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INTRODUCTION: The clinical presentation of coronavirus disease 2019 (COVID-19) can vary widely, and while the primary infection involves the respiratory system, other organs can also be affected. This study presents the clinical and epidemiological characteristics of hospitalized COVID-19 patients in a tertiary hospital in Ado Ekiti, South-West Nigeria. MATERIALS AND METHODS: This is a retrospective study involving COVID-19 patients admitted to the isolation ward between August 2020 and January 2021. The data used for this study was obtained from the patient's medical record, which includes demographic characteristics, clinical presentation, baseline co-morbidities, and laboratory investigations. RESULTS: The average age of the patients was 60.3 years, and more than two-thirds were male. The most common symptoms were fever, shortness of breath, cough, and tiredness. Comorbidities identified among the patients included diabetes mellitus, heart disease, obesity, and chronic kidney disease. The most common radiological findings were bilateral homogeneous patchy opacities and peripheral fluffy infiltrates. The overall mortality rate was 21.9%, with 13 deaths in patients with severe disease. Age and duration of admission were found to be significant predictors of death. CONCLUSION: The results of this study provide valuable insights into the clinical presentation of COVID-19 in Nigeria and may guide future management strategies for similar infections.
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INTRODUCTION: Diabetes mellitus (DM) is an important global public health challenge, and the burden of the disease is huge, particularly in low- and middle-income countries (LMICs), where the majority of people with this condition reside. Undiagnosed DM is more prevalent in LMICs. The aim of this study is to determine the prevalence and associated factors for DM in Ekiti State. MATERIALS AND METHODS: A cross-sectional, household-based survey using a four-stage multistage sampling design and the World Health Organization (WHO)-STEPS survey manual was conducted from July to September 2020 as a part of the Ekiti State coronavirus disease 2019 (COVID-19) survey. Of the 5,145 sampled households, 4,726 individuals gave consent to participate in the survey. Out of these, 3043 had fasting plasma glucose results available and were included in the analysis. RESULTS: There were 2257 (74.2%) women and 786 (25.8%) men. The prevalence of DM was 6.5% (6.5% in males and 6.6% in females, P = 0.946). Diabetes was found to be more prevalent among those with a secondary school education or higher (10.9%); employed in the formal sector (13.4%); separated, divorced, or widowed (8.5%); with raised blood pressure (9.3%); and who were aged 30-59 years (all P < 0.05). Multivariable logistic regression showed that age, education, occupation, and hypertension were all positively and significantly associated with an increased risk of DM. CONCLUSION: The prevalence of DM in Ekiti State is high, and its predictors include advancing age, hypertension, education, and occupation. This calls for scaling up public health interventions for controlling DM, targeting the identified risk factors among the people of Ekiti.
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Background: Triglyceride-glucose (TyG) index, a product of triglyceride and fasting plasma glucose, is a novel tool that can identify people with metabolic syndrome (MS). It is unknown if TyG index can identify MS among Nigerians. Methods: Cross-sectional health screening conducted between August and December 2018, among staff and students of Ekiti State University/Ekiti State University Teaching Hospital, Nigeria, Ado-Ekiti. The analysis included 473 participants, aged ≥18 years. Anthropometric indices and blood pressure were measured by standard protocol. Fasting lipid profile and blood glucose were determined. TyG index and product of TyG and anthropometric indices were calculated, and MS defined according to the harmonized criteria. The diagnostic ability of TyG index and related parameters to identify people with MS was determined with the area under curve (AUC) of receiver operating characteristic curves. Stepwise logistic regression analyses were used to generate odd ratios (ORs) for prediction of MS. Results: The mean age of the participants was 39.2 (11.4) years and there were 173 (36.6%) men. In all participants, TyG-waist to height ratio (TyG-WHtR) shows the largest AUC for MS detection (0.863, 95% confidence interval, CI: 0.828-0.892) followed by TyG-waist circumference (TyG-WC) (0.858, 95% CI: 0.823-0.888), TyG-body mass index (TyG-BMI) (0.838, 95% CI: 0.802-0.870), TyG index (0.796, 95% CI: 0.757-0.831), WHtR (0.791, 95% CI: 0.752-0.827), and TyG-waist-to-hip ratio (TyG-WHpR) (0.771, 95% CI: 0.730-0.808) in that order. Gender analysis revealed that TyG-WC and TyG-WHtR have largest AUC in both genders. Before and after adjustment, TyG-WHtR (OR: 6.86, 95% CI: 3.94-11.93) and TyG index (OR: 5.91, 95% CI: 3.01-11.59) presented the highest OR in all participants, respectively. Conclusions: TyG index is effective in identifying MS in this cross-sectional study, and the product of TyG index and anthropometric indices improved identification and prediction of MS.
