Using item response theory to estimate interpretation threshold values for the Frailty Index in community dwelling older adults.

BACKGROUND: Although the frailty index (FI) is designed as a continuous measure of frailty, thresholds are often needed to guide its interpretation. This study aimed to introduce and demonstrate the utility of an item response theory (IRT) method in estimating FI interpretation thresholds in community-dwelling adults and to compare them with cutoffs estimated using the receiver operating characteristics (ROC) method. METHODS: A sample of 1,149 community-dwelling adults (mean[SD], 68[7] years) participated in this cross-sectional study. Participants completed a multi-domain geriatric screen from which the 40-item FI and 3 clinical anchors were computed - namely, (i)self-reported mobility limitations (SRML), (ii)"fair" or "poor" self-rated health (SRH), and (iii) restricted life-space mobility (RLSM). Participants were classified as having SRML-1 if they responded "Yes" to either of the 2 questions regarding walking and stair climbing difficulty and SRML-2 if they reported having walking and stair climbing difficulty. Participants with a Life Space Assessment score <60 points were classified as having RLSM. Threshold values for all anchor questions were estimated using the IRT method and ROC analysis with Youden criterion. RESULTS: The proportions of participants with SRML-1, SRML-2, Fair/Poor SRH, and RLSM were 21 %, 8 %, 22 %, and 9 %, respectively. The IRT-based thresholds for SRML-2 (0.26), fair/poor SRH (0.29), and RLSM (0.32) were significantly higher than those for SRML-1 (0.18). ROC-based FI cutoffs were significantly lower than IRT-based values for SRML-2, SRH, and RLSM (0.12 to 0.17), and they varied minimally and non-systematically across the anchors. CONCLUSIONS: The IRT method identifies biologically plausible FI thresholds that could meaningfully complement and contextualize existing thresholds for defining frailty.

Multimodal prerehabilitation for elderly patients with sarcopenia in colorectal surgery.

Sarcopenia, which is characterized by progressive and generalized loss of skeletal muscle mass and strength, has been well described to be associated with numerous poor postoperative outcomes, such as increased perioperative mortality, postoperative sepsis, prolonged length of stay, increased cost of care, decreased functional outcome, and poorer oncological outcomes in cancer surgery. Multimodal prehabilitation, as a concept that involves boosting and optimizing the preoperative condition of a patient prior to the upcoming stressors of a surgical procedure, has the purported benefits of reversing the effects of sarcopenia, shortening hospitalization, improving the rate of return to bowel activity, reducing the costs of hospitalization, and improving quality of life. This review aims to present the current literature surrounding the concept of sarcopenia, its implications pertaining to colorectal cancer and surgery, a summary of studied multimodal prehabilitation interventions, and potential future advances in the management of sarcopenia.

Development and validation of a physical frailty phenotype index-based model to estimate the frailty index.

BACKGROUND: The conventional count-based physical frailty phenotype (PFP) dichotomizes its criterion predictors-an approach that creates information loss and depends on the availability of population-derived cut-points. This study proposes an alternative approach to computing the PFP by developing and validating a model that uses PFP components to predict the frailty index (FI) in community-dwelling older adults, without the need for predictor dichotomization. METHODS: A sample of 998 community-dwelling older adults (mean [SD], 68 [7] years) participated in this prospective cohort study. Participants completed a multi-domain geriatric screen and a physical fitness assessment from which the count-based PFP and the 36-item FI were computed. One-year prospective falls and hospitalization rates were also measured. Bayesian beta regression analysis, allowing for nonlinear effects of the non-dichotomized PFP criterion predictors, was used to develop a model for FI ("model-based PFP"). Approximate leave-one-out (LOO) cross-validation was used to examine model overfitting. RESULTS: The model-based PFP showed good calibration with the FI, and it had better out-of-sample predictive performance than the count-based PFP (LOO-R2, 0.35 vs 0.22). In clinical terms, the improvement in prediction (i) translated to improved classification agreement with the FI (Cohen's kw, 0.47 vs 0.36) and (ii) resulted primarily in a 23% (95%CI, 18-28%) net increase in FI-defined "prefrail/frail" participants correctly classified. The model-based PFP showed stronger prognostic performance for predicting falls and hospitalization than did the count-based PFP. CONCLUSION: The developed model-based PFP predicted FI and clinical outcomes more strongly than did the count-based PFP in community-dwelling older adults. By not requiring predictor cut-points, the model-based PFP potentially facilitates usage and feasibility. Future validation studies should aim to obtain clear evidence on the benefits of this approach.

Associations of height, weight, and body mass index with handgrip strength: A Bayesian comparison in older adults.

BACKGROUND & AIMS: Handgrip strength is commonly normalized or stratified by body size to define subgroup-specific cut-points and reference limits values. However, it remains unclear which anthropometric variable is most strongly associated with handgrip strength. We aimed to, in older adults with no self-reported mobility limitations, determine whether height, weight, and body mass index (BMI) were meaningfully associated with handgrip strength. METHODS: This cross-sectional study included community-dwelling ambulant participants, and we identified 775 older adults who reported no difficulty walking 100 m, climbing stairs, and rising from the chair. Handgrip strength was measured with a digital dynamometer. Bayesian linear regression was used to estimate the probabilities that the positive associations of height, weight, and BMI with handgrip strength exceeded 0 kg (the null value) and 2.5 kg (the clinically meaningful threshold value). RESULTS: Mean handgrip strength was 22.1 kg (SD, 4) for women and 32.9 kg (SD, 6) for men. Body height, weight, and BMI had >99.9% probabilities of a positive association with handgrip strength; however, the associations of per interquartile increase in body weight and BMI with handgrip strength had low probabilities (<5%) of exceeding the clinically meaningful threshold of 2.5 kg. In contrast, body height had the highest probability (99.6%) of a clinically meaningful association with handgrip strength: adjusting for age and gender, handgrip strength was 3.2 kg (95% CrI, 2.7 to 3.8) greater in older adults 1.61 m tall than in older adults 1.51 m tall. CONCLUSIONS: In a large sample of mobile-intact older adults, handgrip strength differed meaningfully by body height. Although requiring validation, our findings suggest that future efforts should be directed at normalizing handgrip strength by body height to better define subgroup-specific handgrip weakness. A web-based application (https://sghpt.shinyapps.io/ippts/) was created to allow interactive exploration of predicted values and reference limits of age-, gender-, and height-subgroups.

Estimating cutpoints of gait speed and sit-to-stand test values for self-reported mobility limitations in a cohort of community-dwelling older adults from Singapore: comparing receiver operating characteristic (ROC) analysis with adjusted predictive modelling.

OBJECTIVES: Clinical interpretability of the gait speed and 5-times sit-to-stand (5-STS) tests is commonly established by comparing older adults with and without self-reported mobility limitations (SRML) on gait speed and 5-STS performance, and estimating clinical cutpoints for SRML using the receiver operating characteristics (ROC) method. Accumulating evidence, however, suggests that the adjusted predictive modeling (APM) method may be more appropriate to estimate these interpretational cutpoints. Thus, we aimed to compare, in community-dwelling older adults, gait speed and 5-STS cutpoints estimated using the ROC and APM methods. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: This study analyzed data from 955 community-dwelling independently walking older adults (73%women) aged ≥60 years (mean, 68; range, 60-88). METHODS: Participants completed the 10-metre gait speed and 5-STS tests. Participants were classified as having SRML if they responded "Yes" to either of the 2 questions regarding walking and stair climbing difficulty. Cutpoints for SRML and its component questions were estimated using ROC analysis with Youden criterion and the APM method. RESULTS: The proportions of participants with self-reported walking difficulty, self-reported stair climbing difficulty, and SRML were 10%, 19%, and 22%, respectively. Gait speed and 5-STS time were moderately correlated with each other (r=-0.56) and with the self-reported measures (absolute r-values, 0.39-0.44). ROC-based gait speed cutpoints were 0.14 to 0.16 m/s greater than APM-based cutpoints (P < 0.05) whilst ROC-based 5-STS time cutpoints were 0.8 to 3.3 s lower than APM-based cutpoints (P < 0.05 for walking difficulty). Compared with ROC-based cutpoints, APM-based cutptoints were more precise and they varied monotonically with self-reported walking difficulty, self-reported stair climbing difficulty, and SRML. CONCLUSIONS AND IMPLICATIONS: In a sample of 955 older adults, our findings of precise and biologically plausible gait speed and 5-STS cutpoints for SRML estimated using the APM method indicate that this promising method could potentially complement or even replace traditional ROC methods.

Screening accuracy of percentage predicted gait speed for prefrailty/frailty in community-dwelling older adults.

AIM: In order to account for the variability in gait speed due to demographic factors, an observed gait speed value can be compared with its predicted value based on age, sex, and body height (observed gait speed divided by predicted gait speed, termed "GS%predicted" henceforth). This study aimed to examine the screening accuracy of an optimal GS%predicted threshold for prefrailty/frailty. METHODS: This cross-sectional study included 998 community-dwelling ambulant participants aged >50 years (mean age = 68 years). Participants completed a multi-domain geriatric screen and a physical fitness assessment, from which the 10-m habitual gait speed, GS%predicted, Physical Frailty Phenotype (PFP) index, and 36-item Frailty Index (FI) were computed. RESULTS: Based on the FI, ~49% of participants had pre-frailty or frailty. The optimal threshold of GS%predicted (0.93) had greater screening accuracy than the 1.0 m/s fixed threshold for gait speed (AUC, 0.65 vs. 0.60; DeLong's P < 0.001). Replacing gait speed with GS%predicted in the PFP improved its overall discrimination (AUC, 0.70 vs. 0.67 of original PFP; DeLong's P < 0.001). CONCLUSIONS: Defining a "slow" gait speed by a GS%predicted value of <0.93 provided greater screening accuracy than the traditional 1.0 m/s threshold for gait speed. Our results also support the use of GS%predicted-derived PFP to identify older adults at risk of prefrailty/frailty. Geriatr Gerontol Int 2022; 22: 575-580.

Reference Ranges for Gait Speed and Sit-to-Stand Performance in a Cohort of Mobility-Intact Community-Dwelling Older Adults From Singapore.

OBJECTIVES: Slow gait speed and sit-to-stand performance are associated with adverse clinical outcomes in older adults. Identifying older adults with functional performance "below norms" is the first step toward prevention. We aimed to (1) examine the associations of age, body height, and gender with gait speed and sit-to-stand performance and (2) develop subgroup-specific reference ranges in older adults with no self-reported mobility limitations. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: This study analyzed data from 775 community-dwelling older adults who reported no difficulty walking 100 m, climbing stairs, and rising from the chair. METHODS: Gait speed and sit-to-stand performance were measured by the 10-m gait speed test and 5-times sit-to-stand test, respectively. Bayesian linear regression was used to derive 95% reference ranges for gait speed and sit-to-stand performance, defined by different levels of age, body height, and gender. RESULTS: Overall, 95% reference range was 0.89-1.79 m/s for habitual gait speed and 7.4-27.9 stands/30 s for sit-to-stand pace. Age had the highest posterior probability (>99%) of a meaningful association with both functional outcomes. Additionally, height was strongly associated with gait speed: a 10-cm increase in height was associated with 0.07 m/s (95% credible interval, 0.05-0.10) faster gait speed. For sit-to-stand test, the lower 95% reference range limits tended to be similar across gender and gender-specific height subgroups, owing to the associations of faster sit-to-stand pace with shorter height and male gender. Because extensive tables of reference ranges are impractical, a web-based application (https://sghpt.shinyapps.io/ippts/) is created to provide subgroup-specific reference ranges. CONCLUSIONS AND IMPLICATIONS: In a large sample of mobile-intact older adults, reference ranges for gait speed and sit-to-stand performance differed meaningfully by age. Furthermore, gait speed was stature dependent. Although requiring validation, our findings may be used to define subgroup-specific "below-range" values and to complement existing universal clinical cut points for gait speed and sit-to-stand performance.