The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Clinical risk prediction for pre-eclampsia in nulliparous women: development of model in international prospective cohort
Open accessAbstract
OBJECTIVES: To develop a predictive model for pre-eclampsia based on clinical risk factors for nulliparous women and to identify a subgroup at increased risk, in whom specialist referral might be indicated. DESIGN: Prospective multicentre cohort. SETTING: Five centres in Auckland, New Zealand; Adelaide, Australia; Manchester and London, United Kingdom; and Cork, Republic of Ireland. PARTICIPANTS: 3572 "healthy" nulliparous women with a singleton pregnancy from a large international study; data on pregnancy outcome were available for 3529 (99%). MAIN OUTCOME MEASURE: Pre-eclampsia defined as ≥ 140 mm Hg or diastolic blood pressure ≥ 90 mm Hg, or both, on at least two occasions four hours apart after 20 weeks' gestation but before the onset of labour, or postpartum, with either proteinuria or any multisystem complication. Preterm pre-eclampsia was defined as women with pre-eclampsia delivered before 37(+0) weeks' gestation. In the stepwise logistic regression the comparison group was women without pre-eclampsia. RESULTS: Of the 3529 women, 186 (5.3%) developed pre-eclampsia, including 47 (1.3%) with preterm pre-eclampsia. Clinical risk factors at 14-16 weeks' gestation were age, mean arterial blood pressure, body mass index (BMI), family history of pre-eclampsia, family history of coronary heart disease, maternal birth weight, and vaginal bleeding for at least five days. Factors associated with reduced risk were a previous single miscarriage with the same partner, taking at least 12 months to conceive, high intake of fruit, cigarette smoking, and alcohol use in the first trimester. The area under the receiver operating characteristics curve (AUC), under internal validation, was 0.71. Addition of uterine artery Doppler indices did not improve performance (internal validation AUC 0.71). A framework for specialist referral was developed based on a probability of pre-eclampsia generated by the model of at least 15% or an abnormal uterine artery Doppler waveform in a subset of women with single risk factors. Nine per cent of nulliparous women would be referred for a specialist opinion, of whom 21% would develop pre-eclampsia. The relative risk for developing pre-eclampsia and preterm pre-eclampsia in women referred to a specialist compared with standard care was 5.5 and 12.2, respectively. CONCLUSIONS: The ability to predict pre-eclampsia in healthy nulliparous women using clinical phenotype is modest and requires external validation in other populations. If validated, it could provide a personalised clinical risk profile for nulliparous women to which biomarkers could be added. Trial registration ACTRN12607000551493.
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A Global Measure of Perceived Stress
Cohen, S., Kamarck, T., & Mermelstein, R. (1983) · Journal of Health and Social Behavior · doi:10.2307/2136404 · Cited by 32,807
Analysis of Incomplete Multivariate Data
Schafer, J. L. (1997) · doi:10.1201/9781439821862 · Cited by 6,012
Marteau, T. M., & Bekker, H. (1992) · British Journal of Clinical Psychology · doi:10.1111/j.2044-8260.1992.tb00997.x · Cited by 3,238
Bellamy, L., Casas, J.-P., Hingorani, A. D., & Williams, D. J. (2007) · BMJ · doi:10.1136/bmj.39335.385301.be · Cited by 2,552
Prognosis and prognostic research: Developing a prognostic model
Royston, P., Moons, K. G. M., Altman, D. G., & Vergouwe, Y. (2009) · BMJ · doi:10.1136/bmj.b604 · Cited by 1,172
Low socioeconomic status is a risk factor for preeclampsia: the Generation R Study
Silva, L. M., Coolman, M., Steegers, E. A., Jaddoe, V. W., Moll, H. A., Hofman, A., Mackenbach, J. P., & Raat, H. (2008) · Journal of Hypertension · doi:10.1097/hjh.0b013e3282fcc36e · Cited by 250
SPENCE, M., MOSS-MORRIS, R., & CHALDER, T. (2005) · Psychological Medicine · doi:10.1017/s0033291704003484 · Cited by 110
Cited by
Moons, K. G. M., Altman, D. G., Reitsma, J. B., Ioannidis, J. P. A., Macaskill, P., Steyerberg, E. W., Vickers, A. J., Ransohoff, D. F., & Collins, G. S. (2015) · Annals of Internal Medicine · doi:10.7326/m14-0698 · Cited by 5,147
Calculating the sample size required for developing a clinical prediction model
Riley, R. D., Ensor, J., Snell, K. I. E., Harrell, F. E., Martin, G. P., Reitsma, J. B., Moons, K. G. M., Collins, G., & van Smeden, M. (2020) · BMJ · doi:10.1136/bmj.m441 · Cited by 2,917
Brown, M. A., Magee, L. A., Kenny, L. C., Karumanchi, S. A., McCarthy, F. P., Saito, S., Hall, D. R., Warren, C. E., Adoyi, G., & Ishaku, S. (2018) · Hypertension · doi:10.1161/hypertensionaha.117.10803 · Cited by 2,089
Self-citationSOMANZ guidelines for the management of hypertensive disorders of pregnancy 2014
Lowe, S. A., Bowyer, L., Lust, K., McMahon, L. P., Morton, M., North, R. A., Paech, M., & Said, J. M. (2015) · Australian and New Zealand Journal of Obstetrics and Gynaecology · doi:10.1111/ajo.12399 · Cited by 299
Self-citationThe role of hypoxia and hypoxia-inducible factor-1alpha in preeclampsia pathogenesis
Tal, R. (2012) · Biology of Reproduction · doi:10.1095/biolreprod.112.102723 · Cited by 235
Metadata
- Authors
- North, R. A., McCowan, L. M. E., Dekker, G. A., Poston, L., Chan, E. H. Y., Stewart, A. W., Black, M. A., Taylor, R. S., Walker, J. J., Baker, P. N., & Kenny, L. C.
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2011-04-07
- Volume
- 342
- Issue
- apr07 4
- Pages
- d1875-d1875
- ISSN
- 0007-1447 (ISSN-L)
- 0959-8138
- 1468-5833
- OpenAlex
- W2019113075
- Cited by
- 413
- References
- 7
- FWCI
- 42.99
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- North, R. A., McCowan, L. M. E., Dekker, G. A., Poston, L., Chan, E. H. Y., Stewart, A. W., Black, M. A., Taylor, R. S., Walker, J. J., Baker, P. N., & Kenny, L. C. (2011). Clinical risk prediction for pre-eclampsia in nulliparous women: development of model in international prospective cohort. BMJ. https://doi.org/10.1136/bmj.d1875
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