A Systematic Review and Meta-Analysis of Studies of Defibrotide Prophylaxis for Veno-Occlusive Disease/Sinusoidal Obstruction Syndrome

Background and Objectives Defibrotide is approved to treat severe veno-occlusive disease/sinusoidal obstruction syndrome (VOD/SOS) after haematopoietic cell transplantation in patients aged > 1 month in the European Union and for VOD/SOS with renal/pulmonary dysfunction post-haematopoietic cell transplantation in the United States. This meta-analysis estimated the incidence and risk of VOD/SOS after intravenous defibrotide prophylaxis using the published literature. Methods PubMed, Embase and Web of Science were searched through 30 November 2021 for defibrotide studies in VOD/SOS “prevention” or “prophylaxis,” excluding phase I studies, case reports, studies with fewer than ten patients and reviews. Results The search identified 733 records; 24 met inclusion criteria, of which 20 (N = 3005) evaluated intravenous defibrotide for VOD/SOS prophylaxis. Overall VOD/SOS incidence with intravenous defibrotide was 5%, with incidences of 5% in adults and 8% in paediatric patients. In eight studies with data on intravenous defibrotide prophylaxis vs controls (e.g. heparin, no prophylaxis), VOD/SOS incidence in controls was 16%. The risk ratio for developing VOD/SOS with defibrotide prophylaxis vs controls was 0.30 (95% confidence interval 0.12–0.71; p = 0.006). Conclusions This analysis suggests a low incidence of VOD/SOS following intravenous defibrotide prophylaxis, regardless of age group, and a lower relative risk for VOD/SOS with defibrotide prophylaxis vs controls in patient populations at high risk of VOD/SOS

Nurse scheduling using fuzzy multiple objective programming

Nurse scheduling is a complex scheduling problem and involves generating a schedule for each nurse that consists of shift duties and days off within a short-term planning period. The problem involves multiple conflicting objectives such as satisfying demand coverage requirements and maximizing nurses' preferences subject to a variety of constraints imposed by legal regulations, personnel policies and many other hospital-specific requirements. The inherent nature of the nurse scheduling problem (NSP) bears vagueness of information on target values of hospital objectives and on personal preferences. Also, the ambiguity of the constraints is some source of uncertainty that needs to be treated in providing a high quality schedule. Taking these facts into account, this paper presents the application of Fuzzy Set Theory (FST) within the context of NSP and proposes a fuzzy goal programming model. To explore the viability of the proposed model, computational experiments are presented on a real world case problem

Nurse scheduling using fuzzy modeling approach

Nurse scheduling is a complex scheduling problem and involves generating a schedule for each nurse that consists of shift duties and days off within a short-term planning period. In real world applications, multiple sources of uncertainties are needed to be treated in providing higher quality schedules. This paper presents a seminal research on the application of fuzzy set theory to the nurse scheduling problem (NSP) to treat uncertainties in the target values of the hospital management and nurses' preferences. More specifically, a new multi-objective integer programming model for the NSP is developed. Then, based on this model three fuzzy goal programming models are developed using different fuzzy solution approaches. A real world application is presented to confirm the viability of the proposed models. Also, to provide the decision maker for a more confident solution set for policy decision making, a sensitivity analysis is performed. Additionally, to show the efficiency of the proposed model, it is applied to several problem instances. The paper contributes to the literature by revealing that fuzzy modeling approaches can effectively be used in the NSP in providing schedules which are more personalized and equitable for nurses, and more satisfying for hospital management. (C) 2009 Elsevier B.V. All rights reserved

Integrating AI and OR: An industrial engineering perspective

Many researchers have spent significant effort in developing techniques for solving hard combinatorial optimization problems. We see that both the Operations Research (OR) and the Artificial Intelligence (AI) communities are interested in solving these types of problems. OR focuses on tractable representations, such as linear programming whereas AI techniques provide richer and more flexible representations of real world problems. In this paper, we attempt to demonstrate the impressive impact of OR and AI integration. First we discuss opportunities for integration of OR and AI. Then three applications are presented to demonstrate how OR and AI are integrated

The Association Between Hepatit B Virus (HBV) DNA Levels, Alanin Aminotransferaz Levels And HBV Serologic Markers

In the present study, we planned to evaluate the association between serum alanin aminotransferaz (ALT) levels, age, gender, and Hepatitis B virus (HBV) serologic markers of the patients whose HBV DNA levels were 10(4) copy/mL and higher. HBV DNA was quantitatively detected by real-time polymerase chain reaction (PCR) and serologic markers by enzyme immunoassay (EIA). Of the 322 sera which were tested for HBV DNA and HBV serology, 136 (42.2%) patients had HBV DNA levels between 10(4)-10(7) copy/mL and 186 (57.8%) had HBV DNA levels higher than 10(7) copy/mL. ALT levels were more than two times the upper limit of normal in 131 (40.6%) patients and less than two times the upper limit of normal in 191 (59.4%) patients. Of the patients, 96 (29.8%) were HBeAg positive and 266 (70.2%) were HBeAg negative. Of the study population, 63.7% of the patients were males and 36.3% of the patients were females. When the patients were evaluated according to the age distribution, the largest rate of the patients (51.8%) was within the range of 21-40 years. HBV DNA levels, HBV serology, liver enzymes and the clinical findings should be considered together during the diagnosis, treatment and the follow-up of the patients with HBV infection