Predictive performance of four frailty measures in an older Australian population.

BACKGROUND: There are several different frailty measures available for identifying the frail elderly. However, their predictive performance in an Australian population has not been examined. OBJECTIVE: To examine the predictive performance of four internationally validated frailty measures in an older Australian population. METHODS: A retrospective study in the Australian Longitudinal Study of Ageing (ALSA) with 2,087 participants. Frailty was measured at baseline using frailty phenotype (FP), simplified frailty phenotype (SFP), frailty index (FI) and prognostic frailty score (PFS). Odds ratios (OR) were calculated to measure the association between frailty and outcomes at Wave 3 including mortality, hospitalisation, nursing home admission, fall and a combination of all outcomes. Predictive performance was measured by assessing sensitivity, specificity, positive and negative predictive values (PPV and NPV) and likelihood ratio (LR). Area under the curve (AUC) of dichotomised and the multilevel or continuous model of the measures was examined. RESULTS: Prevalence of frailty varied from 2% up to 49% between the measures. Frailty was significantly associated with an increased risk of any outcome, OR (95% confidence interval) for FP: 1.9 (1.4-2.8), SFP: 3.6 (1.5-8.8), FI: 3.4 (2.7-4.3) and PFS: 2.3 (1.8-2.8). PFS had high sensitivity across all outcomes (sensitivity: 55.2-77.1%). The PPV for any outcome was highest for SFP and FI (70.8 and 69.7%, respectively). Only FI had acceptable accuracy in predicting outcomes, AUC: 0.59-0.70. CONCLUSIONS: Being identified as frail by any of the four measures was associated with an increased risk of outcomes; however, their predictive accuracy varied.

Risk factors predictive of adverse drug events and drug-related falls in aged care residents: secondary analysis from the ReMInDAR trial.

BACKGROUND: Residents of aged-care facilities have high rates of adverse drug events. This study aimed to identify risk factors for adverse drug events in aged-care residents. METHOD: This was a secondary study using data from a multicentre randomised controlled trial. Data from 224 residents for whom there was 6 months of baseline information were analysed. We assessed the risk of adverse drug events and falls (post hoc) in the subsequent 6 months. Adverse events were identified via a key word search of the resident care record and adjudicated by a multidisciplinary panel using a modified version of the Naranjo criteria. Covariates identified through univariable logistic regression, including age, sex, medicines, physical activity, cognition (Montreal Cognitive Assessment), previous adverse events and health service use were included in multivariable models. RESULTS: Overall, 224 residents were included, with a mean age of 86 years; 70% were female. 107 (48%) residents had an adverse drug event during the 6-month follow-up. Falls and bleeding were experienced by 73 (33%) and 28 (13%) residents, respectively. Age (odds ratio [OR] 1.05, 95% confidence interval [CI] 1.01-1.10), weight (OR 1.02, 95% CI 1.002-1.04), previous fall (OR 2.58, 95% CI 1.34-4.98) and sedative or hypnotic medicine use (OR 1.98, 95% CI 1.52-2.60) were associated with increased risk of adverse drug events. Increased cognition (OR 0.89, 95% CI 0.83-0.95) was protective. Risk factors for falls were previous fall (OR 3.27, 95% CI 1.68-6.35) and sedative or hypnotic medicines (OR 3.05, 95% CI 1.14-8.16). Increased cognition (OR 0.88, 95% CI 0.83-0.95) was protective. CONCLUSION: Our results suggest residents with a previous fall, reduced cognition, and prescription of sedative or hypnotic medicines were at higher risk of adverse drug events and should be considered for proactive prevention.

Prevalence and Preventability of Adverse Medicine Events in a Sample of Australian Aged-Care Residents: A Secondary Analysis of Data from the ReMInDAR Trial.

BACKGROUND: Aged care residents are vulnerable to the harmful effects of medicines; however, data on the prevalence and preventability of adverse medicine events in aged care residents are scarce. AIM: To determine the prevalence and preventability of adverse medicine events in Australian aged care residents. METHODS: A secondary analysis of data from the Reducing Medicine-Induced Deterioration and Adverse Reactions (ReMInDAR) trial was conducted. Potential adverse medicine events were identified and independently screened by two research pharmacists to produce a short-list of potential adverse medicine events. An expert clinical panel reviewed each potential adverse medicine to determine the likelihood that the event was medicine related (based on the Naranjo Probability Scale criteria). The clinical panel assessed preventability of medicine-related events using Schumock-Thornton criteria. RESULTS: There were 583 adverse events due to medicines, involving 154 residents (62% of the 248 study participants). There was a median of three medication-related adverse events (interquartile range [IQR] 1-5) per resident over the 12-month follow-up period. The most common medication-related adverse events were falls (56%), bleeding (18%) and bruising (9%). There were 482 (83%) medication-related adverse events that were preventable, most commonly falls (66% of preventable adverse medicine events), bleeding (12%) and dizziness (8%). Of the 248 residents, 133 (54% of the cohort) had at least one preventable adverse medicine event, with a median of 2 (IQR 1-4) preventable adverse medicine events per resident. CONCLUSION: In total, 62% of aged care residents in our study had an adverse medicine event and 54% had a preventable adverse medicine event in a 12-month period.

Medicine-related problems: A recurrent issue among residents living in nursing homes.

Aim: To examine the incidence and nature of medicine-related problems over time experienced by nursing home residents. Method: We analyzed records collected in the Reducing Medicine-Induced Deterioration and Adverse Events (ReMInDAR) trial. The trial pharmacists provided services to reduce medicine-induced deterioration and adverse reactions for residents every 8-weeks over a year. The problems identified by the pharmacists were documented in reports and subsequently classified independently by research pharmacists using the D.O.C.U.M.E.N.T system. The number and type of problems at each service and time to develop a new problem post first session were assessed. All analyses were performed using R software (Version 4.1.1). Results: The cohort was 115 nursing home residents who received 575 services. In the 12-months, a total of 673 medicine-related problems or symptom reports were identified in 112 residents. Most residents (75%) experienced a new medicine-related problem by the fourth month post the first assessment. After the first session, the proportion of residents with a new medicine-related problem or symptom report declined at each repeated pharmacy session (59% at visit 2 vs. 28% at visit 6, p < 0.01). Conclusion: Residents living in nursing homes frequently experience medicine-related problems. Our results suggest clinical pharmacist services performed every 4-months may have the potential to reduce the medicine-related problems in nursing homes.

Analysis of anticholinergic and sedative medicine effects on physical function, cognitive function, appetite and frailty: a cross-sectional study in Australia.

OBJECTIVE: To test the association between use of medicines with anticholinergic or sedative properties and physical function, cognitive function, appetite and frailty. DESIGN, SETTING AND PARTICIPANTS: This cross-sectional study analysed baseline data collected as part of the Australian Longitudinal Study of Ageing, a population-based cohort of 2087 participants aged 65 years or over living in South Australia. MAIN OUTCOME MEASURES: Physical function was measured at baseline using measures including hand grip strength, walking speed, chair stands, activities of daily living and instrumental activities of daily living (IADL). Cognitive function was measured using Mini-Mental State Examination. Appetite was measured using Center for Epidemiologic Studies Depression question 2. Frailty was measured using frailty index. The association between use of anticholinergics or sedatives and physical or cognitive function, appetite, or frailty was assessed using analysis of covariance and ordinal or binary logistic regression. RESULTS: Almost half of the population were using anticholinergics or sedatives (n=954, 45.7%). Use of anticholinergics was significantly associated with poorer grip strength, slower walking speed, poorer IADL and poorer appetite. Use of sedatives was significantly associated with poorer grip strength, slower walking speed and poorer IADL. We found no significant association between medicine use and cognitive function. Users of anticholinergics or sedatives were significantly more likely to be frail compared with non-users. CONCLUSION: Use of medicines with anticholinergic or sedative properties is significantly associated with poorer physical function, poorer appetite and increased frailty. Early identification of signs and symptoms of deterioration associated with medicine use is particularly important in older people so that worsening frailty and subsequent adverse events are prevented.

How common is frailty in older Australians?

AIM: To determine the prevalence of frailty in a cohort of older Australians. METHODS: Frailty status of the 2087 participants of the Australian Longitudinal Study of Ageing was assessed based on the questionnaire responses at the baseline interview. Frailty status and prevalence were assessed using four measures: two unidimensional measures (the Frailty Phenotype and Simplified Frailty Phenotype) and two multidimensional measures (Frailty Index and Prognostic Frailty Score). Agreement between the four measures was determined. RESULTS: The multidimensional measures identified more people as frail (17.5 and 49.4%) than did the unidimensional (2 and 8.8%). There was little agreement between the measures; only 0.5% of the participants were identified as frail by all four measures. CONCLUSIONS: The apparent prevalence of frailty varied when different measures were used. It is important for clinicians and researchers to be aware that different frailty measures may identify different groups of older people as frail.