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Construction and validation of a predictive model of pneumonia for ICU patients with traumatic brain injury (TBI)

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Abstract

The incidence of pneumonia in ICU patients with TBI is very high, seriously affecting the prognosis. This study aims to construct a predictive model for pneumonia in ICU patients with TBI and provide help for the prevention of TBI-related pneumonia.

Clinical data of ICU patients with TBI were collected from the Medical Information Mart for Intensive Care (MIMIC)-IV database and hospital data. Variables were screened by lasso and multivariate logistic regression to construct a predictive nomogram model, verified in internal validation cohort and external validation cohort by receiver operator characteristic (ROC) curve, calibration curve and decision curve analysis (DCA).

A total of 1850 ICU patients with TBI were enrolled in the study from the MIMIC-IV database, including 1298 in the training cohort and 552 in internal validation cohort. The external validation cohort included 240 ICU patients with TBI from hospital data. Nine variables were selected from the training cohort by lasso regression and multivariate logistic regression, and a pneumonia prediction nomogram was constructed. This nomogram has a high discrimination in training, internal validation and external validation cohorts (AUC = 0.857, 0.877, 0.836). The calibration curve and DCA showed that this nomogram had a high calibration and better clinical decision-making efficiency.

The nomogram showed excellent discrimination and clinical utility to predict pneumonia, and could identify pneumonia high-risk patients early, thus providing personalised treatment strategies for ICU patients with TBI.

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Data availability

The datasets presented in the current study are available in the MIMIC-IV database. (https://physionet.org/content/mimiciv/2.2/).

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Author information

Author notes

  1. Xin Geng and Hao Wu contributed equally to this work.

Authors and Affiliations

  1. Department of Neurosurgery, the First Affiliated Hospital of Jinan University, Guangzhou, 510630, China

    Xin Geng, Augustine K. Ballah, Wenqiang Che, Shuaishuai Wu, Tengyue Fu, Ning Li & Xiangyu Wang

  2. Department of Neurosurgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, China

    Hao Wu, Xiaocong Wei & Yonghong Wang

  3. Department of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China

    Chenan Liu

  4. Department of Neurology, the First Affiliated Hospital of Jinan University, Guangzhou, 510630, China

    Linrui Qi

  5. Department of Neurosurgery, Shanxi Provincial People’s Hospital, Taiyuan, 030012, China

    Rui Cheng & Hongming Ji

  6. Department of Pneumology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, China

    Zhigang Pang

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  1. Xin Geng
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Contributions

Xin Geng, Hao Wu contributed equally to this work. Xin Geng and Xiangyu Wang proposed and completed the entire study design. Xin Geng, Augustine K. Ballah wrote the main manuscript text. Xin Geng extracted the data from the MIMIC database. Wenqiang Che, Shuaishuai Wu, Tengyue Fu, Ning Li, Linrui Qi participated in processing the data and formulating the analysis strategy. Chenan Liu did the statistical analysis. Xiaocong Wei, Yonghong Wang, Rui Cheng, Zhigang Pang, Hongming Ji, Hao Wu, Xiangyu Wang participated in the treatment of TBI patients and collection of clinical data. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Yonghong Wang or Xiangyu Wang.

Ethics declarations

Ethics approval and consent to participate

The establishment of MIMIC-IV database was approved by the Massachusetts Institute of Technology (Cambridge, MA) and Beth Israel Deaconess Medical Center (Boston, MA), and consent was obtained for the original data collection. Research on clinical data approved by Shanxi Bethune Hospital Ethics Committee (YXLL-2022–124) and Shanxi Provincial People’s Hospital Ethics Committee (2022–395).

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The authors declare no competing interests.

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Geng, X., Wu, H., Liu, C. et al. Construction and validation of a predictive model of pneumonia for ICU patients with traumatic brain injury (TBI). Neurosurg Rev 46, 308 (2023). https://doi.org/10.1007/s10143-023-02208-9

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