Open versus endovascular REBOA control of blood loss during cesarean delivery in the placenta accreta spectrum: A single-center retrospective case control study.

Objective: The aim of this study was to compare two vascular control options for blood loss prevention and hysterectomy during cesarean delivery (CD): endovascular balloon occlusion of the aorta (REBOA) and open bilateral common iliac artery occlusion (CIAO) in women with extensive placenta accreta spectrum (PAS).

Study Design: This was retrospective comparison of cases of PAS using either CIAO (October 2017 through October 2018) or REBOA (November 2018 through November 2019) to prevent pathologic hemorrhage during scheduled CD. Women with confirmed placenta increta/percreta underwent either CD then intraoperative post-delivery, pre-hysterectomy open vascular control of both CIA (CIAO group) or pre-operative, ultrasound-guided, fluoroscopy-free REBOA followed by standard CD and balloon inflation after fetal delivery (REBOA group).

From Cues to Nudge: A Knowledge-Based Framework for Surveillance of Healthcare-Associated Infections.

We propose an integrated semantic web framework consisting of formal ontologies, web services, a reasoner and a rule engine that together recommend appropriate level of patient-care based on the defined semantic rules and guidelines. The classification of healthcare-associated infections within the HAIKU (Hospital Acquired Infections - Knowledge in Use) framework enables hospitals to consistently follow the standards along with their routine clinical practice and diagnosis coding to improve quality of care and patient safety. The HAI ontology (HAIO) groups over thousands of codes into a consistent hierarchy of concepts, along with relationships and axioms to capture knowledge on hospital-associated infections and complications with focus on the big four types, surgical site infections (SSIs), catheter-associated urinary tract infection (CAUTI); hospital-acquired pneumonia, and blood stream infection.

Benchmarking infrastructure for mutation text mining.

Background: Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems.

Results: We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system.

Semantic querying of relational data for clinical intelligence: a semantic web services-based approach.

Background: Clinical Intelligence, as a research and engineering discipline, is dedicated to the development of tools for data analysis for the purposes of clinical research, surveillance, and effective health care management. Self-service ad hoc querying of clinical data is one desirable type of functionality. Since most of the data are currently stored in relational or similar form, ad hoc querying is problematic as it requires specialised technical skills and the knowledge of particular data schemas.

HAIKU: A Semantic Framework for Surveillance of Healthcare-Associated Infections.

Healthcare-Associated Infections (HAI) impose a substantial health and financial burden. Surveillance for HAI is essential to develop and evaluate prevention and control efforts. The traditional approaches to HAI surveillance are often limited in scope and efficiency by the need to manually obtain and integrate data from disparate paper charts and information systems.