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Using the FRAIL scale to compare pre-existing demographic lifestyle and medical risk factors between non-frail, pre-frail and frail older adults accessing primary health care: a cross-sectional study.

ABSTRACT: Background:Few studies in the scientific literature have analyzed frailty status as an ordinal variable (non-frail, pre-frail and frail) rather than as a binary variable (frail vs non-frail). These studies have found that pre-frailty behaves differently from frailty (no ordinality in the variable). However, although the comparison between pre-frail and frail individuals is clinically relevant to understanding how to treat pre-frailty, this comparison was not performed in previous studies. Materials and Methods:A cross-sectional observational study was designed with 621 older individuals aged ?60 years in Spain in 2017-2018, determining factors associated with a higher frailty stage (non-frail, pre-frail and frail) and undertaking this comparison, in addition to measuring non-frailty. The factors assessed through a multinominal regression model were: age, sex, living alone, recent loss of the partner, income and total comorbidities. Results:Of the total participants, 285 were non-frail (45.9%), 210 were pre-frail (33.8%) and 126 were frail (20.3%). Compared to non-frail individuals, pre-frail individuals were older, with more comorbidities and a lower income. Compared to non-frail individuals, frail individuals were more likely to be female, older, with more comorbidities and a lower income. Compared to pre-frail individuals, frail individuals were more likely to be female, older and with more comorbidities. Conclusion:Comparison between the pre-frail and frail groups showed that frail persons were more likely to have a lower income, be female, older and have a higher number of comorbidities.

SUBMITTER: Aznar-Tortonda V

PROVIDER: S-EPMC7666811 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Using the FRAIL scale to compare pre-existing demographic lifestyle and medical risk factors between non-frail, pre-frail and frail older adults accessing primary health care: a cross-sectional study.

Aznar-Tortonda Vanessa V Palazón-Bru Antonio A Gil-Guillén Vicente Francisco VF

PeerJ 20201112

<h4>Background</h4>Few studies in the scientific literature have analyzed frailty status as an ordinal variable (non-frail, pre-frail and frail) rather than as a binary variable (frail vs non-frail). These studies have found that pre-frailty behaves differently from frailty (no ordinality in the variable). However, although the comparison between pre-frail and frail individuals is clinically relevant to understanding how to treat pre-frailty, this comparison was not performed in previous studies ...[more]

PMID: 33240674

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Project description:BackgroundFrailty is characterized by a progressive decline in the physiological functions of multiple body systems that lead to a more vulnerable condition, which is prone to the development of various adverse events, such as falls, hospitalization, and mortality. This study aims to determine whether frailty increases mortality compared to pre-frailty and to identify variables associated with a higher risk of mortality.MaterialsTwo cohorts, frail and pre-frail subjects, are evaluated according to the Fried phenotype. A complete examination of frailty, cognitive status, comorbidities and pharmacology was carried out at hospital admission and was extracted through electronic health record (EHR). Mortality was evaluated from the EHR.MethodsKaplan-Meier estimates of survival probability functions were calculated at two years censoring time for frail and pre-frail cohorts. The log-rank test assessed significant differences between survival probability functions. Significant variables for frailty (p < 0-05) were extracted by independent sample t-test. Further selection was based on variable significance found in multivariate logistic regression discrimination between frail and pre-frail subjects. Cox regression over univariate t-test-selected variables was calculated to identify variables associated with higher proportional hazard risks (HR) at two years.ResultsFrailty is associated with greater mortality at two years censoring time than pre-frailty (log-rank test, p < 0.0001). Variables with significant (p < 0.05) association with mortality identified in both cohorts (HR 95% (CI in the frail cohort) are male sex (0.44 (0.29-0.66)), age (1.05 (1.01-1.09)), weight (0.98 (0.96-1.00)), and use of proton-pump inhibitors (PPIs) (0.60 (0.41-0.87)). Specific high-risk factors in the frail cohort are readmission at 30 days (0.50 (0.33-0.74)), SPPB sit and stand (0.62 (0.45-0.85)), heart failure (0.67 (0.46-0.98)), use of antiplatelets (1.80 (1.19-2.71)), and quetiapine (0.31 (0.12-0.81)). Specific high-risk factors in the pre-frail cohort are Barthel's score (120 (7.7-1700)), Pfeiffer test (8.4; (2.3-31)), Mini Nutritional Assessment (MNA) (1200 (18-88,000)), constipation (0.025 (0.0027-0.24)), falls (18,000 (150-2,200,000)), deep venous thrombosis (8400 (19-3,700,000)), cerebrovascular disease (0.01 (0.00064-0.16)), diabetes (360 (3.4-39,000)), thyroid disease (0.00099 (0.000012-0.085)), and the use of PPIs (0.062 (0.0072-0.54)), Zolpidem (0.000014 (0.0000000021-0.092)), antidiabetics (0.00015 (0.00000042-0.051)), diuretics (0.0003 (0.000004-0.022)), and opiates (0.000069 (0.00000035-0.013)).ConclusionsFrailty is associated with higher mortality at two years than pre-frailty. Frailty is recognized as a systemic syndrome with many links to older-age comorbidities, which are also found in our study. Polypharmacy is strongly associated with frailty, and several commonly prescribed drugs are strongly associated with increased mortality. It must be considered that frail patients need coordinated attention where the diverse specialist taking care of them jointly examines the interactions between the diversity of treatments prescribed.

Project description:Lifelong strength is fundamental to physical function, health, and quality of life. Reliable appropriate strength assessment measures for older adults play an important role in effective evaluation of baseline ability and exercise prescription to counter disease and disuse. This study aimed to investigate the within-session reliability of maximal isometric knee extension and flexion, hip abduction and adduction, and handgrip strength measures in frail and pre-frail older adults. The study was conducted at a residential care home in Birmingham, UK. All care home residents aged ≥ 65 years; pre-frail or frail according to the Fried Frailty phenotype criteria; able to speak and read English; not currently involved in any other clinical trial; without severe sensory impairments; and with a predicted life expectancy greater than the trial length were eligible. Maximal isometric lower limb testing was performed using specialised resistance training equipment and a portable measurement device, and grip strength was assessed using a portable dynamometer. All eligible participants attended a single testing session and performed three trials per measure. Peak force measures were obtained for analysis. Within-session reliability for each measure was calculated from repeated-measures analysis of variance, intraclass correlation coefficients (ICC), and coefficients of variation (CV) with 95% confidence intervals. Eleven frail and eleven pre-frail older adults participated in the study. Within-session absolute and relative measures were found to be reliable with the highest overall repeatability indicated between trial 2 and trial 3 for knee extension, hip abduction, and handgrip (CV ≤ 4.65%, ICC ≥ 0.96) with variation evident across all measures, except knee extension, from trial 1 to 2. Overall, maximal isometric strength in frail and pre-frail older adults with no previous testing experience can be measured with good to high reliability within their first testing session. An initial two familiarisation trials followed by two measurement trials is recommended to achieve the highest level of overall repeatability. The trial was registered with ClinicalTrials.gov: NCT03141879 on 05/05/2017.

Project description:Multi-morbidity is common among older adults; however, for many aging-related diseases there is no information for U.S. elderly population on how earlier-manifested disease affects the risk of another disease manifested later during patient's lifetime. Quantitative evaluation of risks of cancer and non-cancer diseases for older adults with pre-existing conditions is performed using the Surveillance, Epidemiology, and End Results (SEER) Registry data linked to the Medicare Files of Service Use (MFSU). Using the SEER-Medicare data containing individual records for 2,154,598 individuals, we empirically evaluated age patterns of incidence of age-associated diseases diagnosed after the onset of earlier manifested disease and compared these patterns with those in general population. Individual medical histories were reconstructed using information on diagnoses coded in MFSU, dates of medical services/procedures, and Medicare enrollment/disenrollment. More than threefold increase of subsequent diseases risk was observed for 15 disease pairs, majority of them were i) diseases of the same organ and/or system (e.g., Parkinson disease for patients with Alzheimer disease, HR=3.77, kidney cancer for patients with renal failure, HR=3.28) or ii) disease pairs with primary diseases being fast-progressive cancers (i.e., lung, kidney, and pancreas), e.g., ulcer (HR=4.68) and melanoma (HR=4.15) for patients with pancreatic cancer. Lower risk of subsequent disease was registered for 20 disease pairs, mostly among patients with Alzheimer's or Parkinson's disease, e.g., decreased lung cancer risk among patients with Alzheimer's (HR=0.64) and Parkinson's (HR=0.60) disease. Synergistic and antagonistic dependences in geriatric disease risks were observed among US elderly confirming known and detecting new associations of wide spectrum of age-associated diseases. The results can be used in optimization of screening, prevention and treatment strategies of chronic diseases among U.S. elderly population.

Dataset Information

Using the FRAIL scale to compare pre-existing demographic lifestyle and medical risk factors between non-frail, pre-frail and frail older adults accessing primary health care: a cross-sectional study.

Publications

Using the FRAIL scale to compare pre-existing demographic lifestyle and medical risk factors between non-frail, pre-frail and frail older adults accessing primary health care: a cross-sectional study.

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