1. Reweighting and validation of the hospital frailty risk score using electronic health records in Germany: a retrospective observational study
- Author
-
Klaus Kaier, Adrian Heidenreich, Markus Jäckel, Vera Oettinger, Alexander Maier, Ingo Hilgendorf, Philipp Breitbart, Tau Hartikainen, Till Keller, Dirk Westermann, and Constantin von zur Mühlen
- Subjects
Aged ,Machine learning ,Supervised learning ,Clinical frailty scale ,Risk adjustment ,Clinical decision making ,Geriatrics ,RC952-954.6 - Abstract
Abstract Background In the hospital setting, frailty is a significant risk factor, but difficult to measure in clinical practice. We propose a reweighting of an existing diagnoses-based frailty score using routine data from a tertiary care teaching hospital in southern Germany. Methods The dataset includes patient characteristics such as sex, age, primary and secondary diagnoses and in-hospital mortality. Based on this information, we recalculate the existing Hospital Frailty Risk Score. The cohort includes patients aged ≥ 75 and was divided into a development cohort (admission year 2011 to 2013, N = 30,525) and a validation cohort (2014, N = 11,202). A limited external validation is also conducted in a second validation cohort containing inpatient cases aged ≥ 75 in 2022 throughout Germany (N = 491,251). In the development cohort, LASSO regression analysis was used to select the most relevant variables and to generate a reweighted Frailty Score for the German setting. Discrimination is assessed using the area under the receiver operating characteristic curve (AUC). Visualization of calibration curves and decision curve analysis were carried out. Applicability of the reweighted Frailty Score in a non-elderly population was assessed using logistic regression models. Results Reweighting of the Frailty Score included only 53 out of the 109 frailty-related diagnoses and resulted in substantially better discrimination than the initial weighting of the score (AUC = 0.89 vs. AUC = 0.80, p
- Published
- 2024
- Full Text
- View/download PDF