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Updated: Aug 14, 2025
A Rat Lung Transplantation Model of Warm Ischemia/Reperfusion Injury: Optimizations to Improve Outcomes
Published on: October 28, 2021
Establishment of a risk prediction model for prolonged mechanical ventilation after lung transplantation: a
Peigen Gao1,2, Chongwu Li1,2, Junqi Wu1,2
1Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, 507 Zhengmin Road, Shanghai, 200443, China.
Background:
Prolonged mechanical ventilation (PMV), mostly defined as mechanical ventilation > 72 h after lung transplantation with or without tracheostomy, is associated with increased mortality. Nevertheless, the predictive factors of PMV after lung transplant remain unclear. The present study aimed to develop a novel scoring system to identify PMV after lung transplantation.
Methods:
A total of 141 patients who underwent lung transplantation were investigated in this study. The patients were divided into PMV and non-prolonged ventilation (NPMV) groups. Univariate and multivariate logistic regression analyses were performed to assess factors associated with PMV. A risk nomogram was then established based on the multivariate analysis, and model performance was further examined regarding its calibration, discrimination, and clinical usefulness.
Results:
Eight factors were finally identified to be significantly associated with PMV by the multivariate analysis and therefore were included as risk factors in the nomogram as follows: the body mass index (BMI, P = 0.036); primary diagnosis as idiopathic pulmonary fibrosis (IPF, P = 0.038); pulmonary hypertension (PAH, P = 0.034); primary graft dysfunction grading (PGD, P = 0.011) at T0; cold ischemia time (CIT P = 0.012); and three ventilation parameters (peak inspiratory pressure [PIP, P < 0.001], dynamic compliance [Cdyn, P = 0.001], and P/F ratio [P = 0.015]) at T0. The nomogram exhibited superior discrimination ability with an area under the curve of 0.895. Furthermore, both calibration curve and decision-curve analysis indicated satisfactory performance.
Conclusion:
A novel nomogram to predict individual risk of receiving PMV for patients after lung transplantation was established, which may guide preventative measures for tackling this adverse event.
Insights
A new scoring system predicts prolonged mechanical ventilation (PMV) after lung transplantation. This tool helps identify patients at risk, enabling early interventions to improve outcomes.
Area of Science:
- Cardiology
- Pulmonology
- Transplantation Medicine
Background:
- Prolonged mechanical ventilation (PMV) after lung transplantation is linked to higher mortality rates.
- Predictive factors for PMV post-lung transplant are not well-established.
- Identifying patients at risk for PMV is crucial for improving post-transplant care.
Purpose of the Study:
- To develop and validate a novel scoring system for predicting PMV in lung transplant recipients.
- To identify key clinical and ventilatory parameters associated with PMV.
Main Methods:
- A retrospective study involving 141 lung transplant patients, divided into PMV and non-prolonged ventilation (NPMV) groups.
- Univariate and multivariate logistic regression analyses were used to identify predictive factors.
- A risk nomogram was constructed and its performance evaluated for calibration and discrimination.
Main Results:
- Eight factors significantly predicted PMV: BMI, idiopathic pulmonary fibrosis (IPF), pulmonary hypertension (PAH), primary graft dysfunction (PGD) grade, cold ischemia time (CIT), peak inspiratory pressure (PIP), dynamic compliance (Cdyn), and P/F ratio.
- The developed nomogram demonstrated excellent discrimination with an AUC of 0.895.
- Calibration and decision-curve analyses confirmed the nomogram's satisfactory performance.
Conclusions:
- A novel nomogram effectively predicts the individual risk of PMV in lung transplant patients.
- This predictive tool can guide the implementation of preventative strategies to mitigate PMV and improve patient outcomes.
