RESUMO
Methods: We included all patients with respiratory symptoms (dyspnea, fever, and cough) and/or respiratory failure admitted to the SOS Médecins de nuit SARL hospital, DR Congo, during the 2nd and 3rd waves of the COVID-19 pandemic. The diagnosis of COVID-19 was established based on RT-PCR anti-SARS-CoV-2 tests (G1 (RT-PCR positive) vs. G2 (RT-PCR negative)), and all patients had a chest CT on the day of admission. We retrieved the digital files of patients, precisely the clinical, biological, and chest CT parameters of the day of admission as well as the vital outcome (survival or death). Chest CT were read by a very high-definition console using Advantage Windows software and exported to the hospital network using the RadiAnt DICOM viewer. To determine the threshold for the percentage of lung lesions associated with all-cause mortality, we used ROC curves. Factors associated with death, including chest CT parameters, were investigated using logistic regression analysis. Results: The study included 200 patients (average age 56.2 ± 15.2 years; 19% diabetics and 4.5% obese), and COVID-19 was confirmed among 56% of them (G1). Chest CT showed that ground glass (72.3 vs. 39.8%), crazy paving (69.6 vs. 17.0%), and consolidation (83.9 vs. 22.7%), with bilateral and peripheral locations (68.8 vs. 30.7%), were more frequent in G1 vs. G2 (p < 0.001). No case of pulmonary embolism and fibrosis had been documented. The lung lesions affecting 30% of the parenchyma were informative in predicting death (area under the ROC curve at 0.705, p = 0.017). In multivariate analysis, a percentage of lesions affecting 50% of the lung parenchyma increased the risk of dying by 7.194 (1.656-31.250). Conclusion: The chest CT demonstrated certain characteristic lesions more frequently in patients in whom the diagnosis of COVID-19 was confirmed. The extent of lesions affecting at least half of the lung parenchyma from the first day of admission to hospital increases the risk of death by a factor of 7.
Assuntos
COVID-19 , SARS-CoV-2 , Tomografia Computadorizada por Raios X , Humanos , COVID-19/diagnóstico por imagem , COVID-19/mortalidade , Pessoa de Meia-Idade , Feminino , Masculino , Tomografia Computadorizada por Raios X/métodos , Prognóstico , Idoso , Adulto , Pulmão/diagnóstico por imagem , República Democrática do Congo/epidemiologia , Estudos RetrospectivosRESUMO
Introduction: Non-communicable diseases (NCDs), the leading cause of death globally, are estimated to overtake communicable diseases in sub-Sahara Africa, where healthcare workers (HCWs) play a crucial role in prevention and treatment, but are in extreme shortage, thereby increasing the burden of NCDs among this specific population. To provide evidence for policy-making, we assessed the NCD burden, associated factors and treatment among HCWs in four sub-Saharan African countries. Materials and methods: We conducted a cross-sectional study across four sub-Saharan African countries [Côte d'Ivoire (CIV), Democratic Republic of the Congo (DRC), Madagascar (MDG), and Nigeria (NIG)] between February and December 2022. In a standardized questionnaire, sociodemographic, chronic disease and treatment data were self-reported. We estimated the prevalence of (1) at least one chronic disease, (2) hypertension, and used backward elimination logistic regression model to identify risk factors. Results: We recruited a total of 6,848 HCWs. The prevalence of at least one chronic disease ranged between 9.7% in NIG and 20.6% in MDG, the prevalence of hypertension between 5.4% in CIV and 11.3% in MDG. At most, reported treatment rates reached 36.5%. The odds of each of both outcomes increased with age (at least one chronic disease adjusted odds ratio: CIV: 1.04; DRC: 1.09; MDG: 1.06; NIG: 1.10; hypertension: CIV: 1.10; DRC: 1.31; MDG: 1.11; NIG: 1.11) and with BMI (at least one chronic disease: CIV: 1.10; DRC: 1.07; MDG: 1.06; NIG: 1.08; hypertension: CIV: 1.10; DRC: 1.66; MDG: 1.13; NIG: 1.07). Odds of both outcomes were lower among males, except in CIV. In NIG, the odds of both outcomes were higher among medical doctors and odds of hypertension were higher among those working in secondary care. In MDG, working in secondary care increased and working as auxiliary staff decreased the odds of at least one chronic disease. Conclusion: The prevalence of self-reported chronic disease varied across the four sub-Saharan countries with potentially very low treatment rates. We identified several individual (age, sex, and BMI) and occupational (profession, level of healthcare) factors that influence the odds of NCDs. These factors should be taken into account when developing interventions addressing the burden and management of NCDs among HCWs.