Evidence map›Paper›PMID 33130835›Full record

ReviewSaudi medical journal2020

Comorbidities and severity of coronavirus disease 2019 patients.

Nashwa M Radwan, Nagla E Mahmoud, Amal H Alfaifi, Khaled I Alabdulkareem

Abstract readReview
In one paragraph

Review in Saudi medical journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
  4. Observational
  5. Article
  6. Review
  7. Review
  8. Demographics, comorbidities, and outcomes among young and middle-aged COVID-19 patients in Saudi Arabia.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2021
    Article
  9. Article
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

4 authors.

Nashwa M RadwanMinistry of Health, Riyadh, Kingdom of Saudi Arabia. E-mail. radwan.n.m@gmail.com.
Nagla E Mahmoud
Amal H Alfaifi
Khaled I Alabdulkareem

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo determine the association between comorbidities and the severity of the disease among COVID-19 patients.

methodsWe searched the Cochrane, Medline, Trip, and EMBASE databases from 2019. The review included all available studies of COVID-19 patients published in the English language and studied the clinical characteristics, comorbidities, and disease outcomes from the beginning of the pandemic.  Two authors extracted studies characteristics and the risk of bias. Odds ratio (OR) was used to analyze the data with 95% confidence interval (CI).

resultsThe review included 1,885 COVID-19 patients from 7 observational studies with some degree of bias risk and substantial heterogeneity. A significant association was recorded between COVID-19 severity and the following variables: male (OR= 1.60, 95%CI= 1.05 - 2.43); current smoker (OR=2.06, 95%CI= 1.08 - 3.94); and the presence of comorbidities including hypertension (OR=2.05, 95%CI= 1.56 - 2.70), diabetes (OR=2.46, 95%CI= 1.53 - 3.96), coronary heart disease (OR=4.10, 95%CI= 2.36 - 7.12), chronic kidney disease (OR=4.06, 95%CI= 1.45 - 11.35), and cancer (OR=2.28, 95%CI= 1.08 - 4.81).

conclusionsComorbidities among COVID-19 patients may contribute to increasing their susceptibility to severe illness. The identification of these potential risk factors could help reduce mortality by identifying patients with poor prognosis at an early stage.

Indexed as

Cause of DeathComorbidityCoronavirus InfectionsCOVID-19Data ManagementDisease SusceptibilityFemaleHumansIncidenceMalePandemicsPneumonia, ViralSaudi ArabiaSevere Acute Respiratory SyndromeSeverity of Illness IndexSurvival Analysis

Identifiers

PMID33130835
PMCPMC7804237

What OpenQuestion holds

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Registered trials

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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.