A brief clinical instrument to classify frailty in elderly people

Rockwood, Kenneth; Stadnyk, Karen; MacKnight, Chris; McDowell, Ian; Hébert, Réjean; Hogan, David B.

doi:10.1016/s0140-6736(98)04402-x

Cited by 783 publications

(566 citation statements)

References 2 publications

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“…RAILTY is considered to be highly prevalent with increasing age and to confer high risk for adverse health outcomes, including mortality, institutionalization, falls, and hospitalization (1)(2)(3). Numerous geriatric interventions have been developed to improve clinical outcomes for frail older adults (3)(4)(5)(6)(7).…”

mentioning

confidence: 99%

“…Potential definitions of frailty abound, defining frailty as synonymous with disability (1,8,9), comorbidity (8), or advanced old age (3). Increasingly, geriatricians define frailty as a biologic syndrome of decreased reserve and resistance to stressors, resulting from cumulative declines across multiple physiologic systems, and causing vulnerability to adverse outcomes (9)(10)(11)(12)(13).…”

mentioning

confidence: 99%

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Frailty in Older Adults: Evidence for a Phenotype

Fried¹,

Tangen²,

Walston³

et al. 2001

The Journals of Gerontology Series A: Biological Sciences and M

19,220

415

19,090

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mentioning

confidence: 99%

mentioning

confidence: 99%

Frailty in Older Adults: Evidence for a Phenotype

Fried¹,

Tangen²,

Walston³

et al. 2001

The Journals of Gerontology Series A: Biological Sciences and M

19,220

415

19,090

View full text Add to dashboard Cite

“…Because stressors are may be unpredictable, continual monitoring may be required to identify triggers with dynamic indicators of resilience and self‐rating of health status. Dynamic indicators of resilience have been correlated with frailty measures17 and depression,18, 19 and approaches becoming implementable in clinical practice9, 20?…”

Section: Theoretical Model For Static and Dynamic Indicators Of Acutementioning

confidence: 99%

“…Baseline data on the MW intervention cohort included measures which have been validated in the Australian population: Clinical Frailty Index9—frailty is a term widely used to denote a multidimensional syndrome of loss of reserves (energy, physical ability, cognition, health) that gives rise to vulnerability; and worse health outcomes; SF‐12v2 Health Survey10, 11 which measures health‐related quality of life in two domains Physical Component Summary (PCS) and the Mental Component Summary (MCS) scores,12 and the ICECAP‐O (ICEpop CAPability measure for Older people)—a measure of QOL capability in older people that focuses on wellbeing defined in a broader sense (QOL), rather than health 13, 14. At around 6 months into the MW program, as it emerged that some participants appeared to exhibit a lack of psychosocial resilience, the Connor‐Davidson Resilience scale (CD‐RISC)15 was administered to the service cohort as a late baseline measure.…”

Section: Introductionmentioning

confidence: 99%

Resilience, health perceptions, (QOL), stressors, and hospital admissions—Observations from the real world of clinical care of unstable health journeys in Monash Watch (MW), Victoria, Australia

Martin

Hinkley

Stockman

et al. 2018

Evaluation Clinical Practice

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Rationale, aims, and objectivesMonash Watch (MW) aims to reduce potentially preventable hospitalisations in a cohort above a risk “threshold” identified by Health Links Chronic Care (HLCC) algorithms using personal, diagnostic, and service data. MW conducted regular patient monitoring through outbound phone calls using the Patient Journey Record System (PaJR). PaJR alerts are intended to act as a self‐reported barometer of stressors, resilience, and health perceptions with more alerts per call indicating greater risk.Aims: To describe predictors of PaJR alerts (self‐reported from outbound phone calls) and predictors of acute admissions based upon a Theoretical Model for Static and Dynamic Indicators of Acute Admissions.MethodsParticipants: HLCC cohort with predicted 3+ admissions/year in MW service arm for >40 days; n = 244. Baseline measures—Clinical Frailty Index (CFI); Connor Davis Resilience (CD‐RISC): SF‐12v2 Health Survey scores Mental (MSC) and Physical (PSC) and ICECAP‐O. Dynamic measures: PaJR alerts/call in 10 869 MW records. Acute (non‐surgical) admissions from Victorian Admitted Episode database. Analysis: Logistic regression, correlations, and timeseries homogeneity metrics using XLSTAT.FindingsBaseline indicators were significantly correlated except SF‐12_MCS. SF12‐MSC, SF12‐PSC and ICECAP‐O best predicted PaJR alerts/call (ROC: 0.84). CFI best predicted acute admissions (ROC: 0.66), adding CD‐RISC, SF‐12_MCS, SF‐12_PCS and ICECAP‐O with two‐way interactions improved model (ROC: 0.70). PaJR alerts were higher ≤10 days preceding acute admissions and significantly correlated with admissions. Patterns in PaJR alerts in four case studies demonstrated dynamic variations signifying risk. Overall, all baseline indicators were explanatory supporting the theoretical model. Timing of PaJR alerts and acute admissions reflecting changing stressors, resilience, and health perceptions were not predicted from baseline indicators but provided a trigger for service interventions.ConclusionBoth static and dynamic indicators representing stressors, resilience, and health perceptions have the potential to inform threshold models of admission risk in ways that could be clinically useful.

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“…The decrease in function across some systems is related to the aging process, such as neuroendocrine dysregulation, immune dysfunction and neuromuscular disorders. This condition increases vulnerability to adverse health outcomes, such as morbidity, dependency, falls, hospitalization and mortality [1][2][3] .…”

Section: Introductionmentioning

confidence: 99%

Relationship between frailty and respiratory function in the community-dwelling elderly

Pegorari¹,

Ruas²,

Patrizzi³

2013

Braz. J. Phys. Ther.

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| Objective: To evaluate the impact of frailty on respiratory function in a community-dwelling elderly. Method: 51 community-dwelling elderly were evaluated (mean age of 73±6 years), being 29 men (56.7%) and 22 women (43.3%). We collect the following variables: sociodemographic characteristics, frailty phenotype, pulmonary function test and assessment of the respiratory muscles using an analog manometer. The statistical analysis was performed using the Kolmogorov and Smirnov tests, one-way ANOVA, Paired Student's t-test and Pearson correlation coefficient (p<0.05). Results: There were no statistically significant between-group differences among the frail group (FG=9.8%), pre-frail group (PG=47.1%) and non-frail group (NG=43.1%), in relation to anthropometric, demographic and spirometric data. Regarding to the maximum inspiratory and expiratory pressures (MIP and MEP), statistically significant between-group differences were observed among the three groups, being these pressures significantly lower in the FG and PG compared to the NG. With regards to the obtained and predicted values, the FG and PG showed statistically significant difference (p=0.004). The PG showed positive correlations between the MIP and MEP with the values of hand grip strength (r=0.7). The NG showed positive correlation between the MEP and the values of physical activity level (r=0.7). Conclusions: The study demonstrated that maximal respiratory pressures may decrease according to the frailty condition among the nonfrail, pre-frail and frail elderly. Furthermore, it also indicated a positive correlation between inspiratory muscle strength, expiratory muscle strength and hand grip strength in pre-frail elderly. Further investigation with regards to prevention or intervention programs that incorporate actions to minimize the loss of respiratory function are necessary in order to reverse or prevent the progression of the frailty condition.

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A brief clinical instrument to classify frailty in elderly people

Cited by 783 publications

References 2 publications

Frailty in Older Adults: Evidence for a Phenotype

Frailty in Older Adults: Evidence for a Phenotype

Resilience, health perceptions, (QOL), stressors, and hospital admissions—Observations from the real world of clinical care of unstable health journeys in Monash Watch (MW), Victoria, Australia

Relationship between frailty and respiratory function in the community-dwelling elderly

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