Predicting dementia from primary care records: a systematic review and meta-analysis

Introduction Possible dementia is usually identified in primary care by general practitioners (GPs) who refer to specialists for diagnosis. Only two-thirds of dementia cases are currently recorded in primary care, so increasing the proportion of cases diagnosed is a strategic priority for the UK and internationally. Clinical entities in the primary care record may indicate risk of developing dementia, and could be combined in a predictive model to help find patients who are missing a diagnosis. We conducted a meta-analysis to identify clinical entities with potential for use in such a predictive model for dementia in primary care. Methods and Findings We conducted a systematic search in PubMed, Web of Science and primary care database bibliographies. We included cohort or case-control studies which used routinely collected primary care data, to measure the association between any clinical entity and dementia. Meta-analyses were performed to pool odds ratios. A sensitivity analysis assessed the impact of non-independence of cases between studies. From a sift of 3836 papers, 20 studies, all European, were eligible for inclusion, comprising >1 million patients. 75 clinical entities were assessed as risk factors for all cause dementia, Alzheimer’s (AD) and Vascular dementia (VaD). Data included were unexpectedly heterogeneous, and assumptions were made about definitions of clinical entities and timing as these were not all well described. Meta-analysis showed that neuropsychiatric symptoms including depression, anxiety, and seizures, cognitive symptoms, and history of stroke, were positively associated with dementia. Cardiovascular risk factors such as hypertension, heart disease, dyslipidaemia and diabetes were positively associated with VaD and negatively with AD. Sensitivity analyses showed similar results. Conclusions These findings are of potential value in guiding feature selection for a risk prediction tool for dementia in primary care. Limitations include findings being UK-focussed. Further predictive entities ascertainable from primary care data, such as changes in consulting patterns, were absent from the literature and should be explored in future studies

Abstract WP182: Long Term Risk of Ischemic Stroke After Acute Coronary Syndrome

Background: Prior studies have shown an increased risk of ischemic stroke (IS) after myocardial infarction (MI), particularly in the first few days after the event. There is limited evidence, however, on the long-term risk and whether it is directly related to cardiac injury. We hypothesized that the risk of IS after acute coronary syndrome (ACS) is significantly higher when there is evidence of cardiac injury such as ST elevation MI (STEMI) or non-STEMI (NSTEMI) than when there is no evidence of cardiac injury such as Unstable Angina (UA). Methods: Administrative claims data were obtained from all emergency department encounters and hospitalizations at California’s nonfederal acute care hospitals between 2008 and 2011. Patients with STEMI, NSTEMI, and UA were identified using appropriate ICD-9 codes. Age and ICD-9 codes for sex, race-ethnicity, hypertension, diabetes, hyperlipidemia, congestive heart failure, and atrial fibrillation were analyzed. The outcome was IS during 2 years follow-up. Unadjusted and adjusted Cox proportional hazards models were used to determine the association between ACS subtype and ischemic stroke risk. Results: We identified 74,962 ACS patients: 35.9% STEMI, 54.8% NSTEMI, and 9.3% UA. The mean age in years was 66.7 ± 14.4 and 61.5% females; 3.2% of patients had IS during the two year follow-up. When compared to UA, the long term risk of IS was higher in patients with STEMI (adjusted HR 2.07 95% CI 1.67-2.56) and NSTEMI (adjusted HR 1.87, 95% CI 1.51-2.30), even after adjusting for stroke risk factors at baseline and incident atrial fibrillation (Figure). Other stroke risk factors after ACS are shown in the Figure. Conclusion: Analysis from a large administrative dataset revealed that both NSTEMI and STEMI confer an increased risk of ischemic stroke, independent of risk factors, which may be related to cardiac injury. Studies exploring ischemic stroke mechanisms in cardiac patients are needed to improve and tailor stroke prevention strategies. </jats:p

The impact of specimen size and alteration of fiber configuration on the flexural performance of high-performance concrete

This study examines the impact of fiber configuration and specimen size on the flexural performance and thus the energy absorption capacity of moderate and high-performance fiber reinforced concrete (FRC). A total of 180 specimens were produced using hooked-end steel fibers in lengths of 30-mm and 60-mm, and 54-mm long macro synthetic fibers. The specimens, in the form of small beams (75 × 75 × 320 mm3), large beams (150 × 150 × 750 mm3), and square panel specimens (600 × 600 × 100 mm3), were tested in accordance with EN14488-5 and ASTM C1609 standards. The results showed that as the amount of fibers increased, the flexural performance of FRC improved significantly, provided that precautions were taken to avoid mixing and placement issues when using higher amounts of fibers. 60-mm hooked-end steel fibers had the best performance among all the fibers tested with higher ultimate and post-cracking flexural strengths. 54-mm synthetic fibers seemed to be a cost-effective alternative with comparable energy absorption performance when compared to 30-mm hooked-end steel fibers. Small beams had a slightly higher ultimate (∼15% more) and post-cracking (∼35% more) flexural strengths than large beams, but the equivalent flexural strength ratio was not significantly affected by the specimen size. No clear relationship between fiber dosage and ultimate flexural strength was observed, but a relationship was observed between the fiber dosage and the equivalent flexural strength ratio, with R2 values ranging from 65% to 93% depending on the concrete matrix and the fiber type. The study also showed strong correlations (R2>91%) between the energy absorption capacity of plate specimens and beam specimens, suggesting that plate specimens can be used to reduce the time and effort required in testing during trial batches and product development. Finally, the use of high-performance concrete does not seem to be necessary, when the target is to improve the energy absorption capacity of FRC, particularly at low fiber volumes