Development and validation of a prediction model for gestational hypertension in a Ghanaian cohort

被引:21
|
作者
Antwi, Edward [1 ,2 ]
Groenwold, Rolf H. H. [1 ]
Browne, Joyce L. [1 ]
Franx, Arie [3 ]
Agyepong, Irene A. [2 ]
Koram, Kwadwo A. [4 ]
Klipstein-Grobusch, Kerstin [1 ,4 ]
Grobbee, Diederick E. [1 ]
机构
[1] Univ Med Ctr Utrecht, Julius Ctr Hlth Sci & Primary Care, Julius Global Hlth, Utrecht, Netherlands
[2] Ghana Hlth Serv, Accra, Ghana
[3] Univ Med Ctr Utrecht, Dept Obstet & Gynecol, Utrecht, Netherlands
[4] Univ Witwatersrand, Sch Publ Hlth, Div Epidemiol & Biostat, Johannesburg, South Africa
来源
BMJ OPEN | 2017年 / 7卷 / 01期
关键词
predictors; prediction model; hypertensive disorders of pregnancy; risk scores; gestational hypertension; UTERINE ARTERY DOPPLER; RISK-FACTORS; NULLIPAROUS WOMEN; MATERNAL FACTORS; PREECLAMPSIA; PREGNANCY; DISORDERS; BIOMARKERS; DIAGNOSIS; SURVIVAL;
D O I
10.1136/bmjopen-2016-012670
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objective To develop and validate a prediction model for identifying women at increased risk of developing gestational hypertension (GH) in Ghana. Design A prospective study. We used frequencies for descriptive analysis, (2) test for associations and logistic regression to derive the prediction model. Discrimination was estimated by the c-statistic. Calibration was assessed by calibration plot of actual versus predicted probability. Setting Primary care antenatal clinics in Ghana. Participants 2529 pregnant women in the development cohort and 647 pregnant women in the validation cohort. Inclusion criterion was women without chronic hypertension. Primary outcome Gestational hypertension. Results Predictors of GH were diastolic blood pressure, family history of hypertension in parents, history of GH in a previous pregnancy, parity, height and weight. The c-statistic of the original model was 0.70 (95% CI 0.67-0.74) and 0.68 (0.60 to 0.77) in the validation cohort. Calibration was good in both cohorts. The negative predictive value of women in the development cohort at high risk of GH was 92.0% compared to 94.0% in the validation cohort. Conclusions The prediction model showed adequate performance after validation in an independent cohort and can be used to classify women into high, moderate or low risk of developing GH. It contributes to efforts to provide clinical decision-making support to improve maternal health and birth outcomes.
引用
收藏
页数:7
相关论文
共 50 条
  • [31] Development and validation of a risk prediction model for placental abruption in patients with preeclampsia
    Yang, Mei
    Wang, Menghui
    Zhu, Qing
    Li, Nanfang
    PLACENTA, 2025, 164 : 1 - 9
  • [32] A risk prediction model based on machine learning for early cognitive impairment in hypertension: Development and validation study
    Zhong, Xia
    Yu, Jie
    Jiang, Feng
    Chen, Haoyu
    Wang, Zhenyuan
    Teng, Jing
    Jiao, Huachen
    FRONTIERS IN PUBLIC HEALTH, 2023, 11
  • [33] Risk prediction for preeclampsia in CKD patients: development of a model in a retrospective cohort
    Yuan, Fangchen
    Li, Zheng
    Chen, Shi
    He, Yingdong
    Chen, Qian
    Lv, Jicheng
    Zhao, Minghui
    JOURNAL OF NEPHROLOGY, 2024, 37 (09) : 2499 - 2508
  • [34] Development and Validation of a Prediction Model for Enteral Feeding Intolerance in Critical Ill Patients: A Retrospective Cohort Study
    Liu, Lijie
    Li, Jin
    Hu, Liting
    Cai, Xiaowei
    Li, Xiaoyan
    Bai, Yang
    JOURNAL OF CLINICAL NURSING, 2025,
  • [35] Prediction of recurrent gestational diabetes mellitus: a retrospective cohort study
    Hahn, Stephan
    Koerber, Sabine
    Gerber, Bernd
    Stubert, Johannes
    ARCHIVES OF GYNECOLOGY AND OBSTETRICS, 2023, 307 (03) : 689 - 697
  • [36] Development and validation of a risk prediction model for gestational diabetes mellitus in women of advanced maternal age during the first trimester
    Tang, Yao
    Liu, Zhenzhen
    Li, Li
    Liu, Haiyan
    Li, Xiaotian
    Gu, Weirong
    FASEB JOURNAL, 2025, 39 (02)
  • [37] Development and validation of a prediction model for rebound hyperbilirubinemia: a Chinese neonatal cohort study
    Li, Huiyi
    Huang, Xihua
    Liang, Zhenyu
    Liang, Haijian
    He, Si
    Tang, Li
    TRANSLATIONAL PEDIATRICS, 2024, 13 (08) : 1302 - 1311
  • [38] Prediction of postpartum hemorrhage in women with gestational hypertension or mild preeclampsia at term
    Koopmans, Corine M.
    Van der Tuuk, Karin
    Groen, Henk
    Doornbos, Johannes P. R.
    De Graaf, Irene M.
    Van der Salm, Pauline C. M.
    Porath, Martina M.
    Kuppens, Simone M. I.
    Wijnen, Ella J.
    Aardenburg, Robert
    Van Loon, Aren J.
    Akerboom, Bettina M. C.
    Van der Lans, Peggy J. A.
    Mol, Ben W. J.
    Van Pampus, Maria G.
    ACTA OBSTETRICIA ET GYNECOLOGICA SCANDINAVICA, 2014, 93 (04) : 399 - 407
  • [39] Development and validation of a survival prediction model and risk stratification for pancreatic neuroendocrine neoplasms
    Lu, Z.
    Li, T.
    Liu, C.
    Zheng, Y.
    Song, J.
    JOURNAL OF ENDOCRINOLOGICAL INVESTIGATION, 2023, 46 (05) : 927 - 937
  • [40] Prediction of progression to a high risk situation in women with gestational hypertension or mild pre-eclampsia at term
    van der Tuuk, Karin
    Koopmans, Corine M.
    Groen, Henk
    Aarnoudse, Jan G.
    van den Berg, Paul P.
    van Beek, Johannes J.
    Copraij, Frans J. A.
    Kleiverda, Gunilla
    Porath, Martina
    Rijnders, Robbert J. P.
    van der Salm, Paulien C. M.
    Santema, Job G.
    Stigter, Robert H.
    Mol, Ben W. J.
    van Pampus, Maria G.
    AUSTRALIAN & NEW ZEALAND JOURNAL OF OBSTETRICS & GYNAECOLOGY, 2011, 51 (04) : 339 - 346