{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T17:58:07Z","timestamp":1780336687498,"version":"3.54.1"},"reference-count":35,"publisher":"Pensoft Publishers","issue":"3","license":[{"start":{"date-parts":[[2023,6,30]],"date-time":"2023-06-30T00:00:00Z","timestamp":1688083200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["FM"],"abstract":"<jats:p><jats:bold>Introduction<\/jats:bold>: One of the major obstetrical complications, affecting 2%\u20138% of all pregnancies, is preeclampsia. To predict the onset of preeclampsia, several methods have recently been put forth. The Fetal Medicine Foundation has developed combined screening that can identify the vast majority of women who will develop preeclampsia using a combination of maternal factors, obstetrical history, biochemical, and biophysical factors.<\/jats:p>\n          <jats:p><jats:bold>Aim<\/jats:bold>: The objective of the present study was to identify and analyze which classical risk factors may be independent predictors of preeclampsia, and assess their impact on this complication. In order to assess the high risk of preeclampsia, we also suggest further predictors that may optimize the risk constellation.<\/jats:p>\n          <jats:p><jats:bold>Materials and methods<\/jats:bold>: The study included 1511 pregnant women who were examined during their routine checkups in a two-phase retrospective study that took place from January 30, 2018, to August 31, 2020, in the Outpatient Department of the University Hospital in Plovdiv. All primary data were obtained from their archived medical records. Information about the maternal factors, the patients\u2019 medical and obstetric histories, and status was obtained during the first phase of the study (11th gestation week + 0 days \u2013 13th gestation week + 6 days). The second phase was conducted as a telephone interview (up to six months after the birth of the child): we collected data on the mode of birth, weight of the newborn, PE occurrence, at which gestation week the PE onset occurred, presence of gestational hypertension (GH) and diabetes, intrauterine growth retardation (IUGR), whether patients took aspirin and in what dosage, other complications, etc. The patients were divided into two groups: a high-risk group (with a risk for PE higher than 1:150), and a low-risk group, with or without onset of IUGR, GH, diabetes, etc.<\/jats:p>\n          <jats:p><jats:bold>Results<\/jats:bold>: The mean age of the analyzed 1511 pregnant women was 29.91\u00b15.32 years (range 18 \u2013 46 years). Of these, 38 (2.9%) women developed preeclampsia, and 5.9% had gestational hypertension. The classification of participants by risk of developing preeclampsia showed that 591 (39.1%) of the examined patients were reported as high-risk. All patients at risk higher than 1:150 were classified as high-risk, and it was recommended that they should take aspirin 150 mg every night from 12th to 36th week of gestation. 80.6% of the high-risk group took the medication regularly.<\/jats:p>\n          <jats:p>Comparing the beta coefficients for the parameters we studied (beta coefficient indicates the predictors\u2019 impact on PE), we established that the risk factors that are the most significant and apparently independent in predicting preeclampsia were (in ascending order): 1. Weight of newborn, \u03b2=0.157; 2. Mean arterial blood pressure (MAP), \u03b2=0.150; 3. IUGR, \u03b2=0.120; 4. Pregnancy associated plasma protein-A (PAPP-A), \u03b2=0.112; 5. Cervix length, \u03b2=0.095<\/jats:p>\n          <jats:p><jats:bold>Conclusions<\/jats:bold>: In the analysis of the four multiple regression models, adequately describing the role (and independence) of the PE predictors \u2013 common to all pregnant women; in cases of early midterm and term PE: placental growth factor (PlGF), PAPP-A, MAP, mean Ut PI, cervical length, newborn weight, and IUGR. As common for all cases with PE, and depending on whether the PE onset was \u226432, \u22644, or \u226436 week of gestation, the following conclusions can be made: independent predictors of PE in all studied pregnant women were (indicators are ranked according to their degree of impact on the occurrence of PE): 1. MAP; 2. Intrauterine growth retardation (newborn weight is an indirect indicator of probable IUGR); 3. Pregnancy-associated protein-A; 4. Cervix length (with the corresponding standardized coefficients being \u03b2=0.150; \u03b2=0.120; \u03b2=0.112; \u03b2=0.095, respectively).<\/jats:p>","DOI":"10.3897\/folmed.65.e86087","type":"journal-article","created":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T07:18:47Z","timestamp":1688023127000},"page":"384-392","source":"Crossref","is-referenced-by-count":4,"title":["Independent predictors of preeclampsia and their impact on the complication in Bulgarian study group of pregnant women"],"prefix":"10.3897","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5221-3815","authenticated-orcid":true,"given":"Boris","family":"Stoilov","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Polina","family":"Zaharieva-Dinkova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lili","family":"Stoilova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ekaterina","family":"Uchikova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emiliya","family":"Karaslavova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2258","published-online":{"date-parts":[[2023,6,30]]},"reference":[{"key":"86087_B1","doi-asserted-by":"crossref","unstructured":"1. 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