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

A systematic review of predictive accuracy via c-statistic of preoperative frailty tests for extended length of stay, post-operative complications, and mortality

Frailty, as an age-related syndrome of reduced physiological reserve, contributes significantly to post-operative outcomes. With the aging population, frailty poses a significant threat to patients and health systems. Since 2012, preoperative frailty assessment has been recommended, yet its implementation has been inhibited by the vast number of frailty tests and lack of consensus. Since the anesthesiologist is the best placed for perioperative care, an anesthesia-tailored preoperative frailty test must be simple, quick, universally applicable to all surgeries, accurate, and ideally available in an app or online form. This systematic review attempted to rank frailty tests by predictive accuracy using the c-statistic in the outcomes of extended length of stay, 3-month post-operative complications, and 3-month mortality, as well as feasibility outcomes including time to completion, equipment and training requirements, cost, and database compatibility. Presenting findings of all frailty tests as a future reference for anesthesiologists, Clinical Frailty Scale was found to have the best combination of accuracy and feasibility for mortality with speed of completion and phone app availability; Edmonton Frailty Scale had the best accuracy for post-operative complications with opportunity for self-reporting. Finally, extended length of stay had too little data for recommendation of a frailty test. This review also demonstrated the need for changing research emphasis from odds ratios to metrics that measure the accuracy of a test itself, such as the c-statistic.

"The Big Three" of geriatrics: A review of perioperative cognitive impairment, frailty and malnutrition

Cognitive impairment, frailty, and malnutrition are three of the most impactful pathologies facing an aging population, having dramatic effects on morbidity and mortality across nearly all facets of medical care and intervention. By 2050, the World Health Organization estimates that the population of individuals over the age of sixty worldwide will nearly double, and the public health toll of these demographic changes cannot be understated. With these changing demographics comes a need for a sharpened focus on the care and management of this vulnerable population. The average patient presenting for surgery is getting older, and this necessitates that clinicians understand the implications of these pathologies for both their immediate medical care needs and for appropriate procedural selection and prognostication of surgical outcomes. We believe it is incumbent on clinicians to consider the frailty, nutritional status, and cognitive function of each individual patient when offering a surgical intervention, as well as consider interventions that may delay the progression of these pathologies. Unfortunately, despite excellent evidence supporting things like routine pre-operative frailty screening and nutritional optimization, many interventions that would specifically benefit this population still have not been integrated into routine practice. In this review, we will synthesize the existing literature on these topics to provide a pragmatic approach and understanding for anesthesiologists and intensivists faced with this complex population.

Is Frailty a Good Predictor of Postoperative Complications in Elective Abdominal Surgery?-A Single-Center, Prospective, Observational Study

BACKGROUND

Despite the common occurrence of postoperative complications in patients with frailty syndrome, the nature and severity of this relationship remains unclear. We aimed to assess the association of frailty with possible postoperative complications after elective, abdominal surgery in participants of a single-centre prospective study in relation to other risk classification methods.

METHODS

Frailty was assessed preoperatively using the Edmonton Frail Scale (EFS), Modified Frailty Index (mFI) and Clinical Frailty Scale (CFS). Perioperative risk was assessed using the American Society of Anesthesiology Physical Status (ASA PS), Operative Severity Score (OSS) and Surgical Mortality Probability Model (S-MPM).

RESULTS

The frailty scores failed to predict in-hospital complications. The values of AUCs for in-hospital complications ranged between 0.5 and 0.6 and were statistically nonsignificant. The perioperative risk measuring system performance in ROC analysis was satisfactory with AUC ranging from 0.63 for OSS to 0.65 for S-MPM (p < 0.05 for each).

CONCLUSIONS

The analysed frailty rating scales proved to be poor predictors of postoperative complications in the studied population. Scales assessing perioperative risk performed better. Further studies are needed to obtain optimal predictive tools in senior patients undergoing surgery.

Why are frailty indices not used systematically during preoperative spine consultations?

INTRODUCTION

Frailty indices are highly predictive of major medical and mechanical complications, lengths of hospital stay, and mortality rates after spine procedures. However, several barriers limit the extent to which spine surgeons employ these indices. The main purposes of the current study were to assess the use of frailty indices by Latin-American spine surgeons and identify the main barriers perceived to restrict their clinical application.

METHODS

For this cross-sectional survey, a questionnaire evaluating the demographic characteristics of participating surgeons and their utilization of frailty indices were created in Google form and sent by e-mail to every registered member of AO Spine Latin America between October and November 2020.

RESULTS

Of the 1047 surgeons sent the survey, 293 responded (response rate=28%). Half of the surgeons (51.7%) said they were unfamiliar with the terms ¨frailty´ and ¨frailty index", while 70.3% claimed not to use any frailty scale during their pre-operative assessments. The most frequently utilized index was the modified Frailty Index (mFI) (18%). The most important perceived barrier was the excessive amount of time required to calculate each patient's frailty score. Ninety-two percent of the spine surgeons felt sure that these scores could influence their therapeutic decisions, while 91% desired an easier-to-use risk-prevention scale.

CONCLUSION

The main perceived barriers restricting the use of frailty indices were the time required to complete them, lack of index validation, and need for specific instruments to calculate the index score.

Comparison of Electronic Frailty Metrics for Prediction of Adverse Outcomes of Abdominal Surgery

Importance

Electronic frailty metrics have been developed for automated frailty assessment and include the Hospital Frailty Risk Score (HFRS), the Electronic Frailty Index (eFI), the 5-Factor Modified Frailty Index (mFI-5), and the Risk Analysis Index (RAI). Despite substantial differences in their construction, these 4 electronic frailty metrics have not been rigorously compared within a surgical population.

Objective

To characterize the associations between 4 electronic frailty metrics and to measure their predictive value for adverse surgical outcomes.

Design, Setting, and Participants

This retrospective cohort study used electronic health record data from patients who underwent abdominal surgery from January 1, 2010, to December 31, 2020, at 20 medical centers within Kaiser Permanente Northern California (KPNC). Participants included adults older than 50 years who underwent abdominal surgical procedures at KPNC from 2010 to 2020 that were sampled for reporting to the National Surgical Quality Improvement Program.

Main Outcomes and Measures

Pearson correlation coefficients between electronic frailty metrics and area under the receiver operating characteristic curve (AUROC) of univariate models and multivariate preoperative risk models for 30-day mortality, readmission, and morbidity, which was defined as a composite of mortality and major postoperative complications.

Results

Within the cohort of 37 186 patients, mean (SD) age, 67.9 (female, 19 127 [51.4%]), correlations between pairs of metrics ranged from 0.19 (95% CI, 0.18- 0.20) for mFI-5 and RAI 0.69 (95% CI, 0.68-0.70). Only 1085 of 37 186 (2.9%) were classified as frail based on all 4 metrics. In univariate models for morbidity, HFRS demonstrated higher predictive discrimination (AUROC, 0.71; 95% CI, 0.70-0.72) than eFI (AUROC, 0.64; 95% CI, 0.63-0.65), mFI-5 (AUROC, 0.58; 95% CI, 0.57-0.59), and RAI (AUROC, 0.57; 95% CI, 0.57-0.58). The predictive discrimination of multivariate models with age, sex, comorbidity burden, and procedure characteristics for all 3 adverse surgical outcomes improved by including HFRS into the models.

Conclusions and Relevance

In this cohort study, the 4 electronic frailty metrics demonstrated heterogeneous correlation and classified distinct groups of surgical patients as frail. However, HFRS demonstrated the highest predictive value for adverse surgical outcomes.

Frailty and Function in Heart Failure: Predictors of 30-Day Hospital Readmission?

BACKGROUND AND PURPOSE

Although there have been decreases noted in 30-day readmission rates for persons with heart failure since enactment of the Hospital Readmissions Reduction Program, costs related to heart failure readmissions remain high. Consequently, there is a need to better identify persons with heart failure who are at risk for 30-day hospital readmission. Therefore, this study aimed to compare the ability of measures of function and frailty to predict 30-day hospital readmissions for adults 65 years and older with heart failure.

METHODS

Secondary data analysis using the 2011 National Health and Aging Trends Study analysis merged with Medicare claims data. Logistic regression modeling was used to compare the ability of function (Short Physical Performance Battery) and frailty (Fried's Physical Frailty Phenotype) to predict 30-day readmission. Receiver operating characteristic curves were constructed to examine the ability of function and frailty to identify those who were readmitted.

RESULTS AND DISCUSSION

Frailty and function demonstrated comparable ability to predict 30-day readmissions (R2 = 0.087 and R2 = 0.087, respectively). Neither measure identified persons at risk for readmission (AUCSPPB = 0.608; AUCPFP = 0.587).

CONCLUSIONS

Functional assessment demonstrated comparable ability to predict 30-day readmissions in persons with heart failure compared with frailty. However, neither measure was able to identify persons at high risk for readmission. Although frailty status is emphasized in research for older adults with heart failure, functional status is an important patient-level factor associated with readmission.

Comparing the Performance of Different Instruments for Diagnosing Frailty and Predicting Adverse Outcomes among Elderly Patients with Gastric Cancer

OBJECTIVES

To examine the diagnostic performance of the Tilburg Frailty Indicator (TFI), 11-factor modified frailty index (mFI-11), and 5-factor modified frailty index (mFI-5) for frailty defined by Frailty Phenotype (FP), as well as to compare the predictive ability of TFI, mFI-11, and mFI-5 for adverse outcomes in hospital among elderly patients undergoing gastric cancer surgery.

DESIGN

A prospective cohort study.

SETTING

Hospitalization setting, Nanjing, China.

PARTICIPANTS

We recruited 259 elderly patients undergoing gastric cancer surgery from a tertiary hospital.

MEASUREMENTS

Frailty was assessed by the FP, TFI, mFI-11, and mFI-5 before surgery, respectively. The receiver operating characteristic (ROC) curves were plotted to compared the diagnostic performance of TFI, mFI-11, and mFI-5 using FP as the reference. ROC curves were used to examine the performance of TFI, mFI-11, and mFI-5 in predicting adverse outcomes. The area under the curve (AUC)>0.70 was regarded as an indicator of good performance.

RESULTS

The prevalence of frailty ranged from 8.5% (mFI-11) to 45.9% (TFI). The AUCs of TFI (AUC: 0.764, p<0.001) was significantly greater than that of mFI-11 (AUC: 0.600, p=0.033) and mFI-5 (AUC: 0.600, p=0.0311) in the detection of frailty defined by FP, with quite different sensitivity and specificity at their original cutoffs. TFI and mFI-11 both had statistically significant but similarly inadequate predictive accuracy for adverse outcomes in hospital, including total complications (AUCs: 0.618; 0.621), PLOS (AUCs: 0.593; 0.639), increased hospital costs (AUCs: 0.594; 0.624), and hypoproteinemia (AUCs: 0.573; 0.600). For the mFI-5, only the predictive ability for hypoproteinemia was statistically significant, with poor accuracy (AUC: 0.592, p<0.0055).

CONCLUSION

The TFI performed slightly better than mFI-11 and mFI-5 in our study. Moreover, future studies are needed to further determine an optimal frailty instrument with great diagnostic and predictive accuracy.

Improving stamina and mobility with preop walking in surgical patients with frailty traits -OASIS IV: randomized clinical trial study protocol

Background

Frail older surgical patients face more than a two-fold increase in postoperative complications, including myocardial infarction, deep vein thrombosis, pulmonary embolism, pneumonia, ileus, and others. Many of these complications occur because of postoperative loss of stamina and poor mobility. Preoperative exercise may better prepare these vulnerable patients for surgery. We present the protocol for our ongoing randomized trial to assess the impact of a preoperative walking intervention with remote coaching and pedometer on outcomes of stamina (six-minute walk distance- 6MWD) and mobility (postoperative steps) in older adults with frailty traits.

Methods

We will be conducting a randomized clinical trial with a total of 120 patients permitting up to a 33% rate of attrition, to reach a final sample size of 80 (with 40 patients for each study arm). We will include patients who are age 60 or higher, score 4 or greater on the Edmonton Frailty Scale assessment, and will be undergoing a surgical operation that requires a 2 or more night hospital stay to be eligible for our trial. Using block randomization stratified on baseline 6MWD, we will assign patients to wear a pedometer. At the end of three baseline days, an athletic trainer (AT) will provide a daily step count goal reflecting a 10–20% increase from baseline. Subsequently, the AT will call weekly to further titrate the goal or calls more frequently if the patient is not meeting the prescribed goal. Controls will receive general walking advice. Our main outcome is change in 6MWD on postoperative day (POD) 2/3 vs. baseline. We will also collect 6MWD approximately 4 weeks after surgery and daily in-hospital steps.

Conclusion

If changes in a 6MWD and step counts are significantly higher for the intervention group, we believe this will confirm our hypothesis that the intervention leads to decreased loss of stamina and mobility. Once confirmed, we anticipate expanding to multiple centers to assess the interventional impact on clinical endpoints.

Trial registration

The randomized clinical trial was registered on clinicaltrials.gov under the identifier NCT03892187 on March 27, 2019.

Perioperative considerations in nonagenarians

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.

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

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.

Accuracy and Feasibility of Clinically Applied Frailty Instruments before Surgery

Background

A barrier to routine preoperative frailty assessment is the large number of frailty instruments described. Previous systematic reviews estimate the association of frailty with outcomes, but none have evaluated outcomes at the individual instrument level or specific to clinical assessment of frailty, which must combine accuracy with feasibility to support clinical practice.

Methods

The authors conducted a preregistered systematic review (CRD42019107551) of studies prospectively applying a frailty instrument in a clinical setting before surgery. Medline, Excerpta Medica Database, Cochrane Library and the Comprehensive Index to Nursing and Allied Health Literature, and Cochrane databases were searched using a peer-reviewed strategy. All stages of the review were completed in duplicate. The primary outcome was mortality and secondary outcomes reflected routinely collected and patient-centered measures; feasibility measures were also collected. Effect estimates were pooled using random-effects models or narratively synthesized. Risk of bias was assessed.

Results

Seventy studies were included; 45 contributed to meta-analyses. Frailty was defined using 35 different instruments; five were meta-analyzed, with the Fried Phenotype having the largest number of studies. Most strongly associated with: mortality and nonfavorable discharge was the Clinical Frailty Scale (odds ratio, 4.89; 95% CI, 1.83 to 13.05 and odds ratio, 6.31; 95% CI, 4.00 to 9.94, respectively); complications was associated with the Edmonton Frail Scale (odds ratio, 2.93; 95% CI, 1.52 to 5.65); and delirium was associated with the Frailty Phenotype (odds ratio, 3.79; 95% CI, 1.75 to 8.22). The Clinical Frailty Scale had the highest reported measures of feasibility.

Conclusions

Clinicians should consider accuracy and feasibility when choosing a frailty instrument. Strong evidence in both domains support the Clinical Frailty Scale, while the Fried Phenotype may require a trade-off of accuracy with lower feasibility.

Editor’s Perspective

What We Already Know about This Topic

What This Article Tells Us That Is New

Reducing Hospitalizations and Emergency Department Visits in Patients With Venous Thromboembolism Using a Multicomponent Care Transition Intervention

Preventing utilization of hospital and emergency department after diagnosis of venous thromboembolism is a complex problem. The objective of this study is to assess the impact of a care transition intervention on hospitalizations and emergency department visits after venous thromboembolism. We randomized adults diagnosed with a new episode of venous thromboembolism to usual care or a multicomponent intervention that included a home pharmacist visit in the week after randomization (typically occurring at time of discharge), illustrated medication instructions distributed during home visit, and a follow-up phone call with an anticoagulation expert scheduled for 8 to 30 days from time of randomization. Through physician chart review of the 90 days following randomization, we measured the incidence rate of hospital and emergency department visits for each group and their ratio. We also determined which visits were related to recurrent venous thromboembolism, bleeding, or anticoagulation and which where preventable. We enrolled 77 intervention and 85 control patients. The incidence rate was 4.50 versus 6.01 visits per 1000 patient days in the intervention versus control group (incidence rate ratio = 0.71; 95% confidence interval = 0.40-1.27). Most visits in the control group were not related to venous thromboembolism or bleeding (21%) and of those that were, most were not preventable (25%). The adjusted incidence rate ratio for the intervention was 1.05 (95% confidence interval = 0.57-1.91). Our patients had a significant number of hospital and emergency department visits after diagnosis. Most visits were not related to recurrent venous thromboembolism or bleeding and of those that were, most were not preventable. Our multicomponent intervention did not decrease hospitalizations and emergency department visits.

Physical Function and Frailty for Predicting Adverse Outcomes in Older Primary Care Patients

OBJECTIVE

To explore the predictive ability of the Short Physical Performance Battery (SPPB), Late Life Function and Disability Instrument-Function component (LLFDI-function) and frailty phenotype, for falls, hospitalizations, emergency department (ED) visits, and low self-rated health (SRH) over 1 and 2 years in older adults.

DESIGN

Secondary analysis of data from a longitudinal study, the Boston Rehabilitative Impairment Study of the Elderly.

SETTING

Primary care.

PARTICIPANTS

Adults 65 years and older at risk for disability who completed ≥1 follow-up call (N=391).

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

We computed separate logistic regression models using the SPPB, LLFDI-function, and frailty phenotype as independent variables and falls, hospitalizations, ED visits, and SRH over 1 and 2 years as dependent variables. Receiver operating characteristic curves were constructed and the areas under the curves calculated.

RESULTS

Participants had a mean age of 76.5±7.1 years. The SPPB, LLFDI-function, and frailty phenotype all predicted hospitalizations and low SRH over a 1- and 2-year timeframe (odds ratio [OR] min-max, 1.35-1.51 and 1.67-3.07, respectively). Over 2 years, the SPPB predicted ED visits (OR, 1.28), and the LLFDI-function predicted falls (OR, 1.31). The LLFDI-function predicted low SRH better than the frailty phenotype over 1 year. There were no differences between the measures for any of the other outcomes.

CONCLUSIONS

The SPPB, LLFDI-function, and frailty phenotype had similar accuracy for predicting falls, hospitalizations, ED visits, and low SRH over 1 and 2 years among older primary care patients at risk for disability. As a result, when considering the optimal screening tool for older adults, the choice between a measure of function and frailty may ultimately depend on clinical preference and context.

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

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.

Current situation of frailty screening tools for older adults

Frailty is a geriatric syndrome associated with adverse outcomes such as falls, disability, and mortality. Frailty is common and contributes to rising health care costs. Early screening and timely tailored intervention may effectively prevent or delay the adverse outcomes in older adults. Studies on frailty and its specific measurement tools are increasing in number, but the debate on the screening instruments remains. Currently, self-reported screening tools can identify frailty and predict the risk of adverse outcomes in older adults. Because they are easy to use and quickly provide information, self-reported frailty screening tools have significant implication in primary care settings and clinics. We reviewed the frailty screening instruments in older adults and proposed a two-step pathway for frailty identification, and to manage declines in intrinsic capacity as well as boost resilience.

Simple Physical Activity Index Predicts Prognosis in Older Adults: Beijing Longitudinal Study of Aging

OBJECTIVE

Frailty, which involves low physical activity (PA), is as a well-established factor of increased risk of hospitalization, disability, and mortality. To date, there are no specific tools to assess PA among Chinese elderly. As part of the Beijing Longitudinal Study of Aging (BLSA), we aimed to develop the BLSA Leisure-Time Physical Activity Questionnaire (BLSA-PAQ) and assess its prediction of mortality.

DESIGN

Longitudinal study.

SETTING

Community.

PARTICIPANTS

1810 Chinese older adults completed the BLSA-PAQ questionnaire.

MEASUREMENTS

BLSA-PAQ questionnaire containing four items: walking, outdoor chores, low-intensity exercise, and moderate-intensity exercise. Physical function was assessed through the balance test, chair-stand test, and the activities of daily living (ADL), and instrumental activities of daily living (IADL). Frailty was evaluated using a modified frailty phenotype and frailty index.

RESULTS

The following equation was obtained based on the 8-year mortality for the four BLSA-PAQ components: BLSA-PAQ index (BLSA-PAQ total score) = Walking score + Outdoor chores score + 2 × (low-intensity exercise score) + 3 × (moderate-intensity exercise score). The BLSA-PAQ index decreased with age, and was negatively related to modified frailty phenotype score and frailty index. Low PA and pre-low PA statuses were associated with poorer results in the balance and chair-stand tests, ADL dependency, IADL dependency, and frailty. After adjusting for age and gender, the 8-year mortality HRs were 1.453 (95% CI, 1.166-1.811) and 2.358 (95% CI, 1.856-2.995) for low PA and pre-low PA, respectively. Low PA defined by the BLSA-PAQ index was associated with frailty, disability, worse physical function, and higher mortality.

CONCLUSION

The BLSA-PAQ seems to be a reliable tool to measure PA in Chinese older adults. Further studies are needed to confirm these findings and validate the use of the BLSA-PAQ for frailty assessments of older adults.