Physical Function and Frailty for Predicting Adverse Outcomes in Older Primary Care Patients.
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ABSTRACT:
SUBMITTER: O'Hoski S
PROVIDER: S-EPMC7103496 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThis study tested the hypothesis that sarcopenia and its constituent components, reduced lean muscle mass and impaired motor function, are associated with reduced survival and increased risk of incident disabilities.Methods1466 community-dwelling older adults underwent assessment of muscle mass with bioelectrical impedance analysis (BIA), grip strength, gait speed and other components of physical frailty and annual self-report assessments of disability. We used Cox proportional hazards models that controlled for age, sex, race, education and height to examine the associations of a continuous sarcopenia metric with the hazard of death and incident disabilities.ResultsMean baseline age was about 80 years old and follow-up was 5.5 years. In a proportional hazards model controlling for age, sex, race, education and baseline sarcopenia, each 1-SD higher score on a continuous sarcopenia scale was associated with lower hazards of death (HR 0.70, 95%CI [0.62, 0.78]), incident IADL (HR 0.80,95%CI [0.70, 0.93]), incident ADL disability (HR 0.80 95%CI [71, 91]) and incident mobility disability (HR 0.81, 95%CI [0.70, 0.93]). Further analyses suggest that grip strength and gait speed rather than muscle mass drive the associations with all four adverse health outcomes. Similar findings were observed when controlling for additional measures used to assess physical frailty including BMI, fatigue and physical activity.ConclusionsMotor function is the primary driver of the associations of sarcopenia and physical frailty with diverse adverse health outcomes. Further work is needed to identify other facets of muscle structure and motor function which together can identify adults at risk for specific adverse health outcomes.
| S-EPMC7853482 | biostudies-literature
Project description:(1) Objectives: We aimed to identify clusters of physical frailty and cognitive impairment in a population of older primary care patients and correlate these clusters with their associated comorbidities. (2) Methods: We used a latent class analysis (LCA) as the clustering technique to separate different stages of mild cognitive impairment (MCI) and physical frailty into clusters; the differences were assessed by using a multinomial logistic regression model. (3) Results: Four clusters (latent classes) were identified: (1) highly functional (the mean and SD of the "frailty" test 0.58 ± 0.72 and the Mini-Mental State Examination (MMSE) test 27.42 ± 1.5), (2) cognitive impairment (0.97 ± 0.78 and 21.94 ± 1.95), (3) cognitive frailty (3.48 ± 1.12 and 19.14 ± 2.30), and (4) physical frailty (3.61 ± 0.77 and 24.89 ± 1.81). (4) Discussion: The comorbidity patterns distinguishing the clusters depend on the degree of development of cardiometabolic disorders in combination with advancing age. The physical frailty phenotype is likely to exist separately from the cognitive frailty phenotype and includes common musculoskeletal diseases.
| S-EPMC8304880 | biostudies-literature
Project description:BACKGROUND/OBJECTIVE:Current preoperative assessment tools such as the American College of Surgeons Surgical Risk Calculator (ACS Calculator) are suboptimal for evaluating older adults. The objective was to evaluate and compare the performance of the ACS Calculator for predicting risk of serious postoperative complications with the addition of self-reported physical function versus a frailty score. DESIGN:Prospective cohort. SETTING:Two tertiary care academic medical centers in Massachusetts. PARTICIPANTS:Individuals aged 65 and older undergoing any surgery with a risk of serious complication of 5% or greater (N = 403). MEASUREMENTS:We measured self-reported physical function using the Late-Life Function and Disability Instrument (LLFDI FUNCTION) and frailty phenotype (FP), which has a score ranging from 0 to 5 based on slow gait speed, weak handgrip, exhaustion, weight loss, or low activity. Using c-statistic and net classification improvement (NRI), we then analyzed capability of LLFDI-FUNCTION versus FP to improve the ACS Calculator for predicting an adverse postoperative course (serious complication, discharge to nursing home, readmission, death within 30 days of surgery). Increase in c-statistic and net reclassification improvement (NRI) for LLFDI-FUNCTION versus FP in addition to the ACS Calculator for predicting an adverse postoperative course (serious complication, discharge to nursing home, readmission, death within 30 days of surgery) RESULTS: Over 30 days, 26% of participants developed an adverse postoperative course. The increase in c-statistic for the ACS Calculator (baseline value 0.645) was slightly greater with LLFDI-FUNCTION (0.076) than with FP (0.058), with a bootstrapped difference in c-statistic of 0.005 (95% confidence interval = 0.002-0.007). NRI was also better with LLFDI-FUNCTION. CONCLUSION:The LLFDI-FUNCTION predicted postoperative complications slightly better than the FP. Further studies are needed to confirm these findings and validate the use of the LLFDI-FUNCTION with the ACS Calculator for preoperative assessments of older adults.
| S-EPMC5681367 | biostudies-literature
Project description:BackgroundDiagnosis and screening of frailty, a condition characterized by an increased vulnerability to adverse outcomes of COVID-19, has emerged as an essential clinical tool which is strongly recommended by healthcare providers concerned with hospitalized elderly population. The data showing the role of frailty in patients infected with COVID-19 is needed.MethodsThis was a nationwide cohort study conducted at all hospitals in Turkey. All COVID-19 hospitalized patients (? 65 years) were included. Patients who were alive and not discharged up to July 20, 2020, were excluded. The frailty was assessed by using the "Hospital Frailty Risk Score" (HFRS). Patients were classified into three risk groups of frailty based on previously validated cut points as low (<5 points), intermediate (5-15 points), and high (>15 points). Additionally, patients who had the HFRS of ?5 were defined as frail. The primary outcome was in-hospital mortality rates by frailty group.ResultsBetween March 11, 2020, and June 22, 2020, a total of 18,234 COVID-19 patients from all of 81 provinces of Turkey were included. Totally, 12,295 (67.4%) patients were defined as frail (HFRS of >5) of which 2,801 (15.4%) patients were categorized in the highest level of frailty (HFRS of >15). Observed in-hospital mortality rates were 697 (12.0%), 1,751 (18.2%) and 867 (31.0%) in low, intermediate and high hospital frailty risk, respectively (p<0.001). Compared with low HFRS (<5), the adjusted odds ratios for in-hospital mortality were 1.482 (1.334-1.646) for intermediate HFRS (5-15) and 2.084; 95% CI, 1.799-2.413 for high HFRS (>15).ConclusionsAs a claims-based frailty model, the HFRS provides clinicians and health systems, a standardized tool for an effective detection and grading of frailty in patients in COVID-19. A frailty-based tailored management of the older population may provide a more accurate risk categorization for both therapeutic and preventive strategies.
| S-EPMC7521439 | biostudies-literature
Project description:Background Intrinsic capacity (IC) and frailty are complementary in advancing disability prevention through maintaining functionality. Objectives We examined the relationship between IC and frailty status at baseline and 1-year, and evaluated if IC decline predicts frailty onset among robust older adults. The secondary objectives investigated associations between IC, physical fitness and health-related outcomes. Design Prospective cohort study. Setting Community-based assessments. Participants Older adults aged>55 years, who were independent in ambulation (walking aids permitted). Measurements 5 domains of IC were assessed at baseline: locomotion (Short Physical Performance Battery, 6-minute walk test), vitality (nutritional status, muscle mass), sensory (self-reported hearing and vision), cognition (self-reported memory, age- and education adjusted cognitive performance), psychological (Geriatric Depression Scale-15, self-reported anxiety/depression). Composite IC (0–10) was calculated, with higher scores representing greater IC. Frailty status was based on modified Fried criteria, with frailty progression defined as incremental Fried score at 1-year. Results 809 participants (67.6+6.8 years) had complete data for all 5 IC domains. 489 (60.4%) participants were robust but only 213 (26.3%) had no decline in any IC domain. Pre-frail and frail participants were more likely to exhibit decline in all 5 IC domains (p<0.05), with decremental composite IC [9 (8–9), 8 (6–9), 5.5 (4–7.5), p<0.001] across robust, prefrail and frail. IC was significantly associated with fitness performance, independent of age and gender. Higher composite IC reduced risk for frailty progression (OR=0.62, 95% CI 0.48–0.80), and reduced frailty onset among robust older adults (OR=0.53, 95% CI 0.37–0.77), independent of age, comorbidities and social vulnerability. Participants with higher IC were less likely to experience health deterioration (OR=0.70, 95% CI 0.58–0.83), falls (OR=0.76, 95% CI 0.65–0.90) and functional decline (OR=0.64, 95% CI 0.50–0.83) at 1-year. Conclusion Declining IC may present before frailty becomes clinically manifest, increasing risk for poor outcomes. Monitoring of IC domains potentially facilitates personalized interventions to avoid progressive frailty. Electronic Supplementary Material Supplementary material is available for this article at 10.14283/jfa.2022.28 and is accessible for authorized users.
| S-EPMC8966852 | biostudies-literature
Project description:BackgroundPhysical frailty is a powerful tool for identifying nondisabled individuals at high risk of adverse outcomes. The extent to which cognitive impairment in those without dementia adds value to physical frailty in detecting high-risk individuals remains unclear.ObjectivesTo estimate the effects of combining physical frailty and cognitive impairment without dementia (CIND) on the risk of basic activities of daily living (ADL) dependence and death over 8 years.DesignProspective cohort study.SettingThe Health and Retirement Study (HRS).ParticipantsA total of 7338 community-dwelling people, 65 years or older, without dementia and ADL dependence at baseline (2006-2008). Follow-up assessments occurred every 2 years until 2014.MeasurementsThe five components of the Cardiovascular Health Study defined physical frailty. A well-validated HRS method, including verbal recall, series of subtractions, and backward count task, assessed cognition. Primary outcomes were time to ADL dependence and death. Hazard models, considering death as a competing risk, associated physical frailty and CIND with outcomes after adjusting for sociodemographics, comorbidities, depression, and smoking status.ResultsThe prevalence of physical frailty was 15%; CIND, 19%; and both deficits, 5%. In unadjusted and adjusted analyses, combining these factors identified older adults at an escalating risk for ADL dependence (no deficit = 14% [reference group]; only CIND = 26%, sub-hazard ratio [sHR] = 1.5, 95% confidence interval [CI] = 1.3-1.8; only frail = 33%, sHR = 1.7, 95% CI = 1.4-2.0; both deficits = 46%, sHR = 2.0, 95%CI = 1.6-2.6) and death (no deficit = 21%; only CIND = 41%, HR = 1.6, 95% CI = 1.4-1.9; only frail = 56%, HR = 2.2, 95% CI = 1.7-2.7; both deficits = 66%, HR = 2.6, 95% CI = 2.0-3.3) over 8-year follow-up. Adding the cognitive measure to models that already included physical frailty alone increased accuracy in identifying those at higher risk of ADL dependence (Harrell's concordance [C], 0.74 vs 0.71; P < .001) and death (Harrell's C, 0.70 vs 0.67; P < .001).ConclusionPhysical frailty and CIND are independent predictors of incident disability and death. Because together physical frailty and CIND identify vulnerable older adults better, optimal risk assessment should supplement measures of physical frailty with measures of cognitive function. J Am Geriatr Soc 67:477-483, 2019.
| S-EPMC6510389 | biostudies-literature
Project description:Older patients reaching ESRD have a higher risk of adverse health outcomes. We aimed to determine the association of functional and cognitive impairment and frailty with adverse health outcomes in patients reaching ESRD. Understanding these associations could ultimately lead to prediction models to guide tailored treatment decisions or preventive interventions.We searched MEDLINE, Embase, Web of Science, CENTRAL, CINAHL, PsycINFO, and COCHRANE for original studies published until February 8, 2016 reporting on the association of functional or cognitive impairment or frailty with adverse health outcome after follow-up in patients reaching ESRD either with or without RRT.Of 7451 identified citations, we included 30 articles that reported on 35 associations. Mean age was >60 years old in 73% of the studies, and geriatric conditions were highly prevalent. Twenty-four studies (80%) reported on functional impairment, seven (23%) reported on cognitive impairment, and four (13%) reported on frailty. Mortality was the main outcome measure in 29 studies (97%), and one study assessed functional status trajectory. In 34 of 35 (97%) associations reported, functional or cognitive impairment or frailty was significantly and independently associated with adverse health outcomes. The majority of studies (83%) were conducted in selected patient populations, mainly patients on incident dialysis.Functional and cognitive impairment and frailty in patients reaching ESRD are highly prevalent and strongly and independently associated with adverse health outcomes, and they may, therefore, be useful for risk stratification. More research into their prognostic value is needed.
| S-EPMC5012494 | biostudies-other
Project description:Most older persons in primary care suffering clinically significant depressive symptoms do not meet criteria for major or minor depression. The authors tested the hypothesis that patients with subsyndromal depression (SSD) would have poorer psychiatric, medical, and functional outcomes at follow-up than nondepressed patients but not as poor as those with minor or major depression. The authors also explored the relative outcomes of three definitions of SSD to determine their relative prognostic value.Prospective observational cohort study.Primary care practices in Monroe County, NY.Four hundred eighty-one primary care patients aged 65 years and older who completed research assessments at intake and at least 1 year of follow-up evaluation.Depression diagnoses and three definitions of SSD were determined by the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, and the 24-item Hamilton Depression Rating Scale. Other validated measures assessed anxiety, cognition, medical burden, and functional status.Patients with SSD had poorer 1-year lagged outcomes than nondepressed subjects in terms of psychiatric symptoms and functional status, often not significantly different than major or minor depression. Two of the SSD definitions identified subjects with poorer psychiatric and functional outcomes than the third SSD definition.Clinicians should be vigilant in caring for patients with SSD, monitoring for persistent, or worsening depressive symptoms including suicidality, anxiety, cognitive impairment, and functional decline. Researchers may use particular SSD definitions to identify individuals at higher risk of poor outcomes, to better understand the relationships of SSD to functional disability, and to test innovative preventive and therapeutic interventions.
| S-EPMC2827819 | biostudies-literature
Project description:ObjectiveThe aim of this study was to measure the relationship between days spent waiting for primary care and health outcomes among patients diagnosed with diabetes, especially among the elderly population.Data sourceSecondary data from VA administrative databases and Medicare claims.Study designThis is a retrospective observational study. Outcome variables include primary care utilization, mortality, heart attack, stroke, and ambulatory-care sensitive condition (ACSC) hospitalization. The main explanatory variable of interest is VA primary care wait time. Negative binomial models predict utilization and stacked logistic regression models predict the probability of experiencing each health outcome. Models are stratified by the presence of a selected health condition and age.Principal findingsLonger wait times were predicted to decrease utilization between 2 and 4 percent. There was no significant relationship between wait times and health outcomes for the overall sample. In stratified analyses, longer waits were associated with undesirable outcomes for those over age 70 with one of the selected health conditions or in certain narrower 5-year age groups, but the overall pattern of results does not indicate a systematic and significant effect.ConclusionsThere was a modest effect of long wait times on primary care utilization but no robust effect of longer wait times on health outcomes. Waiting for care did not significantly compromise long-term health outcomes for veterans with diabetes.
| S-EPMC3447242 | biostudies-literature
Project description:BackgroundMortality prediction models are useful to guide clinical decision-making based on prognosis. The frailty index, which allows prognostication and personalized care planning, has not been directly compared with validated prognostic models.ObjectiveTo compare the discrimination of mortality, disability, falls, and hospitalization between a frailty index and validated prognostic indices.DesignSecondary Analysis of the National Health and Aging Trends Study.ParticipantsSeven thousand thirty-three Medicare beneficiaries 65 years or older.MeasurementsWe measured a deficit-accumulation frailty index, Schonberg index, and Lee index at the 2011 baseline assessment. Primary outcome was mortality at 5 years. Secondary outcomes were decline in activities of daily living (ADL), decline in instrumental activities of daily living (IADL), fall, and hospitalization at 1 year. We used C-statistics to compare discrimination between indices, adjusting for age and sex.ResultsThe study population included 4146 (44.8%) with age ≥ 75 years, with a median frailty index of 0.15 (interquartile range 0.09-0.25). A total of 1385 participants died (14.7%) and 2386 (35.2%) were lost to follow-up. Frailty, Schonberg, and Lee indices predicted mortality similarly: C-statistics (95% confidence interval) were 0.78 (0.77-0.80) for frailty index; 0.79 (0.78-0.81) for Schonberg index; and 0.78 (0.77-0.80) for Lee index. The frailty index had higher C-statistics for decline in ADL function (frailty index, 0.80 [0.78-0.83]; Schonberg, 0.74 [0.72-0.76]; Lee, 0.74 [0.71-0.77]) and falls (frailty index, 0.66 [0.65-0.68]; Schonberg, 0.61 [0.58-0.63]; Lee, 0.61 [0.59-0.63]). C-statistics were similar for decline in IADL function (frailty index, 0.61 [0.59-0.63]; Schonberg, 0.60 [0.59-0.62]; Lee, 0.60 [0.58-0.62]) and hospitalizations (frailty index, 0.68 [0.66-0.70]; Schonberg, 0.68 [0.66-0.69]; Lee, 0.65 [0.63-0.67]).ConclusionsA deficit-accumulation frailty index performs as well as prognostic indices for mortality prediction, and better predicts ADL disability and falls in community-dwelling older adults. Frailty assessment offers a unifying approach to risk stratification for key health outcomes relevant to older adults.
| S-EPMC7210351 | biostudies-literature