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Perioperative risk factors associated with unplanned neurological intensive care unit readmission following elective supratentorial brain tumor resection.
Yuan, Qiang; Yao, Hai-Jun; Xi, Cai-Hua; Yu, Chun; Du, Zhuo-Ying; Chen, Long; Wu, Bi-Wu; Yang, Lei; Wu, Gang; Hu, Jin.
Affiliation
  • Yuan Q; 1Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai.
  • Yao HJ; 2National Center for Neurological Disorders, Shanghai.
  • Xi CH; 3Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai.
  • Yu C; 4Neurosurgical Institute of Fudan University, Shanghai.
  • Du ZY; 5Shanghai Clinical Medical Center of Neurosurgery, Shanghai; and.
  • Chen L; 1Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai.
  • Wu BW; 2National Center for Neurological Disorders, Shanghai.
  • Yang L; 6Department of Neurosurgery & Neurocritical Care, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.
  • Wu G; 1Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai.
  • Hu J; 2National Center for Neurological Disorders, Shanghai.
J Neurosurg ; : 1-9, 2022 Dec 02.
Article in En | MEDLINE | ID: mdl-36461816
ABSTRACT

OBJECTIVE:

The aim of this study was to describe the clinical and procedural risk factors associated with the unplanned neurosurgical intensive care unit (NICU) readmission of patients after elective supratentorial brain tumor resection and serves as an exploratory analysis toward the development of a risk stratification tool that may be prospectively applied to this patient population.

METHODS:

This was a retrospective observational cohort study. The electronic medical records of patients admitted to an institutional NICU between September 2018 and November 2021 after elective supratentorial brain tumor resection were reviewed. Demographic and perioperative clinical factors were recorded. A prognostic model was derived from the data of 4892 patients recruited between September 2018 and May 2021 (development cohort). A nomogram was created to display these predictor variables and their corresponding points and risks of readmission. External validation was evaluated using a series of 1118 patients recruited between June 2021 and November 2021 (validation cohort). Finally, a decision curve analysis was performed to determine the clinical usefulness of the prognostic model.

RESULTS:

Of the 4892 patients in the development cohort, 220 (4.5%) had an unplanned NICU readmission. Older age, lesion type, Karnofsky Performance Status (KPS) < 70 at admission, longer duration of surgery, retention of endotracheal intubation on NICU entry, and longer NICU length of stay (LOS) after surgery were independently associated with an unplanned NICU readmission. A total of 1118 patients recruited between June 2021 and November 2021 were included for external validation, and the model's discrimination remained acceptable (C-statistic = 0.744, 95% CI 0.675-0.814). The decision curve analysis for the prognostic model in the development and validation cohorts showed that at a threshold probability between 0.05 and 0.8, the prognostic model showed a positive net benefit.

CONCLUSIONS:

A predictive model that included age, lesion type, KPS < 70 at admission, duration of surgery, retention of endotracheal intubation on NICU entry, and NICU LOS after surgery had an acceptable ability to identify elective supratentorial brain tumor resection patients at high risk for an unplanned NICU readmission. These risk factors and this prediction model may facilitate better resource allocation in the NICU and improve patient outcomes.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: J Neurosurg Year: 2022 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: J Neurosurg Year: 2022 Document type: Article