A frailty paradigm would be useful in primary care to identify older people at risk, but appropriate metrics at that level are lacking. We created and validated a simple instrument for frailty ...screening in Europeans aged ≥50. Our study is based on the first wave of the Survey of Health, Ageing and Retirement in Europe (SHARE, http://www.share-project.org), a large population-based survey conducted in 2004-2005 in twelve European countries.
SHARE Wave 1 respondents (17,304 females and 13,811 males).
five SHARE variables approximating Fried's frailty definition. Analyses (for each gender): 1) estimation of a discreet factor (DFactor) model based on the frailty variables using LatentGOLD. A single DFactor with three ordered levels or latent classes (i.e. non-frail, pre-frail and frail) was modelled; 2) the latent classes were characterised against a biopsychosocial range of Wave 1 variables; 3) the prospective mortality risk (unadjusted and age-adjusted) for each frailty class was established on those subjects with known mortality status at Wave 2 (2007-2008) (11,384 females and 9,163 males); 4) two web-based calculators were created for easy retrieval of a subject's frailty class given any five measurements.
Females: the DFactor model included 15,578 cases (standard R2 = 0.61). All five frailty indicators discriminated well (p < 0.001) between the three classes: non-frail (N = 10,420; 66.9%), pre-frail (N = 4,025; 25.8%), and frail (N = 1,133; 7.3%). Relative to the non-frail class, the age-adjusted Odds Ratio (with 95% Confidence Interval) for mortality at Wave 2 was 2.1 (1.4 - 3.0) in the pre-frail and 4.8 (3.1 - 7.4) in the frail. Males: 12,783 cases (standard R2 = 0.61, all frailty indicators had p < 0.001): non-frail (N = 10,517; 82.3%), pre-frail (N = 1,871; 14.6%), and frail (N = 395; 3.1%); age-adjusted OR (95% CI) for mortality: 3.0 (2.3 - 4.0) in the pre-frail, 6.9 (4.7 - 10.2) in the frail.
The SHARE Frailty Instrument has sufficient construct and predictive validity, and is readily and freely accessible via web calculators. To our knowledge, SHARE-FI represents the first European research effort towards a common frailty language at the community level.
•Benzodiazepines (BDZs) users had lower baseline systolic blood pressure values.•BDZs were associated with greater blood pressure fall at 10 s post-stand.•The hypotensive effect of BDZs was ...independent of frailty and comorbidities.•The hypotensive effect of BDZs may increase the risk of falls in older adults.•BDZs should be avoided in older people at risk of falling.
Older people taking benzodiazepines (BDZs) have higher risk of falling, which is mainly attributed to cognitive and psychomotor effects. BDZs may also have hypotensive effects. We investigated the association between BDZs and orthostatic blood pressure behaviour in older people.
We retrospectively analysed data from an outpatient clinic where people aged 60 or older underwent a geriatric assessment. Non-invasive beat-to-beat orthostatic systolic blood pressure (SBP) was assessed at regular time intervals before and after an active stand test. We compared clinical characteristics between BDZs users and non-users and also investigated if BDZs use was an independent predictor of baseline SBP. Factors associated with SBP change were investigated using a repeated measures general linear model.
Of 538 participants (67.7% female, mean age 72.7), 33 (6.1%) reported regular BDZs use. BDZ users had lower baseline SBP (149 versus 161 mmHg, P < 0.05). Multiple linear regression confirmed BDZs use as independent predictor of baseline SBP in N = =538. At 10 s post-stand, the SBP difference between BDZs use groups became maximum (21 mmHg); at this point, SBP still seemed to be decreasing in BDZ-users, whereas in controls it seemed to be recovering. After adjustment (age, sex, hypertension, frailty, comorbidity, antihypertensives), BDZs were associated with greater SBP reduction between baseline and 10 s post-stand (P < 0.05).
Older people taking BDZs may have a higher risk of orthostatic hypotension, perhaps due to an exaggerated immediate BP drop. This adds to other BDZ-related falls risks. BDZs should be avoided in older people at risk of falling.
The number of older patients admitted to acute hospitals has increased; however, their needs are heterogeneous and there is no gold‐standard method of triaging them towards practicing comprehensive ...geriatric assessment (CGA). In our hospital, the SAFE (Specialist Advice for the Frail Elderly) team provide an initial geriatric assessment of all emergency admissions of patients aged ≥75 years (with some assessments also occurring in those aged 65 to 74 years) and recommend as to whether CGA in a dedicated Department of Medicine for the Elderly (DME) ward may be required. SAFE assessments include routine screening for geriatric syndromes using validated tools. Our aim was to compare the characteristics (age, gender, acute illness severity on admission as per modified early warning score (MEWS), Charlson Comorbidity Index, Clinical Frailty Scale (CFS), presence of dementia and delirium) and outcomes (length of stay, delayed discharge, inpatient mortality, discharge to usual place of residence, and new institutionalization) of patients listed to a DME ward, to those not listed. We analyzed all SAFE team assessments of patients admitted nonelectively between February 2015 and November 2016. Of 6192 admissions, 16% were listed for a DME ward. Those were older, had higher MEWS and CFS score, were more often affected by cognitive impairment, had longer hospital stay, higher inpatient mortality, and more often required new institutionalization. Higher CFS and presence of dementia and delirium were the strongest predictors of DME ward recommendation. Routine measurement of markers of geriatric complexity may help maximize access to finite inpatient CGA resources.
Cognitive and motor function in ageing are intertwined, but whether slower motor response time (MRT) to a cognitive stimulus could herald accelerated mobility decline is unknown. Using data from The ...Irish Longitudinal Study on Ageing (TILDA), we examined whether slower MRT may predict a greater than expected increase in Time Up and Go (TUG) after 4 years.
Participants aged 50 years or older were divided into two groups based on their mean MRT (< 250 ms versus ≥ 250 ms). A repeated measures ANOVA compared TUG trajectories between groups, controlling for baseline age, sex, height, education level, mini mental-state examination (MMSE) score, self-reported vision and hearing, medical conditions (cardiovascular, cerebrovascular disease, diabetes), and number of medications.
At Wave 1, 1982 (58.7%) had a mean MRT of < 250 ms, with a mean TUG of 8.1 s (SD 1.6); and 1397 (41.3%) had an MRT of ≥ 250 ms, with a TUG of 9.0 s (SD 2.2). At Wave 3, TUG increased to 8.8 s (SD 2.0) and 10.2 s (SD 3.9), respectively. The results of the adjusted repeated measures ANOVA suggested that there was a statistically significant interaction between MRT group and Wave (P = 0.023, η2p = 0.002).
TILDA participants in the slower MRT group seemed to have faster mobility decline, but this effect was statistically and clinically small.
TILDA is funded by Atlantic Philanthropies, the Irish Department of Health and Irish Life. Roman Romero-Ortuno is funded by Science Foundation Ireland (grant number 18/FRL/6188).
The prevention of falls in older people requires the identification of the most important risk factors. Frailty is associated with risk of falls, but not all falls are of the same nature. In this ...work, we utilised data from The Irish Longitudinal Study on Ageing to implement Random Forests and Explainable Artificial Intelligence (XAI) techniques for the prediction of different types of falls and analysed their contributory factors using 46 input features that included those of a previously investigated frailty index. Data of participants aged 65 years and older were fed into four random forest models (all falls or syncope, simple fall, complex fall, and syncope). Feature importance rankings were based on mean decrease in impurity, and Shapley additive explanations values were calculated and visualised. Female sex and a previous fall were found to be of high importance in all of the models, and polypharmacy (being on five or more regular medications) was ranked high in the syncope model. The more ‘accidental’ (extrinsic) nature of simple falls was demonstrated in its model, where the presence of many frailty features had negative model contributions. Our results highlight that falls in older people are heterogenous and XAI can provide new insights to help their prevention.
Aim: Increasing numbers of older people are admitted to hospital as medical emergencies. They are a heterogeneous population with uncertain trajectories and outcomes. Our aim was to retrospectively ...characterize subgroups of older inpatients based on their acuity trajectories.
Methods: This was a single‐center patient series from St James's Hospital Dublin, Ireland (2002–2010). The Medical Admissions Risk System (MARS) score was used to classify a sample of 14 607 patients aged ≥65 years, from admission to end of episode, into four trajectory groups: (i) static high acuity (group 1); (ii) static low acuity (group 2); (iii) inpatient deterioration (group 3); and (iv) inpatient improvement (group 4). K‐means cluster analysis was used for the classification.
Results: Group 1 (4.1%): median length of stay (LOS) 7.4 days, 23.6% used intensive care, mortality rate 79.2%; sepsis and renal failure were the dominant features. Group 2 (76.6%): median LOS 8.0 days, 5.2% used intensive care, mortality rate 9.5%; younger age, low comorbidity and diseases of non‐vital organs were predominant. Group 3 (7.6%): median LOS 17.2 days, 17.4% used intensive care, mortality rate 76.1%; high comorbidity and sepsis/respiratory disease featured. Group 4 (11.7%): median LOS 12.1 days, 12.8% used intensive care, mortality rate 22.7%; sepsis and renal/metabolic disease were frequent, and comorbidity levels were intermediate.
Conclusions: In older acute medical inpatients, the outcome seemed more driven by specific diagnoses (such as sepsis and renal failure) and comorbidity, than by age. Using the MARS score to retrospectively categorize older inpatients might help to understand their heterogeneity and promote the design of appropriate care pathways. Geriatr Gerontol Int 2013; 13: 405–412.
OBJECTIVES: To identify morphological orthostatic blood pressure (BP) phenotypes in older people and assess their correlation with orthostatic intolerance (OI), falls, and frailty and to compare the ...discriminatory performance of a morphological classification with two established orthostatic hypotension (OH) definitions: consensus (COH) and initial (IOH).
DESIGN: Cross‐sectional.
SETTING: Geriatric research clinic.
PARTICIPANTS: Four hundred forty‐two participants (mean age 72, 72% female) without dementia or risk factors for autonomic neuropathy.
MEASUREMENTS: Active lying‐to‐standing test monitored using a continuous noninvasive BP monitor. For the morphological classification, four orthostatic systolic BP variables were extracted (delta (baseline – nadir) and maximum percentage of baseline recovered by 30 seconds and 1 and 2 minutes) using the 5‐second averages method and entered in K‐means cluster analysis (three clusters). Main outcomes were OI, falls (≥1 in past 6 months), and frailty (modified Fried criteria).
RESULTS: The morphological clusters were small drop, fast overrecovery (n=112); medium drop, slow recovery (n=238); and large drop, nonrecovery (n=92). Their characterization revealed an increasing OI gradient (17.9%, 27.5%, and 44.6% respectively, P<.001) but no significant gradients in falls or frailty. The COH definition failed to reveal clinical differences between COH+ (n=416) and COH− (n=26) participants. The IOH definition resulted in a clinically meaningful separation between IOH+ (n=85) and IOH− (n=357) subgroups, as assessed according to OI (100% vs 11.5%, P<.001), falls (24.7% vs 10.4%, P<.001), and frailty (14.1% vs 5.4%, P=.005).
CONCLUSION: It is recommended that the IOH definition be applied when taking continuous noninvasive orthostatic BP measurements in older people.
Abstract
Background
Chronic diseases are the leading cause of death worldwide. Many of these diseases have modifiable risk factors, including physical activity and sleep, and may be preventable. This ...study investigated independent associations of physical activity and sleep with eight common chronic illnesses.
Methods
Data were from waves 1, 3 and 5 of The Irish Longitudinal Study on Ageing (
n
= 5,680). Inverse probability weighted general estimating equations were used to examine longitudinal lifetime prevalence and cumulative incidence of self-reported conditions.
Results
Sleep problems were significantly associated with increased odds of incident and prevalent arthritis and angina. Additionally sleep problems were associated with higher odds of lifetime prevalence of hypertension and diabetes. Physical activity was negatively associated incident osteoporosis and respiratory diseases and negatively associated with lifetime prevalence of hypertension, high cholesterol and diabetes.
Conclusions
Worse sleep quality and lower physical activity were associated with higher odds of chronic diseases. Interventions to improve sleep and physical activity may improve health outcomes.
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