Literature DB >> 36247275

Multivariate logistic regression analysis of preeclampsia in patients with pregnancy induced hypertension and the risk predictive value of monitoring platelet, coagulation function and thyroid hormone in pregnant women.

Li Zeng1, Chunfang Liao2.   

Abstract

OBJECTIVE: Multivariate logistic regression analysis of preeclampsia in patients with pregnancy induced hypertension and the risk predictive value of monitoring platelet, coagulation function and thyroid hormone in pregnant women.
METHODS: The data of 120 pregnant women who delivered their babies at Xinyu Maternal and Child Health Hospital from January 2019 to January 2022 were analyzed retrospectively. Among the subjects studied, 60 were patients with preeclampsia as a study group and 60 healthy pregnant women were assigned to a control group. The clinical data of pregnant women were recorded, including age, weight gain during pregnancy, nationality, education level, times of antenatal examinations, times of pregnancy and parturition, discovery of gestational weeks, multiple pregnancies, amniotic fluid volume, neonatal weight, history of in vitro fertilization combined with embryo transfer, history of diabetes, kidney disorders or preeclampsia, family background of high blood pressure, anemia and so on. The clinical test data, such as platelet count and volume, coagulation function and thyroid hormone, were collected in two groups of pregnant women. Multivariate logistic regression analysis was performed on preeclampsia. The predictive value of platelet, coagulation function and thyroid hormone on preeclampsia was explored.
RESULTS: We compared the general hematological parameters. Univariate Logistic analysis found that age, history of diabetes, nephropathy or preeclampsia, family background of elevated blood pressure, weight gain during pregnancy, frequency of pregnancy and multiple pregnancies were all risk factors for preeclampsia. Multivariate Logistic regression analysis screened out that age, history of diabetes, kidney disorders or preeclampsia, family background of hypertension were independent risk factors for preeclampsia. The white blood cell count and platelet count of the study group were lower than those of the control group. Moreover, observed patients displayed a larger average platelet volume (P<0.05). Significant differences were found in glutamic pyruvic transaminase, glutamic oxaloacetic transaminase, lactate dehydrogenase, albumin, serum creatinine and uric acid, as well as in thrombin time and activated partial thromboplastin time between the two groups (P<0.05). In terms of thyroid function, obvious differences were found in serum thyrotropin and free thyroxine between the two groups (P<0.05).
CONCLUSION: Age, history of diabetes, kidney disorders or preeclampsia, family background of highly blood pressure are independent risk factors for preeclampsia. Platelet, coagulation function and thyroid hormone levels can have a certain risk predictive value. AJTR
Copyright © 2022.

Entities:  

Keywords:  Preeclampsia; coagulation function; hypertension; platelet; thyroid hormone

Year:  2022        PMID: 36247275      PMCID: PMC9556439     

Source DB:  PubMed          Journal:  Am J Transl Res        ISSN: 1943-8141            Impact factor:   3.940


  38 in total

Review 1.  Pre-eclampsia.

Authors:  Lucy C Chappell; Catherine A Cluver; John Kingdom; Stephen Tong
Journal:  Lancet       Date:  2021-05-27       Impact factor: 79.321

Review 2.  Preeclampsia: Pathophysiology, Challenges, and Perspectives

Authors:  Sarosh Rana; Elizabeth Lemoine; Joey P Granger; S Ananth Karumanchi
Journal:  Circ Res       Date:  2019-03-29       Impact factor: 17.367

3.  Preeclampsia Risk and Prevention among Pregnant Medicaid Beneficiaries.

Authors:  Caitlin Cross-Barnet; Brigette Courtot; Sarah Benatar; Ian Hill
Journal:  J Health Care Poor Underserved       Date:  2020

4.  Intrahepatic cholestasis of pregnancy as a risk factor for preeclampsia.

Authors:  Nissim Arbib; Eran Hadar; Matan Mor; Anat Shmueli; Eyal Krispin; Ron Bardin; Orly Sneh-Arbib; Marius Braun
Journal:  Arch Gynecol Obstet       Date:  2020-02-07       Impact factor: 2.344

Review 5.  The competing risk approach for prediction of preeclampsia.

Authors:  David Wright; Alan Wright; Kypros H Nicolaides
Journal:  Am J Obstet Gynecol       Date:  2019-11-13       Impact factor: 8.661

Review 6.  Preeclampsia Among African American Pregnant Women: An Update on Prevalence, Complications, Etiology, and Biomarkers.

Authors:  Ming Zhang; Philip Wan; Kenneth Ng; Kurnvir Singh; Tzu Hsuan Cheng; Ivan Velickovic; Mudar Dalloul; David Wlody
Journal:  Obstet Gynecol Surv       Date:  2020-02       Impact factor: 2.347

7.  The association between preeclampsia and the risk of metabolic syndrome after delivery: a meta-analysis.

Authors:  Ensiyeh Jenabi; Maryam Afshari; Salman Khazaei
Journal:  J Matern Fetal Neonatal Med       Date:  2019-10-29

Review 8.  Effect of diet- and lifestyle-based metabolic risk-modifying interventions on preeclampsia: a meta-analysis.

Authors:  Rebecca Allen; Ewelina Rogozinska; Priya Sivarajasingam; Khalid S Khan; Shakila Thangaratinam
Journal:  Acta Obstet Gynecol Scand       Date:  2014-10       Impact factor: 3.636

9.  Recognizing Cardiovascular Risk After Preeclampsia: The P4 Study.

Authors:  Mark A Brown; Lynne Roberts; Anna Hoffman; Amanda Henry; George Mangos; Anthony O'Sullivan; Franziska Pettit; George Youssef; Lily Xu; Gregory K Davis
Journal:  J Am Heart Assoc       Date:  2020-11-10       Impact factor: 5.501

10.  Maternal and Perinatal Outcomes in Hypertensive Disorders of Pregnancy and Factors Influencing It: A Prospective Hospital-Based Study in Northeast India.

Authors:  Subrat Panda; Rituparna Das; Nalini Sharma; Ananya Das; Prakash Deb; Kaushiki Singh
Journal:  Cureus       Date:  2021-03-18
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.