Background/Aims: Although prolonged post-operative ileus (PPOI) is an important factor for the prolonged length of post-operative hospital stay, there is still a lack of effective predictive and therapeutic methods for PPOI. Previous studies reported that increased inflammatory markers, such as C-reactive protein (CRP) level and neutrophil to lymphocyte ratio (NLR), are associated with malignancies. The aim of our study is to elucidate the association between peri-operative inflammatory markers and PPOI after gastrectomy for gastric cancer. Methods: We enrolled patients who received gastrectomy for gastric cancer from June 2013 to January 2016 at a single tertiary referral center in Seoul, Korea. We evaluated peri-operative inflammatory markers, including CRP level, NLR, and platelet to lymphocyte ratio (PLR) of enrolled patients. We compared these data between control group and PPOI group. Results: A total of 390 subjects were enrolled in this study, and 132 patients (33.8%) showed PPOI. In univariate analysis, preoperative CRP level and NLR, post-operative day (POD) 1 CRP level, NLR, and PLR, and POD3 CRP level, NLR, and PLR were significantly associated with PPOI. In multivariate analysis, preoperative NLR (P = 0.014), POD1 NLR (P = 0.019), POD3 CRP (P = 0.004), and POD3 NLR (P = 0.008) were independent risk factors for PPOI. Conclusions Peri-operative inflammatory markers, such as CRP level and NLR, are useful predictive factors for PPOI who received gastrectomy for gastric cancer. Moreover, prophylactic antibiotics and anti-inflammatory drugs can be preventive and therapeutic agents for PPOI.

Background/Aims: Although prolonged post-operative ileus (PPOI) is an important factor for the prolonged length of post-operative hospital stay, there is still a lack of effective predictive and therapeutic methods for PPOI. Previous studies reported that increased inflammatory markers, such as C-reactive protein (CRP) level and neutrophil to lymphocyte ratio (NLR), are associated with malignancies. The aim of our study is to elucidate the association between peri-operative inflammatory markers and PPOI after gastrectomy for gastric cancer. Methods: We enrolled patients who received gastrectomy for gastric cancer from June 2013 to January 2016 at a single tertiary referral center in Seoul, Korea. We evaluated peri-operative inflammatory markers, including CRP level, NLR, and platelet to lymphocyte ratio (PLR) of enrolled patients. We compared these data between control group and PPOI group. Results: A total of 390 subjects were enrolled in this study, and 132 patients (33.8%) showed PPOI. In univariate analysis, preoperative CRP level and NLR, post-operative day (POD) 1 CRP level, NLR, and PLR, and POD3 CRP level, NLR, and PLR were significantly associated with PPOI. In multivariate analysis, preoperative NLR (P = 0.014), POD1 NLR (P = 0.019), POD3 CRP (P = 0.004), and POD3 NLR (P = 0.008) were independent risk factors for PPOI. Conclusions Peri-operative inflammatory markers, such as CRP level and NLR, are useful predictive factors for PPOI who received gastrectomy for gastric cancer. Moreover, prophylactic antibiotics and anti-inflammatory drugs can be preventive and therapeutic agents for PPOI.

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.