key: cord-0735240-nozak1xg authors: Zemlin, Annalise E.; Allwood, Brian; Erasmus, Rajiv T.; Masha, Tandi E.; Chapanduka, Zivanai C.; Jalavu, Thumeka P.; Ngah, Vera; Sigwadhi, Lovemore N.; Koegelenberg, Coenraad F.; Irusen, Elvis; Lalla, Usha; Yalew, Anteneh; Baines, Nicola; Tamuzi, Jacques L.; Barasa, Anne K.; Magutu, Valerie Kemunto; Njeru, Caroline; Amayo, Angela; Mureithi, Marianne Wanjiru; Mungania, Mary; Sono-Setati, Musa; Zumla, Alimuddin; Nyasulu, Peter S. title: Prognostic value of biochemical parameters among severe COVID-19 patients admitted to an intensive care unit of a tertiary hospital in South Africa date: 2022-01-23 journal: IJID Regions DOI: 10.1016/j.ijregi.2022.01.012 sha: a6c858703eba36a7694c4720d4d13492979a0d37 doc_id: 735240 cord_uid: nozak1xg Background Data on biochemical markers and their association with mortality rates observed in patients with severe COVID-19 disease admitted to Intensive Care Units (ICUs) in sub-Saharan Africa are scanty. We performed an evaluation of baseline routine biochemical parameters as prognostic biomarkers in COVID-19 patients admitted to ICU. Methods Demographic, clinical, and laboratory data were collected prospectively on patients with PCR-confirmed COVID-19 admitted to the adult ICU in a tertiary hospital in Cape Town, South Africa, between October 2020 and February 2021. Robust Poisson regression methods and 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 (IQR: 46.4-59.7)] were enrolled, of whom 27 (33%) were male. The median duration of ICU stay was 10 days (IQR: 5-14); 54/82 (66% CFR) patients died. Baseline lactate dehydrogenase (LDH) (aRR: 1.002, 95%CI: 1.0004-1.004; P = 0.016) and N-terminal pro B-type natriuretic peptide (NTProBNP) (aRR: 1.0004, 95%CI: 1.0001-1.0007; P = 0.014) were both independent risk factors of a poor prognosis with optimal cut-off values of 449.5 U/L (sensitivity: 1; specificity: 0.43) and 551 pg/mL (sensitivity: 0.49; specificity: 0.86), respectively. Conclusion LDH and NTProBNP appear to be promising predictors of COVID-19 poor prognosis in the ICU. Larger sample size studies are required to confirm the validity of this combination of biomarkers. The The aim of this study was to evaluate baseline routine biochemical findings in patients admitted to the ICU in a tertiary hospital in the Western Cape of South Africa during the second wave and correlate these to the severity of the disease. This cohort study took place at Tygerberg Hospital, a 1380-bed tertiary hospital in Cape Town, South Africa. The hospital provides tertiary services to approximately 3.5 million people from the Western Cape Province. The study population comprised 82 consecutive patients with a positive SARS-COV-2 polymerase chain reaction (PCR) test admitted to the adult ICU during the second wave between 29 October 2020 and 10 February 2021. These biochemical parameters were routinely collected in the ICU. Patients were triaged by the intensivists according to disease severity and likely prognosis, according to provincial guidelines (CCSSA, 2020), and admission was dictated by bed availability. Due to infection control risk, data were captured prospectively using photographs of written clinical notes at the bedside, which were securely stored electronically, and clinical data were entered remotely by data-capturer into a Redcap® database. Laboratory results were imported from the National Health Laboratory Service (NHLS) Laboratory Information System (TrakCare® Lab Enterprise) into the database. Data were quality checked by the 'data entry supervisor' to ensure that data entered were of good quality and reliable. Patient confidentiality was ensured by labelling data with a unique episode number. The study was approved by the Health Research Ethics Committee of Stellenbosch University (approval number N20/04/002_COVID-19). The research project was conducted according to the ethical principles of the Declaration of Helsinki. Serum samples were collected on ICU admission on all study participants and analysed in the NHLS Chemical Pathology Laboratory on the Roche cobas ® 6000 analyser (Roche Diagnostics, Mannheim, Germany) according to the manufacturer's recommendations. The NHLS is the South African national state laboratory providing laboratory services to over 80% of the population. The levels of various parameters were determined as follows: sodium (Na + ) and potassium (K + ) using indirect ionselective electrode potentiometry, creatinine enzymatically, urea using a kinetic assay with urease, alanine aminotransferase (ALT), and lactate dehydrogenase (LDH) enzymatically, bilirubin using the colorimetric diazo method, C-reactive protein (CRP) immunoturbidimetrically and high-sensitivity troponin T (hs-TnT), N-terminal pro-brain natriuretic peptide (NT-proBNP), procalcitonin (PCT) and ferritin using an electrochemiluminescent immunoassay and glycated haemoglobin (HbA1c) using a turbidimetric inhibition immunoassay. The estimated glomerular filtration rate (eGFR) was determined using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula without correction for the race; a calculation recommended by the Kidney Disease Improving Global Outcomes (KDIGO) report (Levey et al., 2020) . National Accreditation Services (SANAS), a regulatory body responsible for laboratory conformity to ISO15189 assessments in South Africa. Result quality is validated with internal quality control and the laboratory participates in an external quality control scheme. Data collected included sociodemographic (age, sex), pre-existing comorbidities associated with severe COVID-19 outcome (hypertension, diabetes mellitus, and hyperlipidaemia), and routinely collected biochemistry. The primary outcome was the proportion of patients who died (non-survivors) after admission to the ICU. Time to death or discharge and length of stay in ICU was assessed. Continuous variables were expressed as mean with standard deviation for normal data and median with inter-quartile range for non-normal data. Categorical variables were expressed using frequencies and percentages. Robust Poisson regression was used to assess the significant association between demographic, laboratory results, and survival. Factors associated with death at p-value < 0.15 in unadjusted univariable robust Poisson regression were included in a multivariable model to identify independent factors associated with death. Due to the high prevalence of mortality, around 66%, the logistic regression overestimated the effect measure with large standard errors resulting in wide confidence intervals, therefore robust Poisson regression was used. Adjusted incidence rate ratios and their 95% CIs were used as a measure of association. Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of various biochemical analytes to discriminate between severely diseased cases in terms of survival and non-survival. Factors with p<0.05 were considered significantly associated with mortality. All statistical analyses were performed using Stata (V.16, Stata Corp, College Station, statistical software. In this cohort, 82 patients with a median age of 53.8 years (IQR: 46.4-59.7) were admitted from October 2020 to February 2021. Table 1 shows the demographic characteristics. There were 27 males (33%) and underlying comorbidities considered in this analysis were hypertension (n = 39, 57%), diabetes mellitus (n= 34, 50%) and hyperlipidaemia (n= 5, 7%). The median duration of stay in ICU was 10 days (IQR: 5-14) days, and of the 82 in whom outcome data were available at database censure, 54/82 (66%) died in ICU. The association between baseline biochemical parameters in survivors and nonsurvivors is shown in table 2. Electrolyte results, namely Na + and K + showed no significant differences between the 2 groups (p= 0.37 and 0.51 respectively). Markers of renal function showed no significant difference in urea and creatinine levels between the 2 groups (p=0.18 and 0.097 respectively), however, the eGFR was decreased (p=0.046) in the non-survivor group. HbA1c showed no statistical difference between survivors and non-survivors (p=0.33). Markers of liver function showed no significant difference in bilirubin and ALT between the 2 groups (p= 0.65 and 0.81 respectively), but the non-specific marker LDH was significantly increased in non-survivors (p=0.014). Markers of cardiac function showed significantly increased levels of TnT and NT-proBNP in nonsurvivors (p=0.006 and 0.004 respectively). Markers of inflammation showed significantly higher levels of CRP and PCT in non-survivors (p= 0.014 and 0.003 respectively). Even though ferritin levels were increased, there was no statistically significant difference between survivors and non-survivors (p= 0.88). As the adjusted RR was significant for LDH and NTProBNP, we determined the optimal cut-offs to predict non-survival and test the performance of these two parameters using ROC curves. The proposed optimum cut-off points for LDH and NT-ProBNP that could predict COVID-19 severity and mortality in the ICU were respectively ≥ 449.5 U/L with sensitivity = 100%, specificity = 43%, AUC = 0.73 and ≥ 551 pg/mL with sensitivity = 49%, specificity = 86%, AUC = 0.72 (Table 4 ). However, the performance of both was suboptimal to use as a prediction marker on their own (see figure 1 ). Although There were several notable findings from this study, including the observation that in non-survivors the eGFR was significantly decreased while the LDH levels were significantly increased. Furthermore, surrogate markers of cardiac dysfunction, namely TnT and NT-proBNP, and inflammatory markers, namely CRP and PCT, were significantly elevated among non-survivors. However, only LDH and NT-proBNP were significant predictors of disease severity. Other biochemical parameters such as serum Na + and K + ( . As these findings are thought to be due to increased transmissibility of the variants of concern, other laboratory biomarkers may be useful to predict disease severity. In our cohort, we examined routine biochemical tests which included electrolytes, markers of renal, hepatic, and cardiac dysfunction as well as markers of inflammation and correlated them with survival. As hepatocytes express angiotensin-converting enzyme (ACE)-2 receptors, liver damage may be due to direct infection (Chai et al., 2020), but also due to hepatotoxic drugs, systemic inflammatory response, hypoxia, or multiorgan failure (Feng et al., 2020) . In our cohort, we found no significant difference in bilirubin or ALT levels, however, LDH was significantly raised in non-survivors. This agrees with previous studies and high LDH was one of the first markers of disease severity survivors and non-survivors, we found increased levels in survivors. However, this difference was not statistically significant, and our numbers were small. When analysing the unadjusted risk ratio in our cohort, urea, creatinine, eGFR, LDH, TnT, NT-proBNP, CRP, and PCT were significantly associated with the risk of nonsurvival. However, using adjusted RR, only LDH and NT-proBNP were significantly associated with risk. We then determined optimal cut-offs of these 2 analytes to predict severity. However, the performance of both was suboptimal to use on their own as predictive markers. Chronic kidney disease is associated with worse outcomes in COVID-19 . In our study, we found slightly higher urea and creatinine with lower eGFR levels in non-survivors, but these differences were neither statistically nor clinically significant. Other studies have described higher urea levels to be associated with severity (Bonetti et al., 2020; Boufrioua et al., 2021) . We found no significant differences in Na + and K + levels between survivors and non- Our findings also showed that non-survivors were slightly older, more likely to be male and smokers, there was no statistical difference between the two groups. ). However, in our cohort, although 57% of the participants were hypertensive, we found no significant difference between survivors and non-survivors for hypertension or diabetes mellitus. It must however be noted that the median HbA1c levels were raised at > 7% in both groups. A level of > 6.5% is diagnostic of diabetes. Our results agree with a recent study conducted in South Africa (Hesse et al., 2021). Our study had some limitations. We had a small population and only analysed baseline ICU admission laboratory data. A larger sample population may have increased the statistical significance of our markers. Ideally, we would have analysed the trend over their ICU stay, but the numbers were too small on subsequent days. Our study had certain strengths, namely, all patients were admitted to the same ICU and had samples analysed on admission in the same laboratory ensuring harmonization of the pre-analytical and analytical phases of testing. Further larger studies are needed to evaluate these biomarkers to determine their use in developing a risk score as earlier identification of patients at high risk of poor prognosis and institution of early interventions may be effective in reducing COVID-19 mortality among patients admitted in the ICU. Our study identified LDH and NT-proBNP biochemical markers which may be associated with poor COVID-19 outcomes in patients admitted to the ICU. To increase predictive probability there is a need to combine biomarkers assessment and not only rely on a single parameter estimate. i.e., combining LDH and NT-proBNP increases the sensitivity of predicting mortality rather than relying on a single biomarker. 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