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

Additional file 1 of Bacterial infections in patients with COVID-19: the impact of procalcitonin testing on antibiotics prescription in the real world

Supplementary Material

Amplification of SOX4 promotes PI3K/Akt signaling in human breast cancer

PURPOSE: The PI3K/Akt signaling axis contributes to the dysregulation of many dominant features in breast cancer including cell proliferation, survival, metabolism, motility and genomic instability. While multiple studies have demonstrated that basal-like or triple negative breast tumors have uniformly high PI3K/Akt activity, genomic alterations that mediate dysregulation of this pathway in this subset of highly aggressive breast tumors remain to be determined. METHODS: In this study, we present an integrated genomic analysis based on the use of a PI3K gene expression signature as a framework to analyze orthogonal genomic data from human breast tumors, including RNA expression, DNA copy number alterations, and protein expression. In combination with data from a genome-wide RNA-mediated interference screen in human breast cancer cell lines we identified essential genetic drivers of PI3K/Akt signaling. RESULTS: Our in silico analyses identified SOX4 amplification as a novel modulator of PI3K/Akt signaling in breast cancers and in vitro studies confirmed its role in regulating Akt phosphorylation. CONCLUSIONS: Taken together, these data establish a role for SOX4 mediated PI3K/Akt signaling in breast cancer and suggest that SOX4 may represent a novel therapeutic target and/or biomarker for current PI3K-family therapies

An integrated genomics approach identifies drivers of proliferation in luminal-subtype human breast cancer

Elucidating the molecular drivers of human breast cancers requires a strategy capable of integrating multiple forms of data and an ability to interpret the functional consequences of a given genetic aberration. Here we present an integrated genomic strategy based on the use of gene expression signatures of oncogenic pathway activity (n=52) as a framework to analyze DNA copy number alterations in combination with data from a genome-wide RNAi screen. We identify specific DNA amplifications, and importantly, essential genes within these amplicons representing key genetic drivers, including known and novel regulators of oncogenesis. The genes identified include eight that are essential for cell proliferation (FGD5, METTL6, CPT1A, DTX3, MRPS23, EIF2S2, EIF6 and SLC2A10) and are uniquely amplified in patients with highly proliferative luminal breast tumors, a clinical subset of patients for which few therapeutic options are effective. Our results demonstrate that this general strategy has the potential to identify putative therapeutic targets within amplicons through an integrated use of genetic, genomic, and genome-wide RNAi data sets