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Pregled bibliografske jedinice broj: 817279

Biochemical and haematological parameters and their value in predicting preeclampsia


Štefanović, Mario; Delić, Ratko
Biochemical and haematological parameters and their value in predicting preeclampsia // Clinical Chemistry and Laboratory Medicine
Portorož, Slovenija, 2012. (pozvano predavanje, nije recenziran, sažetak, znanstveni)


Naslov
Biochemical and haematological parameters and their value in predicting preeclampsia

Autori
Štefanović, Mario ; Delić, Ratko

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Clinical Chemistry and Laboratory Medicine / - , 2012

Skup
4th Slovenian Congress of Clinical Chemistry

Mjesto i datum
Portorož, Slovenija, 28.9.2012.-29.9.2012

Vrsta sudjelovanja
Pozvano predavanje

Vrsta recenzije
Nije recenziran

Ključne riječi
Biochemical; haematological; parameters; preeclampsia

Sažetak
Preeclampsia is a systemic syndrome that occurs in 5 to 8% of pregnancies and is a leading cause of maternal and neonatal morbidity and mortality. There are no clinically available tests that are well in selecting women who will develop preeclampsia. Purpose of the study was to combine standard biochemical and hematological markers at third trimester of pregnancy in assessing the risk of preeclampsia and to evaluate the use of additional generally available standard laboratory tests (in particular or in a group as a test panel), in prognosis of preeclampsia. This retrospective study was carried out on 113 patients with preeclampsia and a control group of 95 uncomplicated pregnancies. All subjects were in their 3-rd trimester of pregnancy and attended at Obstetric Department of the General Hospital Celje, Slovenia. Erythrocytes, leukocytes, thrombocytes, hemoglobin, hematocrit, AST, ALT, GGT, alkaline phosphatase, total bilirubin, urea, creatinine, uric acid, body mass index, parity, age, and blood type were evaluated to predict the occurrence of preeclampsia based on multivariate logistic regression model. ROC curve analysis pointed AUC of urate (0.856), creatinine (0.785) and urea (0.771) as the best preeclampsia predicting tests (p<0, 001). Logistic regression model with uric acid and urea combined as a test panel, correctly classified 79.6% patients. Inclusion of additional four parameters (thrombocytes, hematocrit, aspartate aminotransferase and leukocytes) in this model, correctly classifiy 83.8% patients with preeclampsia. Blood pressure and proteinuria were not included in the model, because they served as diagnostic criteria to diagnose preeclampsia. Our findings show that when combining several standard laboratory tests (thrombocytes, hematocrit, aspartate aminotransferase and leukocytes) in a logistic regression model, it is possible to distinguish 84% of the preeclampsia cases. If coupled with current criteria (a new onset of hypertension and proteinuria after 20 weeks of gestation in previously normotensive woman), this test panel should identify even more cases. After validation in an independent population, proposed test panel could be used as a tool to help identify women at risk for developing preeclampsia.

Izvorni jezik
Engleski

Znanstvena područja
Kliničke medicinske znanosti



POVEZANOST RADA


Autor s matičnim brojem:
Mario Štefanović, (245401)

Citiraj ovu publikaciju

Štefanović, Mario; Delić, Ratko
Biochemical and haematological parameters and their value in predicting preeclampsia // Clinical Chemistry and Laboratory Medicine
Portorož, Slovenija, 2012. (pozvano predavanje, nije recenziran, sažetak, znanstveni)
Štefanović, M. & Delić, R. (2012) Biochemical and haematological parameters and their value in predicting preeclampsia. U: Clinical Chemistry and Laboratory Medicine.
@article{article, year = {2012}, pages = {A186}, keywords = {Biochemical, haematological, parameters, preeclampsia}, title = {Biochemical and haematological parameters and their value in predicting preeclampsia}, keyword = {Biochemical, haematological, parameters, preeclampsia}, publisherplace = {Portoro\v{z}, Slovenija} }

Časopis indeksira:


  • Scopus
  • MEDLINE