Neutrophil gelatinase-associated lipocalin: a biochemical marker for acute kidney injury and long-term outcomes in patients presenting to the emergency department

INTRODUCTION@#Creatinine has limitations in identifying and predicting acute kidney injury (AKI). Our study examined the utility of neutrophil gelatinase-associated lipocalin (NGAL) in predicting AKI in patients presenting to the emergency department (ED), and in predicting the need for renal replacement therapy (RRT), occurrence of major adverse cardiac events (MACE) and all-cause mortality at three months post visit.@*METHODS@#This is a single-centre prospective cohort study conducted at Singapore General Hospital (SGH). Patients presenting to SGH ED from July 2011 to August 2012 were recruited. They were aged ≥21 years, with an estimated glomerular filtration rate <60 mL/min/1.73 m2, and had congestive cardiac failure, systemic inflammatory response syndrome or required hospital admission. AKI was diagnosed by researchers blinded to experimental measurements. Serum NGAL was measured as a point-of-care test.@*RESULTS@#A total of 784 patients were enrolled, of whom 107 (13.6%) had AKI. Mean serum NGAL levels were raised (P < 0.001) in patients with AKI (670.0 ± 431.9 ng/dL) compared with patients without AKI (490.3 ± 391.6 ng/dL). The sensitivity and specificity of NGAL levels >490 ng/dL for AKI were 59% (95% confidence interval [CI] 49%-68%) and 65% (95% CI 61%-68%), respectively. Need for RRT increased 21% per 100 ng/dL increase in NGAL (P < 0.001), whereas odds of death in three months increased 10% per 100 ng/dL increase in NGAL (P = 0.028). No clear relationship was observed between NGAL levels and MACE.@*CONCLUSION@#Serum NGAL identifies AKI and predicts three-month mortality.

Geospatial analysis of severe road traffic accidents in Singapore in 2013-2014

INTRODUCTION@#Injury is a significant cause of mortality and morbidity. We aimed to investigate which areas in Singapore have a significantly higher incidence of road traffic accidents (RTA) resulting in severe injuries (Tier 1), which is defined as an Injury Severity Score (ISS) greater than 15, and to develop a spatiotemporal model.@*METHODS@#Data was obtained from the National Trauma Registry. The RTA locations were geomapped onto the Singapore map, and spatial statistical techniques were used to identify hotspots with the Getis-Ord Gi* algorithm.@*RESULTS@#From 1 January 2013 to 31 December 2014, there were 35,673 people who were injured as a result of RTAs and 976 Tier 1 RTA victims. A total of 920 people were included in the geospatial analysis. Another 56 were involved in RTAs that did not occur within Singapore or had missing location data and thus were not included. 745 (81.0%) were discharged alive, whereas 175 (19.0%) did not survive to discharge (median ISS 38.00, interquartile range 30.00-48.00). Most of the Tier 1 RTA victims were motorcycle riders (50.1%, n = 461), pedestrians (21.8%, n = 201) and cyclists (9.9%, n = 91). The majority were male and aged 20-40 years, and there was a peak occurrence at 0600-0759 hours. Nine hotspots were identified (p < 0.01).@*CONCLUSION@#Information from studying hotspots of RTAs, especially those resulting in severe injuries, can be used by multiple agencies to direct resources efficiently.