Intermediate and high peri-operative cardiac enzyme release following isolated coronary artery bypass surgery are independently associated with higher one-year mortality

BACKGROUND: The relationship between cardiac enzyme (CE) release following coronary artery bypass surgery (CABG) and medium term outcome is unclear. We sought to determine the relationship between post-operative CE release and one-year survival following isolated CABG. METHODS: Over three years 3,024 consecutive patients underwent isolated CABG. Patient characteristics were prospectively recorded in a cardiac surgical database. CE release, taken as the highest single measurement recorded in the first 24 hours post-op, was abstracted from an electronic archive. All cause mortality was taken from a national registry of deaths. RESULTS: Data were complete for 2,860 (94.6%) patients. CK-MB isoenzyme (reference range 5–24 U/l) was recorded in 2,568 (89.8%), total CK in 292 (10.2%). CE release three or more times the upper limit of the reference range (ULR) were recorded in 498 (17.4%) patients, 163 (5.7%) patients had CE more than six times ULR. There were 122 deaths (4.3%). Cox proportional hazards analysis showed that CE release 3–6 times ULR (adjusted HR 2.1 [95% CI: 1.6 to 2.6], p = 0.002) and CE release six or more times the ULR (adjusted HR 5.0 [95% CI: 4.5 to 5.4], p < 0.001) were independently associated with increased one-year mortality. CONCLUSION: Cardiac enzyme release following CABG is associated with increased one-year all-cause mortality. The definition of peri-operative myocardial infarction following CABG should include elevation of CK-MB three or more times the upper limit of normal

Hsp90 orchestrates transcriptional regulation by Hsf1 and cell wall remodelling by MAPK signalling during thermal adaptation in a pathogenic yeast

Acknowledgments We thank Rebecca Shapiro for creating CaLC1819, CaLC1855 and CaLC1875, Gillian Milne for help with EM, Aaron Mitchell for generously providing the transposon insertion mutant library, Jesus Pla for generously providing the hog1 hst7 mutant, and Cathy Collins for technical assistance.Peer reviewedPublisher PD

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