Daniel I McIsaac1,2,3, Emma P Harris1, Emily Hladkowicz1,3, Husein Moloo2,4, Manoj M Lalu1,3, Gregory L Bryson1,3, Allen Huang5, John Joanisse6, Gavin M Hamilton1, Alan J Forster3,7, Carl van Walraven2,3,7. 1. From the Department of Anesthesiology and Pain Medicine, University of Ottawa, and the Ottawa Hospital, Ottawa, Ontario, Canada. 2. School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada. 3. Ottawa Hospital Research Institute, Ottawa, Ontario, Canada. 4. Department of Surgery. 5. Division of Geriatric Medicine, University of Ottawa, and the Ottawa Hospital, Ottawa, Ontario, Canada. 6. Hôpital Montfort, Ottawa, Ontario, Canada. 7. Department of Medicine, University of Ottawa, and the Ottawa Hospital, Ottawa, Ontario, Canada.
Abstract
BACKGROUND: Guidelines recommend routine preoperative frailty assessment for older people. However, the degree to which frailty instruments improve predictive accuracy when added to traditional risk factors is poorly described. Our objective was to measure the accuracy gained in predicting outcomes important to older patients when adding the Clinical Frailty Scale (CFS), Fried Phenotype (FP), or Frailty Index (FI) to traditional risk factors. METHODS: This was an analysis of a multicenter prospective cohort of elective noncardiac surgery patients ≥65 years of age. Each frailty instrument was prospectively collected. The added predictive performance of each frailty instrument beyond the baseline model (age, sex, American Society of Anesthesiologists' score, procedural risk) was estimated using likelihood ratio test, discrimination, calibration, explained variance, and reclassification. Outcomes analyzed included death or new disability, prolonged length of stay (LoS, >75th percentile), and adverse discharge (death or non-home discharge). RESULTS: We included 645 participants (mean age, 74 [standard deviation, 6]); 72 (11.2%) participants died or experienced a new disability, 164 (25.4%) had prolonged LoS, and 60 (9.2%) had adverse discharge. Compared to the baseline model predicting death or new disability (area under the curve [AUC], 0.67; R, 0.08, good calibration), prolonged LoS (AUC, 0.73; R, 0.18, good calibration), and adverse discharge (AUC, 0.78; R, 0.16, poor calibration), the CFS improved fit per the likelihood ratio test (P < .02 for death or new disability, <.001 for LoS, <.001 for discharge), discrimination (AUC = 0.71 for death or new disability, 0.76 for LoS, 0.82 for discharge), calibration (good for death or new disability, LoS, and discharge), explained variance (R = 0.11 for death or new disability, 0.22 for LoS, 0.25 for discharge), and reclassification (appropriate directional reclassification) for all outcomes. The FP improved discrimination and R for all outcomes, but to a lesser degree than the CFS. The FI improved discrimination for death or new disability and R for all outcomes, but to a lesser degree than the CFS and the FP. These results were consistent in internal validation. CONCLUSIONS: Frailty instruments provide meaningful increases in accuracy when predicting postoperative outcomes for older people. Compared to the FP and FI, the CFS appears to improve all measures of predictive performance to the greatest extent and across outcomes. Combined with previous research demonstrating that the CFS is easy to use and requires less time than the FP, clinicians should consider its use in preoperative practice.
BACKGROUND: Guidelines recommend routine preoperative frailty assessment for older people. However, the degree to which frailty instruments improve predictive accuracy when added to traditional risk factors is poorly described. Our objective was to measure the accuracy gained in predicting outcomes important to older patients when adding the Clinical Frailty Scale (CFS), Fried Phenotype (FP), or Frailty Index (FI) to traditional risk factors. METHODS: This was an analysis of a multicenter prospective cohort of elective noncardiac surgery patients ≥65 years of age. Each frailty instrument was prospectively collected. The added predictive performance of each frailty instrument beyond the baseline model (age, sex, American Society of Anesthesiologists' score, procedural risk) was estimated using likelihood ratio test, discrimination, calibration, explained variance, and reclassification. Outcomes analyzed included death or new disability, prolonged length of stay (LoS, >75th percentile), and adverse discharge (death or non-home discharge). RESULTS: We included 645 participants (mean age, 74 [standard deviation, 6]); 72 (11.2%) participantsdied or experienced a new disability, 164 (25.4%) had prolonged LoS, and 60 (9.2%) had adverse discharge. Compared to the baseline model predicting death or new disability (area under the curve [AUC], 0.67; R, 0.08, good calibration), prolonged LoS (AUC, 0.73; R, 0.18, good calibration), and adverse discharge (AUC, 0.78; R, 0.16, poor calibration), the CFS improved fit per the likelihood ratio test (P < .02 for death or new disability, <.001 for LoS, <.001 for discharge), discrimination (AUC = 0.71 for death or new disability, 0.76 for LoS, 0.82 for discharge), calibration (good for death or new disability, LoS, and discharge), explained variance (R = 0.11 for death or new disability, 0.22 for LoS, 0.25 for discharge), and reclassification (appropriate directional reclassification) for all outcomes. The FP improved discrimination and R for all outcomes, but to a lesser degree than the CFS. The FI improved discrimination for death or new disability and R for all outcomes, but to a lesser degree than the CFS and the FP. These results were consistent in internal validation. CONCLUSIONS: Frailty instruments provide meaningful increases in accuracy when predicting postoperative outcomes for older people. Compared to the FP and FI, the CFS appears to improve all measures of predictive performance to the greatest extent and across outcomes. Combined with previous research demonstrating that the CFS is easy to use and requires less time than the FP, clinicians should consider its use in preoperative practice.
Authors: Brian J Douthit; Rachel L Walden; Kenrick Cato; Cynthia P Coviak; Christopher Cruz; Fabio D'Agostino; Thompson Forbes; Grace Gao; Theresa A Kapetanovic; Mikyoung A Lee; Lisiane Pruinelli; Mary A Schultz; Ann Wieben; Alvin D Jeffery Journal: Appl Clin Inform Date: 2022-02-09 Impact factor: 2.342
Authors: Emily Hladkowicz; Kristin Dorrance; Gregory L Bryson; Alan Forster; Sylvain Gagne; Allen Huang; Manoj M Lalu; Luke T Lavallée; Husein Moloo; Janet Squires; Daniel I McIsaac Journal: Can J Anaesth Date: 2022-08-17 Impact factor: 6.713
Authors: Simon Feng; Carl Van Walraven; Manoj Lalu; Husein Moloo; Reilly Musselman; Daniel I McIsaac Journal: BMJ Open Date: 2020-01-07 Impact factor: 2.692
Authors: Carmel L Montgomery; Nguyen X Thanh; Henry T Stelfox; Colleen M Norris; Darryl B Rolfson; Steven R Meyer; Mohamad A Zibdawi; Sean M Bagshaw Journal: CJC Open Date: 2020-09-14