A comparative analysis of the Hospital Frailty Risk Score in predicting postoperative outcomes among intracranial tumor patients

被引:9
作者
Jimenez, Adrian E. [1 ]
Liu, Jiaqi [2 ]
V. Cicalese, Kyle [3 ]
Jimenez, Miguel A. [4 ]
Porras, Jose L. [1 ]
Azad, Tej D. [1 ]
Jackson, Christopher [1 ]
Gallia, Gary L. [1 ]
Bettegowda, Chetan [1 ]
Weingart, Jon [1 ]
Mukherjee, Debraj [1 ,5 ]
机构
[1] Johns Hopkins Univ, Dept Neurosurg, Sch Med, Baltimore, MD USA
[2] Georgetown Univ, Sch Med, Washington, DC USA
[3] Virginia Commonwealth Univ, Sch Med, Richmond, VA USA
[4] Univ Chicago, Pritzker Sch Med, Chicago, IL USA
[5] Johns Hopkins Univ, Sch Med, Baltimore, MD 21205 USA
关键词
KEYWORDS frailty; neuro-oncology; outcomes; tumor; ADVERSE EVENTS; SURGERY; READMISSION; CRANIOTOMY; MORTALITY; PROGRAM; COHORT; ADULTS; INDEX;
D O I
10.3171/2022.11.JNS222033
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
OBJECTIVE In recent years, frailty indices such as the 11-and 5-factor modified frailty indices (mFI-11 and mFI-5), American Society of Anesthesiologists (ASA) physical status classification, and Charlson Comorbidity Index (CCI) have been shown to be effective predictors of various postoperative outcomes in neurosurgical patients. The Hospital Frailty Risk Score (HFRS) is a well-validated tool for assessing frailty; however, its utility has not been evaluated in intracranial tumor surgery. In the present study, the authors investigated the accuracy of the HFRS in predicting outcomes following intracranial tumor resection and compared its utility to those of other validated frailty indices.METHODS A retrospective analysis was conducted using an intracranial tumor patient database at a single institution. Patients eligible for study inclusion were those who had undergone resection for an intracranial tumor between January 1, 2017, and December 31, 2019. ICD-10 codes were used to identify HFRS components and subsequently calculate risk scores. In addition to several postoperative variables, ASA class, CCI, and mFI-11 and mFI-5 scores were determined for each patient. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUROC), and the DeLong test was used to assess for significant differences between AUROCs. Multivariate models for continuous outcomes were constructed using linear regression, whereas logistic regression models were used for categorical outcomes.RESULTS A total of 2518 intracranial tumor patients (mean age 55.3 & PLUSMN; 15.1 years, 53.4% female, 70.4% White) were included in this study. The HFRS had a statistically significant greater AUROC than ASA status, CCI, mFI-11, and mFI-5 for postoperative complications, high hospital charges, nonroutine discharge, and 90-day readmission. In the multivari-ate analysis, the HFRS was significantly and independently associated with postoperative complications (OR 1.14, p < 0.0001), hospital length of stay (coefficient = 0.50, p < 0.0001), high hospital charges (coefficient = 1917.49, p < 0.0001), nonroutine discharge (OR 1.14, p < 0.0001), and 90-day readmission (OR 1.06, p < 0.0001).CONCLUSIONS The study findings suggest that the HFRS is an effective predictor of postoperative outcomes in intra- cranial tumor patients and more effectively predicts adverse outcomes than other frailty indices. The HFRS may serve as an important tool for reducing patient morbidity and mortality in intracranial tumor surgery.
引用
收藏
页码:363 / 372
页数:10
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