OBJECTIVES: Examine cognitive changes over time among nursing home residents and develop a risk model for identifying predictors of cognitive decline. DESIGN: Using secondary analysis design with Minimum Data Set data, cognitive status was based on the Cognitive Performance Scale (CPS). SETTING AND PARTICIPANTS: Baseline and 7 quarterly follow-up analyses of US and Canadian interRAI data (N = 1,257,832) were completed. METHODS: Logistic regression analyses identified predictors of decline to form the CogRisk-NH scale. RESULTS: At baseline, about 15% of residents were cognitively intact (CPS = 0), and 11.2% borderline intact (CPS = 1). The remaining more intact, with mild impairment (CPS = 2), included 15.0%. Approximately 59% residents fell into CPS categories 3 to 6 (moderate to severe impairment). Over time, increasing proportions of residents declined: 17.1% at 6 months, 21.6% at 9 months, and 34.0% at 21 months. Baseline CPS score was a strong predictor of decline. Categories 0 to 2 had 3-month decline rates in midteens, and categories 3 to 5 had an average decline rate about 9%. Consequently, a 2-submodel construction was employed-one for CPS categories 0 to 2 and the other for categories 3 to 5. Both models were integrated into a 6-category risk scale (CogRisk-NH). CogRisk-NH scale score distribution had 15.9% in category 1, 26.84% in category 2, and 36.7% in category 3. Three higher-risk categories (ie, 4-6) represented 20.6% of residents. Mean decline rates at the 3-month assessment ranged from 4.4% to 28.3%. Over time, differentiation among risk categories continued: 6.9% to 38.4.% at 6 months, 11.0% to 51.0% at 1 year, and 16.2% to 61.4% at 21 months, providing internal validation of the prediction model. CONCLUSIONS AND IMPLICATIONS: Cognitive decline rates were higher among residents in less-impaired CPS categories. CogRisk-NH scale differentiates those with low likelihood of decline from those with moderate likelihood and, finally, much higher likelihood of decline. Knowledge of resident risk for cognitive decline enables allocation of resources targeting amenable factors and potential interventions to mitigate continuing decline.

• MeSH
• kognice MeSH
• kognitivní dysfunkce * diagnóza   MeSH
• lidé MeSH
• pečovatelské domovy * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Kanada MeSH

OBJECTIVE: The care processes directed towards institutionalized older people needs to be tailored on goals and priorities that are relevant for this specific population. The aim of the present study was (a) to describe the distribution of selected health determinants in a sample of institutionalized older adults, and (b) to investigate the impact on survival of such measures. DESIGN: Multicentre longitudinal cohort-study. SETTING: 57 nursing homes (NH) in 7EU countries (Czech Republic, England, Finland, France, Germany, Italy, The Netherlands) and 1 non-EU country (Israel). PARTICIPANTS: 3036 NH residents participating in the Services and Health for Elderly in Long TERm care (SHELTER) study. MEASUREMENTS: We described the distribution of 8 health determinants (smoking habit, alcohol use, body mass index [BMI], physical activity, social participation, family visits, vaccination, and preventive visits) and their impact on 1-year mortality. RESULTS: During the one-year follow up, 611 (20%) participants died. Overweight (HR 0.79; 95% C.I. 0.64-0.97) and obesity (HR 0.64; 95% C.I. 0.48-0.87) resulted associated with lower mortality then normal weight. Similarly, physical activity (HR 0.67; 95% C.I. 0.54-0.83), social activities (HR 0.63; 95% C.I. 0.51-0.78), influenza vaccination (HR 0.66; 95% C.I. 0.55-0.80) and pneumococcal vaccination (HR 0.76 95% C.I. 0.63-0.93) were associated with lower mortality. Conversely, underweight (HR 1.28; 95% C.I. 1.03-1.60) and frequent family visits (HR 1.75; 95% C.I. 1.27-2.42) were associated with higher mortality. CONCLUSIONS: Health determinants in older NH residents depart from those usually accounted for in younger and fitter populations. Ad hoc studies are warranted in order to describe other relevant aspects of health in frail older adults, with special attention on those institutionalized, with the ultimate goal of improving the quality of care and life.

• MeSH
• cvičení MeSH
• hubenost MeSH
• index tělesné hmotnosti MeSH
• interpersonální vztahy MeSH
• kohortové studie MeSH
• kouření MeSH
• křehký senior statistika a číselné údaje   MeSH
• lidé MeSH
• nadváha MeSH
• pečovatelské domovy statistika a číselné údaje   MeSH
• pití alkoholu MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• vakcinace MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Evropa epidemiologie   MeSH

INTRODUCTION: In ageing societies, the number of older adults with complex chronic conditions (CCCs) is rapidly increasing. Care for older persons with CCCs is challenging, due to interactions between multiple conditions and their treatments. In home care and nursing homes, where most older persons with CCCs receive care, professionals often lack appropriate decision support suitable and sufficient to address the medical and functional complexity of persons with CCCs. This EU-funded project aims to develop decision support systems using high-quality, internationally standardised, routine care data to support better prognostication of health trajectories and treatment impact among older persons with CCCs. METHODS AND ANALYSIS: Real-world data from older persons aged ≥60 years in home care and nursing homes, based on routinely performed comprehensive geriatric assessments using interRAI systems collected in the past 20 years, will be linked with administrative repositories on mortality and care use. These include potentially up to 51 million care recipients from eight countries: Italy, the Netherlands, Finland, Belgium, Canada, USA, Hong Kong and New Zealand. Prognostic algorithms will be developed and validated to better predict various health outcomes. In addition, the modifying impact of pharmacological and non-pharmacological interventions will be examined. A variety of analytical methods will be used, including techniques from the field of artificial intelligence such as machine learning. Based on the results, decision support tools will be developed and pilot tested among health professionals working in home care and nursing homes. ETHICS AND DISSEMINATION: The study was approved by authorised medical ethical committees in each of the participating countries, and will comply with both local and EU legislation. Study findings will be shared with relevant stakeholders, including publications in peer-reviewed journals and presentations at national and international meetings.

• MeSH
• algoritmy MeSH
• chronická nemoc MeSH
• lidé MeSH
• pozorovací studie jako téma MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• služby domácí péče * MeSH
• stárnutí MeSH
• umělá inteligence * MeSH
• Check Tag
• lidé MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• Publikační typ
• časopisecké články MeSH

• MeSH
• ambulantní zařízení * MeSH
• chůze MeSH
• geriatrické hodnocení MeSH
• kosterní svaly patofyziologie   MeSH
• lidé MeSH
• prevalence MeSH
• sarkopenie diagnóza   epidemiologie   MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• síla ruky MeSH
• složení těla MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• dopisy MeSH