Dataset Information

Prediction models for functional status in community dwelling older adults: a systematic review.

ABSTRACT:

Background

Disability poses a burden for older persons, and is associated with poor outcomes and high societal costs. Prediction models could potentially identify persons who are at risk for disability. An up to date review of such models is missing.

Objective

To identify models developed for the prediction of functional status in community dwelling older persons.

Methods

A systematic review was performed including studies of older persons that developed and/or validated prediction models for the outcome functional status. Medline and EMBASE were searched, and reference lists and prospective citations were screened for additional references. Risk of bias was assessed using the PROBAST-tool. The performance of models was described and summarized, and the use of predictors was collated using the bag-of-words text mining procedure.

Results

Forty-three studies were included and reported 167 evaluations of prediction models. The median c-statistic values for the multivariable development models ranged between 0.65 and 0.76 (minimum = 0.58, maximum = 0.90), and were consistently higher than the values of the validation models for which median c-statistic values ranged between 0.6 and 0.68 (minimum = 0.50, maximum = 0.81). A total of 559 predictors were used in the models. The five predictors most frequently used were gait speed (n = 47), age (n = 38), cognition (n = 27), frailty (n = 24), and gender (n = 22).

Conclusions

No model can be recommended for implementation in practice. However, frailty models appear to be the most promising, because frailty components (e.g. gait speed) and frailty indexes demonstrated good to excellent predictive performance. However, the risk of study bias was high. Substantial improvements can be made in the methodology.

SUBMITTER: Van Grootven B

PROVIDER: S-EPMC9150308 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Publications

Prediction models for functional status in community dwelling older adults: a systematic review.

Van Grootven Bastiaan B van Achterberg Theo T

BMC geriatrics 20220530 1

<h4>Background</h4>Disability poses a burden for older persons, and is associated with poor outcomes and high societal costs. Prediction models could potentially identify persons who are at risk for disability. An up to date review of such models is missing.<h4>Objective</h4>To identify models developed for the prediction of functional status in community dwelling older persons.<h4>Methods</h4>A systematic review was performed including studies of older persons that developed and/or validated pr ...[more]

PMID: 35637447

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Project description:BackgroundIdentification of community-dwelling older adults at risk of unplanned hospitalizations is of importance to facilitate preventive interventions. Our objective was to review and appraise the methodological quality and predictive performance of prediction models for predicting unplanned hospitalizations in community-dwelling older adults.Methods and findingsWe searched MEDLINE, EMBASE and CINAHL from August 2013 to January 2021. Additionally, we checked references of the identified articles for the inclusion of relevant publications and added studies from two previous reviews that fulfilled the eligibility criteria. We included prospective and retrospective studies with any follow-up period that recruited adults aged 65 and over and developed a prediction model predicting unplanned hospitalizations. We included models with at least one (internal or external) validation cohort. The models had to be intended to be used in a primary care setting. Two authors independently assessed studies for inclusion and undertook data extraction following recommendations of the CHARMS checklist, while quality assessment was performed using the PROBAST tool. A total of 19 studies met the inclusion criteria. Prediction horizon ranged from 4.5 months to 4 years. Most frequently included variables were specific medical diagnoses (n = 11), previous hospital admission (n = 11), age (n = 11), and sex or gender (n = 8). Predictive performance in terms of area under the curve ranged from 0.61 to 0.78. Models developed to predict potentially preventable hospitalizations tended to have better predictive performance than models predicting hospitalizations in general. Overall, risk of bias was high, predominantly in the analysis domain.ConclusionsModels developed to predict preventable hospitalizations tended to have better predictive performance than models to predict all-cause hospitalizations. There is however substantial room for improvement on the reporting and analysis of studies. We recommend better adherence to the TRIPOD guidelines.

Project description:ObjectiveTo systematically review and critically appraise prognostic models for falls in community-dwelling older adults.Eligibility criteriaProspective cohort studies with any follow-up period. Studies had to develop or validate multifactorial prognostic models for falls in community-dwelling older adults (60+ years). Models had to be applicable for screening in a general population setting.Information sourceMEDLINE, EMBASE, CINAHL, The Cochrane Library, PsycINFO and Web of Science for studies published in English, Danish, Norwegian or Swedish until January 2020. Sources also included trial registries, clinical guidelines, reference lists of included papers, along with contacting clinical experts to locate published studies.Data extraction and risk of biasTwo authors performed all review stages independently. Data extraction followed the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist. Risk of bias assessments on participants, predictors, outcomes and analysis methods followed Prediction study Risk Of Bias Assessment Tool.ResultsAfter screening 11 789 studies, 30 were eligible for inclusion (n=86 369 participants). Median age of participants ranged from 67.5 to 83.0 years. Falls incidences varied from 5.9% to 59%. Included studies reported 69 developed and three validated prediction models. Most frequent falls predictors were prior falls, age, sex, measures of gait, balance and strength, along with vision and disability. The area under the curve was available for 40 (55.6%) models, ranging from 0.49 to 0.87. Validated models' The area under the curve ranged from 0.62 to 0.69. All models had a high risk of bias, mostly due to limitations in statistical methods, outcome assessments and restrictive eligibility criteria.ConclusionsAn abundance of prognostic models on falls risk have been developed, but with a wide range in discriminatory performance. All models exhibited a high risk of bias rendering them unreliable for prediction in clinical practice. Future prognostic prediction models should comply with recent recommendations such as Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis.Prospero registration numberCRD42019124021.

Project description:BackgroundAge-related decline in physical and cognitive capacity increases older adults' risk of disability, long-term care placement, and mortality rate. Functional training, which uses activities of daily living or simulated movements to complete activities as the intervention medium, could be more effective than rote exercise, which uses repetitive movements without added purpose, in preventing late-life disability in older people. With a growing number of studies in this area, systematically studying the effect of functional training is needed. The purpose of this systematic review was to examine the effects of functional training on the outcomes of activities of daily living, physical functioning, and cognitive function in community-dwelling older adults.MethodsLiterature published between January 2010 and April 2024 in 10 electronic databases were searched and screened. This timeframe was established to include studies published within the last 15 years. Each identified article was screened and reviewed by two authors independently. The methodological quality of the included studies was evaluated using the PEDro Scale. Key findings were synthesized according to participants' characteristics and intervention types.ResultsThe review included 32 studies. In the general community-dwelling older adult population (20 studies), studies that applied functional training as a single-component approach showed a positive effect on activities of daily living. However, the training effect on balance and mobility was not superior to that of other exercise programs. Moreover, the effect was mixed when functional training was combined with other intervention components. In older adults with mild cognitive impairment (5 studies), Simulated Functional Tasks Exercise, a single-component training, consistently demonstrated positive effects on the activities of daily living and cognitive functions. In older adults with dementia (4 studies) or frailty (3 studies), the effect was mixed across the single- and multi-component approaches.ConclusionFunctional training alone is effective in preventing late-life disability in general community-dwelling older adults. When training activities challenge both motor and cognitive abilities, the effect seems to improve the performance of activities of daily living and cognitive functions in older adults with mild cognitive impairment. Additional studies of functional training in older adults with cognitive impairment or frailty are recommended.

Project description:BackgroundRisk prediction models have been developed to identify those at increased risk for emergency admissions, which could facilitate targeted interventions in primary care to prevent these events.ObjectiveSystematic review of validated risk prediction models for predicting emergency hospital admissions in community-dwelling adults.MethodsA systematic literature review and narrative analysis was conducted. Inclusion criteria were as follows;Populationcommunity-dwelling adults (aged 18 years and above); Risk: risk prediction models, not contingent on an index hospital admission, with a derivation and ≥1 validation cohort;Primary outcomeemergency hospital admission (defined as unplanned overnight stay in hospital);Study designretrospective or prospective cohort studies.ResultsOf 18,983 records reviewed, 27 unique risk prediction models met the inclusion criteria. Eleven were developed in the United States, 11 in the United Kingdom, 3 in Italy, 1 in Spain, and 1 in Canada. Nine models were derived using self-report data, and the remainder (n=18) used routine administrative or clinical record data. Total study sample sizes ranged from 96 to 4.7 million participants. Predictor variables most frequently included in models were: (1) named medical diagnoses (n=23); (2) age (n=23); (3) prior emergency admission (n=22); and (4) sex (n=18). Eleven models included nonmedical factors, such as functional status and social supports. Regarding predictive accuracy, models developed using administrative or clinical record data tended to perform better than those developed using self-report data (c statistics 0.63-0.83 vs. 0.61-0.74, respectively). Six models reported c statistics of >0.8, indicating good performance. All 6 included variables for prior health care utilization, multimorbidity or polypharmacy, and named medical diagnoses or prescribed medications. Three predicted admissions regarded as being ambulatory care sensitive.ConclusionsThis study suggests that risk models developed using administrative or clinical record data tend to perform better. In applying a risk prediction model to a new population, careful consideration needs to be given to the purpose of its use and local factors.

Project description:BackgroundPolypharmacy and use of inappropriate medications have been linked to increased risk of falls, hospitalizations, cognitive impairment, and death. The primary objective of this review was to evaluate the effectiveness, comparative effectiveness, and harms of deprescribing interventions among community-dwelling older adults.MethodsWe searched OVID MEDLINE Embase, CINAHL, and the Cochrane Library from 1990 through February 2019 for controlled clinical trials comparing any deprescribing intervention to usual care or another intervention. Primary outcomes were all-cause mortality, hospitalizations, health-related quality of life, and falls. The secondary outcome was use of potentially inappropriate medications (PIMs). Interventions were categorized as comprehensive medication review, educational initiatives, and computerized decision support. Data abstracted by one investigator were verified by another. We used the Cochrane criteria to rate risk of bias for each study and the GRADE system to determine certainty of evidence (COE) for primary outcomes.ResultsThirty-eight low and medium risk of bias clinical trials were included. Comprehensive medication review may have reduced all-cause mortality (OR 0.74, 95% CI: 0.58 to 0.95, I2 = 0, k = 12, low COE) but probably had little to no effect on falls, health-related quality of life, or hospitalizations (low to moderate COE). Nine of thirteen trials reported fewer PIMs in the intervention group. Educational interventions probably had little to no effect on all-cause mortality, hospitalizations, or health-related quality of life (low to moderate COE). The effect on falls was uncertain (very low COE). All 11 education trials that included PIMs reported fewer in the intervention than in the control groups. Two of 4 computerized decision support trials reported fewer PIMs in the intervention arms; none included any primary outcomes.DiscussionIn community-dwelling people aged 65 years and older, medication deprescribing interventions may provide small reductions in mortality and use of potentially inappropriate medications.Registry informationPROSPERO - CRD42019132420.

Dataset Information

Prediction models for functional status in community dwelling older adults: a systematic review.

Background

Objective

Methods

Results

Conclusions

Publications

Prediction models for functional status in community dwelling older adults: a systematic review.

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