Evidence map›Paper›PMID 37808069›Full record

ArticleEuropean journal of radiology open2023

Predictive capabilities of baseline radiological findings for early and late disease outcomes within sensitive and multi-drug resistant tuberculosis cases.

Gabriel Rosenfeld, Andrei Gabrielian, Darrell Hurt, Alex Rosenthal

Open access · goldAbstract read
In one paragraph

Article in European journal of radiology open, 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
0.4field-weighted citation impact, top 39% 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, 2 citations in OpenAlex.

  1. Article
  2. Automated Pulmonary Tuberculosis Severity Assessment on Chest X-rays.Journal of imaging informatics in medicine · 2024
    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

4 authors at 1 institution in 1 country.

Gabriel RosenfeldOffice of Cyber Infrastructure and Computational Biology, National Institutes of Allergy and Infectious Diseases, 5601 Fishers Lane, Rockville, MD 20852, USA.
Andrei GabrielianOffice of Cyber Infrastructure and Computational Biology, National Institutes of Allergy and Infectious Diseases, 5601 Fishers Lane, Rockville, MD 20852, USA.
Darrell HurtOffice of Cyber Infrastructure and Computational Biology, National Institutes of Allergy and Infectious Diseases, 5601 Fishers Lane, Rockville, MD 20852, USA.
Alex RosenthalOffice of Cyber Infrastructure and Computational Biology, National Institutes of Allergy and Infectious Diseases, 5601 Fishers Lane, Rockville, MD 20852, USA.
National Institute of Allergy and Infectious Diseases · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study compares performance of Timika Score to standardized, detailed radiologist observations of Chest X rays (CXR) for predicting early infectiousness and subsequent treatment outcome in drug sensitive (DS) or multi-drug resistant (MDR) tuberculosis cases. It seeks improvement in prediction of these clinical events through these additional observations. Method: This is a retrospective study analyzing cases from the NIH/NIAID supported TB Portals database, a large, trans-national, multi-site cohort of primarily drug-resistant tuberculosis patients. We analyzed patient records with sputum microscopy readings, radiologist annotated CXR, and treatment outcome including a matching step on important covariates of age, gender, HIV status, case definition, Body Mass Index (BMI), smoking, drug use, and Timika Score across resistance type for comparison. Results: 2142 patients with tuberculosis infection (374 with poor outcome and 1768 with good treatment outcome) were retrospectively reviewed. Bayesian ANOVA demonstrates radiologist observations did not show greater predictive ability for baseline infectiousness (0.77 and 0.74 probability in DS and MDR respectively); however, the observations provided superior prediction of treatment outcome (0.84 and 0.63 probability in DS and MDR respectively). Estimated lung abnormal area and cavity were identified as important predictors underlying the Timika Score's performance. Conclusions: Timika Score simplifies the usage of baseline CXR for prediction of early infectiousness of the case and shows comparable performance to using detailed, standardized radiologist observations. The score's utility diminishes for treatment outcome prediction and is exceeded by the usage of the detailed observations although prediction performance on treatment outcome decreases especially in MDR TB cases.

Indexed as

Multi-drug resistantRadiographic featuresTuberculosisX-ray

Identifiers

PMID37808069
PMCPMC10556559
OpenAlexW4387083540

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.