COVID-19: Clinical features, case fatality, and the effect of symptoms on mortality in hospitalized cases in Iran
Rattachement africain : ir. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Objective: Identifying the epidemiological characteristics of COVID-19 could help to control the pandemic. The aim of this study was to characterize the epidemiological features of hospitalized COVID-19 patients in Iran. Methods: , time of admission, and time of discharge were investigated. Sex ratio, case fatality rate (CFR), and daily trends of hospital admissions and deaths were also determined. Descriptive statistics and multiple logistic regression with 95% confidence intervals were used for data analysis. The statistical significance level was set at 0.05. STATA16.0 and Excel 2010 were used for data analysis. Results: The median hospital length of stay (LOS) was 6 days. The following symptoms were most common: cough (63.5%), fever (50%), respiratory distress (46.1%), and muscular pain (40.8%). Hypertension (29.5%), diabetes (24.7%), and cardiovascular diseases (21.8%) were the most prevalent comorbidities. The CFR was calculated at 8.30%. Respiratory symptoms increased the odds of death by 45% (OR 1.45, 95% CI 1.03-2.06). Gastrointestinal symptoms were associated with a reduction in the mortality of COVID-19 cases, but this association was not statistically significant (OR 0.94, 95% CI 0.73-1.21). Conclusions: The results of this study emphasize higher mortality rates among older age groups, male patients, and patients with underlying diseases.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- COVID-19: Clinical features, case fatality, and the effect of symptoms on mortality in hospitalized cases in Iran
- Date Crossref
- 01/10/2022
- Éditeur
- Elsevier BV
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Les institutions déclarées
Une affiliation ne permet pas de déduire la nationalité d’un auteur.