Evidence map›Paper›PMID 38721534›Full record

ArticleFrontiers in public health2024

Tuberculosis and osteoporotic fracture risk: development of individualized fracture risk estimation prediction model using a nationwide cohort study.

Hayoung Choi, Jungeun Shin, Jin-Hyung Jung, Kyungdo Han, Wonsuk Choi, Han Rim Lee, Jung Eun Yoo, Yohwan Yeo, Hyun Lee, Dong Wook Shin

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Tuberculosis-infected macrophage exosomal miR-125b-5p induces osteoporosis by targeting IGF2 through the PI3K/AKT pathway.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025
    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

10 authors.

Hayoung Choi *Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Hallym University Kangnam Sacred Heart Hospital, Seoul, Republic of Korea.
Jungeun Shin *International Healthcare Center, Samsung Medical Center, Seoul, Republic of Korea.
Jin-Hyung JungDepartment of Biostatistics, College of Medicine, Catholic University of Korea, Seoul, Republic of Korea.
Kyungdo HanDepartment of Statistics and Actuarial Science, Soongsil University, Seoul, Republic of Korea.
Wonsuk ChoiDepartment of Internal Medicine, Chonnam National University Hwasun Hospital, Chonnam National University Medical School, Hwasun, Republic of Korea.
Han Rim LeeInternational Healthcare Center, Samsung Medical Center, Seoul, Republic of Korea.
Jung Eun YooDepartment of Family Medicine, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Republic of Korea.
Yohwan YeoDepartment of Family Medicine, Hallym University Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Republic of Korea.
Hyun Lee *Division of Pulmonary Medicine and Allergy, Department of Internal Medicine, Hanyang Medical Center, Hanyang University College of Medicine, Seoul, Republic of Korea.
Dong Wook Shin *Department of Family Medicine, Supportive Care Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Tuberculosis (TB) is linked to sustained inflammation even after treatment, and fracture risk is higher in TB survivors than in the general population. However, no individualized fracture risk prediction model exists for TB survivors. We aimed to estimate fracture risk, identify fracture-related factors, and develop an individualized risk prediction model for TB survivors. Methods: TB survivors ( Results: During median 3.4 (interquartile range, 1.6-5.3) follow-up years, the incident fracture rate was significantly higher in TB survivors than in the matched controls (19.3 vs. 14.6 per 1,000 person-years, Conclusion: TB survivors have a higher fracture risk than matched controls. An individualized prediction model may help prevent fractures in TB survivors, especially in high-risk groups.

Indexed as

Osteoporotic FracturesTuberculosisAdultAgedCohort StudiesFemaleHumansMaleMiddle AgedProportional Hazards ModelsRisk AssessmentRisk FactorsTaiwanepidemiologyfracturesrisk factorsurvivortuberculosis

Identifiers

PMID38721534
PMCPMC11076769

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.