Self‐Reported Function More Informative than Frailty Phenotype in Predicting Adverse Postoperative Course in Older Adults

Kapoor, Alok; Matheos, Theofilos; Walz, Matthias; McDonough, Christine M.; Maheswaran, Abiramy; Ruppell, Evan; Mohamud, Deeqo; Shaffer, Nicholas; Zhou, Yanhua; Kaur, Shubjeet; Heard, Stephen O.; Crawford, Sybil L.; Cabral, Howard; White, Daniel K.; Santry, Heena P.; Jette, Alan M.; Fielding, Roger A.; Silliman, Rebecca A.; Gurwitz, Jerry H.

doi:10.1111/jgs.15108

Cited by 20 publications

(18 citation statements)

References 17 publications

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“…Our analysis combines use of both anchor-and distribution-based techniques for determining the MCID, which strengthens the confidence in our estimates of meaningful increments of change that are both perceptible to patients and above measurement error. Our findings add to the growing body of evidence supporting the psychometric properties of the LLFDI-FC (1,5,7,13) and its usefulness as a patient-reported measure of function for older adults.…”

Section: Discussionsupporting

confidence: 59%

Meaningful Change Estimates for the Late-Life Function and Disability Instrument in Older Adults

Beauchamp

Ward

Jette

et al. 2018

The Journals of Gerontology: Series A

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Background The Late-Life Function and Disability Instrument (LLFDI) is a well-validated and frequently used patient-reported outcome for older adults. The aim of this study was to estimate the minimal clinically important difference (MCID) of the LLFDI-Function Component (LLFDI-FC) and its subscales among community-dwelling older adults with mobility limitations. Methods We performed a secondary analysis of the Boston Rehabilitative Impairment Study of the Elderly, a longitudinal cohort study of older adults with mobility limitations residing in the community. The MCID for each LLFDI-FC scale over 1 year of follow-up was estimated using both anchor- and distribution-based methods, including mean change scores on a patient-reported global rating of change in function scale, the standard error of measurement (SEM), and the minimal detectable change with 90% confidence (MDC90). Results Data from 320 older adults were used in the analysis (mean age 76 years, 69% female, mean of four chronic conditions). Meaningful change estimates for “small change” based on the global rating of change and SEM were 2, 3, 4, and 4 points for the LLFDI-FC overall function scale and basic lower-extremity, advanced lower-extremity, and upper-extremity subscales, respectively. Estimates for “substantial change” based on the global rating of change and minimal detectable change with 90% confidence were 5, 6, 9, and 10 points for the overall function scale and basic lower-extremity, advanced lower-extremity, and upper-extremity subscales, respectively. Conclusion This study provides the first MCID estimates for the LLFDI-FC, a widely used patient-reported measure of function. These values can be used to interpret the outcomes of longitudinal investigations of functional status in similar populations of community-dwelling older adults.

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Section: Discussionsupporting

confidence: 59%

Meaningful Change Estimates for the Late-Life Function and Disability Instrument in Older Adults

Beauchamp

Ward

Jette

et al. 2018

The Journals of Gerontology: Series A

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“…Many investigators report significant associations between measures of frailty and postoperative complications, 1,5,6,8,16,19,20,29,[36][37][38][39][40] but only some report C statistics, 6,29,30,33,36,37,39 which quantify clinical importance. Reported C statistics range from 0.53 to 0.68, with most being between 0.60 and 0.65, 6,29,30,39 which are similar to our findings. A statistically significant odds ratio 34,35 does not imply predictive ability or discriminative classification, making measures of discrimination such as the C statistic critical.…”

Section: Discussionmentioning

confidence: 99%

“…6,36 Additionally, the Fried Index, which is the basis for the Hopkins Frailty Score, has been validated in a perioperative setting. 18,21 Recently, Kapoor et al 39 compared the Fried Index with the self-reported Late Life Function and Disability Instrument and found them to be comparable in perioperative settings. It thus seems unlikely that our results would much differ had we selected other measures of frailty.…”

Section: Preoperative Frailty Assessmentmentioning

confidence: 99%

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

et al. 2020

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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.

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“…The Risk Analysis Index has been found to be a helpful adjunct in addition to the ACS score because of its ability to leverage patient frailty as an identifier for potential surgical prehabilitation [ 25 ]. Furthermore, use of a self-identified functionality scale was a better predictive tool for adverse outcomes when combined with the ACS calculator than the frailty phenotype [ 26 ].…”

Section: Discussionmentioning

confidence: 99%

Perioperative considerations in nonagenarians

Tecos

Kern

Foje

et al. 2020

Surgery Open Science

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Objective The nation's aging population presents novel perioperative challenges. Potential benefits of operative interventions must be scrutinized in relation to recoverable quality of life. The purpose of this study is to evaluate common risk calculators used for medical decision making in a nonagenarian patient population. Methods Retrospective medical record review was performed on patients 90 years or older who underwent operative interventions requiring anesthesia at a large academic medical center between January 1, 2013, and December 31, 2017. GraphPad 8.2.1 was used for statistical analysis. Results Significant differences were found when data were stratified by age for elective versus emergent cases (P value < .0001), ability to return to baseline function (P value  = .0062), and mortality (P value < .0001). Significant differences were found in emergent and elective cases, ability to return to baseline function, readmissions, and mortality (all P values < .0001) when stratified by American Society of Anesthesiologists score. Ability of patients to return to baseline functionality after intervention was influenced by their preintervention level of functionality (P value = .0008). American College of Surgeons and Portsmouth Physiologic and Operative Severity Score for Enumeration of Mortality and Morbidity risk calculators underestimated the need for rehabilitation and overestimated mortality for this population (all P values < .0001). Conclusion Perioperative cares of the extreme geriatric population are complex and should be approached collaboratively. Rehabilitation and postoperative assistance resources should be assessed and used fully. Input from palliative care teams should be sought appropriately. End-of-life and escalation-of-care discussions should ideally be organized prior to emergent interventions. Frailty and risk calculators should be used and considered for formal implementation into the preoperative workflow.

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Self‐Reported Function More Informative than Frailty Phenotype in Predicting Adverse Postoperative Course in Older Adults

Cited by 20 publications

References 17 publications

Meaningful Change Estimates for the Late-Life Function and Disability Instrument in Older Adults

Meaningful Change Estimates for the Late-Life Function and Disability Instrument in Older Adults

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

Perioperative considerations in nonagenarians

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