| Autor: |
Anup K. Mishra, Marjorie Skubic, Mihail Popescu, Kari Lane, Marilyn Rantz, Laurel A. Despins, Carmen Abbott, James Keller, Erin L. Robinson, Steve Miller |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
BMC Medical Informatics and Decision Making, Vol 20, Iss 1, Pp 1-10 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1472-6947 |
| DOI: |
10.1186/s12911-020-01283-y |
| Popis: |
Abstract Background Higher levels of functional health in older adults leads to higher quality of life and improves the ability to age-in-place. Tracking functional health objectively could help clinicians to make decisions for interventions in case of health deterioration. Even though several geriatric assessments capture several aspects of functional health, there is limited research in longitudinally tracking personalized functional health of older adults using a combination of these assessments. Methods We used geriatric assessment data collected from 150 older adults to develop and validate a functional health prediction model based on risks associated with falls, hospitalizations, emergency visits, and death. We used mixed effects logistic regression to construct the model. The geriatric assessments included were Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), and Short Form 12 (SF12). Construct validators such as fall risks associated with model predictions, and case studies with functional health trajectories were used to validate the model. Results The model is shown to separate samples with and without adverse health event outcomes with an area under the receiver operating characteristic curve (AUC) of > 0.85. The model could predict emergency visit or hospitalization with an AUC of 0.72 (95% CI 0.65–0.79), fall with an AUC of 0.86 (95% CI 0.83–0.89), fall with hospitalization with an AUC of 0.89 (95% CI 0.85–0.92), and mortality with an AUC of 0.93 (95% CI 0.88–0.97). Multiple comparisons of means using Turkey HSD test show that model prediction means for samples with no adverse health events versus samples with fall, hospitalization, and death were statistically significant (p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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