Application of omental interposition to reduce pancreatic fistula and related complications in pancreaticoduodenectomy:A propensity score-matched study

BACKGROUND The life-threatening complications following pancreatoduodenectomy(PD),intraabdominal hemorrhage,and postoperative infection,are associated with leaks from the anastomosis of pancreaticoduodenectomy.Although several methods have attempted to reduce the postoperative pancreatic fistula(POPF)rate after PD,few have been considered effective.The safety and short-term clinical benefits of omental interposition remain controversial.AIM To investigate the safety and feasibility of omental interposition to reduce the POPF rate and related complications in pancreaticoduodenectomy.METHODS In total,196 consecutive patients underwent PD performed by the same surgical team.The patients were divided into two groups:An omental interposition group(127,64.8%)and a non-omental interposition group(69,35.2%).Propensity scorematched(PSM)analyses were performed to compare the severe complication rates and mortality between the two groups.RESULTS Following PSM,the clinically relevant POPF(CR-POPF,10.1%vs 24.6%;P=0.025)and delayed postpancreatectomy hemorrhage(1.4%vs 11.6%;P=0.016)rates were significantly lower in the omental interposition group.The omental interposition technique was associated with a shorter time to resume food intake(7 d vs 8 d;P=0.048)and shorter hospitalization period(16 d vs 21 d;P=0.031).Multivariate analyses showed that a high body mass index,nonapplication of omental interposition,and a main pancreatic duct diameter<3 mm were independent risk factors for CR-POPF.CONCLUSION The application of omental interposition is an effective and safe approach to reduce the CR-POPF rate and related complications after PD.

TextGen： a realistic text data content generation method for modern storage system benchmarks

Modem storage systems incorporate data compressors to improve their performance and capacity. As a result, data content can significantly influence the result of a storage system benchmark. Because real-world proprietary datasets are too large to be copied onto a test storage system, and most data cannot be shared due to privacy issues, a benchmark needs to generate data synthetically. To ensure that the result is accurate, it is necessary to generate data content based on the characterization of real-world data properties that influence the storage system performance during the execution of a benchmark. The existing approach, called SDGen, cannot guarantee that the benchmark result is accurate in storage systems that have built-in word-based compressors. The reason is that SDGen characterizes the properties that influence compression performance only at the byte level, and no properties are characterized at the word level. To address this problem, we present TextGen, a realistic text data content generation method for modem storage system benchmarks. TextGen builds the word corpus by segmenting real-world text datasets, and creates a word-frequency distribution by counting each word in the corpus. To improve data generation performance, the word-frequency distribution is fitted to a lognormal distribution by maximum likelihood estimation. The Monte Carlo approach is used to generate synthetic data. The running time of TextGen generation depends only on the expected data size, which means that the time complexity of TextGen is O（n）. To evaluate TextGen, four real-world datasets were used to perform an experiment. The experimental results show that, compared with SDGen, the compression performance and compression ratio of the datasets generated by TextGen deviate less from real-world datasets when end-tagged dense code, a representative of word-based compressors, is evaluated.