1. Time to Recovery of Severely Ill COVID-19 Patients and its Predictors: A Retrospective Cohort Study in Tigray, Ethiopia
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Abebe HT, Zelelow YB, Bezabih AM, Ashebir MM, Tafere GR, Wuneh AD, Araya MG, Kiros NK, Hiluf MK, Ebrahim MM, Gebrehiwot TG, Welderufael AL, and Mohammed AH
- Subjects
covid-19 ,comorbidity ,cox proportional hazard regression ,adjusted hazard ratio ,Medicine (General) ,R5-920 - Abstract
Haftom Temesgen Abebe,1,2 Yibrah Berhe Zelelow,3 Afework Mulugeta Bezabih,4 Mengistu Mitiku Ashebir,5 Getachew Redae Tafere,6 Alem Desta Wuneh,5 Medhanie Gebresilassie Araya,7 Nguse Kahsay Kiros,8 Molla Kahssay Hiluf,9 Mohamedawel Mohamedniguss Ebrahim,10 Tesfay Gebregzabher Gebrehiwot,5 Abadi Leul Welderufael,11 Abrahim Hassen Mohammed12 1Department of Biostatistics, College of Health Sciences, Mekelle University, Mekelle, Ethiopia; 2Laboratory Interdisciplinary Statistical Data Analysis, College of Health Sciences, Mekelle University, Mekelle, Ethiopia; 3Department of Obstetrics and Gynecology, College of Health Sciences, Mekelle University, Mekelle, Ethiopia; 4Department of Nutrition, College of Health Sciences, Mekelle University, Mekelle, Ethiopia; 5Department of Health System, College of Health Sciences, Mekelle University, Mekelle, Ethiopia; 6Department of Environmental and Behavioral Sciences, College of Health Sciences, Mekelle University, Mekelle, Ethiopia; 7Department of Ear, Nose and Throat, College of Health Sciences, Mekelle University, Mekelle, Ethiopia; 8Tigrai Institute of Policy Studies, Mekelle, Ethiopia; 9Department of Public Health, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia; 10Department of Surgery, College of Health Sciences, Mekelle University, Mekelle, Ethiopia; 11Department of Pediatric and Child Health, College of Health Sciences, Mekelle University, Mekelle, Ethiopia; 12Tigrai Health Bureau, Mekelle, EthiopiaCorrespondence: Haftom Temesgen Abebe, Department of Biostatistics, College of Health Sciences, Mekelle University, P.O. Box 1871, Mekelle, Ethiopia, Email haftoma@gmail.comBackground: COVID-19 is one of the leading causes of morbidity and mortality and is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). A patient infected with SARS-CoV-2 is said to be recovered from the infection following negative test results and when signs and symptoms disappear. Different studies have shown different median recovery time of patients with COVID-19 and it varies across settings and disease status. This study aimed to assess time to recovery and its predictors among severely ill COVID-19 patients in Tigray.Methods: A total of 139 severely ill COVID-19 patients who were hospitalized between May 7, 2020 and October 28, 2020 were retrospectively analyzed. Cox proportional hazard regression model was fitted to identify the risk factors associated with the time duration to recovery from severe COVID-19 illness.Results: The median age of the patients was 35 years (IQR, 27– 60). Eighty-three (59.7%) patients recovered with a median time of 26 days (95% CI: 23– 27). The results from the multivariable analysis showed that the recovery time was lower for severely ill patients who had no underline comorbidity diseases (AHR=2.48, 95% CI: 1.18– 5.24), shortness of breath (AHR=2.08, 95% CI: 1.07– 3.98) and body weakness (AHR=2.62, 95% CI: 1.20– 5.72). Moreover, COVID-19 patients aged younger than 40 years had lower recovery time compared to patients aged 60 and above (AHR=4.09, 95% CI: 1.58– 10.61).Conclusion: The median recovery time of severely ill COVID-19 patients was long, and older age, comorbidity, shortness of breath, and body weakness were significant factors related with the time to recovery among the severely ill COVID-19 patients. Therefore, we recommended that elders and individuals with at least one comorbidity disease have to get due attention to prevent infection by the virus. Moreover, attention should be given in the treatment practice for individuals who had shortness of breath and body weakness symptoms.Keywords: COVID-19, comorbidity, cox proportional hazard regression, adjusted hazard ratio
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- 2022