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Introduction As the population ages, increasing numbers of older adults are undergoing surgery. Outcomes for older people are known to be worse than younger people following surgical procedures, and identifying which patients stand to benefit from surgery can be challenging. Frailty is recognised as a major contributor to poor outcomes, however assessing frailty clinically is time-consuming and not routinely undertaken. Using data available from electronic medical records can potentially provide the opportunity to routinely screen for frailty electronically at time of admission. Objectives and Approach This population-based external validation study aimed to: 1. assess the performance of the Hospital Frailty Risk Score (HFRS) in the prediction of adverse outcomes (mortality, prolonged length of stay (LOS) and 28-day readmission), 2. to determine optimal age-groups and lookback periods and 3. compare HFRS performance against the Charlson Comorbidity Index (CCI). Hospital and death data for individuals (n=487,197) aged >50 years admitted under a surgical specialty to all public/private hospitals in NSW, Australia, 2013-2017 were linked. Logistic regression models were tested for each outcome of interest. Area under receiving operator curve (AUC) and Akaike information criterion (AIC) were assessed for each model. Results For prediction of 30-day, all models performed better than age and sex alone; however adjusting for CCI (AUC 0.76) provided marginally better prediction than adjusting for HFRS (AUC 0.75). Models consistently performed better in the younger age-group (50-65), providing excellent discrimination (AUC 0.82). In contrast, all models had poor ability to predict prolonged-LOS (AUC range 0.62- 0.63) or readmission (AUC range 0.62-0.65). Using a 5-year lookback period did not improve model discrimination over using a 2-year period. Conclusion / Implications Adjusting for frailty using the HFRS did not improve prediction of 30-mortality over that achieved by the CCI. Neither HFRS nor CCI were useful for predicting prolonged-LOS r 28-day unplanned readmission.

Introduction Data-linkage studies using administrative hospital data have shown that people with dementia have double the rate of injury-related hospitalisations and poorer health outcomes than those without. No previous research has explored whether people with mild cognitive impairment are also at increased risk of serious injury requiring hospitalisation. Objectives and Approach A major barrier to the use of administrative hospital data for undertaking research focusing on people with MCI is that MCI cannot be reliably identified from ICD-10 coded administrative data. To overcome this limitation, hospitalisation and death data was linked to data from participants (community-dwelling 70-90 year olds) enrolled in the population-based longitudinal Sydney Memory and Ageing Study (MAS). MAS participants underwent comprehensive neuropsychological assessments at baseline, then 2, 4 and 6 years’ follow-up to accurately determine cognitive status at each time-period. Linkage to hospital records allowed identification of injury-related hospitalisations and outcomes for the 2-year period following each assessment. Results There were 335 injury-related hospitalisations for the 867 participants; 222 (25.6%) participants had at least one injury-related hospitalisation. After adjusting for age-and-sex, participants in a state of MCI had 1.7 (95%CI 1.2-2.4) times higher odds of an injury-related hospitalisation than participants in a state of normal cognition, whilst participants with dementia had 2.3 (95%CI 1.2-4.4) times higher odds. There was no difference in odds between participants with MCI and dementia. Of the 116 hospitalisations for people with MCI, the majority (79.3%) were due to falls. Non-fracture head injuries (25.9%), upper limb and trunk fractures (13.8% respectively) were the most common injury type. There were no differences in injury type, mean length of stay, or 30-day mortality between people with normal cognition, MCI and dementia. Conclusion/Implications Older people with objectively defined MCI are at higher risk of injury, predominantly as a result of falls, than their cognitively intact peers. Falls-risk screening and fall prevention initiatives may be indicated for people with MCI. Further research is required to determine which cognitive domains contribute to this increased risk.