RESUMO
BackgroundCOVID-19 experiences on noncommunicable diseases (NCDs) from district-level hospital settings during waves I and II are scarcely documented. The aim of this study is to investigate the NCDs associated with COVID-19 severity and mortality in a district-level hospital with a high HIV/TB burden. MethodsThis was a retrospective observational study that compared COVID-19 waves I and II at Khayelitsha District Hospital in Cape Town, South Africa. COVID-19 adult patients with a confirmed SARS-CoV-2 polymerase chain reaction (PCR) or positive antigen test were included. In order to compare the inter wave period, clinical and laboratory parameters on hospital admission of noncommunicable diseases, the Student t-test or Mann-Whitney U for continuous data and the X2 test or Fishers Exact test for categorical data were used. The role of the NCD subpopulation on COVID-19 mortality was determined using latent class analysis (LCA). FindingsAmong 560 patients admitted with COVID-19, patients admitted during wave II were significantly older than those admitted during wave I. The most prevalent comorbidity patterns were hypertension (87%), diabetes mellitus (65%), HIV/AIDS (30%), obesity (19%), Chronic Kidney Disease (CKD) (13%), Congestive Cardiac Failure (CCF) (8.8%), Chronic Obstructive Pulmonary Disease (COPD) (3%), cerebrovascular accidents (CVA)/stroke (3%), with similar prevalence in both waves except HIV status [(23% vs 34% waves II and I, respectively), p = 0.022], obesity [(52% vs 2.5%, waves II and I, respectively), p <0.001], previous stroke [(1% vs 4.1%, waves II and I, respectively), p = 0.046]. In terms of clinical and laboratory findings, our study found that wave I patients had higher haemoglobin and HIV viral loads. Wave II, on the other hand, had statistically significant higher chest radiography abnormalities, fraction of inspired oxygen (FiO2), and uraemia. The adjusted odds ratio for death vs discharge between waves I and II was similar (0.94, 95%CI: 0.84-1.05). Wave I had a longer average survival time (8.0 vs 6.1 days) and a shorter average length of stay among patients discharged alive (9.2 vs 10.7 days). LCA revealed that the cardiovascular phenotype had the highest mortality, followed by diabetes and CKD phenotypes. Only Diabetes and hypertension phenotypes had the lowest mortality. ConclusionEven though clinical and laboratory characteristics differed significantly between the two waves, mortality remained constant. According to LCA, the cardiovascular, diabetes, and CKD phenotypes had the highest death probability.
RESUMO
BackgroundThe interaction between COVID-19, non-communicable diseases, and chronic infectious diseases such as HIV and tuberculosis (TB) are unclear, particularly in low- and middle-income countries in Africa. South Africa has a national adult HIV prevalence of 19% and TB prevalence of 0.7%. Using a nationally representative hospital surveillance system in South Africa, we investigated the factors associated with in-hospital mortality among individuals with COVID-19. MethodsUsing data from national active hospital surveillance, we describe the demographic characteristics, clinical features, and in-hospital mortality among hospitalised individuals testing positive for SARS-CoV-2, during 5 March 2020 to 27 March 2021. Chained equation multiple imputation was used to account for missing data and random effect multivariable logistic regression models were used to assess the role of HIV-status and underlying comorbidities on in-hospital COVID-19 mortality. FindingsAmong the 219,265 individuals admitted with laboratory confirmed SARS-Cov-2, 51,037 (23.3%) died. Most commonly observed comorbidities among individuals with available data were hypertension (61,098/163,350; 37.4%), diabetes (43,885/159,932; 27.4%), and HIV (13,793/151,779; %), while TB was reported in 3.6% (5,282/146,381) of individuals. While age was the most important predictor, other factors associated with in-hospital COVID-19 mortality were HIV infection [aOR 1.34, 95% CI: 1.27-1.43), past TB [aOR 1.26, 95% CI: 1.15-1.38), current TB [aOR 1.42, 95% CI: 1.22-1.64) and both past and current TB [aOR 1.48, 95% CI: 1.32-1.67) compared to never TB, as well as other described risk factors for COVID-19, such as male sex, non-white race, and chronic underlying hypertension, diabetes, chronic cardiac disease, chronic renal disease, and malignancy. After adjusting for other factors, PLWH not on ART [aOR 1.45, 95% CI: 1.22-1.72] were more likely to die in-hospital compared to PLWH on ART. Among PLWH, the prevalence of other comorbidities was 29.2% compared to 30.8% among HIV-uninfected individuals. Increasing number of comorbidities was associated with increased mortality risk in both PLWH and HIV-uninfected individuals. InterpretationIdentified high risk individuals (older individuals and those with chronic comorbidities and PLWH, particularly those not on ART) would benefit from COVID-19 prevention programmes such as vaccine prioritisation, as well as early referral and treatment. FundingSouth African National Government Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSince the emergence of the COVID-19 pandemic, studies have identified older age, male sex and presence of underlying comorbidities including heart disease and diabetes as risk factors for severe disease and death. There are very few studies, however, carried out in low- and middle-income countries (LMIC) in Africa, many of whom have high poverty rates, limited access to healthcare, and high prevalence of chronic communicable diseases, such as HIV and tuberculosis (TB). Data are also limited from settings with limited access to HIV treatment programmes. Early small cohort studies mainly from high income countries were not conclusive on whether HIV or TB are risk factors for disease severity and death in COVID-19 patients. Large population cohort studies from South Africas Western Cape province and the United Kingdom (UK) have found people living with HIV (PLWH) to have a moderately increased risk of COVID-19 associated mortality. Of these, only the Western Cape study presented data on mortality risk associated with presence of high viral load or immunosuppression, and found similar levels of severity irrespective of these factors. Recent meta-analyses have confirmed the association of HIV with COVID-19 mortality. No studies reported on the interaction between HIV-infection and other non-communicable comorbidities on COVID-19 associated mortality. We performed separate literature searches on PubMed using the following terms: "COVID-19" "risk factors" and "mortality"; "HIV" "COVID-19" and "mortality"; "TB" "COVID-19" and "mortality". All searches included publications from December 1, 2019 until May 5, 2021, without language restrictions. Pooled together, we identified 2,786 published papers. Additionally, we performed two literature searches on MedRxiv using the terms "HIV" "COVID-19" and "mortality", and "TB" "COVID-19" and "mortality" from April 25, 2020 until May 5, 2021, without language restrictions. Pooled together, we identified 7,744 pre-prints. Added value of this studyAmong a large national cohort of almost 220,000 individuals hospitalised with COVID-19 in a setting with 19% adult HIV prevalence and 0.7%TB prevalence, we found that along with age, sex and other comorbidities, HIV and TB were associated with a moderately increased risk of in-hospital mortality. We found increasing risk of in-hospital mortality among PLWH not on ART compared to those on ART. Among PLWH, the prevalence of other comorbidities was high (29%) and the effect of increasing numbers of comorbidities on mortality was similar in PLWH and HIV-uninfected individuals. Our study included 13,793 PLWH from all provinces in the country with varying levels of access to HIV treatment programmes. Implications of all the available evidenceThe evidence suggests that PLWH and TB-infected individuals should be prioritised for COVID-19 prevention and treatment programmes, particularly those with additional comorbidities. Increasing age and presence of chronic underlying illness are important additional factors associated with COVID-19 mortality in a middle-income African setting. The completeness of data is a limitation of this national surveillance system, and additional data are needed to confirm these findings.
