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Fatal pancreatic fistula after laparoscopic distal pancreatectomy regarding intraductal papillary mucinous carcinoma using pancreaticobiliary maljunction along with sphincterotomized papilla: an instance statement.
The incidence of Infective Endocarditis (IE) is higher in dialysis patients compared to the general population. A major risk factor for IE in this group stems from bacterial invasion during repeated vascular access. Previous studies have shown increased risk of bacteremia in patients with indwelling dialysis catheters compared to permanent vascular access. However, association between the development of IE and the type of dialysis access is unclear. We aimed to examine the associated types of intravascular access and route of infection in dialysis patients who were admitted with infective endocarditis at our center. All patients admitted to Albert Einstein Medical Center in Philadelphia with a diagnosis of infective endocarditis who were on chronic hemodialysis were identified from the hospital database for the period of 1/1/07 to 12/31/18. Modified Duke criteria was used to confirm the diagnosis of infective endocarditis. A total of 96 cases were identified. Of those, 57 patients had an indwelling dialysis catheter while the other 39 had permanent dialysis access. In 82% of patients with dialysis catheters, their dialysis access site was identified as the primary source of infection compared to 30% in those with permanent dialysis access (p less then 0.001). The number of dialysis catheters placed in the preceding 6 months was strongly associated with endocarditis resulting from the dialysis access site (OR = 3.202, p=0.025). Dialysis catheters are more likely to serve as the source of infection in dialysis patients developing IE compared to permanent dialysis access. Increased awareness of risk of IE associated with dialysis catheters is warranted.The coronavirus pandemic, known as coronavirus disease 2019 (COVID-19), is an infectious respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus first identified in patients from Wuhan, China. Since December 2019, SARS-CoV-2 has spread swiftly around the world, infected more than 25 million people, and caused more than 800,000 deaths in 188 countries. Chronic respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD) appear to be risk factors for COVID-19, however, their prevalence remains controversial. In fact, studies in China reported lower rates of chronic respiratory conditions in patients with COVID-19 than in the general population, while the trend is reversed in the United States and Europe. Although the underlying molecular mechanisms of a possible interaction between COVID-19 and chronic respiratory diseases remain unknown, some observations can help to elucidate them. Indeed, physiological changes, immune response, or medications used against SARS-CoV-2 may have a greater impact on patients with chronic respiratory conditions already debilitated by chronic inflammation, dyspnea, and the use of immunosuppressant drugs like corticosteroids. In this review, we discuss importance and the impact of COVID-19 on asthma and COPD patients, the possible available treatments, and patient management during the pandemic.
The primary objective of this study was to predict subgroups of autism spectrum disorder (ASD) based on the Diagnostic Statistical Manual for Mental Disorders-IV Text Revision (DSM-IV-TR) by machine learning (ML). The secondary objective was to set up a ranking of Autism Diagnostic Interview-Revised (ADI-R) diagnostic algorithm items based on ML, and to confirm whether ML can sufficiently predict the diagnosis with these minimum items.

In the first experiment, a multiclass decision forest algorithm was applied, and the diagnostic algorithm score value of 1,269 Korean ADI-R test data was used for prediction. In the second experiment, we used 539 Korean ADI-R case data (over 48 months with verbal language) to apply mutual information to rank items used in the ADI diagnostic algorithm.

In the first experiment, the results of predicting in the case of pervasive developmental disorder not otherwise specified as "ASD" were almost three times higher than predicting it as "No diagnosis." In the second experiment, the top 10 ranking items of ADI-R were mainly related to the quality abnormality of communication.

In conclusion, we verified the applicability of ML in diagnosis and found that the application of artificial intelligence for rapid diagnosis or screening of ASD patients may be useful.
In conclusion, we verified the applicability of ML in diagnosis and found that the application of artificial intelligence for rapid diagnosis or screening of ASD patients may be useful.
The purpose of this study is to identify personality types that can influence breast cancer screening (BCS) compliance among Korean women with breast cancer using a mixed-method approach.

The participants consisted of 93 women who underwent surgery for breast cancer between July 2010 and March 2012. The demographic and medical characteristics of the participants were evaluated through structured interviews. To identify personality types, in-depth interviews were performed and the transcribed interviews were evaluated using interpretive phenomenological analysis. The participants were categorized into two groups (compliance and non-compliance) based on compliance with the Korean Breast Cancer Society recommendations for BCS.

Five personality types were identified through phenomenological analysis. There were significant differences in the chi-square test results for the BCS compliance and non-compliance groups according to age (p=0.048), cancer stage (p<0.001), and personality types (p=0.018). see more Logistility types of individuals with breast cancer in order to predict compliance with BCS.
To investigate the association between gene polymorphism of vesicular monoamine transporter type 2(VMAT2) and schizophrenia in Han Chinese population.

430 patients with schizophrenia and 470 age-sex matched controls were recruited from four mental health centers. All patients were diagnosed by two psychiatrists based on the Structured Clinical Interview for DSM Disorders (SCID). The ligase detection reactions (LDR) method was used to assess the polymorphism of the two SNPs (rs363371 and rs363324) of VMAT2.

No associations of two SNPs with schizophrenia was found. When we stratified males and females for the analysis, we found that that in the recessive model of rs363371, there was an obvious significant association between rs363371 and schizophrenia in males (OR=0.564, 95% CI=0.357-0.892, p=0.014) but not females. For the association between rs363324 and schizophrenia, no association was found in either males or females. No association was found when stratifying early-onset schizophrenia and late-onset schizophrenia.
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