Background The interaction between COVID-19, non-communicable diseases, and chronic infectious diseases such as HIV and tuberculosis is unclear, particularly in low-income and middle-income countries in Africa. South Africa has a national HIV prevalence of 19% among people aged 15-49 years and a tuberculosis prevalence of 0•7% in people of all ages. Using a nationally representative hospital surveillance system in South Africa, we aimed to investigate the factors associated with in-hospital mortality among patients with COVID-19. MethodsIn this cohort study, we used data submitted to DATCOV, a national active hospital surveillance system for COVID-19 hospital admissions, for patients admitted to hospital with laboratory-confirmed SARS-CoV-2 infection between March 5, 2020, and March 27, 2021. Age, sex, race or ethnicity, and comorbidities (hypertension, diabetes, chronic cardiac disease, chronic pulmonary disease and asthma, chronic renal disease, malignancy in the past 5 years, HIV, and past and current tuberculosis) were considered as risk factors for COVID-19-related in-hospital mortality. COVID-19 in-hospital mortality, the main outcome, was defined as a death related to COVID-19 that occurred during the hospital stay and excluded deaths that occurred because of other causes or after discharge from hospital; therefore, only patients with a known in-hospital outcome (died or discharged alive) were included. Chained equation multiple imputation was used to account for missing data and random-effects multivariable logistic regression models were used to assess the role of HIV status and underlying comorbidities on COVID-19 in-hospital mortality. FindingsAmong the 219 265 individuals admitted to hospital with laboratory-confirmed SARS-CoV-2 infection and known in-hospital outcome data, 51 037 (23•3%) died. Most commonly observed comorbidities among individuals with available data were hypertension in 61 098 (37•4%) of 163 350, diabetes in 43 885 (27•4%) of 159 932, and HIV in 13 793 (9•1%) of 151 779. Tuberculosis was reported in 5282 (3•6%) of 146 381 individuals. Increasing age was the strongest predictor of COVID-19 in-hospital mortality. Other factors associated were HIV infection (adjusted odds ratio 1•34, 95% CI 1•27-1•43), past tuberculosis (1•26, 1•15-1•38), current tuberculosis (1•42, 1•22-1•64), and both past and current tuberculosis (1•48, 1•32-1•67) compared with never tuberculosis, as well as other described risk factors for COVID-19, such as male sex; non-White race; underlying hypertension, diabetes, chronic cardiac disease, chronic renal disease, and malignancy in the past 5 years; and treatment in the public health sector. After adjusting for other factors, people with HIV not on antiretroviral therapy (ART; adjusted odds ratio 1•45, 95% CI 1•22-1•72) were more likely to die in hospital than were people with HIV on ART. Among people with HIV, the prevalence of other comorbidities was 29•2% compared with 30•8% among HIV-uninfected individuals. Increasing number of comorbidities was associated with...

Background The first wave of COVID-19 in South Africa peaked in July, 2020, and a larger second wave peaked in January, 2021, in which the SARS-CoV-2 501Y.V2 (Beta) lineage predominated. We aimed to compare in-hospital mortality and other patient characteristics between the first and second waves.Methods In this prospective cohort study, we analysed data from the DATCOV national active surveillance system for COVID-19 admissions to hospital from March 5, 2020, to March 27, 2021. The system contained data from all hospitals in South Africa that have admitted a patient with COVID-19. We used incidence risk for admission to hospital and determined cutoff dates to define five wave periods: pre-wave 1, wave 1, post-wave 1, wave 2, and post-wave 2. We compared the characteristics of patients with COVID-19 who were admitted to hospital in wave 1 and wave 2, and risk factors for in-hospital mortality accounting for wave period using random-effect multivariable logistic regression.Findings Peak rates of COVID-19 cases, admissions, and in-hospital deaths in the second wave exceeded rates in the first wave: COVID-19 cases, 240•4 cases per 100 000 people vs 136•0 cases per 100 000 people; admissions, 27•9 admissions per 100 000 people vs 16•1 admissions per 100 000 people; deaths, 8•3 deaths per 100 000 people vs 3•6 deaths per 100 000 people. The weekly average growth rate in hospital admissions was 20% in wave 1 and 43% in wave 2 (ratio of growth rate in wave 2 compared with wave 1 was 1•19, 95% CI 1•18-1•20). Compared with the first wave, individuals admitted to hospital in the second wave were more likely to be age 40-64 years (adjusted odds ratio [aOR] 1•22, 95% CI 1•14-1•31), and older than 65 years (aOR 1•38, 1•25-1•52), compared with younger than 40 years; of Mixed race (aOR 1•21, 1•06-1•38) compared with White race; and admitted in the public sector (aOR 1•65, 1•41-1•92); and less likely to be Black (aOR 0•53, 0•47-0•60) and Indian (aOR 0•77, 0•66-0•91), compared with White; and have a comorbid condition (aOR 0•60, 0•55-0•67).For multivariable analysis, after adjusting for weekly COVID-19 hospital admissions, there was a 31% increased risk of in-hospital mortality in the second wave (aOR 1•31, 95% CI 1•28-1•35). In-hospital case-fatality risk increased from 17•7% in weeks of low admission (<3500 admissions) to 26•9% in weeks of very high admission (>8000 admissions; aOR 1•24, 1•17-1•32).Interpretation In South Africa, the second wave was associated with higher incidence of COVID-19, more rapid increase in admissions to hospital, and increased in-hospital mortality. Although some of the increased mortality can be explained by admissions in the second wave being more likely in older individuals, in the public sector, and by the increased health system pressure, a residual increase in mortality of patients admitted to hospital could be related to the new Beta lineage.

Rates of healthcare-associated infections (HAIs) among babies born in hospitals in developing countries are 3 -20 times higher than among those born in resource-rich countries. [1] While poor infection prevention and control (IPC) practices are most proximally associated with transmission of HAIs and high infection rates, contributing factors include ageing hospital infrastructure, overcrowded neonatal units, inappropriate use of antimicrobial agents and inadequate institutional support for IPC and antimicrobial stewardship programmes. [2] Klebsiella pneumoniae is a common pathogen causing invasive HAIs in neonates. [1] Factors that predispose neonates to K. pneumoniae infection include prematurity and low birth weight. [3] The emergence of carbapenem-resistant K. pneumoniae in neonatal units has rendered recommended first-line empirical regimens for neonatal sepsis ineffective. [4] OXA-48-producing K. pneumoniae strains, which may remain phenotypically susceptible to carbapenems, can be missed in routine laboratories if not confirmed with molecular testing. [5] This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

Background: HIV infection causes immune dysregulation affecting T-cell and monocyte function, which may alter coronavirus disease 2019 (COVID-19) pathophysiology.Objectives: We investigated the associations among clinical phenotypes, laboratory biomarkers, and hospitalisation outcomes in a cohort of people hospitalised with COVID-19 in a high HIV prevalence area.Method: We conducted a prospective observational cohort study in Tshwane, South Africa. Respiratory disease severity was quantified using the respiratory oxygenation score. Analysed biomarkers included inflammatory and coagulation biomarkers, CD4 T-cell counts, and HIV-1 viral loads (HIVVL).Results: The analysis included 558 patients, of whom 21.7% died during admission. The mean age was 54 years. A total of 82 participants were HIV-positive. People living with HIV (PLWH) were younger (mean age 46 years) than HIV-negative people; most were on antiretroviral treatment with a suppressed HIVVL (72%) and the median CD4 count was 159 (interquartile range: 66–397) cells/µL. After adjusting for age, HIV was not associated with increased risk of mortality during hospitalisation (age-adjusted hazard ratio = 1.1, 95% confidence interval: 0.6–2.0). Inflammatory biomarker levels were similar in PLWH and HIV-negative patients. Detectable HIVVL was associated with less severe respiratory disease. In PLWH, mortality was associated with higher levels of inflammatory biomarkers. Opportunistic infections, and other risk factors for severe COVID-19, were common in PLWH who died.Conclusion: PLWH were not at increased risk of mortality and those with detectable HIVVL had less severe respiratory disease than those with suppressed HIVVL.What this study adds: This study advances our understanding of severe COVID-19 in PLWH.

Background:The Vasoactive Inotropic Score (VIS) is an objective clinical tool that was used to quantify the need for cardiovascular support and used as a predictor of morbidity and mortality in children with septic shock.Methods and materials: This is a prospective cohort study of all septic shock patients aged 1 m to 18 y who were admitted at the PICU. Vasoactive Inotropic Score was calculated at initial, 6, 12, 24, and 48 h post PICU admission as described by Gaies, et. al. Demographic and clinical data were collected. Primary outcomes were ventilator days and ICU length of stay while secondary outcomes were death during hospitalization, cardiac arrest, and need for intubation. STATA 13.1 was used for data analysis. Appropriate descriptive and analytical statistical tests were applied for this data and a P-value <0.05 was considered significant.Results: Eighty-four patients met the inclusion criteria and were enrolled in the study. Sixty-two (73.81%) patients were intubated, 34 (40.48%) went into cardiac arrest and 33 (39.29%) died during hospitalization. Fourteen (22.22%) patients were ventilated for 6 days or more and 20 (23.81%) stayed in the PICU for 12 d or more. This study showed a strong association between VIS at initial, 6, 12, 24, 48 h and maximum VIS with the risk of intubation (P-value of 0.047, 0.007, 0.012, 0.026, 0.012, and 0.009), cardiac arrest (P-value of 0.001-initial; <0.001-6 to 48 h and maximum VIS) and death during hospitalization (P-value of 0.002-initial; <0.001-6 to 48 h and maximum VIS). Results showed that initial upto maximum VIS within 48 h may capture a component of illness in pediatric septic shock and served as a surrogate outcome that highlights cardiovascular instability.Conclusion: This study showed that VIS is independently associated with poor outcomes such as risk for intubation, cardiac arrest, and death during hospitalization. VIS is easily measured and, if validated in pediatric sepsis, has the potential to standardize the quantification of hemodynamic support, identify, and stratify high-risk patient populations, and be used as a surrogate outcome measure.