Time-Stratified Case Crossover Study of the Association of Outdoor Ambient Air Pollution With the Risk of Acute Myocardial Infarction in the Context of Seasonal Exposure to the Southeast Asian Haze Problem

Background-—Prior studies have demonstrated the association of air pollution with cardiovascular deaths. Singapore experiences seasonal transboundary haze. We investigated the association between air pollution and acute myocardial infarction (AMI) incidence in Singapore. Methods and Results-—We performed a time-stratified case-crossover study on all AMI cases in the Singapore Myocardial Infarction Registry (2010–2015). Exposure on days where AMI occurred (case days) were compared with the exposure on days where AMI did not occur (control days). Control days were chosen on the same day of the week earlier and later in the same month and year. We fitted conditional Poisson regression models to daily AMI incidence to include confounders such as ambient temperature, rainfall, wind-speed, and Pollutant Standards Index. We assessed relationships between AMI incidence and Pollutant Standards Index in the entire cohort and subgroups of individual-level characteristics. There were 53 948 cases. Each 30-unit increase in Pollutant Standards Index was association with AMI incidence (incidence risk ratio [IRR] 1.04, 95% CI 1.03–1.06). In the subgroup of ST-segment–elevation myocardial infarction the IRR was 1.00, 95% CI 0.98 to 1.03, while for non–ST-segment– elevation myocardial infarction, the IRR was 1.08, 95% CI 1.05 to 1.10. Subgroup analyses showed generally significant. Moderate/ unhealthy Pollutant Standards Index showed association with AMI occurrence with IRR 1.08, 95% CI 1.05 to 1.11 and IRR 1.09, 95% CI 1.01 to 1.18, respectively. Excess risk remained elevated through the day of exposure and for >2 years after. Conclusions-—We found an effect of short-term air pollution on AMI incidence, especially non–ST-segment–elevation myocardial infarction and inpatient AMI. These findings have public health implications for primary prevention and emergency health services during haze

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

ST-segment elevation myocardial infarction with non-chest pain presentation at the Emergency Department: Insights from the Singapore Myocardial Infarction Registry

ST-segment elevation myocardial infarction (STEMI) often presents acutely at the Emergency Department (ED). Although chest pain is a classical symptom, a significant proportion of patients do not present with chest pain. The impact of a non-chest pain (NCP) presentation on ED processes-of-care and outcomes is not fully understood. We utilised a national registry to characterise predictors, processes-of-care, and outcomes of NCP STEMI presentations. Retrospective data for all STEMI cases occurring between 2010 and 2012 were analysed from the Singapore Myocardial Infarction Registry. Cases of inpatient onset, inter-facility transfers, and out-of-hospital cardiac arrests were excluded. Univariable analysis of demographic, clinical, processes-of-care, and outcome variables was conducted. Multivariable logistic regression ascertained independent predictors of a NCP presentation and 28-day mortality. Of 4667 STEMI cases, 12.9% presented without chest pain. Patients with NCP presentation were older (median, years = 74 vs. 58; p < 0.001), more likely to be female (39.1% vs. 15.7%; p < 0.001), of the Chinese race (72.5% vs. 62.7%; p < 0.001), and with diabetes (48.6% vs. 36.7%; p < 0.001). These patients were more likely to present with syncope (6.0% vs. 1.9%; p < 0.001) or epigastric pain (10.6% vs. 4.9%; p < 0.001). Patients with NCP presentation were less likely to receive percutaneous coronary intervention (27.0% vs. 75.6%; p < 0.001), had longer door-to-balloon time (median, minutes = 83 vs. 63; p < 0.001), and experienced greater mortality at 28 days (31.2% vs. 4.5%; p < 0.001). On multivariable logistic regression, independent predictors of a NCP presentation included age (adjusted odds ratio [aOR] = 1.05, 95% confidence interval [CI] 1.04–1.07), diabetes (aOR = 1.76, 95% CI 1.40–2.19), BMI (aOR = 0.93, 95% CI 0.91–0.96), and dyslipidemia (aOR = 0.73, 95% CI 0.58–0.91). Absence of chest pain was an independent predictor for 28-day mortality (aOR = 3.46, 95% CI 2.64–4.52). Patients who presented with a NCP STEMI had a distinct clinical profile and experienced poorer outcomes. Routine triage ECG could be considered for patients with high-risk factors and non-classical symptoms

RNA interference in the nucleus: roles for small RNAs in transcription, epigenetics and beyond

A growing number of functions are emerging for RNA interference (RNAi) in the nucleus, in addition to well-characterized roles in post-transcriptional gene silencing in the cytoplasm. Epigenetic modifications directed by small RNAs have been shown to cause transcriptional repression in plants, fungi and animals. Additionally, increasing evidence indicates that RNAi regulates transcription through interaction with transcriptional machinery. Nuclear small RNAs include small interfering RNAs (siRNAs) and PIWI-interacting RNAs (piRNAs) and are implicated in nuclear processes such as transposon regulation, heterochromatin formation, developmental gene regulation and genome stability

Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks

A principal task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription and phenotypic information. Here we have validated our method through the characterization of transgenic and knockout mouse models of genes predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being newly confirmed, resulted in significant changes in obesity-related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F(2) intercross studies allows high-confidence prediction of causal genes and identification of pathways and networks involved