Deficit Accumulation and Phenotype Assessments of Frailty Both Poorly Predict Duration of Hospitalization and Serious Complications after Noncardiac Surgery

Abstract

Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New Background Frailty is associated with adverse postoperative outcomes, but it remains unclear which measure of frailty is best. This study compared two approaches: the Modified Frailty Index, which is a deficit accumulation model (number of accumulated deficits), and the Hopkins Frailty Score, which is a phenotype model (consisting of shrinking, weakness, exhaustion, slowness, and low physical activity). The primary aim was to compare the ability of each frailty score to predict prolonged hospitalization. Secondarily, the ability of each score to predict 30-day readmission and/or postoperative complications was compared. Methods This study prospectively enrolled adults presenting for preanesthesia evaluation before elective noncardiac surgery. The Hopkins Frailty Score and Modified Frailty Index were both determined. The ability of each frailty score to predict the primary outcome (prolonged hospitalization) was compared using a ratio of root-mean-square prediction errors from linear regression models. The ability of each score to predict the secondary outcome (readmission and complications) was compared using ratio of root-mean-square prediction errors from logistic regression models. Results The study included 1,042 patients. The frailty rates were 23% (Modified Frailty Index of 4 or higher) and 18% (Hopkins Frailty Score of 3 or higher). In total, 12.9% patients were readmitted or had postoperative complications. The error of the Modified Frailty Index and Hopkins Frailty Score in predicting the primary outcome was 2.5 (95% CI, 2.2, 2.9) and 2.6 (95% CI, 2.2, 3.0) days, respectively, and their ratio was 1.0 (95% CI, 1.0, 1.0), indicating similarly poor prediction. Similarly, the error of respective frailty scores in predicting the probability of secondary outcome was high, specifically 0.3 (95% CI, 0.3, 0.4) and 0.3 (95% CI, 0.3, 0.4), and their ratio was 1.00 (95% CI, 1.0, 1.0). Conclusions The Modified Frailty Index and Hopkins Frailty Score were similarly poor predictors of perioperative risk. Further studies, with different frailty screening tools, are needed to identify the best method to measure perioperative frailty.

Preoperative Frailty Assessment: Reply

“…Indeed, of routinely collected outcomes, hospital length of stay has arguably the highest variation and most substantial contribution from indirect patient predictors (e.g., social status, home supports, availability of allied health services). Neither of the frailty instruments tested by Sonny et al 1 capture these factors and are therefore unlikely to accurately predict or explain a substantial degree of variance in prolongation of stay.…”

“…While we agree that a dichotomized frailty assignment is often used for risk stratification, if the objective of a study is to determine the predictive accuracy of a given scale, it is well demonstrated that dichotomization of a predictor variable can lead to decreased predictive performance compared to continuous representations such as regression splines or polynomials. 7 Last, and perhaps most salient to the study by Sonny et al, 1 type of surgery is likely the most important predictor of complications and length of stay. While the study's primary outcome, prolonged length of stay, was determined based on the difference between actual length of stay and hospitaland surgery-specific expected length of stay (which provides some degree of procedural adjustment), this approach may also downwardly bias measures of accuracy.…”

“…It is not surprising, however, that the two measures selected (the phenotypic Hopkins Frailty Score and a modified deficit accumulation score [i.e., frailty index]) in the study of Sonny et al 1 demonstrated large error in the prediction of prolonged hospitalization across a heterogeneous group of patients undergoing noncardiac surgery. Many studies evaluating perioperative prediction models have consistently shown substantial challenges in accurately estimating prolonged hospitalization.…”

“…As the authors rightly point out, frailty instruments differ in their estimation of a frailty score based on the use of a phenotypic model (requiring prospective ascertainment and direct patient evaluation) or an accumulation of deficits model of frailty (amenable to medical record evaluation, which can be conducted retrospectively or in real time). The phenotype model, developed by Fried et al 3 and adapted in various operationalizations, including the Hopkins Frailty Score (used by Sonny et al 1 ), provides an objective assessment of biologic manifestations of frailty. In the phenotype model, changes and dysregulation present at the cellular and subcellular level are expressed through means that are primarily physical in nature (i.e., decreased energy, strength, gait speed, body mass, and activity levels); this means that the phenotype model does not directly include cognitive or social deficits, both of which are agreed upon by experts to be essential components of the frailty syndrome 4 and both of which are likely to substantively influence a patient's length of hospital stay.…”

“…Unfortunately, the modified frailty index (initially derived for use with the National Surgical Quality Improvement Program administrative database) contains only 11 deficits, 10 of which are specifically medical diagnoses. Although the reduced number of variables increases measurement ease and broad implementation, the additional variables that are missing within the modified frailty index compared to a more traditional Rockwood frailty index likely contribute to risk for perioperative adverse outcomes, particularly in surgical populations with relatively low levels of frailty (~20% in the study by Sonny et al 1 ) This makes the modified frailty index more closely aligned to a condensed comorbidity index (e.g., Charlson index) than a true multidimensional measure of frailty.…”