It is well documented that falls may be prevented, but effectiveness in reducing the risk of falling depends on the uptake of and the adherence to preventive actions.
65+-year-old fallers identified by screening for fall risk were offered referral to a geriatric fall clinic together with fallers referred from general practitioners (GPs). They were assessed to identify individual risk factors for falling, and appropriate interventions were planned, including exercise classes.
A total of 811 persons were identified by screening, 342 of whom accepted referral. Furthermore, 176 were referred from GPs. Only 402 of 518 fallers attended the clinic. A total of 65 dropped out by their own request, 29 stopped because they became seriously ill or died. Another 62 patients were discharged before fulfilling the programme as they were unable to participate due to physical or cognitive problems. Indicators of cessation were cognitive or physical weakness.
Geriatric fall prevention is resource-consuming both in terms of staff needed and with respect to demands made on the patients, and the frailest part of the fall population cannot comply. It is necessary to differentiate fall prevention services for the population of elderly fallers as interventions in primary healthcare have been shown to be more effective among the most frail elderly fallers.
The project received funding from the Danish Ministry of the Interior and Health and from The Fund for Scientific Work in the Geriatric Field within the former Copenhagen Hospital Corporation.
The frailty index (FI) is used to measure the health status of ageing individuals. An FI is constructed as the proportion of deficits present in an individual out of the total number of age-related health variables considered. The purpose of this study was to systematically assess whether dichotomizing deficits included in an FI affects the information value of the whole index.
Secondary analysis of three population-based longitudinal studies of community dwelling individuals: Nova Scotia Health Survey (NSHS, n = 3227 aged 18+), Survey of Health, Ageing and Retirement in Europe (SHARE, n = 37546 aged 50+), and Yale Precipitating Events Project (Yale-PEP, n = 754 aged 70+). For each dataset, we constructed two FIs from baseline data using the deficit accumulation approach. In each dataset, both FIs included the same variables (23 in NSHS, 70 in SHARE, 33 in Yale-PEP). One FI was constructed with only dichotomous values (marking presence or absence of a deficit); in the other FI, as many variables as possible were coded as ordinal (graded severity of a deficit). Participants in each study were followed for different durations (NSHS: 10 years, SHARE: 5 years, Yale PEP: 12 years).
Within each dataset, the difference in mean scores between the ordinal and dichotomous-only FIs ranged from 0 to 1.5 deficits. Their ability to predict mortality was identical; their absolute difference in area under the ROC curve ranged from 0.00 to 0.02, and their absolute difference between Cox Hazard Ratios ranged from 0.001 to 0.009.
Analyses from three diverse datasets suggest that variables included in an FI can be coded either as dichotomous or ordinal, with negligible impact on the performance of the index in predicting mortality.
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Generally, health does not improve with age, and many physical and physiological functions are known to decline. These changes do not occur uniformly, however; for many reasons, some people experience significant improvement in their health over non-trivial time intervals. Earlier, we showed that 5-year transitions in health status in elderly people (age 65+ years) can be modeled as a stochastic process, using a modified Poisson distribution with four readily interpretable parameters. The original description was based on follow-up of a single cross-sectional study, thus mixing age and cohort effects. Here, we again used a multistate Markov chain to model 5-year deficit accumulation in relation to frailty in both a Swedish birth cohort (aged 70 years at inception) and, from the original cross-sectional study, a Canadian birth cohort, aged 69-71. In both datasets, we found again that a modified Poisson describes the transition in health status with high precision. The parameters of the model though different, are close to each other, even though the cohorts are from different countries, were assembled 20 years apart, and counted different deficits. The model suggests that all health transitions, including health improvement, worsening, and death, can be summarized in a unified stochastic model with a few interpretable parameters.
The Tilburg Frailty Indicator (TFI) is a self-administered questionnaire with a bio-psycho-social integrated approach that measures the degree of frailty in elderly persons. The TFI was developed in the Netherlands and tested in a population of elderly Dutch men and women. The aim of this study was to translate and culturally adapt the TFI to a Danish context, and to test face validity of the Danish version by cognitive interviewing. An internationally recognized procedure was applied as a basis for the translation process. The primary tasks were forward translation, reconciliation, back translation, harmonization and pretest. Pretest and review of the preliminary version by cognitive interviewing, were performed at a local community center and in an acute medical ward at the University Hospital in Aalborg, Denmark respectively. A large agreement regarding meaning of the items in the forward translation and reconciliation process was seen. Minor discrepancies were solved by consensus. Back translation revealed unclear wording in one matter. The harmonization committee agreed on a version for cognitive interviewing after revision of minor issues and thirty-four participants were interviewed. Two issues became evident and these were revised. The cognitive interviews and final lay-out resulted in minor adjustments as text type size, specific font, and lining for optimizing readability. In conclusion, we consider the TFI to be translated in such rigorous manner that the instrument can be further tested in clinical practice. The overall objective of the questionnaire being to identify frailty and improve the interventions relating to frail elderly persons in Denmark.
The elderly population in Sweden is increasing. This will lead to an increased need for healthcare resources and put extra demands on healthcare professionals. Consequently, ambulance personnel will be faced with the challenge of meeting extra demands from increasing numbers of older people with complex and atypical clinical presentations. Therefore we highlight that great problems exist for ambulance personnel to understand and meet these patients' care needs. Using a caring science approach, we apply the patient's perspective, and the aim of this study is to identify and illuminate the conditions that affect elderly people assessed with the assessment category "general affected health condition". Thus, we have analyzed the characteristics belonging to this specific condition. The method is a retrospective audit, involving a qualitative content analysis of a total of 88 emergency service records. The conclusion is that by using caring science, the concept of frailty which is based on a comprehensive understanding of human life can clarify the state of "general affected health condition", as either illness or ill-health. This offers a new assessment category and outlines care and treatment that strengthen and support the health and wellbeing of the individual elderly person. Furthermore, the concept of frailty ought to be included in "The International Statistical Classification of Diseases and Related Health Problems" (ICD-10).
The purpose of this study was to examine the association of disability and co-morbidity with frailty in older adults. 2305 participants aged 65+ from the second wave of the Canadian Study of Health and Aging (CSHA), a prospective population-based cohort study, comprised the study sample. Following a standard procedure, two different frailty index (FI) measures were constructed from 37 deficits by dividing the recorded deficits by the total number of measures. One version excluded disability and co-morbidity items, the other included them. Time to death was measured for up to five years. Frailty was defined using either the frailty phenotype or a cut-point applied to each FI. Of people defined as frail using the frailty phenotype, 15/416 (3.6%) experienced neither disability nor co-morbidity. Using 0.25 as the cut-point score for the FI (without disability/co-morbidity) resulted in 101/1176 (8.6%) frail participants that had neither disability nor co-morbidity. Activities of daily living (ADL) limitations and co-morbidities occurred more often among people with the highest levels of frailty. The first ADLs to become impaired with increasing frailty were bathing, managing medication, and cooking with more than 25% of older adults with a FI score (without disability/co-morbidity) >0.22 experiencing dependency on them. The hazard ratio (HR) per 0.1 increase in FI score was 1.25 (95% CI: 1.20-1.30) when disability and co-morbidity were included in the index and 1.21 (1.16-1.25) when they were not included. In conclusion, disability and co-morbidity greatly overlap with other deficits that might be used to define frailty and add to their ability to predict mortality.
Prior studies measuring fidelity of complex interventions have mainly evaluated adherence, and not taken factors affecting adherence into consideration. A need for studies that clarify the concept of fidelity and the function of factors moderating fidelity has been emphasized. The aim of the study was to systematically evaluate implementation fidelity and possible factors influencing fidelity of a complex care continuum intervention for frail elderly people.
The intervention was a systematization of the collaboration between a nurse with geriatric expertise situated at the emergency department, the hospital ward staff, and a multi-professional team with a case manager in the municipal care services for older people. Implementation was evaluated between September 2008 and May 2010 with observations of work practices, stakeholder interviews, and document analysis according to a modified version of The Conceptual Framework for Implementation Fidelity.
A total of 16 of the 18 intervention components were to a great extent delivered as planned, while some new components were added to the model. No changes in the frequency or duration of the 18 components were observed, but the dose of the added components varied over time. Changes in fidelity were caused in a complex, interrelated fashion by all the moderating factors in the framework, i.e., context, staff and participant responsiveness, facilitation, recruitment, and complexity.
The Conceptual Framework for Implementation Fidelity was empirically useful and included comprehensive measures of factors affecting fidelity. Future studies should focus on developing the framework with regard to how to investigate relationships between the moderating factors and fidelity over time.
To investigate the modifying effect of sex on the association between frailty and all-cause mortality, and to determine the effects of changes in frailty status on mortality.
This population-based study comprised 654 persons aged 76-100 years (mean age 82 ± 4.6 years). Frailty status was assessed at baseline in 2005, and reassessed in 2007 (n=546) using the Cardiovascular Health Study criteria. Death dates were received from the official register until the end of 2009. The associations between frailty, changes in frailty and mortality were investigated using Cox regression models.
At baseline, 93 (14%) participants were classified as frail, and 311 (48%) as pre-frail. Over the 4-year follow up, 173 (27%) baseline respondents died. The mortality risk for participants who were frail at baseline was 2.7 (95% CI 1.6-4.5) compared with the robust. In the fully adjusted model, the association was significant for women (HR 2.8, 95% CI 1.5-5.3), and of borderline significance for men (HR 2.4, 95% CI 1.0-5.9). In men, pre-frailty and frailty were both associated with increased mortality risk only in the age-adjusted model (pre-frailty HR 2.3, 95% CI 1.2-4.5; frailty HR 4.0, 95% CI 1.9-8.9). Decline in frailty status during the 2-year follow-up period also markedly increased the risk for mortality over the succeeding 2 years.
Frailty is strongly associated with higher mortality, especially among women. Among men, the association was explained by baseline functional capacity, comorbidity and lifestyle factors. Changes in frailty status should also be taken into consideration when planning geriatric care, as such changes could indicate a more rapid decline in health.
Frailty is a physiological state characterized by the deregulation of multiple physiologic systems of an aging organism determining the loss of homeostatic capacity, which exposes the elderly to disability, diseases, and finally death. An operative definition of frailty, useful for the classification of the individual quality of aging, is needed. On the other hand, the documented heterogeneity in the quality of aging among different geographic areas suggests the necessity for a frailty classification approach providing population-specific results. Moreover, the contribution of the individual genetic background on the frailty status is still questioned. We investigated the applicability of a cluster analysis approach based on specific geriatric parameters, previously set up and validated in a southern Italian population, to two large longitudinal Danish samples. In both cohorts, we identified groups of subjects homogeneous for their frailty status and characterized by different survival patterns. A subsequent survival analysis availing of Accelerated Failure Time models allowed us to formulate an operative index able to correlate classification variables with survival probability. From these models, we quantified the differential effect of various parameters on survival, and we estimated the heritability of the frailty phenotype by exploiting the twin pairs in our sample. These data suggest the presence of a genetic influence on the frailty variability and indicate that cluster analysis can define specific frailty phenotypes in each population.