Objective: To evaluate the variables influencing the length of stay (LoS) for COVID-19 ICU patients at Tygerberg Hospital (Cape Town) and to identify the covariates that significantly influenced it and any potential risk factors associated with LoS. Methods and Results: Poisson, negative binomial (NB), Hurdle–Poisson, and Hurdle–NB regression models were used to model the LoS in this prospective cohort study. The fitted models were compared using the Akaike information criterion (AIC), Vuong’s test criteria, and Rootograms. Based on the chosen performance criteria, the NB model provided the best fit outperforming other candidate models. The baseline LoS count was 8 days. On average, antibiotics reduced LoS by 0.74-fold (95% CI 0.62-0.89) compared to not taking antibiotics. The second wave had a significant effect on the average LoS, which decreased by 0.36-fold (95% CI 0.14-0.93) compared to the first wave. Average LoS increased by 1.01-fold (95% CI 1.01-1.02) for every one-year increase in the age of the patient and by 1.02-fold (95% CI 1.01-1.03) for every 1 unit increase in neutrophils. A 1 ng/L increase in log (TropT) levels decreased the average LoS by 0.87-fold (95% CI 0.81-0.93) similarly, a unit increase in the PF ratio decreased the average LoS by 0.998-fold (95% CI 0.997-0.999) respectively. Conclusion: The study identified common clinical characteristics associated with length of stay in ICU for COVID-19 patients, including age at admission, PF ratio, neutrophils, TropT, Wave, and antibiotic use. These results can aid in identifying risk factors for increased length of stay, assist in healthcare systems planning, and aid in evaluating different models for analysing this type of data.
Abstract Background Investigating the spatial distribution of SARS-CoV-2 at a local level and describing the pattern of disease occurrence can be used as the basis for efficient prevention and control measures. This research project aims to utilize geospatial analysis to understand the distribution patterns of SARS-CoV-2 and its relationship with certain co-existing factors. Methods Spatial characteristics of SARS-CoV-2 were investigated over the first four waves of transmission using ESRI ArcGISPro v2.0, including Local Indicators of Spatial Association (LISA) with Moran’s “I” as the measure of spatial autocorrelation; and Kernel Density Estimation (KDE). In implementing temporal analysis, time series analysis using the Python Seaborn library was used, with separate modelling carried out for each wave. Results Statistically significant SARS-CoV-2 incidences were noted across age groups with p-values consistently < 0.001. The central region of the district experienced a higher level of clusters indicated by the LISA (Moran’s I: wave 1 – 0.22, wave 2 – 0.2, wave 3 – 0.11, wave 4 – 0.13) and the KDE (Highest density of cases: wave 1: 25.1-50, wave 2: 101-150, wave 3: 101-150, wave 4: 50.1-100). Temporal analysis showed more fluctuation at the beginning of each wave with less fluctuation in identified cases within the middle to end of each wave. Conclusion A Geospatial approach of analysing infectious disease transmission is proposed to guide control efforts (e.g., testing/tracing and vaccine rollout) for populations at higher vulnerability. Additionally, the nature and configuration of the social and built environment may be associated with increased transmission. However, locally specific empirical research is required to assess other relevant factors associated with increased transmission.
Abstract Background The coronavirus disease 2019 (COVID-19) pandemic continues to evolve. Globally, COVID-19 continues to strain even the most resilient healthcare systems, with Omicron being the latest variant. We made a thorough search for literature describing the effects of the COVID-19 in a high human immunodeficiency virus (HIV)/tuberculosis (TB) burden district-level hospital setting. We found scanty literature. Methods A retrospective observational study was conducted at Khayelitsha District Hospital in Cape Town, South Africa (SA) over the period March 2020–December 2021. We included confirmed COVID-19 cases with HIV infection aged from 18 years and above. Analysis was performed to identify predictors of mortality or hospital discharge among people living with HIV (PLWH). Predictors investigated include CD4 count, antiretroviral therapy (ART), TB, non-communicable diseases, haematological, and biochemical parameters. Findings This cohort of PLWH with SARS-CoV-2 infection had a median (IQR) age of 46 (37–54) years, male sex distribution of 29.1%, and a median (IQR) CD4 count of 267 (141–457) cells/mm3. Of 255 patients, 195 (76%) patients were discharged, 60 (24%) patients died. One hundred and sixty-nine patients (88%) were on ART with 73(28%) patients having acquired immunodeficiency syndrome (AIDS). After multivariable analysis, smoking (risk ratio [RR]: 2.86 (1.75–4.69)), neutrophilia [RR]: 1.024 (1.01–1.03), and glycated haemoglobin A1 (HbA1c) [RR]: 1.01 (1.007–1.01) were associated with mortality. Conclusion The district hospital had a high COVID-19 mortality rate among PLWH. Easy-to-access biomarkers such as CRP, neutrophilia, and HbA1c may play a significant role in informing clinical management to prevent high mortality due to COVID-19 in PLWH at the district-level hospitals.
Respiratory diseases account for >10% of the global burden of disease when measured in disability-adjusted life-years. The burden of chronic respiratory diseases (CRDs) increases as the world's population ages, with a much greater increase in low- to middle-income countries.To characterise and quantify the reasons for acute respiratory presentations to the acute care services at a tertiary hospital in Cape Town, South Africa.A cross-sectional descriptive study was conducted. Casualty registers and electronic record databases were reviewed to determine the diagnoses of consecutive patients attending the casualty unit from May 2019 to January 2020.A total of 1 053 individual patients presented with a primary respiratory diagnosis. Fewer than 10% of admissions were from outside the Cape Town metropole, while >60% were from the subdistrict immediately adjacent to the hospital. Of all patients, 8.3% were readmitted at least once within the 9-month study period. Six hundred and forty-three (61.1%) of the patients presented with non-CRDs. The main reasons for presentation in these patients were pulmonary tuberculosis (PTB) (n=224; 21.3%), other infections including lower respiratory tract infections, pneumonia and bronchitis (n=272; 25.8%), and cancer (n=140; 13.3%). Haemoptysis was seen in 9.8% of all patients, mainly explained by post-tuberculosis lung disease (PTLD) (37.9%) and PTB (36.9%). Of the patients, 410 (38.9%) had an underlying CRD, with chronic pulmonary obstructive disease (COPD) being the most common (n=192; 18.2%), followed by PTLD (n=88; 8.5%) and asthma (n=52; 5.1%).Over a 9-month period, acute respiratory presentations to a tertiary hospital were mainly for primary/secondary level of care indications, highlighting disparity in accessing tertiary services. COPD and PTLD predominated among CRDs, while infections and cancers were common. A high readmission rate was found for several diseases, suggesting the potential for targeted interventions to prevent both admissions and readmissions and reduce acute hospital utilisation costs.
Before the COVID-19 pandemic, tuberculosis (TB) was the leading infectious cause of death globally. In low- and middle-income countries (LMIC) including Lesotho, treatment outcome is lower than the recommended rate and poor TB treatment outcomes remain a programmatic challenge. The aim of this study was to determine unfavourable treatment outcomes and associated risk factors among TB patients in Butha Buthe district. This was a retrospective record review of TB patients registered between January 2015 and December 2020. Data were collected from TB registers and patients' files and entered Microsoft Excel 2012. Analysis was conducted using R and INLA statistical software. Descriptive statistics were presented as frequencies and percentages. The differences between groups were compared using Pearson's X2 test in bivariate analysis. Frailty Cox proportional hazards model was used to determine the risk of unfavourable outcomes among the variables. A total of 1792 TB patients were enrolled in the study with about 70% males (1,257). Majority (71.7%) of the patients were between 20 and 59 years old, with 48% of the patients being unemployed. Almost a quarter of the patients (23.1%) had unfavourable outcomes with death (342 patients) being the most common unfavourable outcome. Our study has shown that patients older than 59 years, and unemployment increased the risk of having unfavourable treatment outcomes. Death was the most common unfavourable outcome followed by lost-to-follow up. We also observed that the patients in the initiation phase of treatment died at a faster rate compared to those in the continuation phase (p=0.02). TB treatment programs should have efficient follow-up methods geared more toward elderly patients. Active case finding to identify population at risk should be part of a TB program which would improve early diagnosis and treatment initiation. Patients in the intensive phase of the treatment program should be monitored more closely to determine adverse drug effects and nutritional requirement to prevent death during this phase of treatment.
Severe COVID-19 has a poor prognosis, and biomarkers may predict disease severity. This study aimed to assess the effect of baseline Vitamin D (VitD) inadequacy on outcome of patients with severe COVID-19 admitted to intensive care unit (ICU) in a tertiary hospital in South Africa.Patients with confirmed SARS-CoV-2 were recruited during wave II of the pandemic in Cape Town. Eighty-six patients were included in the study. They were categorized into three groups "VitD deficient, VitD insufficient and VitD sufficient". We combined the VitD deficient with insufficient group to form "VitD inadequate'' group. Cox regression analysis was done to assess the association between VitD status and mortality. Factors with p< 0.05 in adjusted multivariable cox regression were considered statistically significant.The proportion of VitD inadequacy was 64% (55/86), with significantly higher proportion of hypertension (66%; p 0.012). Kaplan Meir curve showed no significant difference in the probability of survival among the COVID-19 patients admitted in the ICU with or without VitD inadequacy. However, patients with elevated serum creatinine were significantly more at risk of dying (Adjusted Hazard Ratio 1.008 (1.002 - 1.030, p<0.017).Our study found a high prevalence of VitD inadequacy (combined deficiency and insufficiency) in COVID-19 patients admitted to the ICU. This may indicate a possible risk of severe disease. Whilst there was no statistically significant relationship between VitD status and mortality in this cohort, baseline VitD may be an important prognostic biomarker in COVID-19 patients admitted to the ICU, particularly in those with comorbidities that predispose to VitD deficiency.
Adolescents refer to individuals in the age group 10 to 19 years. Vaccination of people in this age group offers an opportunity to catch-up on vaccinations missed during childhood, boost waning immunity from childhood vaccines, and provide primary immunity with new vaccines. Vaccination coverage among adolescents is suboptimal worldwide, especially in African countries, and it is unclear which interventions could improve the situation. We focus this commentary on a recent Cochrane review that assessed the effects of interventions to increase vaccination coverage among adolescents. The authors conducted a comprehensive search in multiple peer-reviewed and grey literature databases and identified 16 eligible studies, mostly conducted in high-income countries. The most effective interventions for improving adolescent vaccination coverage included: education of adolescents and their parents about the importance of vaccinations; mandatory vaccination, whereby government enacts laws requiring adolescents to be vaccinated as a pre-condition for school enrolment; and providing a complementary package of educational interventions to adolescents and their parents and healthcare workers. Implementing the evidence from this review would improve adolescent vaccination coverage in Africa. However, given that only one eligible study was conducted in an African country, there is need for African researchers to invest on research in this topic.
Background Studies from Asia, Europe and the USA indicate that widely available haematological parameters could be used to determine the clinical severity of Coronavirus disease 2019 (COVID-19) and predict management outcome. There is limited data from Africa on their usefulness in patients admitted to Intensive Care Units (ICUs). We performed an evaluation of baseline haematological parameters as prognostic biomarkers in ICU COVID-19 patients. Methods Demographic, clinical and laboratory data were collected prospectively on patients with confirmed COVID-19, admitted to the adult ICU in a tertiary hospital in Cape Town, South Africa, between March 2020 and February 2021. Robust Poisson regression methods and receiver operating characteristic (ROC) curves were used to explore the association of haematological parameters with COVID-19 severity and mortality. Results A total of 490 patients (median age 54.1 years) were included, of whom 237 (48%) were female. The median duration of ICU stay was 6 days and 309/490 (63%) patients died. Raised neutrophil count and neutrophil/lymphocyte ratio (NLR) were associated with worse outcome. Independent risk factors associated with mortality were age (ARR 1.01, 95%CI 1.0–1.02; p = 0.002); female sex (ARR 1.23, 95%CI 1.05–1.42; p = 0.008) and D-dimer levels (ARR 1.01, 95%CI 1.002–1.03; p = 0.016). Conclusions Our study showed that raised neutrophil count, NLR and D-dimer at the time of ICU admission were associated with higher mortality. Contrary to what has previously been reported, our study revealed females admitted to the ICU had a higher risk of mortality.
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