The Hospital Frailty Risk Score (HFRS) is a recently developed tool that uses ICD-10 codes to measure patient frailty. However, the effectiveness of HFRS has not yet been assessed in meningioma patients specifically. The present study aimed to evaluate the effectiveness of HFRS in predicting surgical outcomes for patients with meningiomas. This retrospective study utilized data from patients undergoing meningioma resection at a single institution (2017–2019). Data were obtained through a combination of automated data retrieval and manual chart review. Bivariate logistic regression was used to assess the prognostic ability of several frailty indices for predicting postoperative outcomes. Further, discrimination for each model was assessed using the area under the receiver operating characteristic curve (AUROC). Generalized linear models with gamma error distributions and a log-link function were used to model hospital length of stay (LOS), total charges, complications, and disposition. A total of 464 meningioma patients (mean age 58.20 years, 72.8 % female, 66.4 % white) were included. HFRS had a significantly greater AUROC when compared to ASA (p = 0.0074) for postoperative complications, and HFRS significantly outperformed ASA (p = 0.0021) and mFI-5 (p = 0.018) when predicting nonroutine discharge. On multivariate analysis, increasing HFRS scores were significantly and independently associated with greater LOS (p < 0.0001), higher hospital charges (p < 0.0001), higher odds of postoperative complications (OR = 1.05, p = 0.019), and nonroutine discharge (OR = 1.12, p < 0.0001). The HFRS was non-inferior compared to the mFI-5, CCI, ASA and mFI-11 in terms of model discrimination. HFRS effectively predicts postoperative outcomes for meningiomas and outperforms other indices in predicting complications and nonroutine discharge. This novel index may be used to improve clinical decision-making and reduce adverse postoperative outcomes among meningioma patients.

中文翻译：

---

医院衰弱风险评分独立预测脑膜瘤患者的术后结果

医院虚弱风险评分 (HFRS) 是最近开发的工具，使用 ICD-10 代码来衡量患者虚弱程度。然而，HFRS 的有效性尚未在脑膜瘤患者中进行专门评估。本研究旨在评估 HFRS 在预测脑膜瘤患者手术结果方面的有效性。这项回顾性研究利用了在单一机构（2017-2019 年）接受脑膜瘤切除术的患者的数据。数据是通过自动数据检索和手动图表审查相结合获得的。使用双变量逻辑回归来评估几种衰弱指数预测术后结果的预后能力。此外，使用受试者工作特征曲线下面积（AUROC）评估每个模型的区分度。使用具有伽马误差分布和对数链接函数的广义线性模型来模拟住院时间 (LOS)、总费用、并发症和处置。共有 464 名脑膜瘤患者（平均年龄 58.20 岁，72.8% 女性，66.4% 白人）纳入研究。对于术后并发症，HFRS 的 AUROC 显着高于 ASA (p = 0.0074)，并且在预测非常规出院时，HFRS 显着优于 ASA (p = 0.0021) 和 mFI-5 (p = 0.018)。在多变量分析中，HFRS 评分的增加与较高的 LOS (p < 0.0001)、较高的住院费用 (p < 0.0001)、较高的术后并发症发生率 (OR = 1.05，p = 0.019) 和非常规出院 (OR = 1.12，p < 0.0001）。就模型辨别力而言，HFRS 与 mFI-5、CCI、ASA 和 mFI-11 相比并不逊色。 HFRS 可以有效预测脑膜瘤的术后结果，并且在预测并发症和非常规出院方面优于其他指标。这一新指标可用于改善脑膜瘤患者的临床决策并减少术后不良结果。