In-hospital Mortality and Associated Factors among Adult Patients with Acute Heart Failure in a Tertiary Hospital, Harar, Eastern Ethiopia: A Cross-Sectional Study

In-hospital Mortality and Associated Factors among Adult Patients with Acute Heart Failure in a Tertiary Hospital, Harar, Eastern Ethiopia: A 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 Short Report In-hospital Mortality and Associated Factors among Adult Patients with Acute Heart Failure in a Tertiary Hospital, Harar, Eastern Ethiopia: A Cross-Sectional Study Chala Deriba, Abera Jambo, Mesay Dechasa, Shambel Nigussie, Jemal Abdela, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2775153/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 : Acute heart failure is the gradual or rapid change of heart failure signs and symptoms, which poses a unique diagnostic and management challenge, requiring urgent therapy. It is responsible for nearly one million hospitalizations each year globally with rising rates. Despite therapeutic advances, it is associated with poor prognosis. Therefore, his study aimed to assess in-hospital mortality and its associated factors among adult acute heart failure patients in a tertiary hospital, Harar, Eastern Ethiopia. Methods : A hospital based retrospective cross-sectional study was employed among 454 adult acute heart failure patients treated in the medical ward of Haramaya University Hiwot Fana Comprehensive Specialized Hospital from June 01, 2016 to May 31, 2021. Data was collected using structured data abstraction format from July 15 to August 14, 2021. Collected data was entered to Epi-Data version 3.1, exported to, and analyzed using statistical package for social science (SPSS) version 21.0. Bivariate and multivariate logistic regression was used to identify factors associated with in-hospital mortality. Results : A total of 454 acute heart failure patient’s medical records were reviewed. More than half, 282(62.1%) of patients were females. The median age of patients was 45 years (±28 IQR). In-hospital mortality was 18.9% and it was more prevalent in the first week of admission, 61(70.9%). Sex (female) (adjusted odds ratio (AOR) = 2.83, P = 0.001)), having smoking history (AOR = 2.51, P = 0.031), generalized body swelling (AOR = 2.67, P = 0.001), hypotension (AOR = 4.56, P = 0.001), and tachycardia (AOR = 4.57, P = 0.000) were factors associated with in-hospital mortality. Conclusions : In-hospital mortality is found to be very high among acute heart failure adult patients. Therefore, dedicated programs need to be developed to reduce mortality from acute heart failure and further prospective study should be conducted to investigate the problem in-depth. Acute Heart Failure In-hospital Mortality Tertiary Hospital Eastern Ethiopia. Figures Figure 1 Figure 2 Introduction Heart failure (HF) is a clinical syndrome characterized by classic symptoms and signs which occurs on exertion or at rest (1). HF is caused by a structural and/or functional cardiac abnormality, resulting in reduced cardiac output and/or elevated intra-cardiac pressure. This pressure impairs the ability of the heart to fill with blood at normal pressure or eject blood adequate to fulfill the needs of the metabolizing organs. HF remains a major cause of mortality and morbidity (2, 3, 4). Acute heart failure (AHF) is defined as a gradual or rapid change in heart failure syndromes, which poses a unique diagnostic and management challenge and requires urgent therapy (5). AHF also covers a wide range of the spectrum, which ranges from mild exacerbations with gradual increases in edema to cardiogenic shock (6). These symptoms in AHF are the result of severe pulmonary congestion due to reduced left ventricular filling pressures with or without low cardiac output (7). AHF is responsible for nearly one million hospitalizations each year with rising rates and after initial hospitalization, 25% of patients are readmitted at 30 days, 35% of which are due to a new exacerbation (8). In Africa, 7% to 10% of all medical admissions to hospitals are due to cardiovascular disease, with heart failure contributing to 3% to 7% (9). There were no data on the prevalence of heart failure in the general population in Ethiopia. A study in single setting at Dabat district, northwest Ethiopia, revealed that out of 216,420 populations 32.2% had heart disease. Hospitalization due to AHF is associated with several factors and comorbidities like older age, female gender, hyperuricemia, obesity, atrial fibrillation, peripheral artery disease, and chronic kidney disease (10). Once diagnosed, AHF patients may be classified using different methods based on presentation. Depending on whether patients have a history of HF or not, it is classified as “acute decompensated heart failure (ADHF) which occurs in patients with heart failure history and De novo AHF that occurs in individuals with no history of heart failure”. Based on systolic blood pressure (SBP) at presentation, AHF is classified as “hypertensive AHF (SBP > 140mmHg), normotensive AHF (SBP is between 90-140mmHg), and hypotensive AHF (SBP < 90mmHg)”. Depending on the hemodynamic condition of the patients, it is classified as “warm and dry (well-perfused without congestion), warm and wet (well-perfused but congested), cold and dry (hypo-perfusion without congestion), and cold and wet (hypo-perfusion and congestion)”. Based on left ventricular ejection fraction (LVEF), AHF is classified as “AHF with reduced ejection fraction and AHF with preserved ejection fraction” (11). Depending on congestive and organ perfusion status the management approaches of AHF involves relief of symptoms, restoration of systemic tissue perfusion via improved cardiac output and minimization of further cardiac damage. These can be attained by using diuretics, neuro-hormonal antagonists and inotropes (12, 13). Despite therapeutic advances, the prognosis of AHF is poor and re-hospitalization is high which is 25% to 30% (14). HF in general is associated with a huge economic burden which the overall cost is estimated at $108 billion globally and $28 million in Ethiopia per annum(15). The burden of AHF is high in resource-limited countries where patient’s low levels of education and income also contribute(16). In sub-Saharan Africa, many of the equipment and drugs commonly used to diagnose and treat AHF in resource-rich settings are lacking (17, 18). In Ethiopia, in addition to this lack of equipment and drugs, knowledge about cardiovascular risk factors is at suboptimal levels (46%) (19) and AHF patients are of middle age (20, 21); this is an additional burden due to the impact on productivity. Regarding in-hospital mortality from AHF, it is 1.5% to 5.3% in developed countries (22, 23, 24). However, it is very high in Ethiopia (17.2% to 24.4%) (20, 25). One single setting study showed a high burden of the HF (32.2% of the population had heart disease) and household food insecurity was among factors associated with the non-communicable disease which include heart disease (26); HF is the third most common reason for immediate admissions, with a prevalence of 16.0% among patients admitted to medical wards (27) . Throughout the country, hospital-based studies on AHF that look into in-hospital mortality of the disease and its associated factors are scarce and are lacking in this study setting. Therefore, this study aimed to assess in-hospital mortality and its associated factors among adult patients with acute heart failure Fana Comprehensive Specialized Hospital from 15 July to 14 August 2021, Harar, Ethiopia. This study provide insights regarding in-hospital mortality of AHF and its associated factors among adult patients. Therefore, primarily it encourage hospital managers and each health professionals who participate in patient care to take measure in the spirit of improving the treatment outcome of AHF by forwarding necessary recommendations for possible changes and to scale up current standard of care in HFSCH and other similar hospitals. This study is also a stepping-stone for the study setting to alarm other researchers to investigate the problem in-depth throughout the country. Furthermore, the finding of this study can be used as input for development of treatment guidelines need to be modified for the future at the national level. Materials and Methods Study design, setting, and period The retrospective cross-sectional study was conducted from July 15 to August 14, 2021 at Hiwot Fana Comprehensive Specialized Hospital (HFCSH), Eastern Ethiopia. HFCSH is a specialized hospital in Eastern Ethiopia, which is found in Harar town, 526 kilometers from Addis Ababa, the capital city of Ethiopia. It is serving as a referral hospital for the entire eastern part of the country including Eastern Oromia, Dire Dawa city administration, Harari, and Somali regional states. There are different wards and clinics within the hospital that provide services for the community such as medical ward, pediatric ward, surgery ward, gynecologic and obstetrics ward, oncology ward, antenatal clinic, dental clinic, a tuberculosis clinic, ante-retroviral therapy clinic, dermatology clinic, and ophthalmologic clinic. The medical ward has 22 beds. Population All adult patients with a diagnosis of AHF treated at HFCSH were source population. All adult patients with a diagnosis of AHF treated at HFCSH in the past five years (from June 01, 2016 to May 31, 2021) who fulfilled the inclusion criteria were the study population. Eligibility criteria All adult patients whose was age less than 18 years with a confirmed diagnosis of AHF and treated during the data retrieval period at the medical ward of HFCSH were included in this study. However, all patients with unknown outcome (referred or disappeared) and lost and/or incomplete patients’ medical records were excluded from the study. Sample size determination For the first two objectives sample size of the study was calculated using single population proportion formula by considering the following assumptions: prevalence of in-hospital mortality (P) = 17.2% taken from another similar study (20), confidence level (CI) = 95% and corresponding Z score of 1.96, margin of error (W) = 5%. Thus sample size was, n = (Zα/ 2 ) 2 p (1-p) /w 2 = (1.96) 2 *0.172*0.828/ (0.05) 2 = 218.8. For the objective of factors associated with in-hospital mortality sample size was calculated using Epi-Info version 7.2.4.0 ( Table 1 ). Table 1: Sample size calculation for factors associated with in-hospital mortality of acute heart failure patients using Epi-Info software (version 7.2.4.0). Determinants of treatment outcome Factors Assumptions % Exposed % unexposed Reference Sample size (N) Smoking CI:95% Power:80% Ratio:1:1 44.4 15.6 (20) 80 Diabetes mellitus CI:95% Power:80% Ratio:1:1 50.0 15.6 (20) 60 Pulmonary hypertension CI:95% Power:80% Ratio:1:1 15.1 41.2 (20) 94 Chronic kidney disease CI:95% Power:80% Ratio:1:1 39.59 22.44 (25) 230 Heart rate > 100beats/min at presentation CI:95% Power:80% Ratio:1:1 34.30 47.9 (25) 412 CI = Confidence interval Therefore, by adding 10% for contingency on the largest sample size, the calculated sample size was found to be 454 adult patients with AHF. Sampling procedures and sampling techniques The 907 adult patients were treated at HFCSH for AHF during the last five years. That is 121, 144, 201, 199, 242 patients from June 01, 2016, to May 31, 2021, each year respectively. For this study, record numbers of those patients’ medical records were obtained from the medical registration book of the Medical ward of HFCSH. Finally, 454 patients’ medical records included in the study were selected using proportionally allocated simple random sampling technique ( Figure 1 ). Data collection method Data were collected from patients’ medical records using an English version of structured and pretested data abstraction format prepared by reviewing different pieces of literature on similar topics, which consists of socio-demographic information, vital signs at presentation, clinical presentations, comorbidities, laboratory and radiologic findings ( Additional file 1) . Record numbers of the individual patients’ medical cards were obtained from medical registration book of Medical ward, and the numbers of those patients’ medical cards to be included in the study were randomly selected using lottery method. Then using randomly selected numbers, patients’ medical cards were drawn from the hospital card room. In-hospital mortality was confirmed by principal investigator from discharge summary. Finally, the data were collected from those medical cards by two clinical pharmacists and one clinical nurse. Operational definitions Acute heart failure :- sign and symptoms of new-onset of heart failure or decompensation or worsening of chronic stable heart failure (ADHF) (2, 28) In-hospital mortality : - AHF patient died in the hospital after he/she was admitted to the medical ward which confirmed by physician’s death summary (29). Elevated blood pressure : - systemic blood pressure of greater than 120/80 mmHg. Data quality control Necessary training was given for data collectors on the contents of the data collecting tool, data collection procedures and consent was obtained from head of hospital before data collection. A pretest was conducted on randomly selected 5% of the sample size (twenty-three AHF patient’s medical records) before the actual data collection. Then, adjustments were made on the tool for final data collection. The supervisors carried close supervision out daily during the data collection time. The principal investigator checked data for completeness, clarity, consistency, and accuracy. Data analysis procedures The collected data were entered to Epi-data (version 3.1), transferred to and analyzed using statistical package for social science (SPSS) version 21.0®. Quantitative variables were reported as a median and inter-quartile range. Categorical variables were presented using percentages and frequency. Bivariate and multivariate logistic regression was used to analyze factors associated with treatment outcome. Each variable with no missing value were checked for association against the outcome variable in the binary model. Then, Variables with P< 0.25 in the bivariate model analyses were entered into the multivariate model. The Binary Logistic Regression model fitness was checked by Hosmer-Lemeshow statistic. Multicollinearity test was carried out to see the correlation between independent variables using variance inflation factor (VIF). Crude odds ratio (COR) and adjusted odds ratio (AOR) were calculated with the 95% confidence interval to measure the strength of the association between the outcome and independent variables. The variable with a p-value less than 0.05 in the multivariable analysis was considered significantly associated with in-hospital mortality. Results Socio-demographic characteristics Out of 454 study participants, more than half 282(62.1%) of them were females. The median age of patients was 45 years (±28 IQR) and the highest percent 192(42.3%) of them were between the age of 40 and 61 years. About 404(89.0%) of the participants were nonsmokers ( Table 1 ). Table 1: Socio-demographic characteristics of acute heart failure adult patients treated from June 01, 2016 to May 31, 2021 at HFCSH, Harar, Eastern Ethiopia (N = 454). Variables Frequency (%) Sex Female 282(62.1) Male 172(37.9) Age in years 18-39 163(35.9) 40-61 192(42.3) 61 and above 99(21.8) Cigarette smoking history Non-smokers 404(89.0) Smoker 50(11.0) Clinical characteristics of participants Among comorbidities of AHF, patients hypertension was the most common 69(36.5%) followed by asthma 28(14.8%), ( Figure 2 ). Pneumonia 115(44.7%) followed by drug discontinuation 94(36.6%) were the major precipitating factors among acute heart failure patients. The majority of the patients had normal vital signs except blood pressure was elevated in 221(48.7%) and tachypnea in 392(86.3%) of patients at admission. Medication used for treatment of acute heart failure Among medications used treatment of AHF, furosemide was most commonly used 442(97.4%) and 358(97.3%) both in hospital and at discharge, respectively. Atenolol was the least medications used for treatment of adult patients with acute heart failure ( Table 2 ). Table 2: Medications used for treatment of adult patients with acute heart failure at HFCSH during the study period, Harar, Eastern Ethiopia, 2021 (N = 454). Medications In hospital At discharge Frequency (%) Frequency (%) Furosemide 442(97.4) 358(97.3) Spironolactone 237(52.2) 210(57.1) Enalapril 163(35.9) 152(41.3) Aspirin 129(28.4) 116(31.5) Digoxin 111(24.4) 70(19.0) Intranasal oxygen 73(16.1) - Atorvastatin 47(10.4) 38(10.3) Simvastatin 41(9.0) 28(7.6) Clopidogrel 39(8.6) 13(3.5) Dopamine 30(6.6) - Amlodipine 18(4) 8(2.2) Nifedipin 16(3.5) 7(1.9) Atenolol 7(1.5) 4(1.1) In-hospital mortality From 454 study participants, 368(81.1%) were survived and in-hospital mortality was 86 (18.9%) at a 95% CI of 15.3- 22.5. In-hospital mortality was more prevalent in the first week of admission, 61(70.9%) and median time to death was 9 days ( Table 3 ). Table 3: In-hospital mortality of acute heart failure patients at HFCSH, Harar, Eastern Ethiopia, from June 01, 2016 to May 31, 2021 (N = 454). In-hospital mortality Frequency (%) 95%CI Survived 368(81.1%) 1 In-hospital mortality 86 (18.9%) 15.3- 22.5 > 1day and week1 and 30 days 1(1.2%) Factors associated with in-hospital mortality In the bivariate model, eight variables were associated with in-hospital mortality at a p-value < 0.25. The associated variables were; Sex (P = 0.106), smoking history (P = 0.180), presence of generalized body swelling (P = 0.000), murmur sound (0.183), vomiting (0.026), blood pressure (hypotension) (P = 0.000), heart rate ((tachycardia) (P = 0.000), respiratory rate (bradypnea (P = 0.098) and tachypnea (P = 0.051)) at admission. In multivariate binary logistic regression analysis, five variables: sex(female), smoking history, presence of generalized body swelling, blood pressure (hypotension), and heart rate (tachycardia) were retained in the final models. This study showed that the odds of in-hospital mortality among females was 2.83 times than males (AOR = 2.83; 95%CI: 1.50-5.33, P = 0.001). The odds of in-hospital mortality among those who had a smoking history were 2.51 times higher (AOR = 2.51; 95%CI: 1.09-5.77, P = 0.031) when compared with those who had no smoking history. Similarly, the odds of in-hospital mortality among those who had generalized body swelling at admission were 2.67 times higher as compared to those who had no generalized body swelling (AOR = 2.67; 95%CI: 1.49-4.76, P = 0.001). In-hospital mortality among patients who had hypotension at admission was 4.56 times more likely (AOR = 4.56; 95%CI: 1.89-10.10, P = 0.001) as compared to those with normal blood pressure. The likelihoods of in-hospital mortality among those who had tachycardia at admission were 4.57 times (AOR = 4.57; 95% CI: 2.57-8.10, P = 0.000) higher as compared to those who had normal heart rates ( Table 4 ). Table 4: Factors associated with in-hospital mortality of acute heart failure patients treated at HFCSH, Harar, Ethiopia, from June 01 2016 to May 31, 2021 (N = 454) Variables Treatment outcomes Bivariate Multivariate Mortality (86) Survival (368) COR (95%CI) AOR (95%CI) Sex Male 26 146 1 1 Female 60 222 1.52(0.92-2.52) 2.83(1.50-5.33)* Smoking history Non smoker 73 331 1 1 Smoker 13 37 1.59(0.81-3.15) 2.51(1.09-5.77)* Generalized body swelling No 23 181 1 1 Yes 63 187 2.65(1.58-4.46) 2.67(1.49-4.76)* Murmur at admission No 42 209 1 1 Yes 44 159 1.38(0.86-2.20) 1.33(0.78-2.27) Vomiting at admission No 58 290 1 1 Yes 28 78 1.79(1.07-3.01) 1.70(0-94-3.07) Blood pressure at admission Normal 34 163 1 1 Hypotension 18 18 4.79(2.26-10.16) 4.56(1.89-10.10)* Elevated 34 187 0.87(0.52-1.47) 0.68(0.38-1.22) Heart rate Normal 25 230 1 1 Bradycardia 3 14 1.97(0.53-7.33) 0.73(0.08-6.91) Tachycardia 58 124 4.30(2.57-7.22) 4.57(2.57-8.10)* Respiratory rate Normal 5 51 1 1 Bradypnea 2 4 5.10(0.74-35.14) 2.32(0.11-49.55) Tachypnea 79 313 2.57(0.99-6.67) 1.87(0.64-5.55) Note : COR = Crude odds ratio; AOR = Adjusted odds ratio; *indicates significantly associated at P<0.05. Discussion The findings of this study indicated that of AHF patients were higher among young. The patients in the current study are older than previous study in Ethiopia, median 45 years versus 34 years (20). However, our patients are younger than AHF patients are in global study and in developed countries, median age of 67 to 79 years (22, 30, 31). The discrepancy might be due to high level of awareness on prevention of cardiovascular disease, age cut-point differences of participants, and life expectance of patients in developed countries. The overall in-hospital mortality was found to be 18.9% at a 95% confidence interval of 15.3% to 22.5%. Being female, having a smoking history, presence of generalized body swelling, hypotension, and tachycardia at admission were factors associated with in-hospital mortality. The magnitude of in-hospital mortality found in this study is 18.9% in the current study. A prospective study conducted at Tikur Anbessa Specialized Hospital, Ethiopia (17.2%) (20), and a retrospective study conducted at Yaoundé Central Hospital, Cameroon (18.45%) (32) reported similar magnitude of in-hospital mortality. On the other hand, the finding of this study is higher than the studies reported from Gondar Comprehensive Specialized Hospital (10.6%) (29); Middle East and North Africa (5.4%) (16); and European and Mediterranean countries 5.3% (23). This could be due to advanced health care service in these study settings as they included patients from developed countries. However, it is lower than the study conducted in Addis Ababa, Ethiopia (24.4%) (25). The discrepancy might be due to patient’s age difference, patient care process and setting differences. In this study, in-hospital mortality among females was 2.83 times more likely as compared to males. This might be attributable to a high proportion of female patients (62.1%) in this study. The finding is similar with the result reported from study conducted at St. Paul’s Hospital Millennium Medical College in Addis Ababa that showed the association of female sex with in-hospital mortality among heart failure patients (25). The odds of in-hospital mortality were more than double among those who had a smoking history than those who had no smoking history. Cigarette smoking is well-established cardiovascular risk factor. It makes the heart work harder due to its blood pressure increasing effect and thus, negatively affect the treatment outcome of AHF (33, 34). Other studies also showed an association between smoking and in-hospital mortality among AHF patients (20, 35). In-hospital mortality among patients who had generalized body swelling at admission was found to be 2.67 times more likely as compared to those who had no generalized body swelling at admission in the current study. Generalized body swelling is the result of the activation of a series of humoral and neurohumoral mechanisms that promote sodium and water reabsorption by the kidneys and expansion of the extracellular fluid. It occurs after signs of dyspnea and fatigue, which means it is not an early sign of heart failure, indicating that the acute heart failure patients with generalized body swelling is relatively at an advanced stage which negatively affects the outcome of the treatment (36). There was significant differences in clinical characteristics such as hypotension between survivors and non-survivors among acute heart failure patients (25). In-hospital mortality among patients who had hypotension was more than four times as compare to normotensive patients in present study. This may be due to the life threatening effect of shock. This finding is supported by other different studies (1, 25, 35, 37, 38). The odds of in-hospital mortality were more than four times higher among those who had tachycardia than those with normal heart rates in this study. The possible explanation is that as tachycardia is a compensatory mechanism in heart failure to meet the body’s oxygen and nutrient requirement, over time it causes a rapid decline in left ventricular function and worsens the acutely failed heart resulting in poor treatment outcome (death). This finding is almost similar with other studies that showed mortality rate is higher among patients with tachycardia (24, 25, 35). Strength and limitations of the study Although this study is among a few of its kind and it can serve as a stepping-stone for further investigation, it has some limitations. First, the study was based on a retrospective chart review. Thus, due to poor documentation, important variables like adherence and adverse drug effect were missed. This might have influenced the results. Second, the data was collected from a single health facility and generalizability of the results is limited. Finally, since this study used cross-sectional study design, it cannot make a causal inference. Therefore, the authors recommend further follow-up study with stronger study design to address these limitations. Conclusions In this study, in-hospital mortality is very high, which is almost one in six among patients admitted to HFCSH with AHF. Being female, having a smoking history, presences of generalized body swelling, hypotension, and tachycardia at admission were variables found to be significantly associated with in-hospital mortality among patients with AHF. Therefore, the current study outlined that there is a need for the reduction of in-hospital mortality among adult patients with acute heart failure in hospitals. Furthermore, a prospective research with strong design regarding in-hospital mortality and its associated factors among AHF is need to be conducted to investigate the problem in-depth and to establish causality. Abbreviations ACEI: Angiotensin-Converting Enzyme Inhibitors; ADHF: Acute Decompensated Heart Failure; AHF: Acute Heart Failure: HFCSH: Hiwot Fana Comprehensive Specialized Hospital; LVSD: Left ventricular systolic dysfunction; and SBP: Systolic blood pressure. Declarations Ethics approval and consent to participate Ethical clearance was obtained from Haramaya University, College of Health and Medical Sciences, Institutional Health Research Ethics Review Committee (IHRERC) with a reference number of IHRERC/131/2021 and all methods were performed in accordance with Declaration of Helsinki . Written information sheet and consent, which explained the study, was provided to the medical director of HFCSH ( Additional file 2 ). Then, officials at different levels in the hospital were communicated through formal letters. Consent from all participants and/or their legal guardian(s) was not relevant for this study because data were collected from patient’s records, not directly from patients. The information collected in this study was kept confidential through not writing the name of patient on data collection tool. Only medical record number was used for identification. Data collectors informed and trained to preserve confidentiality of the patient information and the investigators used only for the study. Consent for publication Not applicable Availability of data and materials All data generated or analyzed during this study are included in this manuscript. Data collection tool submitted with manuscript as Annexes (supplementary information files) and raw data can be accessible upon request from the authors. Competing interests The authors have no competing interests. Funding The authors did not receive any fund for this research from any funding agency. Authors’ contributions CD is principal author responsible for designing the study, data collection and analysis, and interpretation of the findings. CD, FA and JA are responsible in the conception. CD, FA, SN, JA, AJ and MD participated in study design, analysis and interpretation of the findings. MD and AJ drafted the manuscript. All authors read, revised and approved the final manuscript for submission. Acknowledgments Before all, we would like to acknowledge our staffs for providing constructive comments and suggestions in writing this research paper. We would also like to express our sincere thanks to Haramaya University research ethical committee for evaluating the paper. In addition, we would like to forward our gratitude to Hiwot Fana Comprehensive Specialized Hospital (HFCSH) mangers for allowing us to conduct this study in this setting and to the staff for their cooperation. 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Acute myocardial infarction and acute heart failure in the Middle East and North Africa: Study design and pilot phase study results from the PEACE MENA registry. PloS one. 2020;15(7):e0236292. Bukhman AK, Nsengimana VJP, Lipsitz MC, Henwood PC, Tefera E, Rouhani SA, et al. Diagnosis and management of acute heart failure in sub-Saharan Africa. Current cardiology reports. 2019;21(10):1-8. Carlson S, Duber HC, Achan J, Ikilezi G, Mokdad AH, Stergachis A, et al. Capacity for diagnosis and treatment of heart failure in sub-Saharan Africa. Heart. 2017;103(23):1874-9. Negesa LB, Magarey J, Rasmussen P, Hendriks JM. Patients’ knowledge on cardiovascular risk factors and associated lifestyle behaviour in Ethiopia in 2018: A cross-sectional study. Plos one. 2020;15(6):e0234198. Tirfe M, Nedi T, Mekonnen D, Berha AB. Treatment outcome and its predictors among patients of acute heart failure at a tertiary care hospital in Ethiopia: a prospective observational study. BMC cardiovascular disorders. 2020;20(1):16. Tsega TA, Demissei BG. A systematic review of epidemiology, treatment and prognosis of heart failure in adults in Ethiopia. Journal of Cardiovascular Medicine. 2018;19(3):91-7. Filippatos G, Angermann CE, Cleland JGF, Lam CSP, Dahlström U, Dickstein K, et al. Global Differences in Characteristics, Precipitants, and Initial Management of Patients Presenting With Acute Heart Failure. JAMA cardiology. 2020;5(4):401-10. Chioncel O, Mebazaa A, Maggioni AP, Harjola VP, Rosano G, Laroche C, et al. Acute heart failure congestion and perfusion status - impact of the clinical classification on in-hospital and long-term outcomes; insights from the ESC-EORP-HFA Heart Failure Long-Term Registry. European journal of heart failure. 2019;21(11):1338-52. Jia Q, Wang YR, He P, Huang XL, Yan W, Mu Y, et al. Prediction model of in-hospital mortality in elderly patients with acute heart failure based on retrospective study. Journal of geriatric cardiology: JGC. 2017;14(11):669. woldeyes Asfaw E. Five years clinical characteristics and in hospital outcome of acute heart failure at tertiary care hospital in Ethiopia. Ethiopian Medical Journal. 2020;58(01). Abebe SM, Andargie G, Shimeka A, Alemu K, Kebede Y, Wubeshet M, et al. The prevalence of non-communicable diseases in Northwest Ethiopia: survey of Dabat health and demographic surveillance system. BMJ open. 2017;7(10). Bane A, Bayisa T, Adamu F, Abdissa SG. Medical admissions and outcomes at Saint Paul’s Hospital, Addis Ababa, Ethiopia: a retrospective study. Ethiopian Journal of Health Development. 2016;30(1):50-6. Rodgers BNRaJE. Acute Decompensated Heart Failure. book chapter 36. 2020;11th edition. Tigabe M, Fentahun A, Getawa S, Gelaye KA, Gebreyohannes EA. Clinical Characteristics and In-Hospital Outcome of Acute Heart Failure Patients Admitted to the Medical Ward of University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia. Vascular Health and Risk Management. 2021;17:581. Storrow AB, Jenkins CA, Self WH, Alexander PT, Barrett TW, Han JH, et al. The burden of acute heart failure on US emergency departments. JACC: Heart Failure. 2014;2(3):269-77. Logeart D, Isnard R, Resche‐Rigon M, Seronde MF, De Groote P, Jondeau G, et al. Current aspects of the spectrum of acute heart failure syndromes in a real‐life setting: the OFICA study. European journal of heart failure. 2013;15(4):465-76. Boombhi J. Clinical pattern and outcome of acute heart failure at the Yaounde Central Hospital. Open Access Library Journal. 2017;4(03):1. Meijers WC, de Boer RA. Common risk factors for heart failure and cancer. Cardiovascular research. 2019;115(5):844-53. Ahmed AA, Patel K, Nyaku MA, Kheirbek RE, Bittner V, Fonarow GC, et al. Risk of heart failure and death after prolonged smoking cessation: role of amount and duration of prior smoking. Circulation: Heart Failure. 2015;8(4):694-701. Abdellah AT, Mohamed AD, Hendawi HA, Omera MA. Clinical and laboratory characteristics of short-term mortality in Egyptian patients with acute heart failure. The Egyptian Heart Journal. 2017;69(3):201-8. Rodgers BNRaJE. Acute Decompensated Heart Failure. 2017:673-732. Lee SE, Lee H-Y, Cho H-J, Choe W-S, Kim H, Choi JO, et al. Clinical characteristics and outcome of acute heart failure in Korea: results from the Korean Acute Heart Failure Registry (KorAHF). Korean circulation journal. 2017;47(3):341-53. Spinar J, Parenica J, Vitovec J, Widimsky P, Linhart A, Fedorco M, et al. Baseline characteristics and hospital mortality in the Acute Heart Failure Database (AHEAD) Main registry. Critical care. 2011;15(6):1-13. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2775153","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":361475222,"identity":"ccd205a7-7224-4795-9920-2b4f6a104eab","order_by":0,"name":"Chala Deriba","email":"","orcid":"","institution":"Bisidimo Health Science College","correspondingAuthor":false,"prefix":"","firstName":"Chala","middleName":"","lastName":"Deriba","suffix":""},{"id":361475223,"identity":"3770ae93-900f-481c-ba59-1d5b1bac3a72","order_by":1,"name":"Abera Jambo","email":"","orcid":"","institution":"Haramaya 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07:59:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2775153/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2775153/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66069554,"identity":"0a4f4d9b-5248-4c88-bea7-0767730a6b20","added_by":"auto","created_at":"2024-10-07 11:51:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":41667,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of sampling procedure for study on in-hospital mortality and its associated factors among adult acute heart failure patients at HFCSH, Harar, Ethiopia 2021.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2775153/v1/f70b9b04adb1ac7c0d81c28d.png"},{"id":66069274,"identity":"fa915865-e581-451a-9e80-2d50f2490428","added_by":"auto","created_at":"2024-10-07 11:43:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":42330,"visible":true,"origin":"","legend":"\u003cp\u003eComorbidities among acute heart failure patients treated at HFCSH, Harar, Ethiopia, from June 01, 2016 to May 31, 2021.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2775153/v1/7424d6a4ad1f10781dd4bf0d.png"},{"id":66069555,"identity":"d5b62f89-7223-40e7-a6c8-bf06a16e899f","added_by":"auto","created_at":"2024-10-07 11:51:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":871570,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2775153/v1/e1cf7fa0-3e17-4b7b-9f2c-beb843e095b7.pdf"},{"id":66067888,"identity":"e6dd07f7-8a0d-415a-a6b8-153b05209b53","added_by":"auto","created_at":"2024-10-07 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11:43:52","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":33184,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEchecklistv4combined.docx","url":"https://assets-eu.researchsquare.com/files/rs-2775153/v1/d8c3584813e8b381b49217e8.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"In-hospital Mortality and Associated Factors among Adult Patients with Acute Heart Failure in a Tertiary Hospital, Harar, Eastern Ethiopia: A Cross-Sectional Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHeart failure (HF) is a clinical syndrome characterized by classic symptoms and signs which occurs on exertion or at rest (1). HF is caused by a structural and/or functional cardiac abnormality, resulting in reduced cardiac output and/or elevated intra-cardiac pressure. This pressure impairs the ability of the heart to fill with blood at normal pressure or eject blood adequate to fulfill the needs of the metabolizing organs. HF remains a major cause of mortality and morbidity (2, 3, 4).\u003c/p\u003e\n\u003cp\u003eAcute heart failure (AHF) is defined as a gradual or rapid change in heart failure syndromes, which poses a unique diagnostic and management challenge and requires urgent therapy (5). AHF also covers a wide range of the spectrum, which ranges from mild exacerbations with gradual increases in edema to cardiogenic shock (6). These symptoms in AHF are the result of severe pulmonary congestion due to reduced left ventricular filling pressures with or without low cardiac output (7).\u003c/p\u003e\n\u003cp\u003eAHF\u0026nbsp; is responsible for nearly one million hospitalizations each year with rising rates and after initial hospitalization, 25% of patients are readmitted at 30 days, 35% of which are due to a new exacerbation (8). In Africa, 7% to 10% of all medical admissions to hospitals are due to cardiovascular disease, with heart failure contributing to 3% to 7% (9). There were no data on the prevalence of heart failure in the general population in Ethiopia. A study in single setting at Dabat district, northwest Ethiopia, revealed that out of 216,420 populations 32.2% had heart disease. Hospitalization due to AHF is associated with several factors and comorbidities like older age, female gender, hyperuricemia, obesity, atrial fibrillation, peripheral artery disease, and chronic kidney disease (10).\u003c/p\u003e\n\u003cp\u003eOnce diagnosed, AHF patients may be classified using different methods based on presentation. Depending on whether patients have a history of HF or not, it is classified as \u0026ldquo;acute decompensated heart failure (ADHF) which occurs in patients with heart failure history and De novo AHF that occurs in individuals with no history of heart failure\u0026rdquo;.\u0026nbsp; Based on systolic blood pressure (SBP) at presentation, AHF is classified as \u0026ldquo;hypertensive AHF (SBP \u003cu\u003e\u0026gt;\u003c/u\u003e 140mmHg), normotensive AHF (SBP is between 90-140mmHg), and hypotensive AHF (SBP \u003cu\u003e\u0026lt;\u003c/u\u003e 90mmHg)\u0026rdquo;. Depending on the hemodynamic condition of the patients, it is classified as \u0026ldquo;warm and dry (well-perfused without congestion), warm and wet (well-perfused but congested), cold and dry (hypo-perfusion without congestion), and cold and wet (hypo-perfusion and congestion)\u0026rdquo;. Based on left ventricular ejection fraction (LVEF), AHF is classified as \u0026ldquo;AHF with reduced ejection fraction and AHF with preserved ejection fraction\u0026rdquo; (11).\u003c/p\u003e\n\u003cp\u003eDepending on congestive and organ perfusion status the management approaches of AHF involves relief of symptoms, restoration of systemic tissue perfusion via improved cardiac output and minimization of further cardiac damage. These can be attained by using diuretics, neuro-hormonal antagonists and inotropes (12, 13). Despite therapeutic advances, the prognosis of AHF is poor and re-hospitalization is high which is\u0026nbsp; 25% to 30% (14). HF in general is associated with a huge economic burden which the overall cost is estimated at $108 billion globally and $28 million in Ethiopia per annum(15).\u003c/p\u003e\n\u003cp\u003eThe burden of AHF is high in resource-limited countries where patient\u0026rsquo;s low levels of education and income also contribute(16). In sub-Saharan Africa, many of the equipment and drugs commonly used to diagnose and treat AHF in resource-rich settings are lacking (17, 18). In Ethiopia, in addition to this lack of equipment and drugs, knowledge about cardiovascular risk factors is at suboptimal levels (46%) (19) and AHF patients are of middle age (20, 21); this is an additional burden due to the impact on productivity.\u003c/p\u003e\n\u003cp\u003eRegarding in-hospital mortality from AHF, it is 1.5% to 5.3% in developed countries (22, 23, 24). However, it is very high in Ethiopia (17.2% to 24.4%) (20, 25). One single setting study showed a high burden of the HF (32.2% of the population had heart disease) and household food insecurity was among factors associated with the non-communicable disease which include heart disease (26); HF is the third most common reason for immediate admissions, with a prevalence of 16.0% among patients admitted to medical wards (27) .\u003c/p\u003e\n\u003cp\u003eThroughout the country, hospital-based studies on AHF that look into in-hospital mortality of the disease and its associated factors are scarce and are lacking in this study setting. Therefore, this study aimed to assess in-hospital mortality and its associated factors among adult patients with acute heart failure Fana Comprehensive Specialized Hospital from 15 July to 14 August 2021, Harar, Ethiopia.\u003c/p\u003e\n\u003cp\u003eThis study provide insights regarding in-hospital mortality of AHF and its associated factors among adult patients. Therefore,\u0026nbsp; primarily it encourage hospital managers and each health professionals who participate in patient care to take measure in the spirit of improving the treatment outcome of AHF by forwarding necessary recommendations for possible changes and to scale up current standard of care in HFSCH and other similar hospitals. This study is also a stepping-stone for the study setting to alarm other researchers to investigate the problem in-depth throughout the country. Furthermore, the finding of this study can be used as input for development of treatment guidelines need to be modified for the future at the national level.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003ch2\u003eStudy design, setting, and period\u003c/h2\u003e\n\u003cp\u003eThe retrospective cross-sectional study was conducted from July 15 to August 14, 2021 at Hiwot Fana Comprehensive Specialized Hospital (HFCSH), Eastern Ethiopia. HFCSH is a specialized hospital in Eastern Ethiopia, which is found in Harar town, 526 kilometers from Addis Ababa, the capital city of Ethiopia. It is serving as a referral hospital for the entire eastern part of the country including Eastern Oromia, Dire Dawa city administration, Harari, and Somali regional states. There are different wards and clinics within the hospital that provide services for the community such as medical ward, pediatric ward, surgery ward, gynecologic and obstetrics ward, oncology ward, antenatal clinic, dental clinic, a tuberculosis clinic, ante-retroviral therapy clinic, dermatology clinic, and ophthalmologic clinic. The medical ward has 22 beds.\u003c/p\u003e\n\u003ch2\u003ePopulation\u003c/h2\u003e\n\u003cp\u003eAll adult patients with a diagnosis of AHF treated at HFCSH were source population. All adult patients with a diagnosis of AHF treated at HFCSH in the past five years (from June 01, 2016 to May 31, 2021) who fulfilled the inclusion criteria were the study population.\u003c/p\u003e\n\u003ch2\u003eEligibility criteria\u003c/h2\u003e\n\u003cp\u003eAll adult patients whose was age less than 18 years with a confirmed diagnosis of AHF and treated during the data retrieval period at the medical ward of HFCSH were included in this study. However, all patients with unknown outcome (referred or disappeared) and lost and/or incomplete patients\u0026rsquo; medical records were excluded from the study.\u003c/p\u003e\n\u003ch2\u003eSample size determination\u003c/h2\u003e\n\u003cp\u003eFor the first two objectives sample size of the study was calculated using single population proportion formula by considering the following assumptions: prevalence of in-hospital mortality (P) = 17.2% taken from another similar study (20), confidence level (CI) = 95% and corresponding Z score of 1.96, margin of error (W) = 5%. Thus sample size was, n = (Z\u0026alpha;/\u003csub\u003e2\u003c/sub\u003e)\u003csup\u003e2\u003c/sup\u003e p (1-p) /w\u003csup\u003e2\u003c/sup\u003e = (1.96)\u003csup\u003e2\u003c/sup\u003e*0.172*0.828/ (0.05)\u003csup\u003e2\u003c/sup\u003e = 218.8. For the objective of factors associated with in-hospital mortality sample size was calculated using Epi-Info version 7.2.4.0 (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eTable 1: Sample size calculation for factors associated with in-hospital mortality of acute heart failure patients using Epi-Info software (version 7.2.4.0).\u003c/p\u003e\n\u003ctable border=\"1\" width=\"117%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeterminants of treatment outcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAssumptions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% Exposed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% unexposed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample size (N)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003eCI:95% Power:80% Ratio:1:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e44.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14%;\"\u003e\n \u003cp\u003e(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003eDiabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003eCI:95% Power:80% Ratio:1:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14%;\"\u003e\n \u003cp\u003e(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003ePulmonary hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003eCI:95% Power:80% Ratio:1:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003e41.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14%;\"\u003e\n \u003cp\u003e(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003eChronic kidney disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003eCI:95% Power:80% Ratio:1:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e39.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003e22.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14%;\"\u003e\n \u003cp\u003e(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003eHeart rate \u0026gt; 100beats/min at presentation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003eCI:95% Power:80% Ratio:1:1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e34.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16%;\"\u003e\n \u003cp\u003e47.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14%;\"\u003e\n \u003cp\u003e(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003e412\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCI = Confidence interval\u003c/p\u003e\n\u003cp\u003eTherefore, by adding 10% for contingency on the largest sample size, the calculated sample size was found to be 454 adult patients with AHF.\u003c/p\u003e\n\u003ch2\u003eSampling procedures and sampling techniques\u003c/h2\u003e\n\u003cp\u003eThe 907 adult patients were treated at HFCSH for AHF during the last five years. That is 121, 144, 201, 199, 242 patients from June 01, 2016, to May 31, 2021, each year respectively. For this study, record numbers of those patients\u0026rsquo; medical records were obtained from the medical registration book of the Medical ward of HFCSH. Finally, 454 patients\u0026rsquo; medical records included in the study were selected using proportionally allocated simple random sampling technique (\u003cstrong\u003eFigure 1\u003c/strong\u003e).\u003c/p\u003e\n\u003ch2\u003eData collection method\u003c/h2\u003e\n\u003cp\u003eData were collected from patients\u0026rsquo; medical records using an English version of structured and pretested data abstraction format prepared by reviewing different pieces of literature on similar topics, which consists of socio-demographic information, vital signs at presentation, clinical presentations, comorbidities, laboratory and radiologic findings (\u003cstrong\u003eAdditional file 1)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eRecord numbers of the individual patients\u0026rsquo; medical cards were obtained from medical registration book of Medical ward, and the numbers of those patients\u0026rsquo; medical cards to be included in the study were randomly selected using lottery method. Then using randomly selected numbers, patients\u0026rsquo; medical cards were drawn from the hospital card room. In-hospital mortality was confirmed by principal investigator from discharge summary. Finally, the data were collected from those medical cards by two clinical pharmacists and one clinical nurse.\u003c/p\u003e\n\u003ch2\u003eOperational definitions\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eAcute heart failure\u003c/strong\u003e:- sign and symptoms of new-onset of heart failure or decompensation or worsening of chronic stable heart failure (ADHF) (2, 28)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn-hospital mortality\u003c/strong\u003e: - AHF patient died in the hospital after he/she was admitted to the medical ward which confirmed by physician\u0026rsquo;s death summary (29).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eElevated blood pressure\u003c/strong\u003e: - systemic blood pressure of greater than 120/80 mmHg.\u003c/p\u003e\n\u003ch2\u003eData quality control\u003c/h2\u003e\n\u003cp\u003eNecessary training was given for data collectors on the contents of the data collecting tool, data collection procedures and consent was obtained from head of hospital before data collection. A pretest was conducted on randomly selected 5% of the sample size (twenty-three AHF patient\u0026rsquo;s medical records) before the actual data collection. Then, adjustments were made on the tool for final data collection. The supervisors carried close supervision out daily during the data collection time. The principal investigator checked data for completeness, clarity, consistency, and accuracy.\u003c/p\u003e\n\u003ch2\u003eData analysis procedures\u003c/h2\u003e\n\u003cp\u003eThe collected data were entered to Epi-data (version 3.1), transferred to and analyzed using statistical package for social science (SPSS) version 21.0\u0026reg;. Quantitative variables were reported as a median and inter-quartile range. Categorical variables were presented using percentages and frequency. Bivariate and multivariate logistic regression was used to analyze factors associated with treatment outcome. Each variable with no missing value were checked for association against the outcome variable in the binary model. Then, Variables with P\u0026lt;\u0026nbsp;0.25 in the bivariate model analyses were entered into the multivariate model.\u003c/p\u003e\n\u003cp\u003eThe Binary Logistic Regression model fitness was checked by Hosmer-Lemeshow statistic. Multicollinearity test was carried out to see the correlation between independent variables using variance inflation factor (VIF). Crude odds ratio (COR) and adjusted odds ratio (AOR) were calculated with the 95% confidence interval to measure the strength of the association between the outcome and independent variables. The variable with a p-value less than 0.05 in the multivariable analysis was considered significantly associated with in-hospital mortality.\u003c/p\u003e"},{"header":"Results","content":"\u003ch3\u003eSocio-demographic characteristics\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eOut of 454 study participants, more than half 282(62.1%) of them were females. The median age of patients was 45 years (\u0026plusmn;28 IQR) and the highest percent 192(42.3%) of them were between the age of 40 and 61 years. About 404(89.0%) of the participants were nonsmokers (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eTable 1:\u0026nbsp;Socio-demographic characteristics of acute heart failure adult patients treated from June 01, 2016 to May 31, 2021 at HFCSH, Harar, Eastern Ethiopia (N = 454).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"602\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8405%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52.1595%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8405%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52.1595%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8405%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52.1595%;\"\u003e\n \u003cp\u003e282(62.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8405%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52.1595%;\"\u003e\n \u003cp\u003e172(37.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8405%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge in years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52.1595%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8405%;\"\u003e\n \u003cp\u003e18-39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52.1595%;\"\u003e\n \u003cp\u003e163(35.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8405%;\"\u003e\n \u003cp\u003e40-61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52.1595%;\"\u003e\n \u003cp\u003e192(42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8405%;\"\u003e\n \u003cp\u003e61 and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52.1595%;\"\u003e\n \u003cp\u003e99(21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8405%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCigarette smoking history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52.1595%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8405%;\"\u003e\n \u003cp\u003eNon-smokers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52.1595%;\"\u003e\n \u003cp\u003e404(89.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 47.8405%;\"\u003e\n \u003cp\u003eSmoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52.1595%;\"\u003e\n \u003cp\u003e50(11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eClinical\u0026nbsp;characteristics of participants\u003c/h2\u003e\n\u003cp\u003eAmong comorbidities of AHF, patients hypertension was the most common 69(36.5%) followed by asthma 28(14.8%), (\u003cstrong\u003eFigure 2\u003c/strong\u003e). Pneumonia 115(44.7%) followed by drug discontinuation 94(36.6%) were the major precipitating factors among acute heart failure patients. The majority of the patients had normal vital signs except blood pressure was elevated in 221(48.7%) and tachypnea in 392(86.3%) of patients at admission.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch2\u003eMedication used for treatment of acute heart failure\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eAmong medications used treatment of AHF, furosemide was most commonly used 442(97.4%) and 358(97.3%) both in hospital and at discharge, respectively. \u0026nbsp;Atenolol was the least medications used for treatment of adult patients with acute heart failure (\u003cstrong\u003eTable 2\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eTable 2:\u0026nbsp;Medications used for treatment of adult patients with acute heart failure at HFCSH during the study period, Harar, Eastern Ethiopia, 2021 (N = 454).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"639\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMedications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIn hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAt discharge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eFrequency (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eFrequency (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eFurosemide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e442(97.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e358(97.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eSpironolactone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e237(52.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e210(57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eEnalapril\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e163(35.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e152(41.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eAspirin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e129(28.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e116(31.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eDigoxin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e111(24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e70(19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eIntranasal oxygen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e73(16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eAtorvastatin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e47(10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e38(10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eSimvastatin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e41(9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e28(7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eClopidogrel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e39(8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e13(3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eDopamine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e30(6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eAmlodipine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e18(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e8(2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eNifedipin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e16(3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e7(1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003eAtenolol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e7(1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e4(1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eIn-hospital mortality \u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eFrom 454 study participants, 368(81.1%) were survived and in-hospital mortality was 86 (18.9%) at a 95% CI of 15.3- 22.5. In-hospital mortality was more prevalent in the first week of admission, 61(70.9%) and median time to death was 9 days (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3: In-hospital mortality of acute heart failure patients at HFCSH, Harar, Eastern Ethiopia, from June 01, 2016 to May 31, 2021 (N = 454).\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"632\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIn-hospital mortality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSurvived\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e368(81.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIn-hospital mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e86 (18.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.3- 22.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cu\u003e\u0026gt;\u003c/u\u003e1day and \u003cu\u003e\u0026lt;\u003c/u\u003e week 1 of admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61(70.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt; week1 and \u003cu\u003e\u0026lt;\u003c/u\u003e 30 days admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24(27.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;30 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1(1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\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\u003ch2\u003eFactors associated with in-hospital mortality\u003c/h2\u003e\n\u003cp\u003eIn the bivariate model, eight variables were associated with in-hospital mortality at a p-value \u0026lt; 0.25. The associated variables were; Sex (P = 0.106), smoking history (P = 0.180), presence of generalized body swelling (P = 0.000), murmur sound (0.183), vomiting (0.026), blood pressure (hypotension) (P = 0.000), heart rate ((tachycardia) (P = 0.000), respiratory rate (bradypnea (P = 0.098) and tachypnea (P = 0.051)) at admission. In multivariate binary logistic regression analysis, five variables: sex(female), smoking history, presence of generalized body swelling, blood pressure (hypotension), and heart rate (tachycardia) were retained in the final models.\u003c/p\u003e\n\u003cp\u003eThis study showed that the odds of in-hospital mortality among females was 2.83 times than males (AOR = 2.83; 95%CI: 1.50-5.33, P = 0.001). The odds of in-hospital mortality among those who had a smoking history were 2.51 times higher (AOR = 2.51; 95%CI: 1.09-5.77, P = 0.031) when compared with those who had no smoking history. Similarly, the odds of in-hospital mortality among those who had generalized body swelling at admission were 2.67 times higher as compared to those who had no generalized body swelling (AOR = 2.67; 95%CI: 1.49-4.76, P = 0.001). In-hospital mortality among patients who had hypotension at admission was 4.56 times more likely (AOR = 4.56; 95%CI: 1.89-10.10, P = 0.001) as compared to those with normal blood pressure. The likelihoods of in-hospital mortality among those who had tachycardia at admission were 4.57 times (AOR = 4.57; 95% CI: 2.57-8.10, P = 0.000) higher as compared to those who had normal heart rates (\u003cstrong\u003eTable 4\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eTable 4: \u0026nbsp;Factors associated with in-hospital mortality of acute heart failure patients treated at HFCSH, Harar, Ethiopia, from June 01 2016 to May 31, 2021 (N = 454)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"761\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment outcomes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eMortality (86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eSurvival (368)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eCOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eAOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.52(0.92-2.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.83(1.50-5.33)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eSmoking history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Non smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.59(0.81-3.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.51(1.09-5.77)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eGeneralized body swelling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e2.65(1.58-4.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.67(1.49-4.76)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eMurmur at admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.38(0.86-2.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1.33(0.78-2.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eVomiting at admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.79(1.07-3.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1.70(0-94-3.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eBlood pressure at admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Normal \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Hypotension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e4.79(2.26-10.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.56(1.89-10.10)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Elevated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.87(0.52-1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e0.68(0.38-1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eHeart rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Bradycardia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.97(0.53-7.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e0.73(0.08-6.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Tachycardia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e4.30(2.57-7.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.57(2.57-8.10)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eRespiratory rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Bradypnea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e5.10(0.74-35.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e2.32(0.11-49.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Tachypnea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e2.57(0.99-6.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1.87(0.64-5.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e: COR = Crude odds ratio; AOR = Adjusted odds ratio; *indicates significantly associated at P\u0026lt;0.05.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings of this study indicated that of AHF patients were higher among young. The patients in the current study are older than previous study in Ethiopia, median 45 years versus 34 years (20). However, our patients are younger than AHF patients are in global study and in developed countries, median age of 67 to 79 years (22, 30, 31). The discrepancy might be due to high level of awareness on prevention of cardiovascular disease, age cut-point differences of participants, and life expectance of patients in developed countries. The overall in-hospital mortality was found to be 18.9% at a 95% confidence interval of 15.3% to 22.5%. Being female, having a smoking history, presence of generalized body swelling, hypotension, and tachycardia at admission were factors associated with in-hospital mortality.\u003c/p\u003e\n\u003cp\u003eThe magnitude of in-hospital mortality found in this study is 18.9% in the current study. A prospective study conducted at Tikur Anbessa Specialized Hospital, Ethiopia (17.2%) (20), and a retrospective study conducted at Yaound\u0026eacute; Central Hospital, Cameroon (18.45%) (32) reported similar magnitude of in-hospital mortality. On the other hand, the finding of this study is higher than the studies reported from Gondar Comprehensive Specialized Hospital (10.6%) (29); Middle East and North Africa (5.4%) (16); and European and Mediterranean countries 5.3% (23). This could be due to advanced health care service in these study settings as they included patients from developed countries. However, it is lower than the study conducted in Addis Ababa, Ethiopia (24.4%) (25). The discrepancy might be due to patient\u0026rsquo;s age difference, patient care process and setting differences.\u003c/p\u003e\n\u003cp\u003eIn this study, in-hospital mortality among females was 2.83 times more likely as compared to males. This might be attributable to a high proportion of female patients (62.1%) in this study. The finding is similar with the result reported from study conducted at St. Paul\u0026rsquo;s Hospital Millennium Medical College in Addis Ababa that showed the association of female sex with in-hospital mortality among heart failure patients (25).\u003c/p\u003e\n\u003cp\u003eThe odds of in-hospital mortality were more than double among those who had a smoking history than those who had no smoking history. Cigarette smoking is well-established cardiovascular risk factor. It makes the heart work harder due to its blood pressure increasing effect and thus, negatively affect the treatment outcome of AHF (33, 34). Other studies also showed an association between smoking and in-hospital mortality among AHF patients (20, 35).\u003c/p\u003e\n\u003cp\u003eIn-hospital mortality among patients who had generalized body swelling at admission was found to be 2.67 times more likely as compared to those who had no generalized body swelling at admission in the current study. Generalized body swelling\u0026nbsp;is the result of the activation of a series of humoral and neurohumoral mechanisms that promote sodium and water reabsorption by the kidneys and expansion of the extracellular fluid. It occurs after signs of dyspnea and fatigue, which means it is not an early sign of heart failure, indicating that the acute heart failure patients with generalized body swelling is relatively at an advanced stage which negatively affects the outcome of the treatment (36).\u003c/p\u003e\n\u003cp\u003eThere was significant differences in clinical characteristics such as hypotension between survivors and non-survivors among acute heart failure patients (25). In-hospital mortality among patients who had hypotension was more than four times as compare to normotensive patients in present study. This may be due to the life threatening effect of shock. This finding is supported by other different studies (1, 25, 35, 37, 38).\u003c/p\u003e\n\u003cp\u003eThe odds of in-hospital mortality were more than four times higher among those who had tachycardia than those with normal heart rates in this study. The possible explanation is that as tachycardia is a compensatory mechanism in heart failure to meet the body\u0026rsquo;s oxygen and nutrient requirement, over time it causes a rapid decline in left ventricular function and worsens the acutely failed heart resulting in poor treatment outcome (death). This finding is almost similar with other studies that showed mortality rate is higher among patients with tachycardia (24, 25, 35).\u003c/p\u003e\n\u003ch1\u003eStrength and limitations of the study\u003c/h1\u003e\n\u003cp\u003eAlthough this study is among a few of its kind and it can serve as a stepping-stone for further investigation, it has some limitations. First, the study was based on a retrospective chart review. Thus, due to poor documentation, important variables like adherence and adverse drug effect were missed. This might have influenced the results. Second, the data was collected from a single health facility and generalizability of the results is limited. Finally, since this study used cross-sectional study design, it cannot make a causal inference. Therefore, the authors recommend further follow-up study with stronger study design to address these limitations.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this study, in-hospital mortality is very high, which is almost one in six among patients admitted to HFCSH with AHF. Being female, having a smoking history, presences of generalized body swelling, hypotension, and tachycardia at admission were variables found to be significantly associated with in-hospital mortality among patients with AHF. Therefore,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ethe current study outlined that there is a need for the reduction of in-hospital mortality among adult patients with acute heart failure in hospitals. Furthermore, a prospective research with strong design regarding in-hospital mortality and its associated factors among AHF is need to be conducted to investigate the problem in-depth and to establish causality.\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACEI: Angiotensin-Converting Enzyme Inhibitors; ADHF: Acute Decompensated Heart Failure; AHF: Acute Heart Failure: HFCSH: Hiwot Fana Comprehensive Specialized Hospital; LVSD: Left ventricular systolic dysfunction; and SBP: Systolic blood pressure.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance was obtained from Haramaya University, College of Health and Medical Sciences, Institutional Health Research Ethics Review Committee (IHRERC) with a reference number of \u003cstrong\u003eIHRERC/131/2021\u0026nbsp;\u003c/strong\u003eand all methods were performed in accordance with \u003cstrong\u003eDeclaration of Helsinki\u003c/strong\u003e. Written information sheet and consent, which explained the study, was provided to the medical director of HFCSH (\u003cstrong\u003eAdditional file 2\u003c/strong\u003e). Then, officials at different levels in the hospital were communicated through formal letters. Consent from all participants and/or their legal guardian(s) was not relevant for this study because data were collected from patient\u0026rsquo;s records, not directly from patients. The information collected in this study was kept confidential through not writing the name of patient on data collection tool. Only medical record number was used for identification. Data collectors informed and trained to preserve confidentiality of the patient information and the investigators used only for the study. \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Not applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this manuscript. Data collection tool submitted with manuscript as Annexes\u0026nbsp;(supplementary information files) and raw data can be accessible upon request from the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors did not receive any fund for this research from any funding agency. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;CD is principal author responsible for designing the study, data collection and analysis, and interpretation of the findings. CD, FA and JA are responsible in the conception. CD, FA, SN, JA, AJ and MD participated in study design, analysis and interpretation of the findings. MD and AJ drafted the manuscript. All authors read, revised and approved the final manuscript for submission.\u0026nbsp;\u003c/p\u003e\n\u003ch1\u003eAcknowledgments\u003c/h1\u003e\n\u003cp\u003eBefore all, we would like to acknowledge our staffs for providing constructive comments and suggestions in writing this research paper. We would also like to express our sincere thanks to Haramaya University research ethical committee for evaluating the paper. In addition, we would like to forward our gratitude to Hiwot Fana Comprehensive Specialized Hospital (HFCSH) mangers for allowing us to conduct this study in this setting and to the staff for their cooperation.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOliva F, Mortara A, Cacciatore G, Chinaglia A, Di Lenarda A, Gorini M, et al. Acute heart failure patient profiles, management and in‐hospital outcome: results of the Italian Registry on Heart Failure Outcome. 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Clinical pattern and outcome of acute heart failure at the Yaounde Central Hospital. Open Access Library Journal. 2017;4(03):1.\u003c/li\u003e\n\u003cli\u003eMeijers WC, de Boer RA. Common risk factors for heart failure and cancer. Cardiovascular research. 2019;115(5):844-53.\u003c/li\u003e\n\u003cli\u003eAhmed AA, Patel K, Nyaku MA, Kheirbek RE, Bittner V, Fonarow GC, et al. Risk of heart failure and death after prolonged smoking cessation: role of amount and duration of prior smoking. Circulation: Heart Failure. 2015;8(4):694-701.\u003c/li\u003e\n\u003cli\u003eAbdellah AT, Mohamed AD, Hendawi HA, Omera MA. Clinical and laboratory characteristics of short-term mortality in Egyptian patients with acute heart failure. The Egyptian Heart Journal. 2017;69(3):201-8.\u003c/li\u003e\n\u003cli\u003eRodgers BNRaJE. Acute Decompensated Heart Failure. 2017:673-732.\u003c/li\u003e\n\u003cli\u003eLee SE, Lee H-Y, Cho H-J, Choe W-S, Kim H, Choi JO, et al. Clinical characteristics and outcome of acute heart failure in Korea: results from the Korean Acute Heart Failure Registry (KorAHF). Korean circulation journal. 2017;47(3):341-53.\u003c/li\u003e\n\u003cli\u003eSpinar J, Parenica J, Vitovec J, Widimsky P, Linhart A, Fedorco M, et al. Baseline characteristics and hospital mortality in the Acute Heart Failure Database (AHEAD) Main registry. Critical care. 2011;15(6):1-13.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Acute Heart Failure, In-hospital Mortality, Tertiary Hospital, Eastern Ethiopia. ","lastPublishedDoi":"10.21203/rs.3.rs-2775153/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2775153/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Acute heart failure is the gradual or rapid change of heart failure signs and symptoms, which poses a unique diagnostic and management challenge, requiring urgent therapy. It is responsible for nearly one million hospitalizations each year globally with rising rates. Despite therapeutic advances, it is associated with poor prognosis. Therefore, his study aimed to assess in-hospital mortality and its associated factors among adult acute heart failure patients in a tertiary hospital, Harar, Eastern Ethiopia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: A hospital based retrospective cross-sectional study was employed among 454 adult acute heart failure patients treated in the medical ward of Haramaya University Hiwot Fana Comprehensive Specialized Hospital from June 01, 2016 to May 31, 2021. Data was collected using structured data abstraction format from July 15 to August 14, 2021. Collected data was entered to Epi-Data version 3.1, exported to, and analyzed using statistical package for social science (SPSS) version 21.0. Bivariate and multivariate logistic regression was used to identify factors associated with in-hospital mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: A total of 454 acute heart failure patient’s medical records were reviewed. More than half, 282(62.1%) of patients were females. The median age of patients was 45 years (±28 IQR). In-hospital mortality was 18.9% and it was more prevalent in the first week of admission, 61(70.9%). Sex (female) (adjusted odds ratio (AOR) = 2.83, P = 0.001)), having smoking history (AOR = 2.51, P = 0.031), generalized body swelling (AOR = 2.67, P = 0.001), hypotension (AOR = 4.56, P = 0.001), and tachycardia (AOR = 4.57, P = 0.000) were factors associated with in-hospital mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: In-hospital mortality is found to be very high among acute heart failure adult patients. Therefore, dedicated programs need to be developed to reduce mortality from acute heart failure and further prospective study should be conducted to investigate the problem in-depth.\u003c/p\u003e","manuscriptTitle":"In-hospital Mortality and Associated Factors among Adult Patients with Acute Heart Failure in a Tertiary Hospital, Harar, Eastern Ethiopia: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-07 11:35:48","doi":"10.21203/rs.3.rs-2775153/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":"7c38135a-6c76-4bf2-8dde-75acc1b1ec19","owner":[],"postedDate":"October 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-07T11:35:48+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-07 11:35:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2775153","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2775153","identity":"rs-2775153","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}