BackgroundCognitive impairment of various kinds is common in older people admitted to hospital, but previous research has usually focused on single conditions in highly-selected groups and has rarely examined associations with outcomes. This study examined prevalence and outcomes of cognitive impairment in a large unselected cohort of people aged 65+ with an emergency medical admission.MethodsBetween January 1, 2012, and June 30, 2013, admissions to a single general hospital acute medical unit aged 65+ underwent a structured specialist nurse assessment (n = 10,014). We defined ‘cognitive spectrum disorder’ (CSD) as any combination of delirium, known dementia, or Abbreviated Mental Test (AMT) score < 8/10. Routine data for length of stay (LOS), mortality, and readmission were linked to examine associations with outcomes.ResultsA CSD was present in 38.5% of all patients admitted aged over 65, and in more than half of those aged over 85. Overall, 16.7% of older people admitted had delirium alone, 7.9% delirium superimposed on known dementia, 9.4% known dementia alone, and 4.5% unspecified cognitive impairment (AMT score < 8/10, no delirium, no known dementia). Of those with known dementia, 45.8% had delirium superimposed. Outcomes were worse in those with CSD compared to those without – LOS 25.0 vs. 11.8 days, 30-day mortality 13.6% vs. 9.0%, 1-year mortality 40.0% vs. 26.0%, 1-year death or readmission 62.4% vs. 51.5% (all P < 0.01). There was relatively little difference by CSD type, although people with delirium superimposed on dementia had the longest LOS, and people with dementia the worst mortality at 1 year.ConclusionsCSD is common in older inpatients and associated with considerably worse outcomes, with little variation between different types of CSD. Healthcare systems should systematically identify and develop care pathways for older people with CSD admitted as medical emergencies, and avoid only focusing on condition-specific pathways such as those for dementia or delirium alone.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-017-0899-0) contains supplementary material, which is available to authorized users.

Background The application of a uniform definition for acute kidney injury (AKI) is vital to advance understanding and management of AKI. International Classification of Diseases (Tenth Revision) (ICD-10) coding is frequently used to define AKI, but its accuracy is unclear. The aim of this study was to determine whether ICD-10 coding is a reliable method of monitoring rates and outcomes of AKI in inpatients compared with biochemically defined AKI, and whether electronic alerts (e-alerts) for AKI affect ICD-10 AKI coding. Methods An observational cohort study of all 505 662 adult admissions to acute hospitals in two Scottish Health Boards [National Health Service (NHS) Tayside and NHS Fife] from January 2013 to April 2017 was performed. AKI e-alerts were implemented in NHS Tayside in April 2015. Sensitivity, specificity, positive and negative predictive values of ICD-10 coding for AKI compared with biochemically defined AKI using the Kidney Disease: Improving Global Outcomes definition and relative risk of 30-day mortality in people with ICD-10 and biochemically defined AKI before and after AKI e-alert implementation were performed. Results Sensitivity of ICD-10 coding for identifying biochemically defined AKI was very poor in both health boards for all AKI (Tayside 25.7% and Fife 35.8%) and for Stages 2 and 3 AKI (Tayside 43.8% and Fife 53.8%). Positive predictive value was poor both for all AKI (Tayside 76.1% and Fife 45.5%) and for Stages 2 and 3 AKI (Tayside 45.5% and Fife 36.8%). Measured mortality fell following implementation of AKI e-alerts in the ICD-10-coded population but not in the biochemically defined AKI population, reflecting an increase in the proportion of Stage 1 AKI in ICD-10-coded AKI. There was no evidence that the introduction of AKI e-alerts in Tayside improved ICD-10 coding of AKI. Conclusion ICD-10 coding should not be used for monitoring of rates and outcomes of AKI for either research or improvement programmes.

Background Improving recognition of patients at increased risk of acute kidney injury (AKI) in the community may facilitate earlier detection and implementation of proactive prevention measures that mitigate the impact of AKI. The aim of this study was to develop and externally validate a practical risk score to predict the risk of AKI in either hospital or community settings using routinely collected data. Methods Routinely collected linked datasets from Tayside, Scotland, were used to develop the risk score and datasets from Kent in the UK and Alberta in Canada were used to externally validate it. AKI was defined using the Kidney Disease: Improving Global Outcomes serum creatinine–based criteria. Multivariable logistic regression analysis was performed with occurrence of AKI within 1 year as the dependent variable. Model performance was determined by assessing discrimination (C-statistic) and calibration. Results The risk score was developed in 273 450 patients from the Tayside region of Scotland and externally validated into two populations: 218 091 individuals from Kent, UK and 1 173 607 individuals from Alberta, Canada. Four variables were independent predictors for AKI by logistic regression: older age, lower baseline estimated glomerular filtration rate, diabetes and heart failure. A risk score including these four variables had good predictive performance, with a C-statistic of 0.80 [95% confidence interval (CI) 0.80–0.81] in the development cohort and 0.71 (95% CI 0.70–0.72) in the Kent, UK external validation cohort and 0.76 (95% CI 0.75–0.76) in the Canadian validation cohort. Conclusion We have devised and externally validated a simple risk score from routinely collected data that can aid both primary and secondary care physicians in identifying patients at high risk of AKI.