Body mass index and pneumothorax risk after CT-guided pulmonary nodule localization: a nonlinear analysis using restricted cubic splines

Pneumothorax remains the most frequent complication of CT-guided pulmonary nodule localization, yet the role of body mass index (BMI) is poorly understood. We investigated the nonlinear relationship between BMI and pneumothorax risk using restricted cubic spline (RCS) analysis. In this retrospective cohort study, 175 patients undergoing CT-guided localization for solitary pulmonary nodules (≤ 20 mm) were analyzed. Multivariable logistic regression and RCS models adjusted for clinical/procedural confounders identified BMI threshold effects. Pneumothorax definition (per British Thoracic Society guidelines): (1) Visible visceral pleural line on CT; (2) Lung compression ≥ 10%. The overall pneumothorax rate was 34.3% (60/175). RCS revealed a nonlinear association (P for nonlinearity = 0.016) with an inflection point at BMI = 24.8 kg/m². Below this point, each 1-unit BMI increase was associated with reduced pneumothorax risk (OR: 0.66, 95% CI: 0.54–0.82; P < 0.001). Above it, the association was not significant (OR: 1.40, 95% CI: 0.97–2.02; P = 0.071). The mean nodule size was 8.9 ± 2.1 mm, and most nodules were located in the peripheral lung regions. This single-center retrospective analysis suggests a nonlinear relationship between BMI and pneumothorax risk, with the lowest risk observed near BMI = 24.8 kg/m². These findings highlight the potential for BMI-based risk stratification but require validation in larger, prospective studies.

Authors

Institutions

Publication Details

Journal
Journal of Cardiothoracic Surgery
Published
2026-03-04
DOI
https://doi.org/10.1186/s13019-026-03938-9
Primary Topic
Lung Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Body mass index and pneumothorax risk after CT-guided pulmonary nodule localization: a nonlinear analysis using restricted cubic splines

Chengbin Huang, Zekai Chen, Jun Guan, Yangsheng Ou et al.
Journal of Cardiothoracic Surgery
Lung Cancer Diagnosis and Treatment
article

Body mass index and pneumothorax risk after CT-guided pulmonary nodule localization: a nonlinear analysis using restricted cubic splines

Chengbin Huang, Zekai Chen, Jun Guan, Yangsheng Ou, Jianyang Wu, Junkai Xiong, Jian-Xin Xu
article en

Abstract

Pneumothorax remains the most frequent complication of CT-guided pulmonary nodule localization, yet the role of body mass index (BMI) is poorly understood. We investigated the nonlinear relationship between BMI and pneumothorax risk using restricted cubic spline (RCS) analysis. In this retrospective cohort study, 175 patients undergoing CT-guided localization for solitary pulmonary nodules (≤ 20 mm) were analyzed. Multivariable logistic regression and RCS models adjusted for clinical/procedural confounders identified BMI threshold effects. Pneumothorax definition (per British Thoracic Society guidelines): (1) Visible visceral pleural line on CT; (2) Lung compression ≥ 10%. The overall pneumothorax rate was 34.3% (60/175). RCS revealed a nonlinear association (P for nonlinearity = 0.016) with an inflection point at BMI = 24.8 kg/m². Below this point, each 1-unit BMI increase was associated with reduced pneumothorax risk (OR: 0.66, 95% CI: 0.54–0.82; P < 0.001). Above it, the association was not significant (OR: 1.40, 95% CI: 0.97–2.02; P = 0.071). The mean nodule size was 8.9 ± 2.1 mm, and most nodules were located in the peripheral lung regions. This single-center retrospective analysis suggests a nonlinear relationship between BMI and pneumothorax risk, with the lowest risk observed near BMI = 24.8 kg/m². These findings highlight the potential for BMI-based risk stratification but require validation in larger, prospective studies.

Journal of Cardiothoracic Surgery
Fujian Medical University (CN), Putian University (CN)
Good health and well-being
Openalex Percentile: Top 33%
Lung Cancer Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.