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.

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: The aim of this study was 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) at Tygerberg Hospital, Cape Town. Methods and results: A latent class analysis (LCA) model was applied in a prospective, observational cohort study. Data from 343 COVID-19 patients were analysed. Two distinct phenotypes (1 and 2) were identified, comprising 68.46% and 31.54% of patients, respectively. The phenotype 2 patients were characterized 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 value 79 µmol/L vs 69.5 µmol/L; p < 0.003), under-perfusion markers (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 8.68; p < 0.001 and median monocyte 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 a prognostic marker in the 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.

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.