Evaluations of Laparoscopic Proctocolectomy Versus Traditional Technique in Patients With Rectal Cancer

These authors conclude that laparoscopic surgery for rectal cancer can be performed safely with a reduced rate of postoperative complications, need for blood transfusions, infection, and hospital stay

The Hellenic emergency laparotomy study (HELAS): a prospective multicentre study on the outcomes of emergency laparotomy in Greece

Background Emergency laparotomy (EL) is accompanied by high post-operative morbidity and mortality which varies significantly between countries and populations. The aim of this study is to report outcomes of emergency laparotomy in Greece and to compare them with the results of the National Emergency Laparotomy Audit (NELA). Methods This is a multicentre prospective cohort study undertaken between 01.2019 and 05.2020 including consecutive patients subjected to EL in 11 Greek hospitals. EL was defined according to NELA criteria. Demographics, clinical variables, and post-operative outcomes were prospectively registered in an online database. Multivariable logistic regression analysis was used to identify independent predictors of post-operative mortality. Results There were 633 patients, 53.9% males, ASA class III/IV 43.6%, older than 65 years 58.6%. The most common operations were small bowel resection (20.5%), peptic ulcer repair (12.0%), adhesiolysis (11.8%) and Hartmann’s procedure (11.5%). 30-day post-operative mortality reached 16.3% and serious complications occurred in 10.9%. Factors associated with post-operative mortality were increasing age and ASA class, dependent functional status, ascites, severe sepsis, septic shock, and diabetes. HELAS cohort showed similarities with NELA patients in terms of demographics and preoperative risk. Post-operative utilisation of ICU was significantly lower in the Greek cohort (25.8% vs 56.8%) whereas 30-day post-operative mortality was significantly higher (16.3% vs 8.7%). Conclusion In this study, Greek patients experienced markedly worse mortality after emergency laparotomy compared with their British counterparts. This can be at least partly explained by underutilisation of critical care by surgical patients who are at high risk for death

Development and internal validation of a clinical prediction model for serious complications after emergency laparotomy

Purpose Emergency laparotomy (EL) is a common operation with high risk for postoperative complications, thereby requiring accurate risk stratification to manage vulnerable patients optimally. We developed and internally validated a predictive model of serious complications after EL. Methods Data for eleven carefully selected candidate predictors of 30-day postoperative complications (Clavien-Dindo grade >  = 3) were extracted from the HELAS cohort of EL patients in 11 centres in Greece and Cyprus. Logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO) was applied for model development. Discrimination and calibration measures were estimated and clinical utility was explored with decision curve analysis (DCA). Reproducibility and heterogeneity were examined with Bootstrap-based internal validation and Internal–External Cross-Validation. The American College of Surgeons National Surgical Quality Improvement Program’s (ACS-NSQIP) model was applied to the same cohort to establish a benchmark for the new model. Results From data on 633 eligible patients (175 complication events), the SErious complications After Laparotomy (SEAL) model was developed with 6 predictors (preoperative albumin, blood urea nitrogen, American Society of Anaesthesiology score, sepsis or septic shock, dependent functional status, and ascites). SEAL had good discriminative ability (optimism-corrected c-statistic: 0.80, 95% confidence interval [CI] 0.79–0.81), calibration (optimism-corrected calibration slope: 1.01, 95% CI 0.99–1.03) and overall fit (scaled Brier score: 25.1%, 95% CI 24.1–26.1%). SEAL compared favourably with ACS-NSQIP in all metrics, including DCA across multiple risk thresholds. Conclusion SEAL is a simple and promising model for individualized risk predictions of serious complications after EL. Future external validations should appraise SEAL’s transportability across diverse settings

Management of intra-abdominal infections : recommendations by the WSES 2016 consensus conference

This paper reports on the consensus conference on the management of intra-abdominal infections (IAIs) which was held on July 23, 2016, in Dublin, Ireland, as a part of the annual World Society of Emergency Surgery (WSES) meeting. This document covers all aspects of the management of IAIs. The Grading of Recommendations Assessment, Development and Evaluation recommendation is used, and this document represents the executive summary of the consensus conference findings.Peer reviewe

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Unraveling the Wide Spectrum of Melanoma Biomarkers.

The use of biomarkers in medicine has become essential in clinical practice in order to help with diagnosis, prognostication and prediction of treatment response. Since Alexander Breslow's original report on "melanoma and prognostic values of thickness", providing the first biomarker for melanoma, many promising new biomarkers have followed. These include serum markers, such as lactate dehydrogenase and S100 calcium-binding protein B. However, as our understanding of the DNA mutational profile progresses, new gene targets and proteins have been identified. These include point mutations, such as mutations of the BRAF gene and tumour suppressor gene tP53. At present, only a small number of the available biomarkers are being utilised, but this may soon change as more studies are published. The aim of this article is to provide a comprehensive review of melanoma biomarkers and their utility for current and, potentially, future clinical practice

Development of new poly(ADP-ribose) polymerase (PARP) inhibitors in ovarian cancer:quo vadis?

Abstract Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality among women, potentially due to ineffectiveness of screening tests for early detection. Patients typically present with advanced disease at diagnosis, whereas, up to 80% relapse and the estimated median progression-free survival (PFS) is approximately 12–18 months. Increased knowledge on the molecular biology of EOC resulted in the development of several targeted therapies, including poly(ADP-ribose) polymerase (PARP) inhibitors. These agents have changed the therapeutic approach of the EOC and exploit homologous recombination (HR) deficiency through synthetic lethality, especially in breast cancer genes 1 and 2 (BRCA1/2) mutation carriers. Furthermore, BRCA wild-type patients with other defects in the HR repair pathway, or those with platinum-resistant tumors may obtain benefit from this treatment. While PARP inhibitors as a class display many similarities, several differences in structure can translate into differences in tolerability and antitumor activity. Currently, olaparib, rucaparib, and niraparib have been approved by Food and Drug Administration (FDA) and/or European Medicines Agency (EMA) for the treatment of EOC, while veliparib is in the late stage of clinical development. Finally, since October 2018 talazoparib is FDA and EMA approved for BRCA carriers with metastatic breast cancers. In this article, we explore the mechanisms of DNA repair, synthetic lethality, efficiency of PARP inhibition, and provide an overview of early and ongoing clinical investigations of the novel PARP inhibitors veliparib and talazoparib

Prospective multicenter external validation of postoperative mortality prediction tools in patients undergoing emergency laparotomy

BACKGROUND Accurate preoperative risk assessment in emergency laparotomy (EL) is valuable for informed decision-making and rational use of resources. Available risk prediction tools have not been validated adequately across diverse healthcare settings. Herein, we report a comparative external validation of 4 widely cited prognostic models. METHODS A multicenter cohort was prospectively composed of consecutive patients undergoing EL in 11 Greek hospitals from January 2020 to May 2021 using the National Emergency Laparotomy (NELA) audit inclusion criteria. 30-day mortality risk predictions were calculated using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), NELA, Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (P-POSSUM) and Predictive Optimal Trees in Emergency Surgery Risk (POTTER) tools. Surgeons’ assessment of postoperative mortality using pre-defined cutoffs was recorded, and a surgeon-adjusted ACS-NSQIP prediction was calculated when the original model’s prediction was relatively low. Predictive performances were compared using scaled Brier scores, discrimination and calibration measures and plots, and decision curve analysis. Heterogeneity across hospitals was assessed by random-effects meta-analysis. RESULTS 631 patients were included and 30-day mortality was 16.3%. The ACS-NSQIP and its surgeon-adjusted version had the highest scaled Brier scores. All models presented high discriminative ability, with concordance statistics ranging from 0.79 for P-POSSUM to 0.85 for NELA. However, except the surgeon-adjusted ACS-NSQIP (Hosmer-Lemeshow test p = 0.742), all other models were poorly calibrated (p < 0.001). Decision curve analysis revealed superior clinical utility of the ACS-NSQIP. Following recalibrations, predictive accuracy improved for all models but ACS-NSQIP retained the lead. Between-hospital heterogeneity was minimum for the ACS-NSQIP model and maximum for P-POSSUM. CONCLUSION The ACS-NSQIP tool was most accurate for mortality predictions after EL in a broad external validation cohort, demonstrating utility for facilitating preoperative risk management in the Greek healthcare system. Subjective surgeon assessments of patient prognosis may optimise ACS-NSQIP predictions. Level of Evidence Level II, Diagnostic test/criteri