Evidence map›Paper›PMID 37962782›Full record

ArticleJournal of epidemiology and global health2023

Joint Involvement Can Predict Chikungunya in a Dengue Syndemic Setting in India.

Abhinav Sinha, Deepali Savargaonkar, Auley De, Aparna Tiwari, C P Yadav, Anupkumar R Anvikar

Abstract read
In one paragraph

Article in Journal of epidemiology and global health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Abhinav Sinha *ICMR-National Institute of Malaria Research, New Delhi, India. abhinavsinha@icmr.gov.in.ORCID 0000-0003-1900-7686
Deepali Savargaonkar *ICMR-National Institute of Malaria Research, New Delhi, India.
Auley DeICMR-National Institute of Malaria Research, New Delhi, India.
Aparna TiwariICMR-National Institute of Malaria Research, New Delhi, India.
C P YadavICMR-National Institute of Malaria Research, New Delhi, India.
Anupkumar R AnvikarICMR-National Institute of Malaria Research, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dengue and chikungunya have been endemic in India but have the tendency to cause periodic epidemics, often together, wherein they are termed 'syndemic'. Such a syndemic was observed in 2016 in India which resulted in a further scarcity of already resource-poor specific diagnostic infrastructure even in many urban conglomerates. A cross-sectional study was thus conducted, on 978 fever patients that consulted the ICMR-NIMR fever clinic, New Delhi, in September 2016, with an objective to identify symptom/s that could predict chikungunya with certainty. The overall aim was to rationally channelize the most clinically suitable patients for the required specific diagnosis of chikungunya. Based on their clinical profile, febrile patients attending NIMR's clinic, appropriate laboratory tests and their association analyses were performed. Bivariate analysis on 34 clinical parameters revealed that joint pain, joint swelling, rashes, red spots, weakness, itching, loss of taste, red eyes, and bleeding gums were found to be statistically significantly associated predictors of chikungunya as compared to dengue. While, in multivariate analysis, only four symptoms (joint pain in elbows, joint swelling, itching and bleeding gums) were found in statistically significant association with chikungunya. Hence, based on the results, a clinician may preferably channelize febrile patients with one or more of these four symptoms for chikungunya-specific diagnosis and divert the rest for dengue lab diagnosis in a dengue-chikungunya syndemic setting.

Indexed as

Chikungunya FeverDengueArthralgiaCross-Sectional StudiesFeverHumansIndiaPruritusSyndemicChikungunyaDengueIndiaJoint painJoint swelling

Identifiers

PMID37962782
PMCPMC10686949

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.