Evidence map›Paper›PMID 33017424›Full record

ArticlePloS one2020

Low pectoralis muscle index, cavitary nodule or mass and segmental to lobar consolidation as predictors of primary multidrug-resistant tuberculosis: A comparison with primary drug sensitive tuberculosis.

Hwa Seon Shin, Dae Seob Choi, Jae Boem Na, Hye Young Choi, Ji-Eun Kim, Ho Cheol Choi, Jung Ho Won, Seung Jun Lee, Mi Jung Park

Open access · goldAbstract readComparative Study
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 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
0.2field-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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. 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

9 authors at 1 institution in 1 country.

Hwa Seon ShinDepartment of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Gyeongsangnam-do, Republic of Korea.
Dae Seob ChoiDepartment of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Gyeongsangnam-do, Republic of Korea.
Jae Boem NaDepartment of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Gyeongsangnam-do, Republic of Korea.ORCID 0000-0002-6182-2986
Hye Young ChoiDepartment of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Gyeongsangnam-do, Republic of Korea.
Ji-Eun KimDepartment of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Gyeongsangnam-do, Republic of Korea.
Ho Cheol ChoiDepartment of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Gyeongsangnam-do, Republic of Korea.ORCID 0000-0001-8614-6753
Jung Ho WonDepartment of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Gyeongsangnam-do, Republic of Korea.
Seung Jun LeeDivision of Pulmonology, Department of Internal Medicine, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Gyeongsangnam-do, Republic of Korea.
Mi Jung ParkDepartment of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, Gyeongsangnam-do, Republic of Korea.ORCID 0000-0002-1136-1763
Gyeongsang National University Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe loss of muscle mass in primary multidrug-resistant tuberculosis (MDR-TB) has not been examined in previous studies. This study aimed to investigate that low pectoralis muscle index and characteristic CT features can help differentiate patients with primary MDR-TB from those with drug-sensitive tuberculosis (DS-TB). MATERIAL AND

methodsFrom 2010 to 2016, we retrospectively enrolled 90 patients with primary MDR-TB and 90 age- and sex-matched patients with primary DS-TB. The pectoralis muscle mass was quantitatively measured on axial CT images using density histogram analysis. The pectoralis muscle index (PMI) was defined as the pectoralis muscle mass divided by body mass index. We compared the PMI and characteristic CT features of pulmonary tuberculosis between the two groups.

resultsLow PMI, segmental to lobar consolidation, cavity in consolidation, cavitary nodule or mass, and bilateral involvement were more frequently observed in patients with MDR-TB than in those with DS-TB. In stepwise multivariate logistic regression analysis, low PMI (odds ratio, 2.776; 95% confidence interval, 1.450-5.314; p = 0.002), segmental or lobar consolidation (odds ratio, 3.123; 95% confidence interval, 1.629-5.987; p = 0.001), and cavitary nodule or mass (odds ratio, 2.790; 95% confidence interval, 1.348-5.176; p = 0.002) were significant factors for MDR-TB.

conclusionLow pectoralis muscle index, segmental to lobar consolidation and cavitary nodule or mass can help differentiate primary MDR-TB from DS-TB.

Indexed as

Antitubercular AgentsFemaleHumansImage Processing, Computer-AssistedLungMaleMiddle AgedOrgan SizePectoralis MusclesRetrospective StudiesTomography, X-Ray ComputedTuberculosis, Multidrug-ResistantAntitubercular Agents

Identifiers

PMID33017424
PMCPMC7535045
OpenAlexW3089723804

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.