IADR Abstract Archives
Pulmonary Infections Leading to Sepsis
Objectives: Pulmonary infections are continuously a major factor in the development of sepsis in patients. The objective of this study is to graph clinical patterns and outcomes of pulmonary infections involving sepsis for mapping clinical practice guidelines used in decision-making.
Methods: A literature research was conducted from a bibliome of 17 articles using the search engines: Google Scholars, PubMed, and Google, as well as the CSUSB P.fau library database. Of the 17 articles found, 4 articles and 4 case reports were reviewed and analyzed. Patterns and outcomes were mapped using Neo4j graph database principles for a schema that began with the Patient node and progresseg to other subnodes. A transversal graph of patterns and outcomes achieved Subject Matter Expert level knowledge of node to node relationships with edge-probabilities reported at the outcome terminus when evidenced.
Results: Mapping of pulmonary infections resulting in sepsis began as a subnode of Infection. For this study, the subnode Pulmonary Infection graph transversal went to several children nodes that began with the Bacteria node, Microorganism node, and from there to final outcomes: Mortality and morbidity. The infection rate of F. necrophorum bacteria remains unknown, Leptospira was .33%, B. cepacia genomovar 3%, and Rhodococcus equi unknown. For mortality rates, F. necrophorum, the rate was < 20 %, Leptospira 5 %, B. cepacia genomovar was unknown, and Rhodococcus equi bacteria, also unknown. The morbidity rate of F. necrophorum was 81.7%, Leptospira .0012%, and for B. cepacia genomovar, 66%. Gaps were evidenced due to limited data of recent reporting and knowledge within articles used.
Conclusions: Mapping of the clinical patterns and outcomes produced a vested probability schema but demonstrated gaps where new knowledge was not evidenced in the literature.
Methods: A literature research was conducted from a bibliome of 17 articles using the search engines: Google Scholars, PubMed, and Google, as well as the CSUSB P.fau library database. Of the 17 articles found, 4 articles and 4 case reports were reviewed and analyzed. Patterns and outcomes were mapped using Neo4j graph database principles for a schema that began with the Patient node and progresseg to other subnodes. A transversal graph of patterns and outcomes achieved Subject Matter Expert level knowledge of node to node relationships with edge-probabilities reported at the outcome terminus when evidenced.
Results: Mapping of pulmonary infections resulting in sepsis began as a subnode of Infection. For this study, the subnode Pulmonary Infection graph transversal went to several children nodes that began with the Bacteria node, Microorganism node, and from there to final outcomes: Mortality and morbidity. The infection rate of F. necrophorum bacteria remains unknown, Leptospira was .33%, B. cepacia genomovar 3%, and Rhodococcus equi unknown. For mortality rates, F. necrophorum, the rate was < 20 %, Leptospira 5 %, B. cepacia genomovar was unknown, and Rhodococcus equi bacteria, also unknown. The morbidity rate of F. necrophorum was 81.7%, Leptospira .0012%, and for B. cepacia genomovar, 66%. Gaps were evidenced due to limited data of recent reporting and knowledge within articles used.
Conclusions: Mapping of the clinical patterns and outcomes produced a vested probability schema but demonstrated gaps where new knowledge was not evidenced in the literature.