Evidence map›Paper›PMID 34813631›Full record

ArticlePloS one2021

Differentiating transient from persistent diabetic range hyperglycemia in a cohort of people completing tuberculosis treatment in Dhaka, Bangladesh.

Yosra M A Alkabab, Samanta Biswas, Shahriar Ahmed, Kishor Paul, Jyothi Nagajyothi, Sayera Banu, Scott Heysell

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.3field-weighted citation impact, top 38% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Impact of Diabetes Mellitus in Tuberculosis (TB) Patients on TB Transmission.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
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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

7 authors at 4 institutions in 3 countries.

Yosra M A AlkababUniversity of Virginia Medical Center, Division of Infectious diseases and International Health, Department of Medicine, Charlottesville, VA, United States of America.ORCID 0000-0002-7743-9172
Samanta BiswasInternational Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) Enteric and Respiratory Infections, Infectious Diseases Division, Dhaka, Bangladesh.ORCID 0000-0001-8774-2880
Shahriar AhmedInternational Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) Enteric and Respiratory Infections, Infectious Diseases Division, Dhaka, Bangladesh.ORCID 0000-0002-8833-4130
Kishor PaulThe Kirby Institute, University of New South Wales, Surveillance Evaluation Research Program, Kensington, NSW, Australia.ORCID 0000-0002-6054-3571
Jyothi NagajyothiCenter for Discovery and Innovation, Hackensack University Medical Center, Nutley, New Jersey, United States of America.
Sayera BanuInternational Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) Enteric and Respiratory Infections, Infectious Diseases Division, Dhaka, Bangladesh.
Scott HeysellUniversity of Virginia Medical Center, Division of Infectious diseases and International Health, Department of Medicine, Charlottesville, VA, United States of America.
International Centre for Diarrhoeal Disease Research · BDUniversity of Virginia Medical Center · USHackensack University Medical Center · USUNSW Sydney · AU

Funding

INFECTIOUS DISEASES TRAINING PROGRAMT32AI007046 · NIAID · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Alison K Criss, William A Petri · 1985 to 2026
$15.3M
NIAID NIH HHS T32 AI007046
6 · The paper itself

Abstract

backgroundIn recent non-pandemic periods, tuberculosis (TB) has been the leading killer worldwide from a single infectious disease. Patients with DM are three times more likely to develop active TB and poor treatment outcomes. Single glycemic measurements at TB diagnosis may inaccurately diagnose or mischaracterize DM severity. Data are limited regarding glycemic dynamics from TB diagnosis through treatment.

methodsProspective study of glycemia dynamics in response to TB treatment measured glycosylated haemoglobin (HbA1c) in patients presenting to TB screening centres in Bangladesh to determine the prevalence and risk factors of hyperglycemia before and at TB treatment completion.

results429 adults with active TB disease were enrolled and divided into groups based on history of DM and initial HbA1c range: normoglycemia, prediabetes, and DM. DM was diagnosed in 37%. At treatment completion,14(6%) patients from the normoglycemia and prediabetes groups had HbA1c>6.5%, thus increasing the prevalence of DM to 39%. The number needed to screen to diagnose one new case of DM at TB diagnosis was 5.7 and 16 at treatment completion in the groups without DM. Weight gain>5% at treatment completion significantly increased the risk of hyperglycemia in the groups without DM at TB diagnosis (95% CI 1.23-26.04, p<0.05).

conclusionHbA1c testing prior to and at TB treatment completion found a high prevalence of prediabetes and DM, including a proportion found at treatment completion and commonly in people with a higher percentage of weight gain. Further longitudinal research is needed to understand the effects of TB disease and treatment on insulin resistance and DM complications.

Indexed as

AdolescentAdultBangladeshDiabetes MellitusDisease ManagementFemaleGlycated HemoglobinHumansHyperglycemiaMaleMiddle AgedPrediabetic StateProspective StudiesRisk FactorsTuberculosisYoung AdultGlycated Hemoglobinhemoglobin A1c protein, human

Identifiers

PMID34813631
PMCPMC8610235
OpenAlexW3216057264

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.