Semantic Querying of Hospital Data Using an Ontology-Based Model of Discharge Summaries and ICD 10.

This paper focusses on the question of knowledge-based modeling of discharge summaries for semantic requesting in the context of hospital reporting process. An ontology was designed and implemented to capture patient data and required expert knowledge. The modeling process was carried out manually using Protégé after an initial reverse engineering of the official format of discharge summaries. An OWL 2 model was built integrating discharge summaries ontology and ICD 10 hierarchy. The framework is operationalized using the OpenLink Virtuoso database system (RDF store), enabling SPARQL queries and basic reasoning features. The evaluation was performed by implementing a use case based on patient comorbidities.

Association of Occupational Pesticide Exposure With Immunochemotherapy Response and Survival Among Patients With Diffuse Large B-Cell Lymphoma.

Importance: Professional use of pesticides is a risk factor for non-Hodgkin lymphoma. The main biological mechanisms of pesticides and chemotherapy are genotoxicity and reactive oxygen species generation. Cellular adaptation among patients exposed to low doses of genotoxic and oxidative compounds might hinder chemotherapy efficiency in patients with lymphoma. Objective: To examine the association of occupational exposure to pesticides with immunochemotherapy response and survival among patients treated for diffuse large B-cell lymphoma. Design, Setting, and Participants: This retrospective cohort study assessed patients treated from July 1, 2010, to May 31, 2015, for diffuse large B-cell lymphoma, with a 2-year follow-up. The study took place at 6 university and nonuniversity hospitals in Languedoc-Roussillon, France. A total of 404 patients with newly diagnosed diffuse large B-cell lymphoma treated with anthracycline-based immunochemotherapy were included before the study began. Occupational history was reconstructed for 244 patients and analyzed with the PESTIPOP French job-exposure matrix to determine likelihood of occupational exposure to pesticides. Analysis of the data was performed from July 15, 2017, to July 15, 2018. Main Outcomes and Measures: Treatment failure (ie, partial response, stable disease, disease progression, or interruption for toxic effects) rate, 2-year event-free survival, and overall survival between exposed and nonexposed patients after adjustment for confounding factors. Results: A total of 244 patients (mean [SD] age, 61.3 [15.2] years; 153 [62.7%] male) had complete occupational data. Of these patients, 67 (27.4%) had occupational exposure to pesticides, with 38 exposed through agricultural occupations. Occupational exposure was not associated with clinical and biological characteristics at diagnosis. Occupationally exposed patients had a significantly higher treatment failure rate (22.4% vs 11.3%; P = .03; adjusted odds ratio [AOR] for confounding factors, 3.0; 95% CI, 1.3-6.9); this difference was higher among patients with exposing agricultural occupations compared with other patients (29.0% vs 11.7%; AOR, 5.1; 95% CI, 2.0-12.8). Two-year event-free survival was 70% in the occupationally exposed group vs 82% in the unexposed group (adjusted hazard ratio [AHR] for confounding factors, 2.2; 95% CI, 1.3-3.9). Among patients with exposing agricultural occupations compared with other patients, the difference was more pronounced (2-year event-free survival, 56% vs 83%; AHR, 3.5; 95% CI, 1.9-6.5). Similarly, 2-year overall survival was lower in the group of patients with exposing agricultural occupations compared with other patients (81% vs 92%; AHR, 3.9; 95% CI, 1.5-10.0). Conclusions and Relevance: This retrospective study showed that agricultural occupational exposure to pesticides was associated with treatment failure, event-free survival, and overall survival among patients with diffuse large B-cell lymphoma.

The issue of building generative terminologies for automatic medical data aggregation.

This work addresses the problem of medical terminologies building. Starting from a set of elementary knowledge, a multi-hierarchical terminology is generated according to formal principles that are based on explicit classificatory points of view. The experimentation has been carried out on kidney diseases. Hierarchical conceptual structures are generated starting from Conceptual Graph based definition of kidney disease, a hierarchy of defining types and a set of organizing rules. The generated hierarchy includes new potential disease concepts with different level of likeliness. This "ready to use" generated multi-hierarchical terminology can be used for coding, includes new potential terms for the future and, due to the formalization of classificatory principles, offers improved opportunities of diseases instances aggregation. These features are looking very promising in the context of epidemiological observation tools (registries, long term cohort studies). They offer mean to meet two critical requirements: the statistical continuity in data analysis and the sustainable management of the underlying terminological system.