Development and Temporal Validation of Staged Prediction Models for Acute Respiratory Distress Syndrome After Thymic Epithelial Tumour Resection.
- 1Department of Critical Care Medicine, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China.
- 2Intensive Care Unit, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, China.
Abstract
Background/Objectives: To develop and temporally validate staged models for predicting acute respiratory distress syndrome (ARDS) after thymic epithelial tumour resection. Methods: This single-centre retrospective study included 596 adults with pathologically confirmed thymic epithelial tumours. Patients treated in 2005-2020 formed the development cohort (n = 395), and those treated in 2021-2026 formed the temporal validation cohort (n = 201). Postoperative ARDS was adjudicated using the 2024 global definition. A preoperative model and a postoperative landmark model incorporating intraoperative, pathological, and early postoperative variables were developed using least absolute shrinkage and selection operator and multivariable logistic regression. Performance was assessed using discrimination, calibration, Brier score, decision curve analysis, bootstrap internal validation, and temporal validation. Results: ARDS occurred in 116 development patients (29.4%) and 58 validation patients (28.9%). The postoperative landmark model included the preoperative linear predictor, one-lung ventilation duration, Masaoka-Koga stage, perioperative transfusion, and early postoperative glucose, albumin, and C-reactive protein. It achieved higher AUCs than the preoperative model in the development (0.908 vs. 0.693; p < 0.001) and validation cohorts (0.928 vs. 0.655; p < 0.001), with lower Brier scores (0.107 vs. 0.187 and 0.094 vs. 0.192, respectively; both p < 0.001). The optimism-corrected development AUC was 0.898. Calibration and decision curve analyses also favoured the postoperative landmark model. Conclusions: Incorporating perioperative information improved ARDS prediction after thymic epithelial tumour surgery. The staged models may support sequential perioperative risk assessment; however, prospective evaluation and independent multicentre validation are required before implementation.
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BibTeX
@article{wang2026development,
title = {{Development and Temporal Validation of Staged Prediction Models for Acute Respiratory Distress Syndrome After Thymic Epithelial Tumour Resection.}},
author = {Ruize Wang and Siyu Yao and Lifeng Huang and Qiuyue Liu},
journal = {Journal of clinical medicine},
year = {2026},
month = oct,
doi = {10.3390/jcm15197715},
url = {https://europepmc.org/article/MED/42882176},
note = {CC BY},
}
RIS
TY - JOUR
TI - Development and Temporal Validation of Staged Prediction Models for Acute Respiratory Distress Syndrome After Thymic Epithelial Tumour Resection.
AU - Ruize Wang
AU - Siyu Yao
AU - Lifeng Huang
AU - Qiuyue Liu
PY - 2026
DA - 2026/10/06
JO - Journal of clinical medicine
DO - 10.3390/jcm15197715
UR - https://europepmc.org/article/MED/42882176
AB - Background/Objectives: To develop and temporally validate staged models for predicting acute respiratory distress syndrome (ARDS) after thymic epithelial tumour resection. Methods: This single-centre retrospective study included 596 adults with pathologically confirmed thymic epithelial tumours. Patients treated in 2005-2020 formed the development cohort (n = 395), and those treated in 2021-2026 formed the temporal validation cohort (n = 201). Postoperative ARDS was adjudicated using the 2024 global definition. A preoperative model and a postoperative landmark model incorporating intraoperative, pathological, and early postoperative variables were developed using least absolute shrinkage and selection operator and multivariable logistic regression. Performance was assessed using discrimination, calibration, Brier score, decision curve analysis, bootstrap internal validation, and temporal validation. Results: ARDS occurred in 116 development patients (29.4%) and 58 validation patients (28.9%). The postoperative landmark model included the preoperative linear predictor, one-lung ventilation duration, Masaoka-Koga stage, perioperative transfusion, and early postoperative glucose, albumin, and C-reactive protein. It achieved higher AUCs than the preoperative model in the development (0.908 vs. 0.693; p < 0.001) and validation cohorts (0.928 vs. 0.655; p < 0.001), with lower Brier scores (0.107 vs. 0.187 and 0.094 vs. 0.192, respectively; both p < 0.001). The optimism-corrected development AUC was 0.898. Calibration and decision curve analyses also favoured the postoperative landmark model. Conclusions: Incorporating perioperative information improved ARDS prediction after thymic epithelial tumour surgery. The staged models may support sequential perioperative risk assessment; however, prospective evaluation and independent multicentre validation are required before implementation.
SN - 2077-0383
ER -