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Open Access 01-12-2024 | Spinal Tumor | Research

Nomogram for predicting postoperative pulmonary complications in spinal tumor patients

Authors: Jingcheng Zou, Ge Luo, Liwang Zhou, Xuena Wang, Tingting Wang, Qi Gao, Tao Lv, Guangxin Xu, Yuanyuan Yao, Min Yan

Published in: BMC Anesthesiology | Issue 1/2024

Abstract

Objectives

Although several independent risk factors for postoperative pulmonary complications (PPCs) after spinal tumor surgery have been studied, a simple and valid predictive model for PPC occurrence after spinal tumor surgery has not been developed.

Patients and methods

We collected data from patients who underwent elective spine surgery for a spinal tumor between 2013 and 2020 at a tertiary hospital in China. Data on patient characteristics, comorbidities, preoperative examinations, intraoperative variables, and clinical outcomes were collected. We used univariable and multivariable logistic regression models to assess predictors of PPCs and developed and validated a nomogram for PPCs. We evaluated the performance of the nomogram using the area under the receiver operating characteristic curve (ROC), calibration curves, the Brier Score, and the Hosmer–Lemeshow (H–L) goodness-of-fit test. For clinical use, decision curve analysis (DCA) was conducted to identify the model’s performance as a tool for supporting decision-making.

Results

Among the participants, 61 (12.4%) individuals developed PPCs. Clinically significant variables associated with PPCs after spinal tumor surgery included BMI, tumor location, blood transfusion, and the amount of blood lost. The nomogram incorporating these factors showed a concordance index (C-index) of 0.755 (95% CI: 0.688–0.822). On internal validation, bootstrapping with 1000 resamples yielded a bias-corrected area under the receiver operating characteristic curve of 0.733, indicating the satisfactory performance of the nomogram in predicting PPCs. The calibration curve demonstrated accurate predictions of observed values. The decision curve analysis (DCA) indicated a positive net benefit for the nomogram across most predicted threshold probabilities.

Conclusions

We have developed a new nomogram for predicting PPCs in patients who undergo spinal tumor surgery.

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Title: Nomogram for predicting postoperative pulmonary complications in spinal tumor patients
Authors: Jingcheng Zou
Ge Luo
Liwang Zhou
Xuena Wang
Tingting Wang
Qi Gao
Tao Lv
Guangxin Xu
Yuanyuan Yao
Min Yan
Publication date: 01-12-2024
Publisher: BioMed Central
Keyword: Spinal Tumor
Published in: BMC Anesthesiology / Issue 1/2024
Electronic ISSN: 1471-2253
DOI: https://doi.org/10.1186/s12871-024-02443-7

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Nomogram for predicting postoperative pulmonary complications in spinal tumor patients

Abstract

Objectives

Patients and methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Objectives

Patients and methods

Results

Conclusions

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