Evidence map›Paper›PMID 33937730›Full record

ArticleEClinicalMedicine2021

Mumbai mayhem of COVID-19 pandemic reveals important factors that influence susceptibility to infection.

Radha Yadav, Arup Acharjee, Akanksha Salkar, Renuka Bankar, Viswanthram Palanivel, Sachee Agrawal, Jayanthi Shastri, Sanjeev V Sabnis, Sanjeeva Srivastava

Abstract read
In one paragraph

Article in EClinicalMedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

9 authors.

Radha YadavDepartment of Mathematics, Indian Institute of Technology Bombay, Mumbai 400076, India.
Arup AcharjeeDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai 400076, India.
Akanksha SalkarDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai 400076, India.
Renuka BankarDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai 400076, India.
Viswanthram PalanivelDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai 400076, India.
Sachee AgrawalKasturba Hospital for Infectious Diseases, Chinchpokli, Mumbai, Maharashtra 400034, India.
Jayanthi ShastriKasturba Hospital for Infectious Diseases, Chinchpokli, Mumbai, Maharashtra 400034, India.
Sanjeev V SabnisDepartment of Mathematics, Indian Institute of Technology Bombay, Mumbai 400076, India.
Sanjeeva SrivastavaDepartment of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai 400076, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCOVID-19 severity is disproportionately high in the elderly and people with comorbidities. However, other factors that predispose individuals to increased chances of infection are unclear.

methodsData from 18,600 people screened for COVID-19 in Mumbai during the outbreak's initial phase, March 7 to June 30, 2020, were used to assess risk factors associated with COVID-19 using the odds ratio analysis.

findingsMales aged ≥60 years having both diabetes and hypertension were at the highest risk of COVID-19 infection (M vs

interpretationOur research indicates that the risk of getting COVID-19 disease is not equal. When considering sex, age, and comorbidity together, we found that males aged ≥60 years and having both diabetes and hypertension had a significantly high risk of COVID-19 infection. Therefore, remedial measures such as vaccination programs should be prioritized for at-risk individuals.

fundingSERB, India: SB/S1/COVID-2/2020 and Seed grant RD/0520-IRCCHC0-006 from IRCC, IIT Bombay.

Identifiers

PMID33937730
PMCPMC8068776

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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.