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INTRODUCTION: Identification of factors predicting prolonged hospitalization of patients with coronavirus disease (COVID-19) guides the planning, care and flow of patients in the COVID-19 Treatment Units (CTUs). We determined the length of hospital stay and factors associated with prolonged hospitalization among patients with COVID-19 at six CTUs in Uganda. METHODS: We conducted a retrospective cohort study of patients admitted with COVID-19 between January and December 2021 in six CTUs in Uganda. We conducted generalized linear regression models of the binomial family with a log link and robust variance estimation to estimate risk ratios of selected exposure variables and prolonged hospitalization (defined as a hospital stay for 14 days or more). We also conducted negative binomial regression models with robust variance to estimate the rate ratios between selected exposures and hospitalization duration. RESULTS: Data from 968 participants were analyzed. The median length of hospitalization was 5 (range: 1-89) days. A total of 136/968 (14.1%: 95% confidence interval (CI): 11.9-16.4%) patients had prolonged hospitalization. Hospitalization in a public facility (adjusted risk ratio (ARR) = 2.49, 95% CI: 1.65-3.76), critical COVID-19 severity scores (ARR = 3.24: 95% CI: 1.01-10.42), and malaria co-infection (adjusted incident rate ratio (AIRR) = 0.67: 95% CI: 0.55-0.83) were associated with prolonged hospitalization. CONCLUSION: One out of seven COVID-19 patients had prolonged hospitalization. Healthcare providers in public health facilities should watch out for unnecessary hospitalization. We encourage screening for possible co-morbidities such as malaria among patients admitted for COVID-19.
ABSTRACT
BACKGROUND: Assessing factors associated with mortality among COVID-19 patients could guide in developing context relevant interventions to mitigate the risk. The study aimed to describe mortality and associated factors among COVID-19 patients admitted at six health facilities in Uganda. METHODS: We reviewed medical records of patients admitted with COVID-19 between January 1st 2021 and December 31st 2021 in six hospitals in Uganda. Using Stata version 17.0, Kaplan Meier and Cox regression analyses were performed to describe the time to death and estimate associations between various exposures and time to death. Finally, accelerated failure time (AFT) models with a lognormal distribution were used to estimate corresponding survival time ratios. RESULTS: Out of the 1040 study participants, 234 (22.5%: 95%CI 12.9 to 36.2%) died. The mortality rate was 30.7 deaths per 1000 person days, 95% CI (26.9 to 35.0). The median survival time was 33 days, IQR (9-82). Factors associated with time to COVID-19 death included; age ≥ 60 years [adjusted hazard ratio (aHR) = 2.4, 95% CI: [1.7, 3.4]], having malaria test at admission [aHR = 2.0, 95% CI:[1.0, 3.9]], a COVID-19 severity score of severe/critical [aHR = 6.7, 95% CI:[1.5, 29.1]] and admission to a public hospital [aHR = 0.4, 95% CI:[0.3, 0.6]]. The survival time of patients aged 60 years or more is estimated to be 63% shorter than that of patients aged less than 60 years [adjusted time ratio (aTR) 0.37, 95% CI 0.24, 0.56]. The survival time of patients admitted in public hospitals was 2.5 times that of patients admitted in private hospitals [aTR 2.5 to 95%CI 1.6, 3.9]. Finally, patients with a severe or critical COVID-19 severity score had 87% shorter survival time than those with a mild score [aTR 0.13, 95% CI 0.03, 0.56]. CONCLUSION: In-hospital mortality among COVID-19 patients was high. Factors associated with shorter survival; age ≥ 60 years, a COVID-19 severity score of severe or critical, and having malaria at admission. We therefore recommend close monitoring of COVID-19 patients that are elderly and also screening for malaria in COVID-19 admitted patients.
ABSTRACT
An estimated 80% of the population in developing countries is dependent on traditional medicine for their health needs, including use during pregnancy despite limited knowledge of potential side effects including teratogenicity. Controlling use of traditional medicines during pregnancy requires understanding the driving factors. This study aimed at determining the health system factors that influence traditional herbal medicine use during pregnancy in a Ugandan setting. A cross-sectional study was conducted among 315 post-partum women obtained by random sampling from post-natal clinics of health facilities in Mpigi District after informed consent. We carried out concurrent triangulation by conducting two focused group discussions of 10 post-natal mothers each, and four Key informant interviews. Quantitative Data analysis involved descriptive statistics and logistic regression analysis. Qualitative data was analyzed by thematic content analysis and presented as narratives. Prevalence of herbal medicine use during pregnancy was 79% (95% Confidence Interval (CI) 68.1% - 86.9%), mainly consumed through oral route (96%). Costly health care adjusted Prevalence Ratio (aPR) 1.61 (95% CI 1.02-2.53), p-value 0.042, and presence and influence of Traditional Birth Attendants aPR 1.21(95% CI 1.05-1.41), p-value 0.011 were significantly associated with use of traditional herbal medicines during pregnancy. Use of traditional herbal medicines is driven by the high costs of quality health care and influence from Traditional Birth Attendants. Innovations in health financing should be promoted and Traditional Birth Attendants should be sensitized and incorporated in the mainstream health care system as community referral agents.
