Evidence map›Paper›PMID 33306710›Full record

ArticlePloS one2020

Evaluation of underweight status may improve identification of the highest-risk patients during outpatient evaluation for pulmonary tuberculosis.

Peter J Kitonsa, Annet Nalutaaya, James Mukiibi, Olga Nakasolya, David Isooba, Caleb Kamoga, Yeonsoo Baik, Katherine Robsky, David W Dowdy, Achilles Katamba and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.1field-weighted citation impact, top 51% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  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

11 authors at 2 institutions in 2 countries.

Peter J KitonsaUganda Tuberculosis Implementation Research Consortium, Makerere University, College of Health Sciences, Kampala, Uganda.ORCID 0000-0003-2971-216X
Annet NalutaayaUganda Tuberculosis Implementation Research Consortium, Makerere University, College of Health Sciences, Kampala, Uganda.ORCID 0000-0003-3903-303X
James MukiibiUganda Tuberculosis Implementation Research Consortium, Makerere University, College of Health Sciences, Kampala, Uganda.
Olga NakasolyaUganda Tuberculosis Implementation Research Consortium, Makerere University, College of Health Sciences, Kampala, Uganda.
David IsoobaUganda Tuberculosis Implementation Research Consortium, Makerere University, College of Health Sciences, Kampala, Uganda.
Caleb KamogaUganda Tuberculosis Implementation Research Consortium, Makerere University, College of Health Sciences, Kampala, Uganda.
Yeonsoo BaikDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States America.
Katherine RobskyDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States America.ORCID 0000-0001-7789-5779
David W DowdyUganda Tuberculosis Implementation Research Consortium, Makerere University, College of Health Sciences, Kampala, Uganda.
Achilles KatambaUganda Tuberculosis Implementation Research Consortium, Makerere University, College of Health Sciences, Kampala, Uganda.
Emily A KendallUganda Tuberculosis Implementation Research Consortium, Makerere University, College of Health Sciences, Kampala, Uganda.
Makerere University · UGJohns Hopkins University · US

Funding

Hotspot versus clinic-based active case finding for TB in Uganda: A pragmatic randomized trialR01HL138728 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI David Wesley Dowdy, Emily A Kendall · 2017 to 2026
$5.4M
Translational modeling of individual- and population-level outcomes of novel tuberculosis drug regimensK08AI127908 · NIAID · JOHNS HOPKINS UNIVERSITY · PI KENDALL, EMILY A · 2017 to 2021
$879k
NHLBI NIH HHS R01 HL138728NIAID NIH HHS K08 AI127908
6 · The paper itself

Abstract

backgroundWhen evaluating symptomatic patients for tuberculosis (TB) without access to same-day diagnostic test results, clinicians often make empiric decisions about starting treatment. The number of TB symptoms and/or underweight status could help identify patients at highest risk for a positive result. We sought to evaluate the usefulness of BMI assessment and a count of characteristic TB symptoms for identifying patients at highest risk for TB.

methodsWe enrolled adult patients receiving pulmonary TB diagnoses and a representative sample with negative TB evaluations at four outpatient health facilities in Kampala, Uganda. We asked patients about symptoms of chronic cough, night sweats, chest pain, fever, hemoptysis, or weight loss; measured height and weight; and collected sputum for mycobacterial culture. We evaluated the diagnostic accuracy (for culture-positive TB) of two simple scoring systems: (a) number of TB symptoms, and (b) number of TB symptoms plus one or more additional points for underweight status (body mass index [BMI] ≤ 18.5 kg/m2).

resultsWe included 121 patients with culture-positive TB and 370 patients with negative culture results (44 of whom had been recommended for TB treatment by evaluating clinicians). Of the six symptoms assessed, the median number of symptoms that patients reported was two (interquartile range [IQR]: 1, 3). The median BMI was 20.9 kg/m2 (IQR: 18.6, 24.0), and 118 (24%) patients were underweight. Counting the number of symptoms provided an area under the Receiver Operating Characteristic curve (c-statistic) of 0.77 (95% confidence interval, CI: 0.72, 0.81) for identifying culture-positive TB; adding two points for underweight status increased the c-statistic to 0.81 (95%CI: 0.76, 0.85). A cutoff of ≥3 symptoms had sensitivity and specificity of 65% and 74%, whereas a score of ≥4 on the combined score (≥2 symptoms if underweight, ≥4 symptoms if not underweight) gave higher sensitivity and specificity of 69% and 81% respectively. A sensitivity analysis defining TB by Xpert MTB/RIF status produced similar results.

conclusionA count of patients' TB symptoms may be useful in clinical decision-making about TB diagnosis. Consideration of underweight status adds additional diagnostic value.

Indexed as

AdolescentAdultFemaleHumansMaleMiddle AgedMycobacterium tuberculosisOutpatientsRisk FactorsSensitivity and SpecificitySputumThinnessTuberculosisTuberculosis, PulmonaryUganda

Identifiers

PMID33306710
PMCPMC7732099
OpenAlexW3110794830

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.