Health-related quality of life among people living with HIV in the era of universal test and treat: results from a cross-sectional study in KwaZulu-Natal, South Africa

BACKGROUND

The World Health Organisation's (WHO) key population-based strategy for ending the human immunodeficiency virus (HIV) epidemic is universal HIV test and treat (UTT) along with pre-exposure prophylaxis (PrEP), and post-exposure prophylaxis (PEP). Despite the successful scale-up of the UTT strategy in sub-Saharan Africa (SSA), the quality of life (QoL) of people living with HIV (PLHIV) remains sub-optimal. Poor QoL in PLHIV may threaten the UNAIDS 95-95-95 programme targets. Monitoring QoL of PLHIV has become a key focus of HIV research among other outcomes so as to understand health-related QoL (HRQoL) profiles and identify interventions to improve programme performance. This study aimed to describe HRQoL profiles and identify their predictors in PLHIV in KwaZulu Natal, South Africa.

METHODS

We conducted a secondary data analysis of a cross-sectional survey conducted between May and June 2022 among PLHIV (n = 105) accessing HIV services at an outpatient clinic in KwaZulu-Natal, South Africa. Socio-demographic, HRQoL (EQ-5D-5L index scores), clinical data, depressive symptoms (CES-D-10), and viral load data were collected from all participants. We examined predictors of HRQoL using generalised linear models controlling for age and sex.

RESULTS

The mean age of the participants was 45 years (SD = 13). The proportion of participants with disabilities and comorbidities were 3% and 18%, respectively. Depressive symptoms were present in 49% of the participants. Participant's mean EQ-5D-5L index score was 0.87 (SD = 0.21) and ranged from 0.11 to 1.0. The mean general health state (EQ-VAS) was 74.7 (SD = 18.8) and ranged from 6 to 100. Factors that reduced HRQoL were disability (β = -0.607, p ≤ 0.001), comorbidities (β = - 0.23, p ≤ 0.05), presence of depressive symptoms (β = -0.10, p ≤ 0.05), and old age (β = -0.04, p ≤ 0.05). Factors that increased HRQoL were a good perceived health state (β = 0.147, p ≤ 0.001) and availability of social support (β = 0.098, p ≤ 0.05).

CONCLUSION

A combination of old age (60 years and above), any disability and comorbidities had a considerable effect on HRQoL among PLHIV. Our findings support the recommendation for an additional fourth UNAIDS target that should focus on ensuring that 95% of PLHIV have the highest possible HRQoL. Psycho-social support interventions are recommended to improve the HRQoL of PLHIV.

Machine learning algorithms for predicting determinants of COVID-19 mortality in South Africa

Background

COVID-19 has strained healthcare resources, necessitating efficient prognostication to triage patients effectively. This study quantified COVID-19 risk factors and predicted COVID-19 intensive care unit (ICU) mortality in South Africa based on machine learning algorithms.

Methods

Data for this study were obtained from 392 COVID-19 ICU patients enrolled between 26 March 2020 and 10 February 2021. We used an artificial neural network (ANN) and random forest (RF) to predict mortality among ICU patients and a semi-parametric logistic regression with nine covariates, including a grouping variable based on K-means clustering. Further evaluation of the algorithms was performed using sensitivity, accuracy, specificity, and Cohen's K statistics.

Results

From the semi-parametric logistic regression and ANN variable importance, age, gender, cluster, presence of severe symptoms, being on the ventilator, and comorbidities of asthma significantly contributed to ICU death. In particular, the odds of mortality were six times higher among asthmatic patients than non-asthmatic patients. In univariable and multivariate regression, advanced age, PF1 and 2, FiO2, severe symptoms, asthma, oxygen saturation, and cluster 4 were strongly predictive of mortality. The RF model revealed that intubation status, age, cluster, diabetes, and hypertension were the top five significant predictors of mortality. The ANN performed well with an accuracy of 71%, a precision of 83%, an F1 score of 100%, Matthew's correlation coefficient (MCC) score of 100%, and a recall of 88%. In addition, Cohen's k-value of 0.75 verified the most extreme discriminative power of the ANN. In comparison, the RF model provided a 76% recall, an 87% precision, and a 65% MCC.

Conclusion

Based on the findings, we can conclude that both ANN and RF can predict COVID-19 mortality in the ICU with accuracy. The proposed models accurately predict the prognosis of COVID-19 patients after diagnosis. The models can be used to prioritize COVID-19 patients with a high mortality risk in resource-constrained ICUs.

An investigation of the correlation of vitamin D status and management outcomes in patients with severe COVID-19 at a South African tertiary hospital

Background

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.

Methods

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.

Results

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).

Conclusion

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.

The association between acid-base status and clinical outcome in critically ill COVID-19 patients admitted to intensive care unit with an emphasis on high anion gap metabolic acidosis

OBJECTIVE

The aim of this study was to identify arterial blood gas (ABG) abnormalities, with a focus on a high anion gap (AG) metabolic acidosis and evaluate outcomes in coronavirus disease 2019 (COVID-19) patients admitted to the ICU.

METHODS

A retrospective, observational study was conducted in a tertiary hospital in Cape Town during the first and second COVID-19 waves. Age, gender, sodium (Na), potassium (K), chloride (Cl), bicarbonate (HCO₃std), pH, partial pressure of carbon dioxide (pCO₂), creatinine, estimated glomerular filtration rate (eGFR), lactate levels and ABG results were obtained. The Pearson χ2 test or Fisher exact test and the Wilcoxon rank-sum test were used to compare mortality and survival. To identify factors associated with non-survival, a multivariable model was developed.

RESULTS

This study included 465 patients, 226 (48%) of whom were female. The sample population's median (IQR) age was 54.2 (46.1-61.3) years, and 63% of the patients died. ABG analyses found that 283 (61%) of the 465 patients had alkalosis (pH ≥ 7.45), 65 (14%) had acidosis (pH ≤ 7.35) and 117 (25%) had normal pH (7.35-7.45). In the group with alkalosis, 199 (70.3%) had a metabolic alkalosis and in the group with acidosis, 42 (64%) had a metabolic acidosis with an increased AG of more than 17. Non-survivors were older than survivors (56.4 years versus 50.3 years, p < .001).

CONCLUSION

Most of the COVID-19 patients admitted to the ICU had an alkalosis, and those with acidosis had a much worse prognosis. Higher AG metabolic acidosis was not associated with patients' characteristics.

The clinical and epidemiological characteristics of a series of patients living with HIV admitted for COVID-19 in a district hospital

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.

Haematological predictors of poor outcome among COVID-19 patients admitted to an intensive care unit of a tertiary hospital in South Africa

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.

Latent Class Analysis: An innovative approach for identification of clinical and laboratory markers of disease severity among COVID-19 patients admitted to the Intensive Care Unit

Objective

To identify clinical and laboratory phenotype distribution patterns and their usefulness as prognostic markers in COVID-19 patients admitted to the intensive care unit (ICU) in Tygerberg Hospital, Cape Town.

Methods and Results

We used a latent class analysis (LCA) model in a prospective, observational cohort study. Data from 343 COVID-19 patients was analysed. Two distinct phenotypes 1 and 2, comprising 68.46 % and 31.54% patients respectively, were identified. The phenotype 2 patients were characterised by increased coagulopathy markers (D-dimer, median value 1.73 ng/L vs 0.94 ng/L, p <0.001), end-organ dysfunction (creatinine, median 79 µmol/L vs 69.5 µmol/L, p <0.003), under-perfusion marker (lactate, median value 1.60 mmol/L, vs 1.20 mmol/L, p <0.001), abnormal cardiac function markers (median N-terminal pro-brain natriuretic peptide (NT-proBNP) 314 pg/ml vs 63.5 pg/ml, p <0.001 and median high-sensitivity cardiac troponin (Hs-TropT) 39 ng/l vs 12 ng/ l, p<0.001) and acute inflammatory syndrome (median neutrophil-to-lymphocyte ratio 15.08 vs value 8.68, p <0.001 and monocyte, median value 0.68 × 10⁹/L vs 0.45 × 10⁹/L, p <0.001).

Conclusion

The identification of COVID-19 phenotypes and sub-phenotypes in ICU patients could help as prognostic markers in day-to-day management of COVID-19 patients admitted to the ICU.

Predicting COVID-19 outcomes from clinical and laboratory parameters in an intensive care facility during the second wave of the pandemic in South Africa

Background

The second wave of coronavirus disease 2019 (COVID-19) in South Africa was caused by the Beta variant of severe acute respiratory syndrome coronavirurus-2. This study aimed to explore clinical and biochemical parameters that could predict outcome in patients with COVID-19.

Methods

A prospective study was conducted between 5 November 2020 and 30 April 2021 among patients with confirmed COVID-19 admitted to the intensive care unit (ICU) of a tertiary hospital. The Cox proportional hazards model in Stata 16 was used to assess risk factors associated with survival or death. Factors with P<0.05 were considered significant.

Results

Patients who died were found to have significantly lower median pH (P<0.001), higher median arterial partial pressure of carbon dioxide (P<0.001), higher D-dimer levels (P=0.001), higher troponin T levels (P=0.001), higher N-terminal-prohormone B-type natriuretic peptide levels (P=0.007) and higher C-reactive protein levels (P=0.010) compared with patients who survived. Increased standard bicarbonate (HCO3std) was associated with lower risk of death (hazard ratio 0.96, 95% confidence interval 0.93-0.99).

Conclusions

The mortality of patients with COVID-19 admitted to the ICU was associated with elevated D-dimer and a low HCO3std level. Large studies are warranted to increase the identification of patients at risk of poor prognosis, and to improve the clinical approach.

Prognostic value of biochemical parameters among severe COVID-19 patients admitted to an intensive care unit of a tertiary hospital in South Africa

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This study evaluated baseline routine biochemical parameters in COVID-19 patients admitted to the ICU so as to identify risk predictors of disease severity and poor outcomes.

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Lactate dehydrogenase (LDH) and N-terminal pro B-type natriuretic peptide (NT-proBNP) were found to be independent risk factors of poor prognosis among COVID-19 patients admitted in the ICU.

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More detailed investigations on the predictors of COVID-19 severity and mortality in the ICU are required.

Background

Data on biochemical markers and their association with mortality rates in patients with severe coronavirus disease 2019 (COVID-19) admitted to intensive care units (ICUs) in sub-Saharan Africa are scarce. An evaluation of baseline routine biochemical parameters was performed in COVID-19 patients admitted to the ICU, in order to identify prognostic biomarkers.

Methods

Demographic, clinical, and laboratory data were collected prospectively from patients with PCR-confirmed COVID-19 admitted to the adult ICU of a tertiary hospital in Cape Town, South Africa, between October 2020 and February 2021. Robust Poisson regression methods and the receiver operating characteristic (ROC) curve were used to explore the association of biochemical parameters with severity and mortality.

Results

A total of 82 patients (median age 53.8 years, interquartile range 46.4–59.7 years) were enrolled, of whom 55 (67%) were female and 27 (33%) were male. The median duration of ICU stay was 10 days (interquartile range 5–14 days); 54/82 patients died (66% case fatality rate). Baseline lactate dehydrogenase (LDH) (adjusted relative risk 1.002, 95% confidence interval 1.0004–1.004; P = 0.016) and N-terminal pro B-type natriuretic peptide (NT-proBNP) (adjusted relative risk 1.0004, 95% confidence interval 1.0001–1.0007; P = 0.014) were both found to be independent risk factors of a poor prognosis, with optimal cut-off values of 449.5 U/l (sensitivity 100%, specificity 43%) and 551 pg/ml (sensitivity 49%, specificity 86%), respectively.

Conclusions

LDH and NT-proBNP appear to be promising predictors of a poor prognosis in COVID-19 patients in the ICU. Studies with a larger sample size are required to confirm the validity of this combination of biomarkers.

Comparison of patients with severe COVID-19 admitted to an intensive care unit in South Africa during the first and second wave of the COVID-19 pandemic

Background

The second wave of coronavirus disease 2019 (COVID-19), dominated by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Beta variant, has been reported to be associated with increased severity in South Africa (SA).

Objectives

To describe and compare clinical characteristics, management and outcomes of COVID-19 patients admitted to an intensive care unit (ICU) in SA during the first and second waves.

Methods

In a prospective, single-centre, descriptive study, we compared all patients with severe COVID-19 admitted to ICU during the first and second waves. The primary outcomes assessed were ICU mortality and ICU length of stay (LOS).

Results

In 490 patients with comparable ages and comorbidities, no difference in mortality was demonstrated during the second compared with the first wave (65.9% v. 62.5%, p=0.57). ICU LOS was longer in the second wave (10 v. 6 days, p<0.001). More female admissions (67.1% v. 44.6%, p<0.001) and a greater proportion of patients were managed with invasive mechanical ventilation than with non-invasive respiratory support (39.0% v. 14%, p<0.001) in the second wave.

Conclusion

While clinical characteristics were comparable between the two waves, a higher proportion of patients was invasively ventilated and ICU stay was longer in the second. ICU mortality was unchanged.

Factors associated with high HIV-related stigma among commuter populations in Johannesburg, South Africa

Stigma remains an important barrier to seeking and staying in care among individuals infected with Human Immunodeficiency Virus (HIV). Despite continued widespread information, education and communication campaigns to raise awareness about the infection. The aim of the study was to identify factors related to HIV stigma among a commuter population in the inner-city Johannesburg. A self-administered closed-ended questionnaire was loaded onto personal tablet computers during a community outreach campaign. The outcome was measured by asking the respondents to rate their perceptions of stigma as 'high or low'. About 1146 participants were enrolled in the study of which 585 (51.0%) reported high stigma levels. Overall, being married/cohabiting (Adjusted Prevalence Ratio (APR): 1.14 95%CI: 1.02-1.28), divorced (APR: 1.38 95%CI: 1.07-1.78), were associated with high levels of stigma; while being aware of HCT services (APR: 0.85 95%CI: 0.75-0.97) and employment status (APR: 0.78 95%CI: 0.71-0.87) were less likely associated with a high level of stigma. High HIV stigma still exists among those affected in our communities. Enhancement of health promotion intervention and reinforcing the benefits of knowing HIV status is essential to mitigate factors shown to influence stigma in the commuter population. Such an approach would help overcome stigma, an obstacle for expanding access to HIV testing and counselling.