METHODS: Prospective, surveillance study on PVCR-BSI conducted from September 1, 2013, to May 31, 2019, in 727 intensive care units (ICUs), by members of the International Nosocomial Infection Control Consortium (INICC), from 268 hospitals in 141 cities of 42 countries of Africa, the Americas, Eastern Mediterranean, Europe, South East Asia, and Western Pacific regions. For this research, we applied definition and criteria of the CDC NHSN, methodology of the INICC, and software named INICC Surveillance Online System.
RESULTS: We followed 149,609 ICU patients for 731,135 bed days and 743,508 short-term peripheral venous catheter (PVC) days. We identified 1,789 PVCR-BSIs for an overall rate of 2.41 per 1,000 PVC days. Mortality in patients with PVC but without PVCR-BSI was 6.67%, and mortality was 18% in patients with PVC and PVCR-BSI. The length of stay of patients with PVC but without PVCR-BSI was 4.83 days, and the length of stay was 9.85 days in patients with PVC and PVCR-BSI. Among these infections, the microorganism profile showed 58% gram-negative bacteria: Escherichia coli (16%), Klebsiella spp (11%), Pseudomonas aeruginosa (6%), Enterobacter spp (4%), and others (20%) including Serratia marcescens. Staphylococcus aureus were the predominant gram-positive bacteria (12%).
CONCLUSIONS: PVCR-BSI rates in INICC ICUs were much higher than rates published from industrialized countries. Infection prevention programs must be implemented to reduce the incidence of PVCR-BSIs in resource-limited countries.
METHODS: In this open-label, phase 3, multicentre randomised trial, patients aged 21-80 years with cT3 or cT4 gastric cancer undergoing curative resection were enrolled at 22 centres from South Korea, China, Japan, Malaysia, Hong Kong, and Singapore. Patients were randomly assigned to receive surgery and EIPL (EIPL group) or surgery alone (standard surgery group) via a web-based programme in random permuted blocks in varying block sizes of four and six, assuming equal allocation between treatment groups. Randomisation was stratified according to study site and the sequence was generated using a computer program and concealed until the interventions were assigned. After surgery in the EIPL group, peritoneal lavage was done with 1 L of warm (42°C) normal 0·9% saline followed by complete aspiration; this procedure was repeated ten times. The primary endpoint was overall survival. All analyses were done assuming intention to treat. This trial is registered with ClinicalTrials.gov, NCT02140034.
FINDINGS: Between Sept 16, 2012, and Aug 3, 2018, 800 patients were randomly assigned to the EIPL group (n=398) or the standard surgery group (n=402). Two patients in the EIPL group and one in the standard surgery group withdrew from the trial immediately after randomisation and were excluded from the intention-to-treat analysis. At the third interim analysis on Aug 28, 2019, the predictive probability of overall survival being significantly higher in the EIPL group was less than 0·5%; therefore, the trial was terminated on the basis of futility. With a median follow-up of 2·4 years (IQR 1·5-3·0), the two groups were similar in terms of overall survival (hazard ratio 1·09 [95% CI 0·78-1·52; p=0·62). 3-year overall survival was 77·0% (95% CI 71·4-81·6) for the EIPL group and 76·7% (71·0-81·5) for the standard surgery group. 60 adverse events were reported in the EIPL group and 41 were reported in the standard surgery group. The most common adverse events included anastomotic leak (ten [3%] of 346 patients in the EIPL group vs six [2%] of 362 patients in the standard surgery group), bleeding (six [2%] vs six [2%]), intra-abdominal abscess (four [1%] vs five [1%]), superficial wound infection (seven [2%] vs one [<1%]), and abnormal liver function (six [2%] vs one [<1%]). Ten of the reported adverse events (eight in the EIPL group and two in the standard surgery group) resulted in death.
INTERPRETATION: EIPL and surgery did not have a survival benefit compared with surgery alone and is not recommended for patients undergoing curative gastrectomy for gastric cancer.
FUNDING: National Medical Research Council, Singapore.
METHODS: The proposed method uses a 2D contourlet transform and a set of texture features that are efficiently extracted from the transformed image. Then, the combination of a kernel discriminant analysis (KDA)-based feature reduction technique and analysis of variance (ANOVA)-based feature ranking technique was used, and the images were then classified into various stages of liver fibrosis.
RESULTS: Our 2D contourlet transform and texture feature analysis approach achieved a 91.46% accuracy using only four features input to the probabilistic neural network classifier, to classify the five stages of liver fibrosis. It also achieved a 92.16% sensitivity and 88.92% specificity for the same model. The evaluation was done on a database of 762 ultrasound images belonging to five different stages of liver fibrosis.
CONCLUSIONS: The findings suggest that the proposed method can be useful to automatically detect and classify liver fibrosis, which would greatly assist clinicians in making an accurate diagnosis.
METHODS: A convolutional auto-encoder (CAE) based nonlinear compression structure is implemented to reduce the signal size of arrhythmic beats. Long-short term memory (LSTM) classifiers are employed to automatically recognize arrhythmias using ECG features, which are deeply coded with the CAE network.
RESULTS: Based upon the coded ECG signals, both storage requirement and classification time were considerably reduced. In experimental studies conducted with the MIT-BIH arrhythmia database, ECG signals were compressed by an average 0.70% percentage root mean square difference (PRD) rate, and an accuracy of over 99.0% was observed.
CONCLUSIONS: One of the significant contributions of this study is that the proposed approach can significantly reduce time duration when using LSTM networks for data analysis. Thus, a novel and effective approach was proposed for both ECG signal compression, and their high-performance automatic recognition, with very low computational cost.