Dataset Information

Cerebroplacental ratio in predicting adverse perinatal outcome: a meta-analysis of individual participant data.

ABSTRACT:

Objective

To investigate if cerebroplacental ratio (CPR) adds to the predictive value of umbilical artery pulsatility index (UA PI) alone - standard of practice - for adverse perinatal outcome in singleton pregnancies.

Design and setting

Meta-analysis based on individual participant data (IPD).

Population or sample

Ten centres provided 17 data sets for 21 661 participants, 18 731 of which could be included. Sample sizes per data set ranged from 207 to 9215 individuals. Patient populations varied from uncomplicated to complicated pregnancies.

Methods

In a collaborative, pooled analysis, we compared the prognostic value of combining CPR with UA PI, versus UA PI only and CPR only, with a one-stage IPD approach. After multiple imputation of missing values, we used multilevel multivariable logistic regression to develop prediction models. We evaluated the classification performance of all models with receiver operating characteristics analysis. We performed subgroup analyses according to gestational age, birthweight centile and estimated fetal weight centile.

Main outcome measures

Composite adverse perinatal outcome, defined as perinatal death, caesarean section for fetal distress or neonatal unit admission.

Results

Adverse outcomes occurred in 3423 (18%) participants. The model with UA PI alone resulted in an area under the curve (AUC) of 0.775 (95% CI 0.709-0.828) and with CPR alone in an AUC of 0.778 (95% CI 0.715-0.831). Addition of CPR to the UA PI model resulted in an increase in the AUC of 0.003 points (0.778, 95% CI 0.714-0.831). These results were consistent across all subgroups.

Conclusions

Cerebroplacental ratio added no predictive value for adverse perinatal outcome beyond UA PI, when assessing singleton pregnancies, irrespective of gestational age or fetal size.

Tweetable abstract

Doppler measurement of cerebroplacental ratio in clinical practice has limited added predictive value to umbilical artery alone.

SUBMITTER: Vollgraff Heidweiller-Schreurs CA

PROVIDER: S-EPMC7818434 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

Cerebroplacental ratio in predicting adverse perinatal outcome: a meta-analysis of individual participant data.

Vollgraff Heidweiller-Schreurs C A CA van Osch I R IR Heymans M W MW Ganzevoort W W Schoonmade L J LJ Bax C J CJ Mol Bwj B de Groot Cjm C Bossuyt Pmm P de Boer M A MA

BJOG : an international journal of obstetrics and gynaecology 20200608 2

<h4>Objective</h4>To investigate if cerebroplacental ratio (CPR) adds to the predictive value of umbilical artery pulsatility index (UA PI) alone - standard of practice - for adverse perinatal outcome in singleton pregnancies.<h4>Design and setting</h4>Meta-analysis based on individual participant data (IPD).<h4>Population or sample</h4>Ten centres provided 17 data sets for 21 661 participants, 18 731 of which could be included. Sample sizes per data set ranged from 207 to 9215 individuals. Pati ...[more]

PMID: 32363701

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Project description:IntroductionFetal growth restriction is associated with adverse perinatal outcome and the clinical management of these pregnancies is a challenge. The aim of this study was to investigate the potential of cerebroplacental ratio (CPR) to predict adverse perinatal outcome in high-risk pregnancies in the third trimester. Another aim was to study whether the CPR has better predictive value than its components, middle cerebral artery (MCA) pulsatility index (PI) and umbilical artery (UA) PI.Material and methodsThe study was a retrospective cohort study including 1573 singleton high-risk pregnancies with Doppler examinations performed at 32+0 to 40+6 gestational weeks at Lund University Hospital and the University Hospital of Malmö between 29 December 1994 and 31 December 2017. Receiver operating characteristics (ROC) curves were used to investigate the predictive value of the gestational age-specific z-scores for CPR, UA PI and MCA PI, respectively, for the primary outcome "perinatal asphyxia/mortality" and the secondary outcomes "birthweight small for gestational age (SGA)" and two composite outcomes: "appropriate for gestational age/large for gestational age liveborn infants with neonatal morbidity" and "SGA liveborn infants with neonatal morbidity."ResultsThe performance in predicting perinatal asphyxia/mortality was poor for all three variables and did not differ significantly. The ROC area under curve (AUC) was 0.56, 0.55 and 0.53 for CPR, UA PI and MCA PI z-scores, respectively. The ROC AUC for CPR z-scores to predict SGA was 0.73, significantly higher than that for either UA PI or MCA PI (P < .001). The ability of CPR and the MCA PI to predict appropriate for gestational age/large for gestational age infant morbidity and SGA infant morbidity was similar and significantly better than UA PI (P < .001).ConclusionsIn the present study, none of the three Doppler measures proved to be useful in predicting perinatal asphyxia and mortality. CPR and MCA PI were equally good in predicting neonatal morbidity, especially in SGA pregnancies, and both were significantly better predictors than the UA PI. CPR had a high predictive value for SGA at birth, better than that of its two components, UA PI and MCA PI.

Project description:ObjectiveDoppler ultrasonographic assessment of the cerebroplacental ratio (CPR) and middle cerebral artery (MCA) is widely used as an adjunct to umbilical artery (UA) Doppler to identify fetuses at risk of adverse perinatal outcome. However, reported estimates of its accuracy vary considerably. The aim of this study was to review systematically the prognostic accuracies of CPR and MCA Doppler in predicting adverse perinatal outcome, and to compare these with UA Doppler, in order to identify whether CPR and MCA Doppler evaluation are of added value to UA Doppler.MethodsPubMed, EMBASE, the Cochrane Library and ClinicalTrials.gov were searched, from inception to June 2016, for studies on the prognostic accuracy of UA Doppler compared with CPR and/or MCA Doppler in the prediction of adverse perinatal outcome in women with a singleton pregnancy of any risk profile. Risk of bias and concerns about applicability were assessed using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies-2) tool. Meta-analysis was performed for multiple adverse perinatal outcomes. Using hierarchal summary receiver-operating characteristics meta-regression models, the prognostic accuracy of CPR vs MCA Doppler was compared indirectly, and CPR and MCA Doppler vs UA Doppler compared directly.ResultsThe search identified 4693 articles, of which 128 studies (involving 47?748 women) were included. Risk of bias or suboptimal reporting was detected in 120/128 studies (94%) and substantial heterogeneity was found, which limited subgroup analyses for fetal growth and gestational age. A large variation was observed in reported sensitivities and specificities, and in thresholds used. CPR outperformed UA Doppler in the prediction of composite adverse outcome (as defined in the included studies) (P?<?0.001) and emergency delivery for fetal distress (P?=?0.003), but was comparable to UA Doppler for the other outcomes. MCA Doppler performed significantly worse than did UA Doppler in the prediction of low Apgar score (P?=?0.017) and emergency delivery for fetal distress (P?=?0.034). CPR outperformed MCA Doppler in the prediction of composite adverse outcome (P?<?0.001) and emergency delivery for fetal distress (P?=?0.013).ConclusionCalculating the CPR with MCA Doppler can add value to UA Doppler assessment in the prediction of adverse perinatal outcome in women with a singleton pregnancy. However, it is unclear to which subgroup of pregnant women this applies. The effectiveness of the CPR in guiding clinical management needs to be evaluated in clinical trials. © 2017 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Project description:BackgroundIn non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance of the baseline values between the treatment/exposure group and control group. This may bias the study and consequently a meta-analysis (MA) estimate. These estimates may differ across statistical methods used to deal with this issue. Analysis of individual participant data (IPD) allows standardization of methods across studies. We aimed to identify methods used in published IPD-MAs of NRSs for continuous outcomes, and to compare different methods to account for baseline values of outcome variables in IPD-MA of NRSs using two empirical examples from the Thyroid Studies Collaboration (TSC).MethodsFor the first aim we systematically searched in MEDLINE, EMBASE, and Cochrane from inception to February 2021 to identify published IPD-MAs of NRSs that adjusted for baseline outcome measures in the analysis of continuous outcomes. For the second aim, we applied analysis of covariance (ANCOVA), change score, propensity score and the naïve approach (ignores the baseline outcome data) in IPD-MA from NRSs on the association between subclinical hyperthyroidism and depressive symptoms and renal function. We estimated the study and meta-analytic mean difference (MD) and relative standard error (SE). We used both fixed- and random-effects MA.ResultsTen of 18 (56%) of the included studies used the change score method, seven (39%) studies used ANCOVA and one the propensity score (5%). The study estimates were similar across the methods in studies in which groups were balanced at baseline with regard to outcome variables but differed in studies with baseline imbalance. In our empirical examples, ANCOVA and change score showed study results on the same direction, not the propensity score. In our applications, ANCOVA provided more precise estimates, both at study and meta-analytical level, in comparison to other methods. Heterogeneity was higher when change score was used as outcome, moderate for ANCOVA and null with the propensity score.ConclusionANCOVA provided the most precise estimates at both study and meta-analytic level and thus seems preferable in the meta-analysis of IPD from non-randomized studies. For the studies that were well-balanced between groups, change score, and ANCOVA performed similarly.

Project description:BackgroundPre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting.MethodsIPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis.ResultsOf 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model's calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%.ConclusionsThe evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice.Trial registrationPROSPERO ID: CRD42015029349 .

Project description:ImportanceChronic kidney disease (low estimated glomerular filtration rate [eGFR] or albuminuria) affects approximately 14% of adults in the US.ObjectiveTo evaluate associations of lower eGFR based on creatinine alone, lower eGFR based on creatinine combined with cystatin C, and more severe albuminuria with adverse kidney outcomes, cardiovascular outcomes, and other health outcomes.Design, setting, and participantsIndividual-participant data meta-analysis of 27 503 140 individuals from 114 global cohorts (eGFR based on creatinine alone) and 720 736 individuals from 20 cohorts (eGFR based on creatinine and cystatin C) and 9 067 753 individuals from 114 cohorts (albuminuria) from 1980 to 2021.ExposuresThe Chronic Kidney Disease Epidemiology Collaboration 2021 equations for eGFR based on creatinine alone and eGFR based on creatinine and cystatin C; and albuminuria estimated as urine albumin to creatinine ratio (UACR).Main outcomes and measuresThe risk of kidney failure requiring replacement therapy, all-cause mortality, cardiovascular mortality, acute kidney injury, any hospitalization, coronary heart disease, stroke, heart failure, atrial fibrillation, and peripheral artery disease. The analyses were performed within each cohort and summarized with random-effects meta-analyses.ResultsWithin the population using eGFR based on creatinine alone (mean age, 54 years [SD, 17 years]; 51% were women; mean follow-up time, 4.8 years [SD, 3.3 years]), the mean eGFR was 90 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 11 mg/g (IQR, 8-16 mg/g). Within the population using eGFR based on creatinine and cystatin C (mean age, 59 years [SD, 12 years]; 53% were women; mean follow-up time, 10.8 years [SD, 4.1 years]), the mean eGFR was 88 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 9 mg/g (IQR, 6-18 mg/g). Lower eGFR (whether based on creatinine alone or based on creatinine and cystatin C) and higher UACR were each significantly associated with higher risk for each of the 10 adverse outcomes, including those in the mildest categories of chronic kidney disease. For example, among people with a UACR less than 10 mg/g, an eGFR of 45 to 59 mL/min/1.73 m2 based on creatinine alone was associated with significantly higher hospitalization rates compared with an eGFR of 90 to 104 mL/min/1.73 m2 (adjusted hazard ratio, 1.3 [95% CI, 1.2-1.3]; 161 vs 79 events per 1000 person-years; excess absolute risk, 22 events per 1000 person-years [95% CI, 19-25 events per 1000 person-years]).Conclusions and relevanceIn this retrospective analysis of 114 cohorts, lower eGFR based on creatinine alone, lower eGFR based on creatinine and cystatin C, and more severe UACR were each associated with increased rates of 10 adverse outcomes, including adverse kidney outcomes, cardiovascular diseases, and hospitalizations.

Project description:A fundamental aspect of epidemiological studies concerns the estimation of factor-outcome associations to identify risk factors, prognostic factors and potential causal factors. Because reliable estimates for these associations are important, there is a growing interest in methods for combining the results from multiple studies in individual participant data meta-analyses (IPD-MA). When there is substantial heterogeneity across studies, various random-effects meta-analysis models are possible that employ a one-stage or two-stage method. These are generally thought to produce similar results, but empirical comparisons are few.We describe and compare several one- and two-stage random-effects IPD-MA methods for estimating factor-outcome associations from multiple risk-factor or predictor finding studies with a binary outcome. One-stage methods use the IPD of each study and meta-analyse using the exact binomial distribution, whereas two-stage methods reduce evidence to the aggregated level (e.g. odds ratios) and then meta-analyse assuming approximate normality. We compare the methods in an empirical dataset for unadjusted and adjusted risk-factor estimates.Though often similar, on occasion the one-stage and two-stage methods provide different parameter estimates and different conclusions. For example, the effect of erythema and its statistical significance was different for a one-stage (OR?=?1.35, [Formula: see text]) and univariate two-stage (OR?=?1.55, [Formula: see text]). Estimation issues can also arise: two-stage models suffer unstable estimates when zero cell counts occur and one-stage models do not always converge.When planning an IPD-MA, the choice and implementation (e.g. univariate or multivariate) of a one-stage or two-stage method should be prespecified in the protocol as occasionally they lead to different conclusions about which factors are associated with outcome. Though both approaches can suffer from estimation challenges, we recommend employing the one-stage method, as it uses a more exact statistical approach and accounts for parameter correlation.

Dataset Information

Cerebroplacental ratio in predicting adverse perinatal outcome: a meta-analysis of individual participant data.

Objective

Design and setting

Population or sample

Methods

Main outcome measures

Results

Conclusions

Tweetable abstract

Publications

Cerebroplacental ratio in predicting adverse perinatal outcome: a meta-analysis of individual participant data.

Similar Datasets

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