Hip fractures in the winter - Using the National Hip Fracture Database to examine seasonal variation in incidence and mortality.

We set out to examine the implications of seasonal variation in hip fracture for trauma services and for the frail older people who typically suffer this injury. Since 2007 the National Hip Fracture Database (NHFD) has been reporting data for all over-60 year old patients presenting in England, Wales and Northern Ireland. We analysed published NHFD data for the 450,764 people who presented during the seven years from April 2011 to March 2018. We found marked seasonal variation in the number of people presenting: 8% more people presenting in the winter months (December-February) than in the summer (June-August). The total number of people dying within 30 days of hip fracture was 30.5% higher among those presenting in these winter months. In total 33,649 people (7.5%) died within 30 days of hip fracture, but this figure varied significantly (p < 0.001, Chi2 test); ranging from 6.7% in July to 8.7% (30% higher) in January. The public health impact of these findings is significant. An 8% increase in hip fracture numbers during the winter would equate with 1250 additional fractures during these months each year. Patients average over 20 days in hospital, so these additional cases will compound the stresses on hospital services over the Christmas and New Year holiday period. Such factors must be taken into consideration when organising trauma services if we are to try and avoid the additional 325 deaths that we found to occur each winter.

Acute kidney injury risk assessment at the hospital front door: what is the best measure of risk?

BACKGROUND: We examined the prevalence of acute kidney injury (AKI) risk factors in the emergency medical unit, generated a modified risk assessment tool and tested its ability to predict AKI. METHODS: A total of 1196 patients admitted to medical admission units were assessed for patient-associated AKI risk factors. Subsequently, 898 patients were assessed for a limited number of fixed risk factors with the addition of hypotension and sepsis. This was correlated to AKI episodes. RESULTS: In the first cohort, the prevalence of AKI risk factors was 2.1 ± 2.0 per patient, with a positive relationship between age and the number of risk factors and a higher number of risk factors in patients ≥65 years. In the second cohort, 12.3% presented with or developed AKI. Patients with AKI were older and had a higher number of AKI risk factors. In the AKI cohort, 72% of the patients had two or more AKI risk factors compared with 43% of the cohort with no AKI. When age ≥65 years was added as an independent risk factor, 84% of those with AKI had two or more AKI risk factors compared with 55% of those with no AKI. Receiver operating characteristic analysis suggests that the use of common patient-associated known AKI risk factors performs no better than age alone as a predictor of AKI. CONCLUSIONS: Detailed assessment of well-established patient-associated AKI risk factors may not facilitate clinicians to apportion risk. This suggests that additional work is required to develop a more sensitive validated AKI-predictive tool that would be useful in this clinical setting.