Evidence map›Paper›PMID 37476129›Full record

ArticleCureus2023

Symptomatology and Demographic Profile of COVID-19 Patients Admitted to a Tertiary Care Center in India: A Hospital Record-Based Study.

Arumadi Anupama, Rupesh Raman, R Ratheesh, Sujesh Palakkunnath

Abstract read
In one paragraph

Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Arumadi AnupamaCommunity Medicine, Kunhitharuvai Memorial Charitable Trust (KMCT) Medical College, Kozhikode, IND.
Rupesh RamanCommunity Medicine, Kunhitharuvai Memorial Charitable Trust (KMCT) Medical College, Kozhikode, IND.
R RatheeshPharmacology, Kunhitharuvai Memorial Charitable Trust (KMCT) Medical College, Kozhikode, IND.
Sujesh PalakkunnathCommunity Medicine, Kunhitharuvai Memorial Charitable Trust (KMCT) Medical College, Kozhikode, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSince its arrival in late 2019, COVID-19 has caused more than 760 million cases and nearly seven million deaths worldwide. As a novel infection research is still underway to understand the epidemiology of COVID-19. The present study was conducted in a tertiary care center in south India to understand the symptomatology of the disease in a local context.

methodsInformation for the study was retrieved from the hospital records of the Kunhitharuvai Memorial Charitable Trust (KMCT) COVID Hospital, Kerala, India, of patients admitted from 1st May 2021 to 31st October 2021 (six months). Data on their clinico-demographic profile and treatment outcomes were collected and entered into a proforma.

resultsOut of the 2744 patients included in the study, the proportion of males and females was comparable. About 38.6% of patients were above 60 years of age. The most common presenting complaints were fever, cough, and breathlessness. About 2.7% were asymptomatic. The mortality rate during the study period was 4.8% (132 deaths).

conclusionThe present study highlights differences in the symptomology and other demographic features of COVID-19 patients admitted to a hospital in Kerala, India, compared to other regional, national, and international studies. Despite limitations, these differences may have important implications for diagnosing and managing COVID-19 patients in the region.

Indexed as

covid-19epidemiologyindiakeralasars-cov-2symptoms

Identifiers

PMID37476129
PMCPMC10355227

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.