Evidence map›Paper›PMID 38620969›Full record

ArticleClinical epidemiology and global health

COVID-19 cases and their outcome among patients with uncommon co-existing illnesses: A lesson from Northern India.

D Himanshu Reddy, Virendra Atam, Priyanka Rai, Farman Khan, Saurabh Pandey, Hardeep Singh Malhotra, Kamlesh Kumar Gupta, Satyendra Kumar Sonkar, Rajeev Verma, KGMU COVID-19 working group

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Article in Clinical epidemiology and global health. 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
0.4field-weighted citation impact, top 41% 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

0 citing papers in PubMed, 4 citations in OpenAlex.

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

10 authors at 2 institutions in 1 country.

D Himanshu ReddyDepartment of Internal Medicine, KGMU, Lucknow, India.
Virendra AtamDepartment of Internal Medicine, KGMU, Lucknow, India.
Priyanka RaiDepartment of Pathology, MVASMC, Basti, India.
Farman KhanDepartment of Internal Medicine, KGMU, Lucknow, India.
Saurabh PandeyMedicine & Infectious Diseases Unit, PMC Hospital, Basti, India.
Hardeep Singh MalhotraDepartment of Neurology, KGMU, Lucknow, India.
Kamlesh Kumar GuptaDepartment of Internal Medicine, KGMU, Lucknow, India.
Satyendra Kumar SonkarDepartment of Internal Medicine, KGMU, Lucknow, India.
Rajeev VermaDepartment of Internal Medicine, AIIMS, Gorakhpur, India.
KGMU COVID-19 working group
King George's Medical University · INAll India Institute of Medical Sciences Raipur · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Newer coexisting conditions should be identified in order to modify newer risk factors. Aim was to identify patients with non-classical or less common coexisting conditions in patients infected of COVID 19. Method: Single centred study from June 2020 to May 2021 at a tertiary centre in North India. A preformed questionnaire was used to record clinical and laboratory parameters and to identify cases which are in addition to CDC list and Indian data. Results: 0.67% (46) cases out of 6832 patients were identified to have non-classical coexisting illness. It was divided into 2 groups-infections A (60.1%) and non-infections B (39.9%). Group A included-tuberculosis- pulmonary (14.3%) & extra pulmonary (32.9%), bacterial (25.0%) viral infections [dengue, hepatitis B & C] (14.3%), HIV disease (10.7%) and malaria (3.6%). Group B included- organ transplant (27.8%), autoimmune [myasthenia gravis, polymyositis, psoriasis] (22.6%), haematologic [Haemophilia, ITP, Aplastic anaemia, APML, CML] (27.8%), uncommon malignancies [disseminated sacral chordoma and GTN] (11.1%) and snakebite (11.1%). Serum Procalcitonin was not helpful for diagnosis of bacterial infection in COVID-19 disease. Group A had significantly longer duration of illness, hepatitis and elevated CRP. The mortality in group A & B were 32.1% and 43.8% respectively. Death in non-severe COVID cases was in tetanus and snakebite. 30.7% death among tuberculosis patients. More than 70% of deaths were attributable to COVID 19 in both the groups. Conclusion: In Indian settings, comorbidities like tuberculosis and bacterial infections can precipitate severe COVID 19 unlike other parts of the world where tuberculosis is relatively uncommon.

Indexed as

BacterialCOVID 19HIVIndiaRheumatologictransplatationTropical infectionsTuberculosisUncommon coexisting illness

Identifiers

PMID38620969
PMCPMC9004146
OpenAlexW4223471570

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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.