Kimball JT. Treatment of myocardial infarction in a coronary care unit. A two year experience with 250 patients. \u003cem\u003eAm j Cardiol\u003c/em\u003e. 1967;20(4):457\u0026ndash;464. doi:10.1016/0002-9149(67)90023-9\u003c/li\u003e\n\u003cli\u003eCharatcharoenwitthaya P, K.K., Aekplakorn W. Cigarette smoking increased risk of overall mortality in patients with non-alcoholic fatty liver disease: a nationwide population-based cohort study. Front Med. 2020;7:604919. doi:10.3389/fmed.2020.604919.\u003c/li\u003e\n\u003cli\u003eZhang C, Q.Y., Chen Q, et al. Alcohol intake and risk of stroke: a dose-response meta-analysis of prospective studies. Int J Cardiol. 2014;174 (3):669\u0026ndash;677. doi:10.1016/j.ijcard.2014.04.225.\u003c/li\u003e\n\u003cli\u003eBashandy M, Abd Elgalil H, Abou Elhassan H. Epidemiological and clinical profile of acute coronary syndrome of Egyptian patients admitted to the Coronary Care Unit, Al-Azhar University Hospital, New Damietta. Sci J Al-Azhar Med Fac Girls 2019; 3(3): 625. \u003c/li\u003e\n\u003cli\u003eKolo 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. \u003cem\u003eNiger Postgrad Med J\u003c/em\u003e. 2013;20:5\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eShavadia J, Yonga G, Otieno H. A prospective review of acute coronary syndromes in an urban hospital in sub-Saharan Africa. Cardiovasc J Afr. 2012 Jul;23(6):318-21. doi: 10.5830/CVJA-2012-002. PMID: 22836154; PMCID: PMC3734739.\u003c/li\u003e\n\u003cli\u003eComendeiro-Maal\u0026oslash;e M, E.n.R.F., Thygesen LC, Mateus C, Merlo J,Bernal-Delgado E, et al. (2020) Acknowledging the role of patient heterogeneity in hospital outcome reporting: Mortality after acute myocardial infarction in five European countries. PLoS ONE 15(2): e0228425. https://doi.org/10.1371/journal.pone.0228425.\u003c/li\u003e\n\u003cli\u003eOrvin K, E.A., Goldenberg I, et al. Outcome of contemporary acute coronary syndrome complicated by ventricular tachyarrhythmias. Europace 2016; 18(2): 219\u0026ndash;226.\u003c/li\u003e\n\u003cli\u003eShaheen S, W.A., Mokarab M, et al. Presentation, management, and outcomes of STEMI in Egypt: results from the European Society of Cardiology Registry on ST elevation myocardial infarction. Egypt Heart J 2020; 72: 35.\u003c/li\u003e\n\u003cli\u003eEkou A, Y.H., Kouam\u0026eacute; I, et al. 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\u0026ndash;204.\u003c/li\u003e\n\u003cli\u003eAddad F, M.A., Gouider J, et al. Management of patients with acute ST-elevation myocardial infarction: results of the FAST-MI Tunisia registry. PLoS One 2019; 14(2): 1\u0026ndash;11.\u003c/li\u003e\n\u003cli\u003eSangarre Z, T.A., Doumbia IS, et al. Evaluation of thrombolysis in the management of St-Elevation Myocardial Infarction (STEMI) in isolated cardiology unit. Cardiol Vasc Res 2017; 1(1): 1\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eZorbozan O, C.A., Acar N, et al. Predictors of mortality in ST-elevation MI patients. A prospective study. Medicine. 2018;97(9):e0065. doi:10.1097/MD.0000000000010065.\u003c/li\u003e\n\u003cli\u003eKanič V, V.M., Tapajner A, Sinkovic A. Sex-related 30-day and long-term mortality in acute myocardial infarction patients treated with percutaneous coronary intervention. J Women\u0026rsquo;s Health. 2017;26(4):374\u0026ndash;379. doi:10.1089/jwh.2016.5957.\u003c/li\u003e\n\u003cli\u003eBugiardini R, R.B., Cenko E, et al. Delayed Care and Mortality Among Women and Men With Myocardial Infarction. J Am Heart Assoc. 2017;6:e005968.\u003c/li\u003e\n\u003cli\u003eRohani C, J.H., Mortazavi Y, Esbakian B, Gholinia H. Mortality in patients with myocardial infarction and potential risk factors: A five-year data analysis. ARYA Atheroscler 2022; 18: 2427.\u003c/li\u003e\n\u003cli\u003eAlabas OA, H.M., Dondo TB, Rutherford MJ, Timmis AD, Batin PD, et al. Long-term excess mortality associated with diabetes following acute myocardial infarction: A population-based cohort study. J Epidemiol Community Health 2017; 71(1): and 25-32.\u003c/li\u003e\n\u003cli\u003eKebede, B., et al., Acute coronary syndrome and its treatment outcomes in Ethiopia: a systematic review and meta-analysis. Journal of Pharmaceutical Policy and Practice, 2023. 16(1): p. 98.\u003c/li\u003e\n\u003cli\u003eTousek P, T.F., Horak D, Cervinka P, Rokyta R, Pesl L, Jarkovsky J, Widimsky P, CZECH-2 Investigators. The incidence and outcomes of acute coronary syndromes in a central European country: results of the CZECH-2 registry. Int J Cardiol. 2014;173(2):204\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eOhman EM, A.P., Christenson RH, et al. Cardiac troponin T levels fo risk stratification in acute myocardial ischemia. GUSTO IIA Investigators. N Engl J Med 1996;335:1333-41.\u003c/li\u003e\n\u003cli\u003eNewby LK, C.R., Ohman EM, et al. Value of serial troponin T measures for early and late risk stratification in patients with acute coronary syndromes. The GUSTO-IIa Investigators. Circulation 1998;98:1853-9.\u003c/li\u003e\n\u003cli\u003eHashmi K A, A.F., Ahmed O, et al. (December 21, 2020) Risk Assessment of Patients After ST-Segment Elevation Myocardial Infarction by Killip Classification: An Institutional Experience. Cureus 12(12): e12209. DOI 10.7759/cureus.12209.\u003c/li\u003e\n\u003cli\u003eParakh K, T.B., Bhat U, Fauerbach JA, Bush DE, Ziegelstein RC: Long-term significance of Killip class and left ventricular systolic dysfunction. Am J Med. 2008, 121:1015-8. 10.1016/j.amjmed.2008.06.020.\u003c/li\u003e\n\u003cli\u003eMello BH, O.G., Ramos RF, et al.: Validation of the Killip-Kimball classification and late mortality after acute myocardial infarction. Arq Bras Cardiol. 2014, 103:107-17. 10.5935/abc.20140091.\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":"Cardiovascular disease, Myocardial infarction, Mortality, Sub Sahara Africa","lastPublishedDoi":"10.21203/rs.3.rs-5325801/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5325801/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: The prevalence of ischemic heart disease is increasing in Sub Saharan Africa countries, but adequate data are lacking regarding the in hospital mortality and associated factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e To assess the magnitude of in hospital mortality due to myocardial infarction and associated factors among hospitalized patients at two public referral hospitals, Bahir Dar, Ethiopia, 2023.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Institution based retrospective cross-sectional study was conducted, using sample size of 317, among patients who were hospitalized between November 2020 to December 2023 due myocardial infarction in two public referral hospitals at Bahir Dar, Ethiopia. Pre-developed check list were used to extract data from the medical registry. Data were entered using Epidata Manager Version 4.6 and analyzed using SPSS version 27. Multivariate logistic regression analysis was used, considering with a p-value of \u0026lt;0.05 as statically significant, with a 95% confidence interval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResult\u003c/strong\u003e. The in-hospital mortality rate was 21.5% (95% CI: 16.6, 25.9). Age greater than 65 (AOR 6.85, 95% CI 1.58-29.71), presence of diabetes mellitus (AOR 7.02; 95% CI 2.47-19.91), high level of serum troponin (AOR=9.98; 95% CI: 4.06-24.53), elevated serum creatinine (AOR=4.21, 95% CI-1.47-12.08), higher Killip class (AOR-15.52, 95% CI: 5.19-46.46),and STEMI (AOR=5.75; 95% CI-1.66-19.87) were factors associated with in hospital mortality due MI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion and recommendation\u003c/strong\u003e: The in-hospital mortality due MI was found to be high and it was associated with advanced age, high Killip class, STEMI, high serum troponin, diabetes mellitus and high serum creatinine. Addressing these major factors and effective preventive tools are required to reduce this burden.\u003c/p\u003e","manuscriptTitle":"In hospital mortality and associated factors among patients admitted with myocardial infarction at public referral hospitals, Bahir Dar, Ethiopia, 2023. A multicenter three years, retrospective cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-25 14:17:43","doi":"10.21203/rs.3.rs-5325801/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":"aed62df5-2a56-4378-90dd-e53f1bcd6b4f","owner":[],"postedDate":"November 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":40628469,"name":"Health sciences/Cardiology"},{"id":40628470,"name":"Health sciences/Diseases"},{"id":40628471,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-01-21T02:28:37+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-25 14:17:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5325801","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5325801","identity":"rs-5325801","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}