National Institute of Social Security, Valencia, Spain.
Department of Clinical Medicine, Miguel Hernández University, San Juan de Alicante, Alicante, Spain.
Br J Gen Pract. 2019 Dec 26;70(690):e29-e35. doi: 10.3399/bjgp19X706577. Print 2020 Jan.
The main instruments used to assess frailty are the Fried frailty phenotype and the Fatigue, Resistance, Ambulation, Illnesses, and Loss of Weight (FRAIL) scale. Both instruments contain items that must be obtained in a personal interview and cannot be used with an electronic medical record only.
To develop and internally validate a prediction model, based on a points system and integrated in an application (app) for Android, to predict frailty using only variables taken from a patient's clinical history.
A cross-sectional observational study undertaken across the Valencian Community, Spain.
A sample of 621 older patients was analysed from January 2017 to May 2018. The main variable was frailty measured using the FRAIL scale. Candidate predictors were: sex, age, comorbidities, or clinical situations that could affect daily life, polypharmacy, and hospital admission in the last year. A total of 3472 logistic regression models were estimated. The model with the largest area under the receiver operating characteristic curve (AUC) was selected and adapted to the points system. This system was validated by bootstrapping, determining discrimination (AUC), and calibration (smooth calibration).
A total of 126 (20.3%) older people were identified as being frail. The points system had an AUC of 0.78 and included as predictors: sex, age, polypharmacy, hospital admission in the last year, and diabetes. Calibration was satisfactory.
A points system was developed to predict frailty in older people using parameters that are easy to obtain and recorded in the clinical history. Future research should be carried out to externally validate the constructed model.
评估虚弱的主要工具是 Fried 虚弱表型和疲劳、抵抗力、活动能力、疾病和体重减轻（FRAIL）量表。这两种工具都包含必须通过个人访谈获得的项目，并且不能仅使用电子病历使用。
开发和内部验证一个预测模型，该模型基于一个积分系统，并集成在一个用于 Android 的应用程序中，仅使用从患者临床病史中获取的变量来预测虚弱。
这是一项在西班牙巴伦西亚社区进行的横断面观察性研究。
从 2017 年 1 月至 2018 年 5 月分析了 621 名老年患者的样本。主要变量是使用 FRAIL 量表测量的虚弱。候选预测因子为：性别、年龄、合并症或可能影响日常生活的临床情况、多药治疗和去年住院。共估计了 3472 个逻辑回归模型。选择了具有最大接收者操作特征曲线（AUC）面积的模型，并将其适应积分系统。通过自举法验证该系统，确定判别（AUC）和校准（平滑校准）。
共有 126 名（20.3%）老年人被确定为虚弱。积分系统的 AUC 为 0.78，包括预测因子：性别、年龄、多药治疗、去年住院和糖尿病。校准令人满意。
开发了一个积分系统，使用易于获得和记录在临床病史中的参数来预测老年人的虚弱。未来的研究应该对外验证构建的模型。
