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Can resources moderate the impact of levels of frailty on adverse outcomes among (pre-) frail older people? A longitudinal study.

ABSTRACT: Higher levels of frailty result in higher risks of adverse frailty outcomes such as hospitalisation and mortality. There are, however, indications that more factors than solely frailty play a role in the development of these outcomes. The presence of resources, e.g. sufficient income and good self-management abilities, might slow down the pathway from level of frailty to adverse outcomes (e.g. mortality). In the present paper we studied whether resources (i.e. educational level, income, availability of informal care, living situation, sense of mastery and self-management abilities) moderate the impact of the level of frailty on the adverse outcomes mortality, hospitalisation and the development of disability over a two-year period.Longitudinal data on a sample of 2420 community-dwelling pre-frail and frail older people were collected. Participants filled out a questionnaire every six months, including measures of frailty, resources and outcomes. To study the moderating effects of the selected resources their interaction effects with levels of frailty on outcomes were studied by means of multiple logistics and linear regression models.Frail older participants had increased odds of mortality and hospitalisation, and had more deteriorating disability scores compared to their pre-frail counterparts. No moderating effects of the studied resources were found for the outcomes mortality and hospitalisation. Only for the outcome disability statistically significant moderating effects were present for the resources income and living situation, yet these effects were in the opposite direction to what we expected. Overall, the studied resources showed hardly any statistically significant moderating effects and the directions of the trends were inconsistent.Frail participants were more at risk of mortality, hospitalisation, and an increase in disability. However, we were unable to demonstrate a clear moderating effect of the studied resources on the adverse outcomes associated with frailty (among pre-frail and frail participants). More research is needed to increase insight into the role of moderating factors. Other resources or outcome measures should be considered.

SUBMITTER: Op Het Veld LPM

PROVIDER: S-EPMC5561574 | biostudies-other | 2017 Aug

REPOSITORIES: biostudies-other

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Project description:BackgroundPeople living with HIV (PLWH) are at risk of frailty, which is predictive for death. As an overactivity of the immune system is thought to fuel frailty, we characterized the immune activation profiles linked to frailty.MethodsWe quantified twenty-seven activation markers in forty-six virological responders (four females and forty-two males; median age, 74 years; median duration of infection, 24 years; median duration of undetectability, 13 years), whose frailty was determined according to the Fried criteria. T cell and NK cell activation was evaluated by flow cytometry, using a panel of cell surface markers. Soluble markers of inflammation, and monocyte activation and endothelial activation were measured by ELISA. The participants' immune activation was profiled by an unsupervised double hierarchical clustering analysis. We used ANOVA p-values to rank immunomarkers most related to Fried score. A Linear Discriminant Analysis (LDA) was performed to link immune activation markers to frailty.Results41% of the participants were pre-frail, including 24% with a Fried score of 1, and 17% with a Fried score of 2. ANOVA identified the 14 markers of T cell, monocyte, NK cell, endothelial activation, and inflammation the most linked to Fried 3 classes. The LDA performed with these 14 markers was capable of discriminating volunteers according to their Fried score. Two out of the 5 immune activation profiles revealed by the hierarchical clustering were linked to and predictive of pre-frailty. These two profiles were characterized by a low percentage of CD4 T cells and a high percentage of CD8 T cells, activated CD4 T cells, CD8 T cells, and NK cells, and inflammation.ConclusionsWe identified a particular immune activation profile associated with pre-frailty in PLWH. Profiling participants at risk of developing frailty might help to tailor the screening and prevention of medical complications fueled by loss of robustness. Further studies will indicate whether this frailty signature is specific or not of HIV infection, and whether it also precedes frailty in the general population.

Project description:Frailty is considered a predictor for negative outcomes such as disability, decreased quality of life, and hospital admission. Frailty measures have been developed that include different dimensions. We examined whether people who are physically frail are more at risk for negative outcomes of frailty if they also suffer from psychological, cognitive, or social frailty. Frailty was measured at baseline by means of the Groningen Frailty Indicator (GFI), which comprises a physical, cognitive, social, and psychological dimension. Only frail persons were included in the study (GFI ≥ 5) that, in addition, had to be frail in the physical dimension (i.e., ≥1 on this dimension). IADL disability and quality of life were measured at baseline and at 12 months. Hospital admission was assessed during this period. In this, physically frail sample effects of the other three frailty dimensions were studied in regression models. The sample (n = 334, mean age 78.1, and range 70-92) included 40.1 % frail men and 59.9 % frail women. Overall, no additional effects for the cognitive, social, or psychosocial dimensions were found: other frailty dimensions did not have an additional impact on disability, quality of life, or hospital admission in people who already suffered from physical frailty. Higher scores of physical frailty were significantly related to IADL disability (p < 0.05) and hospital admission (p < 0.05). Additional analysis showed that the physical frailty score predicted IADL disability and hospital admission better than the GFI overall score. Results of this study suggest that persons, who are physically frail, according to the GFI, are not more at risk for negative outcomes of frailty (i.e., IADL disability, decreased quality of life, and hospital admission) if they in addition suffer from cognitive, social, or psychological frailty. In addition, for the prediction of IADL disability or hospital admission, the focus for screening should be on the physical frailty score instead of the GFI overall score including different dimensions.

Project description:Frail and pre-frail older people often need to take medications. However, factors related to medication adherence among this population remain unclear, warranting further research. This study aims to identify correlates of medication adherence among frail and pre-frail older adults. From November 2020 to December 2020; a total of 4218 community-dwelling residents aged ≥ 60 years were interviewed by a cross-sectional survey in China. Data on subjects' general information; medication adherence; and frailty status was obtained via the face-to-face structured questionnaire. Logistic regression models were fitted; separately; to examine these factors linked to medication adherence. We found that 36.2% (n = 1527) and 18.8% (n = 792) of respondents were classified as pre-frail and frail. According to the Morisky scale scores, 66.74% (n = 2815) were found to have adequate medication adherence, and 33.26% (n = 1403) were found to have inadequate medication adherence. Among the pre-frail respondents, age (adjusted odds ratio (AOR) = 1.64; 95% confidence interval (CI): 1.18-2.29, P = 0.003), marital status (AOR = 1.52; 95% CI: 1.04-2.21, P = 0.030), smoking status (AOR = 0.61; 95% CI: 0.37-0.99, P = 0.044), and functional ability (AOR = 0.72; 95% CI: 0.58-0.91, P = 0.006) were significantly related to medication adherence. Among them, advanced age and single were risk factors, which were positively related to the medication adherence of subjects in pre-frailty, while quitting smoking and limited functional ability contributed to improving their medication adherence. In contrast, only age (AOR = 1.77; 95% CI: 1.16-2.69, P = 0.008) was significantly associated with medication adherence among frail subjects. Influencing factors to medication adherence of old people in pre-frailty and frailty have been enriched, which provides a certain reference for promoting medication adherence in this population. Future adherence intervention methods should be designed based on these factors.

Project description:Objectives:To examine how various combinations of cognitive impairment (overall performance and specific domains) and pre-frailty predict risks of adverse outcomes; and to determine whether cognitive frailty may be defined as the combination of cognitive impairment and the presence of pre-frailty. Design:Community-based cohort study. Participants:Chinese men and women (n?=?3,491) aged 65+ without dementia, Parkinson's disease and/or frailty at baseline. Measurements:Frailty was characterized using the Cardiovascular Health Study criteria. Overall cognitive impairment was defined by a Cantonese Mini-Mental Status Examination (CMMSE) total score (<21/24/27, depending on participants' educational levels); delayed recall impairment by a CMMSE delayed recall score (<3); and language and praxis impairment by a CMMSE language and praxis score (<9). Adverse outcomes included poor quality of life, physical limitation, increased cumulative hospital stay, and mortality. Results:Compared to those who were robust and cognitively intact at baseline, those who were robust but cognitively impaired were more likely to develop pre-frailty/frailty after 4?years (P?<?0.01). Compared to participants who were robust and cognitively intact at baseline, those who were pre-frail and with overall cognitive impairment had lower grip strength (P?<?0.05), lower gait speed (P?<?0.01), poorer lower limb strength (P?<?0.01), and poorer delayed recall at year 4 [OR, 1.6; 95% confidence interval (CI), 1.2-2.3]. They were also associated with increased risks of poor quality of life (OR, 1.5; 95% CI, 1.1-2.2) and incident physical limitation at year 4 (OR, 1.8; 95% CI, 1.3-2.5), increased cumulative hospital stay at year 7 (OR, 1.5; 95% CI, 1.1-2.1), and mortality over an average of 12?years (OR, 1.5; 95% CI, 1.0-2.1) after adjustment for covariates. There was no significant difference in risks of adverse outcomes between participants who were pre-frail, with/without cognitive impairment at baseline. Similar results were obtained with delayed recall and language and praxis impairments. Conclusion:Robust and cognitively impaired participants had higher risks of becoming pre-frail/frail over 4?years compared with those with normal cognition. Cognitive impairment characterized by the CMMSE overall score or its individual domain score improved the predictive power of pre-frailty for poor quality of life, incident physical limitation, increased cumulative hospital stay, and mortality. Our findings support to the concept that cognitive frailty may be defined as the occurrence of both cognitive impairment and pre-frailty, not necessarily progressing to dementia.

Project description:ObjectivesDeprescribing has been proposed as a way to reduce polypharmacy in frail older people. We aimed to reduce the number of medicines consumed by people living in residential aged care facilities (RACF). Secondary objectives were to explore the effect of deprescribing on survival, falls, fractures, hospital admissions, cognitive, physical, and bowel function, quality of life, and sleep.MethodsNinety-five people aged over 65 years living in four RACF in rural mid-west Western Australia were randomised in an open study. The intervention group (n = 47) received a deprescribing intervention, the planned cessation of non-beneficial medicines. The control group (n = 48) received usual care. Participants were monitored for twelve months from randomisation. Primary outcome was change in the mean number of unique regular medicines. All outcomes were assessed at baseline, six, and twelve months.ResultsStudy participants had a mean age of 84.3 ± 6.9 years and 52% were female. Intervention group participants consumed 9.6 ± 5.0 and control group participants consumed 9.5 ± 3.6 unique regular medicines at baseline. Of the 348 medicines targeted for deprescribing (7.4 ± 3.8 per person, 78% of regular medicines), 207 medicines (4.4 ± 3.4 per person, 59% of targeted medicines) were successfully discontinued. The mean change in number of regular medicines at 12 months was -1.9 ± 4.1 in intervention group participants and +0.1 ± 3.5 in control group participants (estimated difference 2.0 ± 0.9, 95%CI 0.08, 3.8, p = 0.04). Twelve intervention participants and 19 control participants died within 12 months of randomisation (26% versus 40% mortality, p = 0.16, HR 0.60, 95%CI 0.30 to 1.22) There were no significant differences between groups in other secondary outcomes. The main limitations of this study were the open design and small participant numbers.ConclusionsDeprescribing reduced the number of regular medicines consumed by frail older people living in residential care with no significant adverse effects on survival or other clinical outcomes.Trial registrationAustralian New Zealand Clinical Trials Registry ACTRN12611000370909.

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Can resources moderate the impact of levels of frailty on adverse outcomes among (pre-) frail older people? A longitudinal study.

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