Age and ageing · 2014
Optimal screening for increased risk for adverse outcomes in hospitalised older adults.
СтатьяМногоцентровое исследованиеНаблюдательное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Heim Noor, van Fenema Ester M, Weverling-Rijnsburger Annelies W E, Tuijl Jolien P, Jue Peter, Oleksik Anna M, Verschuur Margot J, Haverkamp Jasper S, Blauw Gerard Jan, van der Mast Roos C, Westendorp Rudi G J
Аннотация
BACKGROUND: Screening for frailty might help to prevent adverse outcomes in hospitalised older adults.
OBJECTIVE: To identify the most predictive and efficient screening tool for frailty.
DESIGN AND SETTING: Two consecutive observational prospective cohorts in four hospitals in the Netherlands.
SUBJECTS: Patients aged ≥70 years, electively or acutely hospitalised for ≥2 days.
METHODS: Screening instruments included in the Dutch Safety Management Programme [VeiligheidsManagementSysteem (VMS)] on four geriatric domains (ADL, falls, undernutrition and delirium) were used and the Identification of Seniors At Risk, the 6-item Cognitive Impairment Test and the Mini-Mental State Examination were assessed. Three months later, adverse outcomes including functional decline, high-healthcare demand or death were determined. Correlation and regression tree analyses were performed and predictive capacities were assessed.
RESULTS: Follow-up data were available of 883 patients. All screening instruments were similarly predictive for adverse outcome (predictive power 0.58-0.66), but the percentage of positively screened patients (13-72%), sensitivity (24-89%) and specificity (35-91%) highly differed. The strongest predictive model for frailty was scoring positive on ≥3 VMS domains if aged 70-80 years; or being aged ≥80 years and scoring positive on ≥1 VMS domains. This tool classified 34% of the patients as frail with a sensitivity of 68% and a specificity of 74%. Comparable results were found in the validation cohort.
CONCLUSIONS: The VMS-tool plus age (VMS+) offers an efficient instrument to identify frail hospitalised older adults at risk for adverse outcome. In clinical practice, it is important to weigh costs and benefits of screening given the rather low-predictive power of screening instruments.
OBJECTIVE: To identify the most predictive and efficient screening tool for frailty.
DESIGN AND SETTING: Two consecutive observational prospective cohorts in four hospitals in the Netherlands.
SUBJECTS: Patients aged ≥70 years, electively or acutely hospitalised for ≥2 days.
METHODS: Screening instruments included in the Dutch Safety Management Programme [VeiligheidsManagementSysteem (VMS)] on four geriatric domains (ADL, falls, undernutrition and delirium) were used and the Identification of Seniors At Risk, the 6-item Cognitive Impairment Test and the Mini-Mental State Examination were assessed. Three months later, adverse outcomes including functional decline, high-healthcare demand or death were determined. Correlation and regression tree analyses were performed and predictive capacities were assessed.
RESULTS: Follow-up data were available of 883 patients. All screening instruments were similarly predictive for adverse outcome (predictive power 0.58-0.66), but the percentage of positively screened patients (13-72%), sensitivity (24-89%) and specificity (35-91%) highly differed. The strongest predictive model for frailty was scoring positive on ≥3 VMS domains if aged 70-80 years; or being aged ≥80 years and scoring positive on ≥1 VMS domains. This tool classified 34% of the patients as frail with a sensitivity of 68% and a specificity of 74%. Comparable results were found in the validation cohort.
CONCLUSIONS: The VMS-tool plus age (VMS+) offers an efficient instrument to identify frail hospitalised older adults at risk for adverse outcome. In clinical practice, it is important to weigh costs and benefits of screening given the rather low-predictive power of screening instruments.
Предметные рубрики MeSH
Accidental FallsActivities of Daily LivingAge FactorsAgedAged, 80 and overAgingDeliriumFemaleFrail ElderlyGeriatric AssessmentHealth StatusHospitalizationHumansMaleNetherlandsNeuropsychological TestsNutrition AssessmentNutritional StatusPredictive Value of TestsPrognosisProspective StudiesRisk AssessmentRisk FactorsSurveys and QuestionnairesTime Factors