Loreto C Pulido1, Matthias Meyer2, Jan Reinhard2, Tobias Kappenschneider2, Joachim Grifka2, Markus Weber3. 1. Department of Orthopedic Surgery, University Medical Center Regensburg, Asklepios Klinikum Bad Abbach, Kaiser-Karl-V-Allee 3, 93077, Bad Abbach, Germany. loreto.pulido@ukr.de. 2. Department of Orthopedic Surgery, University Medical Center Regensburg, Asklepios Klinikum Bad Abbach, Kaiser-Karl-V-Allee 3, 93077, Bad Abbach, Germany. 3. Department of Orthopedic and Trauma Surgery, Hospital Barmherzige Brüder Regensburg, Prüfeninger Str. 86, 93049, Regensburg, Germany.
Abstract
PURPOSE: The Hospital Frailty Risk Score (HFRS) is derived from routinely collected data and validated as a geriatric risk stratification tool. This study aimed to evaluate the utility of the HFRS as a predictor for postoperative adverse events in spine surgery. METHODS: In this retrospective analysis of 2042 patients undergoing spine surgery at a university spine center between 2011 and 2019, HFRS was calculated for each patient. Multivariable logistic regression models were used to assess the relationship between the HFRS and postoperative adverse events. Adverse events were compared between patients with high or low frailty risk. RESULTS: Patients with intermediate or high frailty risk showed a higher rate of reoperation (19.7% vs. 12.2%, p < 0.01), surgical site infection (3.4% vs. 0.4%, p < 0.001), internal complications (4.1% vs. 1.1%, p < 0.01), Clavien-Dindo IV complications (8.8% vs. 3.4%, p < 0.001) and transfusion (10.9% vs. 1.5%, p < 0.001). Multivariable logistic regression analyses revealed a high HFRS as independent risk factor for reoperation [odds ratio (OR) = 1.1; 95% confidence interval (CI) 1.0-1.2], transfusion (OR = 1.3; 95% CI 1.2-1.4), internal complications (OR = 1.2; 95% CI 1.1-1.3), surgical site infections (OR = 1.3; 95% CI 1.2-1.5) and other complications (OR = 1.3; 95% CI 1.2-1.4). CONCLUSION: The HFRS can predict adverse events and is an easy instrument, fed from routine hospital data. By identifying risk patients at an early stage, the individual patient risk could be minimized, which leads to less complications and lower costs. LEVEL OF EVIDENCE: Level III - retrospective cohort study TRIAL REGISTRATION: The study was approved by the local ethics committee (20-1821-104) of the University of Regensburg in February 2020.
PURPOSE: The Hospital Frailty Risk Score (HFRS) is derived from routinely collected data and validated as a geriatric risk stratification tool. This study aimed to evaluate the utility of the HFRS as a predictor for postoperative adverse events in spine surgery. METHODS: In this retrospective analysis of 2042 patients undergoing spine surgery at a university spine center between 2011 and 2019, HFRS was calculated for each patient. Multivariable logistic regression models were used to assess the relationship between the HFRS and postoperative adverse events. Adverse events were compared between patients with high or low frailty risk. RESULTS: Patients with intermediate or high frailty risk showed a higher rate of reoperation (19.7% vs. 12.2%, p < 0.01), surgical site infection (3.4% vs. 0.4%, p < 0.001), internal complications (4.1% vs. 1.1%, p < 0.01), Clavien-Dindo IV complications (8.8% vs. 3.4%, p < 0.001) and transfusion (10.9% vs. 1.5%, p < 0.001). Multivariable logistic regression analyses revealed a high HFRS as independent risk factor for reoperation [odds ratio (OR) = 1.1; 95% confidence interval (CI) 1.0-1.2], transfusion (OR = 1.3; 95% CI 1.2-1.4), internal complications (OR = 1.2; 95% CI 1.1-1.3), surgical site infections (OR = 1.3; 95% CI 1.2-1.5) and other complications (OR = 1.3; 95% CI 1.2-1.4). CONCLUSION: The HFRS can predict adverse events and is an easy instrument, fed from routine hospital data. By identifying risk patients at an early stage, the individual patient risk could be minimized, which leads to less complications and lower costs. LEVEL OF EVIDENCE: Level III - retrospective cohort study TRIAL REGISTRATION: The study was approved by the local ethics committee (20-1821-104) of the University of Regensburg in February 2020.
Authors: Frank L Acosta; Jamal McClendon; Brian A O'Shaughnessy; Heiko Koller; Chris J Neal; Oliver Meier; Christopher P Ames; Tyler R Koski; Stephen L Ondra Journal: J Neurosurg Spine Date: 2011-09-02
Authors: Emily K Miller; Brian J Neuman; Amit Jain; Alan H Daniels; Tamir Ailon; Daniel M Sciubba; Khaled M Kebaish; Virginie Lafage; Justin K Scheer; Justin S Smith; Shay Bess; Christopher I Shaffrey; Christopher P Ames Journal: Neurosurg Focus Date: 2017-12 Impact factor: 4.047