To explore the effect of sleep duration at baseline on the incident IADL disability among middle-aged and older Chinese, and test whether cognition mediates this causality. Data were collected from wave 1 (2011-2012) to wave 3 (2015-2016) of the China Health and Retirement Longitudinal Study (CHARLS). Sleep duration was self-reported at baseline. Cognitive function, including episodic memory and mental intactness were measured via a questionnaire. IADL was assessed at baseline and follow-up. Baron and Kenny's causal steps and Karlson/Holm/Breen (KHB) method were conducted to examine the mediating effect. A total of 10,328 participants free of IADL disability at baseline were included in this study. Over 4 years of follow-up, 17.1% of participants developed IADL disability. Compared to 7-8 h sleep duration, both short sleep (OR=1.460; 95% CI 1.261-1.690 for sleeping ≤5 h; OR= 1.189; 95% CI 1.011-1.400 for sleeping 5-7 h) and long sleep (OR=1.703; 95% CI 1.269-2.286 for sleeping >9 h) were linked with incident IADL disability. KHB method identified significant mediating effect of cognition on the relationship between extreme sleep durations (≤5 h or >9 h) and IADL disability and the proportional mediation through cognition was 21.32% and 21.06% for sleeping ≤5 h and >9 h, respectively. Both short (sleeping ≤5 h) and long sleep duration (sleeping >9 h) predicted incident IADL disability. Cognition partially mediated the effect of extreme sleep durations on IADL disability. 9 h) predicted incident IADL disability. Cognition partially mediated the effect of extreme sleep durations on IADL disability. Several techniques are available to identify, among patients with mild cognitive impairment (MCI), those at risk of conversion to Alzheimer dementia (CAD). However, simple cost-effective methods to assess the risk are not available yet. This retrospective study included 143 MCI outpatients (76.6±5.2 years, 46.8% women). Baseline variables were common neuropsychological tests (including Mini Mental State Examination-MMSE and Montreal Cognitive Assessment-MoCA), brain CT and 18F-fluorodeoxyglucose (FDG)-PET. Outcome variable was CAD after 1 year. At follow-up, 31 (21.7%) patients had CAD. In multivariable analysis (OR, 95% CI), female sex (4.7, 1.6-14.0), MoCA-executive component <3 (6.3, 2.1-19.2), left medial temporal atrophy (MTA) ≥3 (5.4, 1.9-15.7) and FDG-PET suggesting CAD (5.4, 1.9-15.7) were associated with CAD (area under ROC curve 0.873). Without FDG-PET, MMSE score <28 remained associated with CAD (6.0, 2.2-16.9). As first step (before FDG-PET execution), we counted 1 point for MMSE <28, executive MoCA <3 and left MTA ≥3. With 2-3 points CAD probability was high (75%) and with 0 points it was low (6.5%). Thus, FDG-PET (second step) might be performed only in patients with 1 point (probability 19.7%, 42.7% of patients). Among them, 35% had a positive FDG-PET, suggesting high risk. Overall, 28.0% of patients were considered at high risk (specificity 83.9%, sensitivity 71.0%, accuracy 81.1%). With a 2-step procedure, less than half of MCI patients might undergo FDG-PET and nearly a quarter of our patients was found to be at high CAD risk, including almost three quarters of future CADs. With a 2-step procedure, less than half of MCI patients might undergo FDG-PET and nearly a quarter of our patients was found to be at high CAD risk, including almost three quarters of future CADs. This study aimed to determine the incidence, predictors of postoperative delirium and develop a post-surgery delirium risk scoring tool. A total of 6672 hip fracture patients with documented assessment for delirium were analyzed from the Australia and New Zealand Hip Fracture Registry between June 2017 and December 2018.Thirty-six variables for the prediction of delirium using univariate and multivariate logistic regression were assessed. The models were assessed for diagnostic accuracy using C-statistic and calibration using Hosmer-Lemeshow goodness-of-fit test. A Delirium Risk Score was developed based on the regression coefficients. Delirium developed in 2599/6672 (39.0%) hip fracture patients. Seven independent predictors of delirium were identified; age above 80 years (OR=1.6 CI 1.4-1.9; p=0.001), male (OR=1.3 CI 1.1-1.5; p=0.007), absent pre-operative cognitive assessment (OR=1.5 CI 1.3-1.9; p=0.001), impaired pre-operative cognitive state (OR=1.7 CI 1.3 -2.1; p=0.001), surgery delay (OR=1.7 CI 1.2-2.5; p=0.002) and mobilisation day 1 post-surgery (OR=1.9 CI 1.4-2.6; p=0.001). https://www.selleckchem.com/products/lxs-196.html The C-statistics for the training and validation datasets were 0.74 and 0.75, respectively. Calibration was good (χ2=35.72 (9); p<0.001). The Delirium Risk Score for patients ranged from 0 to 42 in the validation data and when used alone as a risk predictor, had similar levels of diagnostic accuracy (C-statistic=0.742) indicating its potential for use as a stand-alone risk scoring tool. We have designed and validated a delirium risk score for predicting delirium following surgery for a hip fracture using seven predicting factors. This could assist clinicians in identifying high risk patients requiring higher levels of observation and post-surgical care. We have designed and validated a delirium risk score for predicting delirium following surgery for a hip fracture using seven predicting factors. This could assist clinicians in identifying high risk patients requiring higher levels of observation and post-surgical care. The aim of this study was to investigate the effects of pre-stroke frailty status on short-term functional outcome in older patients with acute stroke. In this prospective longitudinal study, we assessed the pre-stroke frailty status (robust, prefrail, or frail) by the Frailty Screening Index, disease severity by the National Institutes of Stroke Scale (NIHSS), and short-term functional outcome by the modified Rankin Scale (mRS) at discharge from acute hospital in patients with older stroke. We considered poor functional outcome to be a mRS >2. Logistic regression analysis and mediation analysis were used to investigate the relationships among pre-stroke frailty status, disease severity, length of stay (LOS), and short-term functional outcome. A total of 232 patients were enrolled in this study. The NIHSS and LOS were significantly different between groups (p<0.001, p=0.01, respectively), but there was no relationship between frailty status and short-term functional outcome (p=0.22). Based on the logistic regression analyses after adjusting for potential confounders, the NIHSS (odds ratio (OR) 1.