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Risk Factors Associated with Mortality Among Patients with Novel Coronavirus Disease (COVID-19) in Africa.

ABSTRACT: BACKGROUND:The novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in China and later spread rapidly to other parts of the world, including Africa. Africa was projected to be devastated by COVID-19. There is currently limited data regarding regional predictors of mortality among patients with COVID-19. This study aimed to evaluate the independent risk factors associated with mortality among patients with COVID-19 in Africa. METHODS:A total of 1028 confirmed cases of COVID-19 from Africa with definite survival outcomes were identified retrospectively from an open-access individual-level worldwide COVID-19 database. The live version of the dataset is available at https://github.com/beoutbreakprepared/nCoV2019 . Multivariable logistic regression was conducted to determine the risk factors that independently predict mortality among patients with COVID-19 in Africa. RESULTS:Of the 1028 cases included in study, 432 (42.0%) were females with a median (interquartile range, IQR) age of 50 (24) years. Older age (adjusted odds ratio {aOR} 1.06; [95% confidence intervals {95% CI}, 1.04-1.08]), presence of chronic disease (aOR 9.63; [95% CI, 3.84-24.15]), travel history (aOR 2.44; [95% CI, 1.26-4.72]), as well as locations of Central Africa (aOR 0.14; [95% CI, 0.03-0.72]) and West Africa (aOR 0.12; [95% CI, 0.04-0.32]) were identified as the independent risk factors significantly associated with increased mortality among the patients with COVID-19. CONCLUSIONS:The COVID-19 pandemic is evolving gradually in Africa. Among patients with COVID-19 in Africa, older age, presence of chronic disease, travel history, and the locations of Central Africa and West Africa were associated with increased mortality. A regional response should prioritize strategies that will protect these populations. Also, conducting a further in-depth study could provide more insights into additional factors predictive of mortality in COVID-19 patients.

SUBMITTER: Mohammed M

PROVIDER: S-EPMC7553376 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Risk Factors Associated with Mortality Among Patients with Novel Coronavirus Disease (COVID-19) in Africa.

Mohammed Mustapha M Muhammad Surajuddeen S Mohammed Fatima Zaji FZ Mustapha Sagir S Sha'aban Abubakar A Sani Najib Yahaya NY Ahmad Mubarak Hussaini MH Bala Auwal Adam AA Ungogo Marzuq Abubakar MA Alotaibi Nawaf M NM Zainal Hadzliana H

Journal of racial and ethnic health disparities 20201013 5

<h4>Background</h4>The novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in China and later spread rapidly to other parts of the world, including Africa. Africa was projected to be devastated by COVID-19. There is currently limited data regarding regional predictors of mortality among patients with COVID-19. This study aimed to evaluate the independent risk factors associated with mortality among patients with COVID-19 ...[more]

PMID: 33051749

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Project description:ObjectivesCoronavirus Disease 2019 (COVID-19) has become a pandemic outbreak. Risk stratification at hospital admission is of vital importance for medical decision making and resource allocation. There is no sophisticated tool for this purpose. This study aimed to develop neural network models with predictors selected by genetic algorithms (GA).MethodsThis study was conducted in Wuhan Third Hospital from January 2020 to March 2020. Predictors were collected on day 1 of hospital admission. The primary outcome was the vital status at hospital discharge. Predictors were selected by using GA, and neural network models were built with the cross-validation method. The final neural network models were compared with conventional logistic regression models.ResultsA total of 246 patients with COVID-19 were included for analysis. The mortality rate was 17.1% (42/246). Non-survivors were significantly older (median (IQR): 69 (57, 77) vs. 55 (41, 63) years; p < 0.001), had higher high-sensitive troponin I (0.03 (0, 0.06) vs. 0 (0, 0.01) ng/L; p < 0.001), C-reactive protein (85.75 (57.39, 164.65) vs. 23.49 (10.1, 53.59) mg/L; p < 0.001), D-dimer (0.99 (0.44, 2.96) vs. 0.52 (0.26, 0.96) mg/L; p < 0.001), and ?-hydroxybutyrate dehydrogenase (306.5 (268.75, 377.25) vs. 194.5 (160.75, 247.5); p < 0.001) and a lower level of lymphocyte count (0.74 (0.41, 0.96) vs. 0.98 (0.77, 1.26) × 109/L; p < 0.001) than survivors. The GA identified a 9-variable (NNet1) and a 32-variable model (NNet2). The NNet1 model was parsimonious with a cost on accuracy; the NNet2 model had the maximum accuracy. NNet1 (AUC: 0.806; 95% CI [0.693-0.919]) and NNet2 (AUC: 0.922; 95% CI [0.859-0.985]) outperformed the linear regression models.ConclusionsOur study included a cohort of COVID-19 patients. Several risk factors were identified considering both clinical and statistical significance. We further developed two neural network models, with the variables selected by using GA. The model performs much better than the conventional generalized linear models.

Project description:BackgroundDuring the coronavirus disease 2019 (COVID-19) pandemic, Iran reported its first confirmed cases of syndrome coronavirus 2 (SARS-CoV-2) infections on 19 February 2020 in Qom. Although the numbers of cases are increasing, no report about clinical manifestations, laboratory results, and imaging findings of the children infected with COVID-19 in Iran has been published. The aim of this study was to evaluate the epidemiological, clinical, and radiological and laboratory findings of 24 children who had proven SARS-CoV-2 infection and performed chest computed tomographic (CT) in Qom, Iran.MethodsDemographic information and clinical characteristics of the patients including signs and symptoms, chest CT scan manifestation, laboratory findings and clinical outcomes were collected. Diagnosing of the confirmed case was based on positive real-time reverse-transcriptase-polymerase-chain-reaction test for SARS-CoV-2.FindingsDuring the first 3 months of the epidemic in Qom, Iran, 24 children with confirmed diagnosis of COVID-19 were included. The median age of the cases was 6 years [inter-quartile range 3.5-9.5 years]. The most common presenting symptoms were fever (100%), dry cough (62.5%), tachypnea (29%), abdominal pain (21%), and vomiting (21%). Three cases (12.5%) presented with a history of diarrhea in addition to fever and cough. According to the chest CT findings, 2 cases (8%) showed no abnormality. Typical CT findings were found in 6 patients (25%), 2 patients showed indeterminate appearance, and 14 patients (58%) showed atypical findings. Two children with SARS-CoV-2 infection manifested as a hyperinflammatory syndrome with multi-organ involvement similar to Kawasaki disease shock syndrome. Seventy-one percent of the patients showed severe SARS-CoV-2 infection and the mortality of 12.5% (3 cases) were reported.InterpretationHigh frequency of atypical chest CT finding in children should raise concern for pediatricians. Early recognition of patients with SARS-CoV-2 infection is of crucial importance in controlling of the outbreak and atypical imaging features should be interpreted with caution.

Project description:ImportanceThere are limited data on mortality and complications rates in patients with coronavirus disease 2019 (COVID-19) who undergo surgery.ObjectiveTo evaluate early surgical outcomes of patients with COVID-19 in different subspecialties.Design, setting, and participantsThis matched cohort study conducted in the general, vascular and thoracic surgery, orthopedic, and neurosurgery units of Spedali Civili Hospital (Brescia, Italy) included patients who underwent surgical treatment from February 23 to April 1, 2020, and had positive test results for COVID-19 either before or within 1 week after surgery. Gynecological and minor surgical procedures were excluded. Patients with COVID-19 were matched with patients without COVID-19 with a 1:2 ratio for sex, age group, American Society of Anesthesiologists score, and comorbidities recorded in the surgical risk calculator of the American College of Surgeons National Surgical Quality Improvement Program. Patients older than 65 years were also matched for the Clinical Frailty Scale score.ExposuresPatients with positive results for COVID-19 and undergoing surgery vs matched surgical patients without infection. Screening for COVID-19 was performed with reverse transcriptase-polymerase chain reaction assay in nasopharyngeal swabs, chest radiography, and/or computed tomography. Diagnosis of COVID-19 was based on positivity of at least 1 of these investigations.Main outcomes and measuresThe primary end point was early surgical mortality and complications in patients with COVID-19; secondary end points were the modeling of complications to determine the importance of COVID-19 compared with other surgical risk factors.ResultsOf 41 patients (of 333 who underwent operation during the same period) who underwent mainly urgent surgery, 33 (80.5%) had positive results for COVID-19 preoperatively and 8 (19.5%) had positive results within 5 days from surgery. Of the 123 patients of the combined cohorts (78 women [63.4%]; mean [SD] age, 76.6 [14.4] years), 30-day mortality was significantly higher for those with COVID-19 compared with control patients without COVID-19 (odds ratio [OR], 9.5; 95% CI, 1.77-96.53). Complications were also significantly higher (OR, 4.98; 95% CI, 1.81-16.07); pulmonary complications were the most common (OR, 35.62; 95% CI, 9.34-205.55), but thrombotic complications were also significantly associated with COVID-19 (OR, 13.2; 95% CI, 1.48-∞). Different models (cumulative link model and classification tree) identified COVID-19 as the main variable associated with complications.Conclusions and relevanceIn this matched cohort study, surgical mortality and complications were higher in patients with COVID-19 compared with patients without COVID-19. These data suggest that, whenever possible, surgery should be postponed in patients with COVID-19.

Dataset Information

Risk Factors Associated with Mortality Among Patients with Novel Coronavirus Disease (COVID-19) in Africa.

Publications

Risk Factors Associated with Mortality Among Patients with Novel Coronavirus Disease (COVID-19) in Africa.

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