| scholarly article | Q13442814 |
| P50 | author | Ben W. Mol | Q61861924 |
| Asma Khalil | Q86495956 | ||
| Louise Kenny | Q45947568 | ||
| Jenny Myers | Q47504187 | ||
| Basky Thilaganathan | Q45633986 | ||
| P2093 | author name string | Asif Ahmed | |
| Lucy Chappell | |||
| Karel G M Moons | |||
| Shakila Thangaratinam | |||
| Lucilla Poston | |||
| Richard D Riley | |||
| Marcus Green | |||
| Khalid S Khan | |||
| Richard Hooper | |||
| Julie Dodds | |||
| Ewelina Rogozinska | |||
| John Allotey | |||
| Kym I E Snell | |||
| Claire Chan | |||
| Peter Von Dadelszen | |||
| IPPIC Collaborative Network | |||
| Liona Poon | |||
| P2860 | cites work | Chronic hypertension and pregnancy outcomes: systematic review and meta-analysis | Q24568046 |
| Accuracy of circulating placental growth factor, vascular endothelial growth factor, soluble fms-like tyrosine kinase 1 and soluble endoglin in the prediction of pre-eclampsia: a systematic review and meta-analysis | Q26825271 | ||
| Developing and validating risk prediction models in an individual participant data meta-analysis | Q26859694 | ||
| Measuring inconsistency in meta-analyses | Q27860655 | ||
| Prognosis Research Strategy (PROGRESS) 2: prognostic factor research | Q28709212 | ||
| A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta-analysis | Q30585625 | ||
| Multiple imputation for handling systematically missing confounders in meta-analysis of individual participant data. | Q30655448 | ||
| Assessing risk prediction models using individual participant data from multiple studies | Q30724002 | ||
| Imputation of systematically missing predictors in an individual participant data meta-analysis: a generalized approach using MICE. | Q30890031 | ||
| Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data: the PRISMA-IPD Statement | Q30940208 | ||
| How should variable selection be performed with multiply imputed data? | Q31143046 | ||
| Use of uterine artery Doppler ultrasonography to predict pre-eclampsia and intrauterine growth restriction: a systematic review and bivariable meta-analysis | Q33323271 | ||
| Serum screening with Down's syndrome markers to predict pre-eclampsia and small for gestational age: systematic review and meta-analysis | Q33357689 | ||
| Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines | Q33488063 | ||
| ICH Harmonised Tripartite Guideline. Statistical principles for clinical trials. International Conference on Harmonisation E9 Expert Working Group | Q73110915 | ||
| Prognosis and prognostic research: what, why, and how? | Q83391342 | ||
| Prognosis and prognostic research: validating a prognostic model | Q83939735 | ||
| Prediction of progression to a high risk situation in women with gestational hypertension or mild pre-eclampsia at term | Q84633077 | ||
| Saving Mothers' Lives: Reviewing maternal deaths to make motherhood safer: 2006-2008. The Eighth Report of the Confidential Enquiries into Maternal Deaths in the United Kingdom | Q46328300 | ||
| Pregnancy-related mortality from preeclampsia and eclampsia | Q46353535 | ||
| Critical care in obstetrical patients: an eight-year review. | Q46357519 | ||
| The Preterm Prediction Study: recurrence risk of spontaneous preterm birth. National Institute of Child Health and Human Development Maternal-Fetal Medicine Units Network. | Q48020334 | ||
| Strategy for standardization of preeclampsia research study design. | Q51744646 | ||
| Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. | Q53162513 | ||
| Pre-eclampsia | Q56019568 | ||
| Construction and validation of a prognostic model across several studies, with an application in superficial bladder cancer | Q56094352 | ||
| Meta-analysis of individual participant data: rationale, conduct, and reporting | Q33530020 | ||
| The effect of factor V Leiden carriage on maternal and fetal health | Q33878487 | ||
| Classification of stillbirth by relevant condition at death (ReCoDe): population based cohort study | Q34131952 | ||
| Individual participant data meta-analysis of prognostic factor studies: state of the art? | Q34244162 | ||
| Incidence of preeclampsia: risk factors and outcomes associated with early- versus late-onset disease. | Q34366368 | ||
| Decision curve analysis: a novel method for evaluating prediction models | Q34581068 | ||
| Pre-eclampsia is associated with, and preceded by, hypertriglyceridaemia: a meta-analysis | Q34823757 | ||
| First-trimester uterine artery Doppler and adverse pregnancy outcome: a meta-analysis involving 55,974 women. | Q35067015 | ||
| Subclassification of preeclampsia | Q35196220 | ||
| Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model. | Q35682635 | ||
| Bias and Precision of the "Multiple Imputation, Then Deletion" Method for Dealing With Missing Outcome Data | Q35763930 | ||
| World Health Organization systematic review of screening tests for preeclampsia | Q35968177 | ||
| Assessing the performance of prediction models: a framework for traditional and novel measures | Q36617895 | ||
| Accuracy of fibronectin tests for the prediction of pre-eclampsia: a systematic review. | Q36733347 | ||
| Combining fractional polynomial model building with multiple imputation | Q36912447 | ||
| External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges | Q37028590 | ||
| Methods of prediction and prevention of pre-eclampsia: systematic reviews of accuracy and effectiveness literature with economic modelling. | Q37106725 | ||
| Predicting adverse outcomes in women with severe pre-eclampsia | Q37493258 | ||
| Combining biochemical and ultrasonographic markers in predicting preeclampsia: a systematic review | Q37665733 | ||
| Prevention of preeclampsia and intrauterine growth restriction with aspirin started in early pregnancy: a meta-analysis. | Q37776132 | ||
| New insights into the etiology of preeclampsia: identification of key elusive factors for the vascular complications | Q37832037 | ||
| Prediction and primary prevention of pre-eclampsia | Q37859997 | ||
| Preeclampsia in low and middle income countries-health services lessons learned from the PRE-EMPT (PRE-Eclampsia-Eclampsia Monitoring, Prevention and Treatment) project | Q38052188 | ||
| Prognostic models in obstetrics: available, but far from applicable | Q38526658 | ||
| Meta-analysis of prediction model performance across multiple studies: Which scale helps ensure between-study normality for the C-statistic and calibration measures? | Q38798776 | ||
| A guide to systematic review and meta-analysis of prediction model performance | Q39069133 | ||
| Multiple imputation for IPD meta-analysis: allowing for heterogeneity and studies with missing covariates | Q39374483 | ||
| Multiple imputation using chained equations: Issues and guidance for practice | Q39513291 | ||
| Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers | Q41814979 | ||
| A re-evaluation of random-effects meta-analysis. | Q41866179 | ||
| Interpretation of random effects meta-analyses. | Q43810883 | ||
| A refined method for the meta-analysis of controlled clinical trials with binary outcome | Q43848299 | ||
| Prognosis and prognostic research: Developing a prognostic model | Q45768539 | ||
| P433 | issue | 1 | |
| P921 | main subject | pre-eclampsia | Q61335 |
| P304 | page(s) | 16 | |
| P577 | publication date | 2017-10-03 | |
| P1433 | published in | Diagnostic and Prognostic Research | Q68092009 |
| P1476 | title | External validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis: the International Prediction of Pregnancy Complication Network (IPPIC pre-eclampsia) protocol | |
| P478 | volume | 1 |
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