SummaryBackgroundStatin treatment and variants in the gene encoding HMG-CoA reductase are associated with reductions in both the concentration of LDL cholesterol and the risk of coronary heart disease, but also with modest hyperglycaemia, increased bodyweight, and modestly increased risk of type 2 diabetes, which in no way offsets their substantial benefits. We sought to investigate the associations of LDL cholesterol-lowering PCSK9 variants with type 2 diabetes and related biomarkers to gauge the likely effects of PCSK9 inhibitors on diabetes risk.MethodsIn this mendelian randomisation study, we used data from cohort studies, randomised controlled trials, case control studies, and genetic consortia to estimate associations of PCSK9 genetic variants with LDL cholesterol, fasting blood glucose, HbA1c, fasting insulin, bodyweight, waist-to-hip ratio, BMI, and risk of type 2 diabetes, using a standardised analysis plan, meta-analyses, and weighted gene-centric scores.FindingsData were available for more than 550 000 individuals and 51 623 cases of type 2 diabetes. Combined analyses of four independent PCSK9 variants (rs11583680, rs11591147, rs2479409, and rs11206510) scaled to 1 mmol/L lower LDL cholesterol showed associations with increased fasting glucose (0·09 mmol/L, 95% CI 0·02 to 0·15), bodyweight (1·03 kg, 0·24 to 1·82), waist-to-hip ratio (0·006, 0·003 to 0·010), and an odds ratio for type diabetes of 1·29 (1·11 to 1·50). Based on the collected data, we did not identify associations with HbA1c (0·03%, −0·01 to 0·08), fasting insulin (0·00%, −0·06 to 0·07), and BMI (0·11 kg/m2, −0·09 to 0·30).InterpretationPCSK9 variants associated with lower LDL cholesterol were also associated with circulating higher fasting glucose concentration, bodyweight, and waist-to-hip ratio, and an increased risk of type 2 diabetes. In trials of PCSK9 inhibitor drugs, investigators should carefully assess these safety outcomes and quantify the risks and benefits of PCSK9 inhibitor treatment, as was previously done for statins.FundingBritish Heart Foundation, and University College London Hospitals NHS Foundation Trust (UCLH) National Institute for Health Research (NIHR) Biomedical Research Centre.

SummaryUsing a retrospective analysis of the Intensive Care National Audit and Research Centre Case Mix Programme Database (ICNARC CMPD), we have summarised the characteristics and outcomes for mechanically ventilated patients admitted to UK intensive care units (ICUs) after cardiac arrest. Descriptive statistics on case mix, physiology, treatment, service delivery, outcome and activity were described separately for community cardiac arrest, in-hospital cardiac arrest (peri-operative) and in-hospital cardiac arrest (not peri-operative). The impact on outcome of several patient characteristics and physiological values were analysed using multivariable logistic regression. Mechanically ventilated survivors of cardiac arrest accounted for 24 132 (5.8%) of all admissions to the 174 ICUs in the ICNARC CMP. Of these, 10 347 (42.9%) survived to leave the ICU and 6778 (28.6%) survived to acute hospital discharge. The ICNARC model gives much better discrimination than APACHE II for predicting hospital mortality after admission to ICU following cardiac arrest: the predicted hospital mortality based on the APACHE II and ICNARC model was 41.9% and 79.7%, respectively.

Introduction Patients with haematological malignancy admitted to intensive care have a high mortality. Adverse prognostic factors include the number of organ failures, invasive mechanical ventilation and previous bone marrow transplantation. Severityof-illness scores may underestimate the mortality of critically ill patients with haematological malignancy. This study investigates the relationship between admission characteristics and outcome in patients with haematological malignancies admitted to intensive care units (ICUs) in England, Wales and Northern Ireland, and assesses the performance of three severity-of-illness scores in this population.

Introduction Dermatology is usually thought of as an outpatient specialty with low mortality, however some skin conditions require intensive care. These conditions are relatively rare and hence are best studied using clinical databases or disease registries. We interrogated a large, high-quality clinical database from a national audit of adult intensive care units (ICUs), with the aim of identifying and characterising patients with dermatological conditions requiring admission to ICU.

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