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Preeclampsia is a disease which characterizes up to 10% of the pregnancies due to the elevated blood pressure that occurs during the third trimester of labour. As preeclampsia evolves into a severe condition, more factors should be taken into account. The paper proposes a three layered weighted network consisting of illnesses, symptoms and treatments. The network is used to determine the secondary illnesses of the pregnant women. The human disease and the symptom ontologies developed by the Northwestern University from the United States of America, offer information about the first two characteristics and they have been used at the creation phase of the corresponding layers. The treatments given by doctors build the third layer of the weighted network. The illnesses patterns are determined based on the three layer network. Some of the illnesses which characterize the presence of preeclampsia are constipation, cystitis, retinal detachment, lactic acidosis, hepatic coma, and the HELLP syndrome. Based on the analysis, it was proved that many patients have glomerular endotheliosis. In the severe cases of preeclampsia, hemolysis, and low platelets, a sign of HELPP syndrome, are some of the most often illnesses. Medical professionals are able to improve the existent layers of the considered network through the use of an intuitive graphical user interface. This also allows other doctors to learn and apply new principles while treating their patients who develop preeclampsia and further secondary diseases. The proposed solution enhances the illness definition, development and monitoring process, thus improving the lives of many pregnant women and their unborn children. [ABSTRACT FROM AUTHOR]

Preeclampsia is one of the most cases in developing country that signed by placenta dysfunction and systemic inflammation process which activate endothelium and coagulation. Many researches review the connection between inflammation and preeclampsia. However, using leukocytes, platelet, lymphocytes, and PLR (platelet lymphocytes ratio) as an inflammation marker is not still much to do yet. Therefore, this research is held to know inflammation marker that is cheap and achievable, so it can help enforcement of diagnosis and next implementation. The analytic observational research method is holding a cross-sectional descriptive retrospective, from the birthing room of inpatients medical records in Ulin General Hospital. It consists of 204 samples from 102 preterm birth and 102 term birth samples on January-December 2017 period. Sample technique uses the nonprobability method that followed purposive sampling. Data analysis uses the t-student test with α=5%. Research result shows that characteristic and laboratory of preterm birth and term preeclampsia consist of leukocytes, platelet, lymphocytes, and PLR toward PValue (0.00). The conclusion of platelet lymphocytes ratio (PLR) on preterm is birth lower significantly as compared to term preeclampsia. [ABSTRACT FROM AUTHOR]