Common structure and properties of filtering systems

Abstrac

Nature and Clinical Outcomes of Acute Hemorrhagic Rectal Ulcer

Acute hemorrhagic rectal ulcer (AHRU) is a relatively rare disease that can lead to massive hematochezia. Although AHRU is a potentially life-threatening disease, its characteristics and clinical course are not fully understood. In this study, the clinical features were compared between AHRU and lower gastrointestinal bleeding (LGIB) from other causes (non-AHRU). Then, risk factors for all-cause in-hospital mortality in patients with AHRU were identified. A total of 387 consecutive adult patients with LGIB who were managed at two tertiary academic hospitals in Akita prefecture in Japan were retrospectively enrolled. Subjects were divided into AHRU and non-AHRU groups according to the source of bleeding. Regression analyses were used to investigate significant associations, and the results were expressed as odds ratios (ORs) and 95% confidence intervals (CIs). AHRU was found as the bleeding source in 72 (18.6%) of the patients. In comparison to non-AHRU, having AHRU was significantly associated with in-hospital onset, age > 65 years, and systolic blood pressure < 90 mmHg. The AHRU group had a significantly higher in-hospital mortality rate in comparison to the non-AHRU group (18.0% vs. 8.3, p = 0.02), and hypoalbuminemia (<2.5 g/dL) was significantly associated with in-hospital mortality in the AHRU group (OR, 4.04; 95%CI, 1.11-14.9; p = 0.03). AHRU accounts for a substantial portion (18.6%) of LGIB in our area, where the aging rate is the highest in Japan. Since AHRU is a potentially life-threatening disease that requires urgent identification and management, further studies to identify robust risk factors associated with serious clinical outcomes are required

Usefulness of the CHAMPS score for risk stratification in lower gastrointestinal bleeding

We have recently developed a simple prediction score, the CHAMPS score, to predict in-hospital mortality in patients with upper gastrointestinal bleeding. In this study, the primary outcome of this study was the usefulness of the CHAMPS score for predicting in-hospital mortality with lower gastrointestinal bleeding (LGIB). Consecutive adult patients who were hospitalized with LGIB at two tertiary academic medical centers from 2015 to 2020 were retrospectively enrolled. The performance for predicting outcomes with CHAMPS score was assessed by a receiver operating characteristic curve analysis, and compared with four existing scores. In 387 patients enrolled in this study, 39 (10.1%) of whom died during the hospitalization. The CHAMPS score showed good performance in predicting in-hospital mortality in LGIB patients with an AUC (95% confidence interval) of 0.80 (0.73-0.87), which was significantly higher in comparison to the existing scores. The risk of in-hospital mortality as predicted by the CHAMPS score was shown: low risk (score = 4), 37.1%. The CHAMPS score is useful for predicting in-hospital mortality in patients with LGIB

Atezolizumab plus bevacizumab versus lenvatinib or sorafenib in non-viral unresectable hepatocellular carcinoma: an international propensity score matching analysis

A growing body of evidence suggests that non-viral hepatocellular carcinoma (HCC) might benefit less from immunotherapy

Sequential therapies after atezolizumab plus bevacizumab or lenvatinib first-line treatments in hepatocellular carcinoma patients

Introduction: The aim of this retrospective proof-of-concept study was to compare different second-line treatments for patients with hepatocellular carcinoma and progressive disease (PD) after first-line lenvatinib or atezolizumab plus bevacizumab.Materials and methods: A total of 1381 patients had PD at first-line therapy. 917 patients received lenvatinib as first-line treatment, and 464 patients atezolizumab plus bevacizumab as first-line.Results: 49.6% of PD patients received a second-line therapy without any statistical difference in overall survival (OS) between lenvatinib (20.6 months) and atezolizumab plus bev-acizumab first-line (15.7 months; p = 0.12; hazard ratio [HR] = 0.80). After lenvatinib first-line, there wasn't any statistical difference between second-line therapy subgroups (p = 0.27; sorafenib HR: 1; immunotherapy HR: 0.69; other therapies HR: 0.85). Patients who under-went trans-arterial chemo-embolization (TACE) had a significative longer OS than patients who received sorafenib (24.7 versus 15.8 months, p &lt; 0.01; HR = 0.64). After atezolizumab plus bevacizumab first-line, there was a statistical difference between second-line therapy subgroups (p &lt; 0.01; sorafenib HR: 1; lenvatinib HR: 0.50; cabozantinib HR: 1.29; other therapies HR: 0.54). Patients who received lenvatinib (17.0 months) and those who under-went TACE (15.9 months) had a significative longer OS than patients treated with sorafenib (14.2 months; respectively, p = 0.01; HR = 0.45, and p &lt; 0.05; HR = 0.46).Conclusion: Approximately half of patients receiving first-line lenvatinib or atezolizumab plus bevacizumab access second-line treatment. Our data suggest that in patients progressed to atezolizumab plus bevacizumab, the systemic therapy able to achieve the longest survival is lenvatinib, while in patients progressed to lenvatinib, the systemic therapy able to achieve the longest survival is immunotherapy

Abstract Common structure and properties of filtering systems

Recommendation systems have been studied actively since the 1990s. Generally, recommendation systems choose one or more candidates from a set of candidates through a filtering process. Methods of filtering can be divided into two categories: collaborative filtering, in which candidates are chosen based on choices of other persons whose interests or tastes are similar, and content-based filtering, in which items are chosen based on the profile or action history of the recommendee. However, these methods share the same structure in the sense that both of them recommend items based on relevance degrees of items and references, as well as relevance degrees between the recommendee and each reference. Most discussions about recommendation systems focus on the methods of choosing recommended candidates; few focus on foundational concepts of recommendation conditions that systems must satisfy, and problems that current systems have compared with these conditions. In this paper, recommendation systems are reconsidered from the viewpoint of multi-criteria decision making. Conventional filtering methods (e.g., collaborative filtering and content-based filtering) are formulated as linear weighted sum type recommendation systems. Several properties of linear weighted sum type recommendation systems are identified and formulated from the viewpoint of voting