Evidence map›Paper›PMID 34233638›Full record

ArticleBMC infectious diseases2021

Demographic and clinical characteristics of severe Covid-19 infections: a cross-sectional study from Mashhad University of Medical Sciences, Iran.

Ladan Goshayeshi, Mina Akbari Rad, Robert Bergquist, Abolghasem Allahyari, Kamila Hashemzadeh, MUMS Covid-19 Research Team, Benyamin Hoseini

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
2.5field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 2 syntheses or guidelines pooled it, 42 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  8. Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2023
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  9. Review
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  14. Prediction of Patients with COVID-19 Requiring Intensive Care: A Cross-sectional Study Based on Machine-learning Approach from Iran.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2022
    Article
  15. Article
  16. Article
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  18. Priority setting in cardiovascular research in Iran using standard indigenous methods.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2022
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  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Ladan Goshayeshi *Department of Gastroenterology and Hepatology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Mina Akbari Rad *Department of Internal Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Robert BergquistIngerod, SE-454 94, Brastad, Sweden.
Abolghasem AllahyariDepartment of Internal Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Kamila HashemzadehRheumatic Diseases Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
MUMS Covid-19 Research Team
Benyamin HoseiniDepartment of Health Information Technology, Neyshabur University of Medical Sciences, Neyshabur, Iran. Hoseinib1@nums.ac.ir.ORCID http://orcid.org/0000-0002-0355-6181
Mashhad University of Medical Sciences · IRUniversity of Neyshabur · IRWorld Health Organization · CH

Funding

Mashhad University of Medical Sciences 981800
6 · The paper itself

Abstract

backgroundCoronavirus Disease 2019 (Covid-19) is expanding worldwide. The characteristics of this infection in patients varies from country to country. To move forward, clinical data on infected patients are needed. Here, we report a comparison between fatalities and recovery of patients with severe Covid-19, based on demographic and clinical characteristics.

methodsBetween 5 March and 12 May 2020 in Mashhad, Iran, 1278 of 4000 suspected Covid-19 patients were confirmed positive by real-time reverse-transcriptase-polymerase-chain-reaction assay of upper respiratory specimens. We compared the demographic, exposure history and clinical symptoms of 925 survivors and 353 fatal cases with confirmed disease.

resultsMean (SD) age for all confirmed patients was 56.9 (18.7) years, 67.1 (15.9) years in fatal cases and 53.0 (18.3) years in survivors. Multivariate logistic regression analysis showed that the outcome of patients was associated with age (odds ratio = 1.049, P = 0.0001, 95% CI = 1.040-1.057). Despite a high burden of Covid-19 infections in the 30-39 and 40-49 year age groups, most of these (89.6 and 87.2%, respectively) recovered. The median (IQR) duration of hospitalization was 9.0 (6.0-14.0) days. The most prevalent co-morbidities were cardiovascular disorders (21%) and diabetes (16.3%). Dyspnoea (72.7%), cough (68.1%) and fever (63.8%) were the most frequent clinical symptoms. Healthcare workers, of whom two (3%) died, comprised 5.2% of infected cases. Combination antiviral and antibiotic therapy was used in 43.0% of cases.

conclusionsThe characteristics of severe Covid-19 varied substantially between fatal cases and survivors, with diabetes and cardiovascular disorders the most prevalent co-morbidities. In contrast to other studies, there were a higher number of fatalities in younger patients in our setting.

Indexed as

AdolescentAdultAgedAged, 80 and overAnti-Bacterial AgentsAntiviral AgentsCardiovascular DiseasesChildChild, PreschoolComorbidityCoughCOVID-19COVID-19 Drug TreatmentCross-Sectional StudiesDiabetes MellitusDyspneaAnti-Bacterial AgentsAntiviral AgentsCOVID-19, SARS-COV-2Epidemiological characteristicsSymptoms, Iran

Identifiers

PMID34233638
PMCPMC8261035
OpenAlexW3181392020

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.