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Frailty is very common in old age and often associated with adverse events. Transitioning between frailty states is possible in both directions (improvement and worsening) offering targets for interventions. Frailty is more prevalent in women, but little is known about the impact of gender on frailty transition. The aim of this study is to identify gender differences for frailty transition in older adults and to develop gender-stratified prognostic prediction models for frailty transition. We performed a longitudinal analyses of the Berlin Initiative (cohort) Study with a frailty follow-up of 2.1 years. Description of frailty transition using the frailty phenotype and development of prognostic prediction models using multivariable logistic regressions for transition (improvement or worsening) stratified by gender following the TRIPOD statement were performed. In total, the study population consisted of 1158 community-dwelling adults with a mean age of 84.4 years and of whom 55% were women. Out of 1158 participants 225 (19%) were robust, 532 (46%) prefrail and 401 (35%) frail. After 2.1 (IQR 2.0–2.3) years, half of the participants had transitioned between frailty states. Men worsened more often and those who were already frail died more often than women. Gender-stratified prediction models for frailty transition demonstrated that some predictors (age, self-rated health, cognitive impairment, baseline frailty status) were included in all models. While stroke, diabetes mellitus, smoking and glomerular filtration rate were unique predictors in the models for females, osteoarthritis, hospitalization and education were predictors in the models for males. There are gender differences in frailty transition rates, patterns and prediction. This supports the importance of considering gender when addressing frailty and targeting interventions in old age. [ABSTRACT FROM AUTHOR]

Zinc-alpha 2-glycoprotein (AZGP1) is a serum protein with postulated functions in metabolism, cancer and cardiovascular disease. We developed new prediction models for mortality or cardiovascular events investigating the predictive potential of serum AZGP1 in a community-based cohort of older adults. We measured AZGP1 (μg/ml) in stored serum samples of 930 individuals of the Berlin Initiative Study, a prospective, population-based cohort of adults aged ≥ 70. We determined the prognostic potential of 20 knowledge-based predictors including AZGP1 for the outcomes of mortality or the composite endpoint of death and cardiovascular events (stroke, myocardial infarction (MI)) using Cox models; their model fit was evaluated with calibration plots, goodness-of-fit tests and c-indices. During median follow-up of 48.3 months, 70 incident strokes, 38 incident MI and 234 deaths occurred. We found no associations or correlations between AZGP1 and other candidate variables. After multivariable Cox regression with backward-selection AZGP1 remained in both models for mortality (HR = 0.44, 95%CI: 0.24–0.80) and for the composite endpoint (HR = 0.43, 95%CI: 0.23–0.82). Within newly built prediction models, we found that increased AZGP1 levels were predictive for lower risk of mortality and the composite endpoint in older adults. AZGP1 as a predictor warrants further validation in older adults. [ABSTRACT FROM AUTHOR]