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BackgroundDespite it being a global pandemic, there is little research examining the clinical features of severe COVID-19 in sub-Saharan Africa. This study aims to identify predictors of mortality in COVID-19 patients at Kinshasa Medical Center (KMC).MethodsIn this retrospective, observational, cohort study carried out at the Kinshasa Medical Center (KMC) between March 10, 2020 and July 10, 2020, we included all adult inpatients (≥ 18 years old) with a positive COVID-19 PCR result. The end point of the study was survival. The study population was dichotomized into survivors and non-survivors group. Kaplan–Meier plot was used for survival analyses. The Log-Rank test was employed to compare the survival curves. Predictors of mortality were identified by Cox regression models. The significance level of p value was set at 0.05.Results432 patients with confirmed COVID-19 were identified and only 106 (24.5%) patients with moderate, severe or critical illness (mean age 55.6 ± 13.2 years old, 80.2% were male) were included in this study, of whom 34 (32%) died during their hospitalisation. The main complications of the patients included ARDS in 59/66 (89.4%) patients, coagulopathy in 35/93 (37.6%) patients, acute cardiac injury in 24/98 (24.5%) patients, AKI in 15/74 (20.3%) patients and secondary infection in 12/81 (14.8%) patients. The independent predictors of mortality were found to be age [aHR 1.38; 95% CI 1.10–1.82], AKI stage 3 [aHR 2.51; 95% CI 1.33–6.80], proteinuria [aHR 2.60; 95% CI 1.40–6.42], respiratory rate [aHR 1.42; 95% CI 1.09–1.92] and procalcitonin [aHR 1.08; 95% CI 1.03–1.14]. The median survival time of the entire group was 12 days. The cumulative survival rate of COVID-19 patients was 86.9%, 65.0% and 19.9% respectively at 5, 10 and 20 days.Levels of creatinine (p = 0.012), were clearly elevated in non-survivors compared with survivors throughout the clinical course and increased deterioration.ConclusionMortality rate of COVID-19 patients is high, particularly in intubated patients and is associated with age, respiratory rate, proteinuria, procalcitonin and acute kidney injury.

Background: it is difficult to measure directly insulin sensitivity in routine practice. An easily measured anthropometric parameter associated with insulin resistance (IR) would be a very useful tool in detecting people at risk. Objective: To investigate the association between neck circumference (NC) and Insulin Resistance (IR) in Bantu population. Methods: Cross-sectional health screening conducted between February and May 2019, among Bantu population from Brazzaville in Republic of Congo. The analysis included 500 participants, aged ≥ 20 years. Anthropometric indices and blood pressure were measured by standard protocol. Fasting lipid profile, blood glucose and insulin were determined. Triglyceride Glucose index (TyG index) and triglyceride/high density lipoprotein ratio (TG/HDL) were calculated. IR was defined as HOMA-IR ≥ 2. TyG index was calculated by using the formula: Ln [TG (mg/dL) x FPG (mg/dL)/2]. To investigate if there was a statistically association between NC and IR parameters, a correlation was computed. To evaluate the influence of NC on IR parameters, the study population was divided in 3 groups by tertiles of NC in both men and women The diagnostic ability of NC, WC, TyG index and TG/HDL ratio to identify people with IR was determined with the receiver operating characteristic (ROC) curves. Results: NC was positively correlated with insulin, TG/HDL, TyG index and HOMA-IR. For all variables, this correlation was stronger in comparison with WC. In all participants, TG/HDL shows the largest AUC for IR detection (0.810, 95% CI: 0.765–0.855) followed by TyG index (0.799, 95% CI: 0.754–0.844), NC (0.624, 95% CI: 0.572–0.677), and WC (0.616, 95% CI: 0.560–0.672) in that order. Conclusion: NC is associated with IR. NC is better than WC to identify IR in Bantu population from Brazzaville in republic of Congo.

Background: The diagnosis of hypertension in children and adolescents is not always easy. The blood pressure-to-height ratios (BPHR) have been proposed as a screening tool for diagnosing hypertension. Objective: To evaluate the diagnostic value of BPHR for detecting hypertension in young adults. Methods: A cross-sectional study was conducted among 12621 healthy young adults aged of 18-25 years in Kinshasa, from July 2018 to February 2019. Systolic blood pressure-to-height ratio (SBPHR) was calculated as systolic blood pressure (SBP) in mmHg devised by height in centimeter. Diastolic blood pressure-to-height ratio (DBPHR) was calculated as diastolic blood pressure (DBP) in mmHg devised by height in centimeter. The receiver operating characteristics (ROC) curve analysis had allowed determining the cut-off points of SBPHR and DBPHR to detect hypertension. Results: The prevalence of hypertension, prehypertension, obesity and overweight were 10.5%, 9.2%, 3.0% and 22.4% respectively. The median values of SBPHR were 0.75 (0.69-0.79) mmHg/cm and 0.77 (0.67-0.80) mmHg/cm respectively in men and in women. The median values of DBPHR were 0.48 (0.44-0.53) mmHg/cm and 0.51 (0.49-0.56) mmHg/cm respectively in men and in women. Optimal cutoff points of SBPHR to identify hypertensionwere0.81mmHg/cm and 0.89 mmHg/cm respectively in men and in women. The threshold of DBPHR to detect hypertension was 0.54 mmHg/cm in both men and women. SBPHR and DBPHR had high sensitivity and specificity for identifying hypertension. Conclusion: SBPHR and DBPHR can be used to detect hypertension in Bantu young adults in Kinshasa.

aims: To investigate the association between neck circumference (NC) and abdominal obesity indicators: waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), Lipid Accumulation Product (LAP), Visceral Adiposity Index (VAI) and Abdominal volume index (AVI), in Bantu population at Brazzaville. Methods: A total of 500 subjects (mean age: 47.2±13.6 years) were recruited in Brazzaville to perform anthropometric measurements, including WC and hip circumference (HC), NC, body mass index (BMI), Blood pressure, fasting glucose and insulin, and lipid profile (total cholesterol TC, high-density lipoprotein cholesterol HDL, low-density lipoprotein cholesterol LDL, and triglyceride TG levels) were determined. The LAP, VAI and AVI were calculated as: LAP=[WC (cm) – 65] x TG (mmol/l); VAI=[WC (cm) / 39.68+ 1.88 x BMI (kg/m2)] x [TG (mmol/l)/1.03) x [1.31/ HDL (cm)] for males and LAP=[WC (cm) – 58] x TG (mmol/l); VAI=[WC (cm) / 36.58+ 1.89 x BMI (kg/m2)] x [TG (mmol/l)/0.81) x [1.52/ HDL (cm)] for females. For both males and females: AVI=[2 cm x WC2 (cm)2 + 0.7 cm x (WC – HC)2]/1000. Results: NC was significantly (p

Objective: To investigate the association between neck circumference (NC) and traditional cardiometabolic risk factors (CMRF) among adult’s population at Kinshasa. Methods: A total of 400 participants were recruited. Spearman’s correlation coefficient was employed to test the correlations between NC and CMRF. The association of NC with CMRF (dependent variables) was assessed by logistic regression. The receiver operating characteristics (ROC) curve analysis had allowed determining the cut-off points of NC to detect the presence of CMRF. Results: The average of age and WC was 55.4±12.0 years and 79.8±12.0 cm, respectively. The median value of BMI was significantly higher in women (24.6 kg/m2) than in men (22.6 kg/m2); whereas the median value of NC was significantly higher in men (37.8 cm) than in women (33.3 cm) (p < 0.001). In both men and women, NC was positively correlated with TC, LDL, TG and WC. Additionally, FPG and HDL were positively correlated with NC significantly. Moreover, there was a significant positive correlation between NECK and FPG but a significant negative correlation between NECK and HDLc among women. TG in men, raised TC, LDL and WC were found to be significantly associated with neck circumference with ORs 1.25 (95% CI: 1.08, 1.44), 0.67 (95% CI: 0.53, 0.85), 1.13 (95% CI: 1.02, 1.26), 1.27 (95% CI: 1.12, 1.45) in men versus 1.18 (95% CI: 1.03, 1.36) in women, 1.19 (95% CI: 1.06, 1.34) in men versus 1.21 (95% CI: 1.06, 1.38) in women and 1.18 (95% CI: 1.06, 1.36) in men versus 1.43 (95% CI: 1.23, 1.66) in women, respectively. Cut-off points for NC to identify CMRF were between 37.5 and 38 cm in men, 32.5 and 33 cm in women. Conclusion: NC is associated with CMRF, and could be a useful and accurate tool to identify high risk participants.