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Journal ArticleDOI

An index of self-rated health deficits in relation to frailty and adverse outcomes in older adults

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TLDR
Measuring SRH by an index of deficits is a valid construct and is associated with adverse health outcomes and may facilitate exploration of the complex relationships between illness burden and health outcomes in older people.
Abstract
Background and aims: Poor self-rated health is associated with adverse outcomes but its relationship with frailty is not completely understood. We examined how self-rated health (SRH) is related to health outcomes and how this relationship might differ by individual level of fitness or frailty in older people. Methods: In the Atlantic Canada sample of the Canadian Study of Health and Aging, individuals aged ≥65 (n=1318) completed a self-administered questionnaire, from which we constructed an index of self-rated health deficits (SRHDI). Heterogeneity in health status was evaluated (n=1260) by determining their Frailty Index (FI). Higher values on the FI indicate worse health status. We evaluated health attitudes in relation to other health markers and to mortality. Results: Comparing those with the lowest vs highest SRHDI, significant differences (p<0.001) were seen in the mean hospital admissions in the past year (0.2 (±0.02) vs 0.8 (±0.08)), 3MS cognitive score (85.0 (±0.5) vs 78.4 (±1.2)) and (p=0.003) for age (75.3 (±0.3) vs 77.1 (±0.6)). The SRHDI and FI were moderately correlated (r=0.49) and both predicted mortality. In the fittest older people, those with poor SRHDI had a significantly increased risk of death (OR=18, 95% CI 6.0–53.6); SRHDI did not affect mortality in those who were frail. Conclusions: Measuring SRH by an index of deficits is a valid construct and is associated with adverse health outcomes. The SRHDI may facilitate exploration of the complex relationships between illness burden and health outcomes in older people. When people are frail, worse health attitude does not seem to increase mortality, but in contrast, appears to increase mortality risk in fit older people.

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Citations
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Cellular senescence and the senescent secretory phenotype: therapeutic opportunities.

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Frailty measurement in research and clinical practice: A review

TL;DR: How well these measurements operationalise frailty according to Clegg's guidelines for frailty classification is examined - that is: their accuracy in identifying frailty; their basis on biological causative theory; and their ability to reliably predict patient outcomes and response to potential therapies.
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Emergency General Surgery in the Elderly: Too Old or Too Frail?

TL;DR: Frailty index independently predicts postoperative complications, major complications, and hospital length of stay in elderly patients undergoing emergency general surgery.
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The frailty syndrome: a comprehensive review.

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References
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Book

Health Measurement Scales: A Practical Guide to Their Development and Use

TL;DR: In this article, the authors propose three basic concepts: devising the items, selecting the items and selecting the responses, from items to scales, reliability and validity of the responses.
Journal ArticleDOI

A global clinical measure of fitness and frailty in elderly people

TL;DR: The ability of the Clinical Frailty Scale to predict death or need for institutional care, and correlated the results with those obtained from other established tools are determined.
Journal Article

The Modified Mini-Mental State (3MS) examination.

TL;DR: The Modified Mini-Mental State (3MS) incorporates four added test items, more graded scoring, and some other minor changes to sample a broader variety of cognitive functions, cover a wider range of difficulty levels, and enhance the reliability and the validity of the scores.
Journal ArticleDOI

A standard procedure for creating a frailty index

TL;DR: A systematic process for creating a frailty index, which relates deficit accumulation to the individual risk of death, showed reproducible properties in the Yale Precipitating Events Project cohort study.
Journal ArticleDOI

Review: A gentle introduction to imputation of missing values

TL;DR: In this paper, the authors show that both single and multiple imputations of missing data almost always result in biased estimates, and they also explain and illustrate why two commonly used methods to handle missing data, i.e., overall mean imputation and the missing-indicator method, almost always yield biased estimates.
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