Cluster analysis to estimate the risk of preeclampsia in the high-risk Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study

被引:20
|
作者
Villa, Pia M. [1 ,2 ]
Marttinen, Pekka [3 ]
Gillberg, Jussi [3 ]
Lokki, A. Inkeri [2 ,4 ,5 ,6 ]
Majander, Kerttu [7 ]
Orden, Maija-Riitta [8 ]
Taipale, Pekka [9 ]
Pesonen, Anukatriina [10 ]
Raikkonen, Katri [10 ]
Hamalainen, Esa [2 ,11 ]
Kajantie, Eero [12 ,13 ,14 ,15 ,16 ,17 ]
Laivuori, Hannele [1 ,2 ,18 ]
机构
[1] Univ Helsinki, Obstet & Gynaecol, Helsinki, Finland
[2] Helsinki Univ Hosp, Helsinki, Finland
[3] Aalto Univ, Helsinki Inst Informat Technol, Dept Comp Sci, Espoo, Finland
[4] Univ Helsinki, Res Programs Unit, Immunobiol, Helsinki, Finland
[5] Univ Helsinki, Med & Clin Genet, Helsinki, Finland
[6] Univ Helsinki, Bacteriol & Immunol, Helsinki, Finland
[7] Univ Tubingen, Inst Archaeol Sci, Tubingen, Germany
[8] Kuopio Univ Hosp, Obstet & Gynecol, Kuopio, Finland
[9] Suomen Terveystalo Oy, Kuopio, Finland
[10] Univ Helsinki, Dept Psychol & Logoped, Helsinki, Finland
[11] Univ Helsinki, HUSLAB, Helsinki, Finland
[12] Natl Inst Hlth & Welf, Helsinki, Finland
[13] Natl Inst Hlth & Welf, Oulu, Finland
[14] Oulu Univ Hosp, MRC Oulu, PEDEGO Res Unit, Oulu, Finland
[15] Univ Oulu, Oulu, Finland
[16] Helsinki Univ Hosp, Childrens Hosp, Helsinki, Finland
[17] Univ Helsinki, Helsinki, Finland
[18] Univ Helsinki, Inst Mol Med Finland, Helsinki, Finland
来源
PLOS ONE | 2017年 / 12卷 / 03期
基金
芬兰科学院;
关键词
LOW-DOSE ASPIRIN; PREGNANCY COMPLICATIONS; WOMEN; VALIDITY; REGISTRY;
D O I
10.1371/journal.pone.0174399
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Objectives Preeclampsia is divided into early-onset (delivery before 34 weeks of gestation) and late-onset (delivery at or after 34 weeks) subtypes, which may rise from different etiopathogenic backgrounds. Early-onset disease is associated with placental dysfunction. Late-onset disease develops predominantly due to metabolic disturbances, obesity, diabetes, lipid dysfunction, and inflammation, which affect endothelial function. Our aim was to use cluster analysis to investigate clinical factors predicting the onset and severity of preeclampsia in a cohort of women with known clinical risk factors. Methods We recruited 903 pregnant women with risk factors for preeclampsia at gestational weeks 12(+0)-13(+6). Each individual outcome diagnosis was independently verified from medical records. We applied a Bayesian clustering algorithm to classify the study participants to clusters based on their particular risk factor combination. For each cluster, we computed the risk ratio of each disease outcome, relative to the risk in the general population. Results The risk of preeclampsia increased exponentially with respect to the number of risk factors. Our analysis revealed 25 number of clusters. Preeclampsia in a previous pregnancy (n = 138) increased the risk of preeclampsia 8.1 fold (95% confidence interval (CI) 5.711.2) compared to a general population of pregnant women. Having a small for gestational age infant (n = 57) in a previous pregnancy increased the risk of early-onset preeclampsia 17.5 fold (95%CI 2.160.5). Cluster of those two risk factors together (n = 21) increased the risk of severe preeclampsia to 23.8-fold (95%CI 5.160.6), intermediate onset (delivery between 34(+0)-36(+6) weeks of gestation) to 25.1-fold (95%CI 3.179.9) and preterm preeclampsia (delivery before 37(+0) weeks of gestation) to 16.4-fold (95%CI 2.052.4). Body mass index over 30 kg/m(2) (n = 228) as a sole risk factor increased the risk of preeclampsia to 2.1-fold (95%CI 1.13.6). Together with preeclampsia in an earlier pregnancy the risk increased to 11.4 (95%CI 4.520.9). Chronic hypertension (n = 60) increased the risk of preeclampsia 5.3-fold (95%CI 2.49.8), of severe preeclampsia 22.2-fold (95%CI 9.941.0), and risk of early-onset preeclampsia 16.7-fold (95%CI 2.057.6). If a woman had chronic hypertension combined with obesity, gestational diabetes and earlier preeclampsia, the risk of term preeclampsia increased 4.8-fold (95%CI 0.121.7). Women with type 1 diabetes mellitus had a high risk of all subgroups of preeclampsia. Conclusion The risk of preeclampsia increases exponentially with respect to the number of risk factors. Early-onset preeclampsia and severe preeclampsia have different risk profile from term preeclampsia.
引用
收藏
页数:14
相关论文
共 50 条
  • [21] Angiogenic biomarkers for prediction of early preeclampsia onset in high-risk women
    Simas, Tiffany A. Moore
    Crawford, Sybil L.
    Bathgate, Susanne
    Yan, Jing
    Robidoux, Laura
    Moore, Melissa
    Maynard, Sharon E.
    [J]. JOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE, 2014, 27 (10): : 1038 - 1048
  • [22] Intrauterine growth restriction and oligohydramnios among high-risk patients
    Chauhan, Suneet P.
    Taylor, Michelle
    Shields, Dawn
    Parker, Donna
    Scardo, James A.
    Magann, Everett F.
    [J]. AMERICAN JOURNAL OF PERINATOLOGY, 2007, 24 (04) : 215 - 221
  • [23] Improving Utilization of Aspirin for Prevention of Preeclampsia in a High-Risk Urban Cohort: A Prospective Cohort Study
    Boelig, Rupsa C.
    Wanees, Mariam
    Zhan, Tingting
    Berghella, Vincenzo
    Roman, Amanda
    [J]. AMERICAN JOURNAL OF PERINATOLOGY, 2021, 38 (06) : 544 - 552
  • [24] Should We Add Pravastatin to Aspirin for Preeclampsia Prevention in High-risk Women?
    Marrs, Caroline C.
    Costantine, Maged M.
    [J]. CLINICAL OBSTETRICS AND GYNECOLOGY, 2017, 60 (01): : 161 - 168
  • [25] The Effect of Garlic Capsule on the Prevention of Preeclampsia in High-risk Turkmen Pregnant Women
    Amin, Gholamreza
    Ardakani, Zeinab Shaker
    Jafariazar, Zahra
    Vosoogh, Shohreh
    Shariat, Mamak
    Haghollahi, Fedyeh
    Afshar, Shima
    [J]. JUNDISHAPUR JOURNAL OF NATURAL PHARMACEUTICAL PRODUCTS, 2020, 15 (01)
  • [26] Combined Doppler ultrasound and platelet indices for prediction of preeclampsia in high-risk pregnancies
    Abdel Razik, Mohamed
    Mostafa, Ahmed
    Taha, Sara
    Salah, Ahmed
    [J]. JOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE, 2019, 32 (24): : 4128 - 4132
  • [27] Role of Shear Wave Elastography of Placenta in Prediction of Preeclampsia in High-Risk Pregnancy
    Singh, Tulika
    Choudhury, Shayeri Roy
    Singh, Mandeep
    Singla, Veenu
    Jain, Vanita
    [J]. ULTRASOUND QUARTERLY, 2024, 40 (02) : 119 - 125
  • [28] Prediction of Intrauterine Growth Restriction and Preeclampsia Using Machine Learning-Based Algorithms: A Prospective Study
    Vasilache, Ingrid-Andrada
    Scripcariu, Ioana-Sadyie
    Doroftei, Bogdan
    Bernad, Robert Leonard
    Carauleanu, Alexandru
    Socolov, Demetra
    Melinte-Popescu, Alina-Sinziana
    Vicoveanu, Petronela
    Harabor, Valeriu
    Mihalceanu, Elena
    Melinte-Popescu, Marian
    Harabor, Anamaria
    Bernad, Elena
    Nemescu, Dragos
    [J]. DIAGNOSTICS, 2024, 14 (04)
  • [29] Placental Growth Factor for the Prediction of Adverse Outcomes in Patients with Suspected Preeclampsia or Intrauterine Growth Restriction
    Sibiude, Jeanne
    Guibourdenche, Jean
    Dionne, Marie-Danielle
    Le Ray, Camille
    Anselem, Olivia
    Serreau, Raphael
    Goffinet, Francois
    Tsatsaris, Vassilis
    [J]. PLOS ONE, 2012, 7 (11):
  • [30] Prediction of Preeclampsia and Intrauterine Growth Restriction: Development of Machine Learning Models on a Prospective Cohort
    Sufriyana, Herdiantri
    Wu, Yu-Wei
    Su, Emily Chia-Yu
    [J]. JMIR MEDICAL INFORMATICS, 2020, 8 (05)