Dataset Information

Time to recovery and its predictors among adults hospitalized with COVID-19: A prospective cohort study in Ethiopia.

ABSTRACT:

Background

Various factors may determine the duration of viral shedding (the time from infection to viral RNA-negative conversion or recovery) in COVID-19 patients. Understanding the average duration of recovery and its predictors is crucial in formulating preventive measures and optimizing treatment options. Therefore, evidence showing the duration of recovery from COVID-19 in different contexts and settings is necessary for tailoring appropriate treatment and prevention measures. This study aimed to investigate the average duration and the predictors of recovery from Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection among COVID-19 patients.

Method

A hospital-based prospective cohort study was conducted at Eka Kotebe General Hospital, COVID-19 Isolation and Treatment Center from March 18 to June 27, 2020. The Center was the first hospital designated to manage COVID-19 cases in Ethiopia. The study participants were all COVID-19 adult patients who were admitted to the center during the study period. Follow up was done for the participants from the first date of diagnosis to the date of recovery (negative Real-time Reverse Transcriptase Polymerase Chain Reaction (rRT-PCT) test of throat swab).

Result

A total of 306 COVID-19 cases were followed up to observe the duration of viral clearance by rRT-PCR. Participants' mean age was 34 years (18-84 years) and 69% were male. The median duration of viral clearance from each participant's body was 19 days, but the range was wide: 2 to 71 days. Cough followed by headache was the leading sign of illness among the 67 symptomatic COVID-19 patients; and nearly half of those with comorbidities were known cancer and HIV/AIDS patients on clinical follow up. The median duration of recovery from COVID-19 was different for those with and without previous medical conditions or comorbidities. The rate of recovery from SARS-CoV-2 infection was 36% higher in males than in females (p = 0.043, CI: 1.01, 1.85). The rate of recovery was 93% higher in those with at least one comorbidity than in those without any comorbidity. The risk of delayed recovery was not influenced by blood type, BMI and presence of signs or symptoms. The findings showed that study participants without comorbidities recovered more quickly than those with at least one comorbidity. Therefore, isolation and treatment centers should be prepared to manage the delayed stay of patients having comorbidity.

SUBMITTER: Abrahim SA

PROVIDER: S-EPMC7773180 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Time to recovery and its predictors among adults hospitalized with COVID-19: A prospective cohort study in Ethiopia.

Abrahim Saro Abdella SA Tessema Masresha M Defar Atkure A Hussen Alemayehu A Ejeta Eshetu E Demoz Getachew G Tereda Addisu Birhanu AB Dillnessa Enatenesh E Feleke Altaye A Amare Misiker M Nigatu Frehiwot F Fufa Yaregal Y Refera Hailu H Aklilu Ayalew A Kassa Munir M Kifle Tsigereda T Whiting Susan S Tollera Getachew G Abate Ebba E

PloS one 20201230 12

<h4>Background</h4>Various factors may determine the duration of viral shedding (the time from infection to viral RNA-negative conversion or recovery) in COVID-19 patients. Understanding the average duration of recovery and its predictors is crucial in formulating preventive measures and optimizing treatment options. Therefore, evidence showing the duration of recovery from COVID-19 in different contexts and settings is necessary for tailoring appropriate treatment and prevention measures. This ...[more]

PMID: 33378367

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Project description:BackgroundStudying the characteristics of hospitalized Coronavirus Disease 2019 (COVID-19) patients is vital for understanding the disease and preparing for future outbreaks. The aim of this study was to analyze and describe the clinical profiles and factors associated with mortality among COVID-19 patients admitted to Jimma Medical Center COVID-19 Treatment Center (JMC CTC) in Ethiopia.MethodsAll confirmed COVID-19 patients admitted to JMC CTC between 17 April 2020 and 05 March 2022 were included in this study. Socio-demographic data, clinical information, and outcome variables were collected retrospectively from medical records and COVID-19 database at the hospital. Bivariable and multivariable analyses were performed to determine factors associated with COVID-19 severity and mortality. A P-value < 0.05 was considered statistically significant.ResultsA total of 542 confirmed COVID-19 patients were admitted to JMC CTC, of which 322 (59.4%) were male. Their median age was 48 years (IQR 32-64). About 51% (n = 277) of them had severe COVID-19 upon admission. Patients with hypertension [AOR: 2.8 (95% CI: 1.02-7.7, p = 0.046)], diabetes [AOR: 8.8 (95% CI: 1.2-17.3, p = 0.039)], and underlying respiratory diseases [AOR: 18.8 (95% CI: 2.06-71.51, p = 0.009)] were more likely to present with severe COVID-19 cases. Overall, 129 (23.8%) died in the hospital. Death rate was higher among patients admitted with severe disease [AHR = 5.5 (3.07-9.9) p < 0.001)] and those with comorbidities such as hypertension [AHR = 3.5 (2.28-5.41), p < 0.001], underlying respiratory disease [AHR = 3.4 (1.97-5.94), p < 0.001], cardiovascular disease (CVDs) [AHR = 2.8 (1.73-4.55), p < 0.001], and kidney diseases [AHR = 3.7 (2.3-5.96), p < 0.001].ConclusionAbout half of COVID-19 cases admitted to the hospital had severe disease upon admission. Comorbidities such as hypertension, diabetes, and respiratory diseases were linked to severe illness. COVID-19 admissions were associated with high inpatient mortality, particularly among those with severe disease and comorbidities.

Project description:IntroductionDespite its alarming spread throughout the world, no effective drug and vaccine is discovered for COVID-19 so far. According to WHO, the recovery time from COVID-19 was estimated to be 2 weeks for patients with mild infection, and 3 to 6 weeks for those with serious illnesses. A studies regarding the median recovery time and its predictors are limited globally and specifically in Ethiopia. Therefore, the aim of this study was to estimate the median time to recovery from COVID-19 and its predictors among COVID-19 cases admitted to WURH, Western Ethiopian.MethodsThis was a hospital-based retrospective cohort study conducted among 263 adult patients admitted with COVID-19 in WURH treatment center from March 29, 2020 through September 30, 2020. Epidata version 3.2 was used for data entry, and STATA version 14 for analysis. A Cox proportional hazard regression model was fitted to determine factors associated with recovery time. A variable with P-value ≤ 0.25 at bivariable Cox regression analysis were selected for multivariable Cox proportional model. Multivariable Cox regression model with 95% CI and Adjusted Hazard Ratio (AHR) was used to identify a significant predictor of time to recovery from COVID-19 at P-value < 0.05.ResultsThe mean age of patient was 36.8 (SD± 10.68) years. At the end of follow up, two hundred twenty seven observations were developed an event (recovered) with median time to recovery of 18 days with IQR of 10-27 days. The overall incidence rate of recovery was of 4.38 per 100 (95% CI: 3.84, 4.99) person-days observations. Being older age (AHR = 1.59, 95% CI: 1.02, 2.49), presence of fever on admission (AHR = 1.78, 95% CI: 1.21, 2.62), and comorbidity (AHR = 0.56, 95% CI, 0.34, 0.90) were found to have statistically significant association with recovery time.Conclusion and recommendationsIn general, the median recovery time of patients with COVID-19 cases was long, and factors such as older age group, presence of fever, and comorbidity was an independent predictors of delayed recovery from COVID-19. Intervention to further reduce recovery time at treatment center has to focus on patients those shows symptoms and with comorbidities.

Project description:AimsThe degree of cardiovascular sequelae following COVID-19 remains unknown. The aim of this study was to investigate whether cardiac function recovers following COVID-19.Methods and resultsA consecutive sample of patients hospitalized with COVID-19 was prospectively included in this longitudinal study. All patients underwent an echocardiographic examination during hospitalization and 2 months later. All participants were successfully matched 1:1 with COVID-19-free controls by age and sex. A total of 91 patients were included (mean age 63 ± 12 years, 59% male). A median of 77 days (interquartile range: 72-92) passed between the two examinations. Right ventricular (RV) function improved following resolution of COVID-19: tricuspid annular plane systolic excursion (TAPSE) (2.28 ± 0.40 cm vs. 2.11 ± 0.38 cm, P < 0.001) and RV longitudinal strain (RVLS) (25.3 ± 5.5% vs. 19.9 ± 5.8%, P < 0.001). In contrast, left ventricular (LV) systolic function assessed by global longitudinal strain (GLS) did not significantly improve (17.4 ± 2.9% vs. 17.6 ± 3.3%, P = 0.6). N-terminal pro-B-type natriuretic peptide decreased between the two examinations [177.6 (80.3-408.0) ng/L vs. 11.7 (5.7-24.0) ng/L, P < 0.001]. None of the participants had elevated troponins at follow-up compared to 18 (27.7%) during hospitalization. Recovered COVID-19 patients had significantly lower GLS (17.4 ± 2.9% vs. 18.8 ± 2.9%, P < 0.001 and adjusted P = 0.004), TAPSE (2.28 ± 0.40 cm vs. 2.67 ± 0.44 cm, P < 0.001 and adjusted P < 0.001), and RVLS (25.3 ± 5.5% vs. 26.6 ± 5.8%, P = 0.50 and adjusted P < 0.001) compared to matched controls.ConclusionAcute COVID-19 affected negatively RV function and cardiac biomarkers but recovered following resolution of COVID-19. In contrast, the observed reduced LV function during acute COVID-19 did not improve post-COVID-19. Compared to the matched controls, both LV and RV function remained impaired.

Project description:BackgroundThe global coronavirus disease 2019 (COVID-19) pandemic offers the opportunity to assess how hospitals manage the care of hospitalized patients with varying demographics and clinical presentations. The goal of this study was to demonstrate the impact of densely populated residential areas on hospitalization and to identify predictors of length of stay and mortality in hospitalized patients with COVID-19 in one of the hardest hit counties internationally.MethodsThis was a single-center cohort study of 1325 sequentially hospitalized patients with COVID-19 in New York between March 2, 2020, to May 11, 2020. Geospatial distribution of study patients' residences relative to population density in the region were mapped, and data analysis included hospital length of stay, need and duration of invasive mechanical ventilation (IMV), and mortality. Logistic regression models were constructed to predict discharge dispositions in the remaining active study patients.ResultsThe median age of the study cohort (interquartile range [IQR]) was 62 (49-75) years, and more than half were male (57%) with history of hypertension (60%), obesity (41%), and diabetes (42%). Geographic residence of the study patients was disproportionately associated with areas of higher population density (r s = 0.235; P = .004), with noted "hot spots" in the region. Study patients were predominantly hypertensive (MAP > 90 mmHg; 670, 51%) on presentation with lymphopenia (590, 55%), hyponatremia (411, 31%), and kidney dysfunction (estimated glomerular filtration rate < 60 mL/min/1.73 m2; 381, 29%). Of the patients with a disposition (1188/1325), 15% (182/1188) required IMV and 21% (250/1188) developed acute kidney injury. In patients on IMV, the median (IQR) hospital length of stay in survivors (22 [16.5-29.5] days) was significantly longer than that of nonsurvivors (15 [10-23.75] days), but this was not due to prolonged time on the ventilator. The overall mortality in all hospitalized patients was 15%, and in patients receiving IMV it was 48%, which is predicted to minimally rise from 48% to 49% based on logistic regression models constructed to project disposition in the remaining patients on ventilators. Acute kidney injury during hospitalization (odds ratioE, 3.23) was the strongest predictor of mortality in patients requiring IMV.ConclusionsThis is the first study to collectively utilize the demographics, clinical characteristics, and hospital course of COVID-19 patients to identify predictors of poor outcomes that can be used for resource allocation in future waves of the pandemic.

Project description:BackgroundFirst reported case of Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) in Kazakhstan was identified in March 2020. Many specialized tertiary hospitals in Kazakhstan including National Research Cardiac Surgery Center (NRCSC) were re-organized to accept coronavirus disease 2019 (COVID-19) infected patients during summer months of 2020. Although many studies from worldwide reported their experience in treating patients with COVID-19, there are limited data available from the Central Asia countries. The aim of this study is to identify predictors of mortality associated with COVID-19 in NRCSC tertiary hospital in Nur-Sultan, Kazakhstan.MethodsThis is a retrospective cohort study of patients admitted to the NRCSC between June 1st-August 31st 2020 with COVID-19. Demographic, clinical and laboratory data were collected from electronic records. In-hospital mortality was assessed as an outcome. Patients were followed-up until in-hospital death or discharge from the hospital. Descriptive statistics and factors associated with mortality were assessed using univariate and multivariate logistic regression models.ResultsTwo hundred thirty-nine admissions were recorded during the follow-up period. Mean age was 57 years and 61% were males. Median duration of stay at the hospital was 8 days and 34 (14%) patients died during the hospitalization. Non-survivors were more likely to be admitted later from the disease onset, with higher fever, lower oxygen saturation and increased respiratory rate compared to survivors. Leukocytosis, lymphopenia, anemia, elevated liver and kidney function tests, hypoproteinemia, elevated inflammatory markers (C-reactive protein (CRP), ferritin, and lactate dehydrogenase (LDH)) and coagulation tests (fibrinogen, D-dimer, international normalized ratio (INR), and activated partial thromboplastin time (aPTT)) at admission were associated with mortality. Age (OR 1.2, CI:1.01-1.43), respiratory rate (OR 1.38, CI: 1.07-1.77), and CRP (OR 1.39, CI: 1.04-1.87) were determined to be independent predictors of mortality.ConclusionThis study describes 14% mortality rate from COVID-19 in the tertiary hospital. Many abnormal clinical and laboratory variables at admission were associated with poor outcome. Age, respiratory rate and CRP were found to be independent predictors of mortality. Our finding would help healthcare providers to predict the risk factors associated with high risk of mortality. Further investigations involving large cohorts should be provided to support our findings.

Project description:BackgroundSeveral anti-cytokine therapies were tested in the randomized trials in hospitalized patients with severe acute respiratory syndrome coronavirus 2 infection (COVID-19). Previously, dexamethasone demonstrated a reduction of case-fatality rate in hospitalized patients with respiratory failure. In this matched control study we compared dexamethasone to a Janus kinase inhibitor, ruxolitinib.MethodsThe matched cohort study included 146 hospitalized patients with COVID-19 and oxygen support requirement. The control group was selected 1:1 from 1355 dexamethasone-treated patients and was matched by main clinical and laboratory parameters predicting survival. Recruitment period was April 7, 2020 through September 9, 2020.ResultsRuxolitinib treatment in the general cohort of patients was associated with case-fatality rate similar to dexamethasone treatment: 9.6% (95% CI [4.6-14.6%]) vs 13.0% (95% CI [7.5-18.5%]) respectively (p = 0.35, OR = 0.71, 95% CI [0.31-1.57]). Median time to discharge without oxygen support requirement was also not different between these groups: 13 vs. 11 days (p = 0.13). Subgroup analysis without adjustment for multiple comparisons demonstrated a reduced case-fatality rate in ruxolitnib-treated patients with a high fever (≥ 38.5 °C) (OR 0.33, 95% CI [0.11-1.00]). Except higher incidence of grade 1 thrombocytopenia (37% vs 23%, p = 0.042), ruxolitinib therapy was associated with a better safety profile due to a reduced rate of severe cardiovascular adverse events (6.8% vs 15%, p = 0.025). For 32 patients from ruxolitinib group (21.9%) with ongoing progression of respiratory failure after 72 h of treatment, additional anti-cytokine therapy was prescribed (8-16 mg dexamethasone).ConclusionsRuxolitinib may be an alternative initial anti-cytokine therapy with comparable effectiveness in patients with potential risks of steroid administration. Patients with a high fever (≥ 38.5 °C) at admission may potentially benefit from ruxolitinib administration. Trial registration The Ruxolitinib Managed Access Program (MAP) for Patients Diagnosed With Severe/Very Severe COVID-19 Illness NCT04337359, CINC424A2001M, registered April, 7, 2020. First participant was recruited after registration date.

Project description:One of the most helpful strategies to deal with ongoing coronavirus pandemics is to use some prudence when treating patients infected with SARS-CoV-2. We aimed to evaluate the clinical, demographic, and laboratory parameters that might have predictive value for in-hospital mortality and the need for intensive care and build a model based on them. This study was a prospective, observational, single-center study including non-critical patients admitted to COVID-19 wards. Besides classical clinic-demographic features, basic laboratory parameters obtained on admission were tested, and then new models for each outcome were developed built on the most significant variables. Receiver operating characteristics (ROC) analyses were performed by calculating each model's probability. A total of 368 non-critical hospitalized patients were recruited, the need for ICU care was observed in 70 patients (19%). The total number of patients who died in either ICU or wards was 39 (10.6%). The first two models (based on clinical features and demographics) were developed to predict ICU and death, respectively; older age, male sex, active cancer, and low baseline saturation were noted to be independent predictors. The area under the curve values of the first two models were noted 0.878 and 0.882 (p < .001; confidence interval [CI] 95% [0.837-0.919], p < .001; CI 95% [0.844-0.922]). Following two models, the third and fourth were based on laboratory parameters with clinic-demographic features. Initial lower sodium and lower albumin levels were determined as independent factors in predicting the need for ICU care; higher blood urea nitrogen and lower albumin were independent factors in predicting in-hospital mortality. The area under the curve values of the third and fourth model was noted 0.938 and 0.929, respectively (p < .001; CI 95% [0.912-0.965], p < .001; CI 95% [0.895-962]). By integrating the widely available blood tests results with simple clinic demographic data, non-critical patients can be stratified according to their risk level. Such stratification is essential to filter the patients' non-critical underlying diseases and conditions that can obfuscate the physician's predictive capacity.

Dataset Information

Time to recovery and its predictors among adults hospitalized with COVID-19: A prospective cohort study in Ethiopia.

Background

Method

Result

Publications

Time to recovery and its predictors among adults hospitalized with COVID-19: A prospective cohort study in Ethiopia.

Similar Datasets

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