Evidence map›Paper›PMID 38073301›Full record

ArticleTherapeutic advances in respiratory disease

A prediction model for risk of low oxygen saturation in patients with post-tuberculosis tracheobronchial stenosis during bronchoscopy.

Hui Chen, Sen Tian, Haidong Huang, Hui Wang, Zhenli Hu, Yuguang Yang, Wei Zhang, Yuchao Dong, Qin Wang, Chong Bai

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Therapeutic advances in respiratory disease. 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
0.5field-weighted citation impact, top 27% 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. Trial
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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

10 authors at 1 institution in 1 country.

Hui ChenDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Sen TianDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China.ORCID 0000-0002-6486-3142
Haidong HuangDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Hui WangNursing Department, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Zhenli HuDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Yuguang YangDepartment of Anesthesiology, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Wei ZhangDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Yuchao DongDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Qin WangDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, No. 168 Changhai Road Yangpu District Shanghai 200433, China.
Chong BaiDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, No. 168 Changhai Road Yangpu District Shanghai 200433, China.
Second Military Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLow oxygen saturation (LOS) is a frequent occurrence for patients with post-tuberculosis tracheobronchial stenosis (PTTS) during bronchoscopic procedures. However, there are currently no systematic assessment tools to predict LOS risk in PTTS patients during bronchoscopy.

objectivesThis study aimed to develop an effective preoperative predictive model to guide clinical practice.

designRetrospective cohort study.

methodsData was retrospectively collected from PTTS patients who underwent bronchoscopic interventions between January 2017 and December 2022. Among all patients included in this study, patients between January 2017 and December 2021 were used as training cohort for the logistic regression model, and patients between January 2022 and December 2022 were utilized as validation cohort for internal validation. We used consistency index (C-index), goodness-of-fit test and calibration plot to evaluate the model performance.

resultsA total of 465 patients who met the inclusion criteria were enrolled in the study. The overall incidence of LOS was 26.0% (121/465). Comorbidity, degree of stenosis, bronchoscopist level, thermal ablation therapy, balloon dilation, and airway stenting, as independent risk factors for the presence of LOS, were used to construct the nomogram prediction model. The C-index of training cohort was 0.827 (95% CI, 0.786-0.869), whereas that of validation cohort was 0.836 (95% CI, 0.757-0.916), combining with the results of the calibration plot and goodness-of-fit test, demonstrating that this model had good predictive ability.

conclusionThe predictive model and derived nomogram with good predictive ability has been developed to preoperatively predict the risk of LOS in PTTS patients during bronchoscopy, allowing for individualized interventions for high-risk patients.

Indexed as

BronchoscopyTuberculosisConstriction, PathologicHumansOxygen SaturationRetrospective Studiesbronchoscopylow oxygen saturationnomogrampredictive modelrisk factortuberculosis

Identifiers

PMID38073301
PMCPMC10712272
OpenAlexW4389567673

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.