Counseling pregnant women on calcium: effects on calcium intake.

OBJECTIVES: To evaluate the effect of incorporating calcium advice into early pregnancy counseling on calcium intake during pregnancy in the Netherlands. METHODS: A multicenter prospective before-after cohort study was conducted introducing risk-based care including calculating individual pre-eclampsia risk. Part of the intervention was to incorporate calcium advice into routine counseling. We calculated individual daily calcium intake and adequacy of calcium intake (≥1,000 mg/day) at 16, 24 and 34 weeks of pregnancy. We performed a multiple logistic regression adjusting for covariates to identify any differences in the risk of inadequate calcium intake between RC and CAC. RESULTS: In regular care (RC, 2013-2015, n=2,477) 60% had inadequate calcium intake, compared to 49% during calcium advice care (CAC, 2017-2018, n=774) (aOR 0.75, 95% CI 0.64-0.88). Specific calcium supplements were used by 2% and 29% in RC and CAC, respectively (OR 25.1, 95% CI 17.8-36.0). Determinants of an inadequate calcium intake were lower age (aOR per additional year 0.96, 95% CI: 0.94-0.98), nulliparity (aOR 1.22, 95% CI: 1.03-1.45) and non-Caucasian origin (aOR 1.83, 95% CI 1.09-3.09). In CAC, risk of inadequate intake decreased with increasing predicted pre-eclampsia risk, which was a trend reversal compared to RC. CONCLUSIONS: Incorporating calcium advice into early pregnancy counseling was shown to lead to a decrease in the risk of inadequate calcium intake during pregnancy, but still inadequate intake in half of the women suggesting the need for further study on improving implementation. Awareness of individual increased PE risk had positive effect on calcium intake.

Impact on perinatal health and cost-effectiveness of risk-based care in obstetrics: a before-after study.

BACKGROUND: Obstetric health care relies on an adequate antepartum risk selection. Most guidelines used for risk stratification, however, do not assess absolute risks. In 2017, a prediction tool was implemented in a Dutch region. This tool combines first trimester prediction models with obstetric care paths tailored to the individual risk profile, enabling risk-based care. OBJECTIVE: To assess impact and cost-effectiveness of risk-based care compared to care-as-usual in a general population. METHODS: A before-after study was conducted using 2 multicenter prospective cohorts. The first cohort (2013-2015) received care-as-usual; the second cohort (2017-2018) received risk-based care. Health outcomes were (1) a composite of adverse perinatal outcomes and (2) maternal quality-adjusted life-years. Costs were estimated using a health care perspective from conception to 6 weeks after the due date. Mean costs per woman, cost differences between the 2 groups, and incremental cost effectiveness ratios were calculated. Sensitivity analyses were performed to evaluate the robustness of the findings. RESULTS: In total 3425 women were included. In nulliparous women there was a significant reduction of perinatal adverse outcomes among the risk-based care group (adjusted odds ratio, 0.56; 95% confidence interval, 0.32-0.94), but not in multiparous women. Mean costs per pregnant woman were significantly lower for risk-based care (mean difference, -€2766; 95% confidence interval, -€3700 to -€1825). No differences in maternal quality of life, adjusted for baseline health, were observed. CONCLUSION: In the Netherlands, risk-based care in nulliparous women was associated with improved perinatal outcomes as compared to care-as-usual. Furthermore, risk-based care was cost-effective compared to care-as-usual and resulted in lower health care costs.

Low-dose-aspirin usage among women with an increased preeclampsia risk: A prospective cohort study.

INTRODUCTION: Low-dose aspirin (LDA) prophylaxis has been shown to reduce women's preeclampsia risk. Evidence regarding LDA adherence rates of pregnant women is based almost exclusively on clinical trials, giving a potentially biased picture. Moreover, these studies do not report on determinants of adherence. Since 2017, obstetric healthcare professionals in a Dutch region have assessed women's preeclampsia risk by means of a prediction tool and counseled those with an above-population average risk on LDA as a prophylactic measure. MATERIAL AND METHODS: From 2017 to 2018, 865 women were recruited in multiple centers and prospectively followed using web-based surveys (Expect Study II). Rates and determinants of LDA usage among women with an increased preeclampsia risk in daily practice were assessed. Results were compared with findings in a similar cohort from a care-as-usual setting lacking risk-based counseling (Expect Study I, n = 2614). Netherlands Trial Register NTR4143. RESULTS: In total, 306 women had a predicted increased preeclampsia risk. LDA usage was higher for women receiving risk-based care than care-as-usual (29.4% vs 1.5%, odds ratio 19.1, 95% confidence interval 11.2-32.5). Daily LDA usage was positively correlated with both predicted risk and women's concerns regarding preeclampsia. Most reported reasons for non- or incomplete use were unawareness of LDA as a preventive intervention, concerns about potential adverse effects and doubts regarding the benefits. CONCLUSIONS: Risk-based counseling was associated with a higher prevalence of LDA usage, but general usage rates were low. Future research regarding potential factors improving the usage of LDA during pregnancy is necessary.

External validation and clinical utility of prognostic prediction models for gestational diabetes mellitus: A prospective cohort study.

INTRODUCTION: We performed an independent validation study of all published first trimester prediction models, containing non-invasive predictors, for the risk of gestational diabetes mellitus. Furthermore, the clinical potential of the best performing models was evaluated. MATERIAL AND METHODS: Systemically selected prediction models from the literature were validated in a Dutch prospective cohort using data from Expect Study I and PRIDE Study. The predictive performance of the models was evaluated by discrimination and calibration. Clinical utility was assessed using decision curve analysis. Screening performance measures were calculated at different risk thresholds for the best model and compared with current selective screening strategies. RESULTS: The validation cohort included 5260 women. Gestational diabetes mellitus was diagnosed in 127 women (2.4%). The discriminative performance of the 12 included models ranged from 68% to 75%. Nearly all models overestimated the risk. After recalibration, agreement between the observed outcomes and predicted probabilities improved for most models. CONCLUSIONS: The best performing prediction models showed acceptable performance measures and may enable more personalized medicine-based antenatal care for women at risk of developing gestational diabetes mellitus compared with current applied strategies.

Prediction models for the risk of spontaneous preterm birth based on maternal characteristics: a systematic review and independent external validation.

INTRODUCTION: Prediction models may contribute to personalized risk-based management of women at high risk of spontaneous preterm delivery. Although prediction models are published frequently, often with promising results, external validation generally is lacking. We performed a systematic review of prediction models for the risk of spontaneous preterm birth based on routine clinical parameters. Additionally, we externally validated and evaluated the clinical potential of the models. MATERIAL AND METHODS: Prediction models based on routinely collected maternal parameters obtainable during first 16 weeks of gestation were eligible for selection. Risk of bias was assessed according to the CHARMS guidelines. We validated the selected models in a Dutch multicenter prospective cohort study comprising 2614 unselected pregnant women. Information on predictors was obtained by a web-based questionnaire. Predictive performance of the models was quantified by the area under the receiver operating characteristic curve (AUC) and calibration plots for the outcomes spontaneous preterm birth <37 weeks and <34 weeks of gestation. Clinical value was evaluated by means of decision curve analysis and calculating classification accuracy for different risk thresholds. RESULTS: Four studies describing five prediction models fulfilled the eligibility criteria. Risk of bias assessment revealed a moderate to high risk of bias in three studies. The AUC of the models ranged from 0.54 to 0.67 and from 0.56 to 0.70 for the outcomes spontaneous preterm birth <37 weeks and <34 weeks of gestation, respectively. A subanalysis showed that the models discriminated poorly (AUC 0.51-0.56) for nulliparous women. Although we recalibrated the models, two models retained evidence of overfitting. The decision curve analysis showed low clinical benefit for the best performing models. CONCLUSIONS: This review revealed several reporting and methodological shortcomings of published prediction models for spontaneous preterm birth. Our external validation study indicated that none of the models had the ability to predict spontaneous preterm birth adequately in our population. Further improvement of prediction models, using recent knowledge about both model development and potential risk factors, is necessary to provide an added value in personalized risk assessment of spontaneous preterm birth.

Adherence rates to a prediction tool identifying women with an increased gestational diabetes risk: An implementation study.

OBJECTIVE: The best screening strategy for gestational diabetes mellitus (GDM) remains a topic of debate. Several organizations made a statement in favor of universal screening, but the volume of oral glucose tolerance tests (OGTT) required may burden healthcare systems. As a result, many countries still rely on selective screening using a checklist of risk factors, but reported diagnostic characteristics vary. Moreover, women's discomfort due to an OGTT is often neglected. Since 2017, obstetric healthcare professionals in a Dutch region assessed women's GDM risk with a prediction model and counseled those with an increased risk regarding an OGTT. METHODS: From 2017 to 2018, 865 women were recruited in a multicenter prospective cohort. RESULTS: In total, 385 women (48%) had an increased predicted GDM risk. Of all women, 78% reported that their healthcare professional discussed their GDM risk. Predicted GDM risks were positively correlated with conducting an OGTT. CONCLUSION: Implementation of a GDM prediction model resulted in moderate rates of OGTTs performed in general, but high rates in high-risk women. As 25% of women experienced discomfort from the OGTT, a selective screening strategy based on a prediction model with a high detection rate may be an interesting alternative to universal screening. STUDY COHORT REGISTRATION: Netherlands Trial Register: NTR4143; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4143.

Implementing a Preeclampsia Prediction Model in Obstetrics: Cutoff Determination and Health Care Professionals' Adherence.

Background. Despite improved management, preeclampsia remains an important cause of maternal and neonatal mortality and morbidity. Low-dose aspirin (LDA) lowers the risk of preeclampsia. Although several guidelines recommend LDA prophylaxis in women at increased risk, they disagree about the definition of high risk. Recently, an externally validated prediction model for preeclampsia was implemented in a Dutch region combined with risk-based obstetric care paths. Objectives. To demonstrate the selection of a risk threshold and to evaluate the adherence of obstetric health care professionals to the prediction tool. Study Design. Using a survey (n = 136) and structured meetings among health care professionals, possible cutoff values at which LDA should be discussed were proposed. The prediction model, with chosen cutoff and corresponding risk-based care paths, was embedded in an online tool. Subsequently, a prospective multicenter cohort study (n = 850) was performed to analyze the adherence of health care professionals. Patient questionnaires, linked to the individual risk profiles calculated by the online tool, were used to evaluate adherence. Results. Health care professionals agreed upon employing a tool with a high detection rate (cutoff: 3.0%; sensitivity 75%, specificity 64%) followed by shared decision between patients and health care professionals on LDA prophylaxis. Of the 850 enrolled women, 364 women had an increased risk of preeclampsia. LDA was discussed with 273 of these women, resulting in an 81% adherence rate. Conclusion. Consensus regarding a suitable risk cutoff threshold was reached. The adherence to this recommendation was 81%, indicating adequate implementation.

Implementation and Effects of Risk-Dependent Obstetric Care in the Netherlands (Expect Study II): Protocol for an Impact Study.

BACKGROUND: Recently, validated risk models predicting adverse obstetric outcomes combined with risk-dependent care paths have been made available for early antenatal care in the southeastern part of the Netherlands. This study will evaluate implementation progress and impact of the new approach in obstetric care. OBJECTIVE: The objective of this paper is to describe the design of a study evaluating the impact of implementing risk-dependent care. Validated first-trimester prediction models are embedded in daily clinical practice and combined with risk-dependent obstetric care paths. METHODS: A multicenter prospective cohort study consisting of women who receive risk-dependent care is being performed from April 2017 to April 2018 (Expect Study II). Obstetric risk profiles will be calculated using a Web-based tool, the Expect prediction tool. The primary outcomes are the adherence of health care professionals and compliance of women. Secondary outcomes are patient satisfaction and cost-effectiveness. Outcome measures will be established using Web-based questionnaires. The secondary outcomes of the risk-dependent care cohort (Expect II) will be compared with the outcomes of a similar prospective cohort (Expect I). Women of this similar cohort received former care-as-usual and were prospectively included between July 1, 2013 and December 31, 2015 (Expect I). RESULTS: Currently, women are being recruited for the Expect Study II, and a total of 300 women are enrolled. CONCLUSIONS: This study will provide information about the implementation and impact of a new approach in obstetric care using prediction models and risk-dependent obstetric care paths. TRIAL REGISTRATION: Netherlands Trial Register NTR4143; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4143 (Archived by WebCite at http://www.webcitation.org/6t8ijtpd9).

Genetic influences on 24 h blood pressure profiles in a hypertensive population: role of the angiotensin-converting enzyme insertion/deletion and angiotensin II type 1 receptor A1166C gene polymorphisms.

OBJECTIVE: Data on the association of the ACE I/D and AT1R A1166C polymorphisms with hypertension are conflicting. Most studies, however, have focused on office blood pressure (BP) only. The objective of the present study was to investigate the association of BP with the angiotensin-converting enzyme insertion/deletion (ACE I/D) and angiotensin II type 1 receptor A1166C (AT1R A1166C) polymorphisms by means of both office and ambulatory blood pressure monitoring (ABPM). METHODS AND RESULTS: A total of 348 hypertensive patients participated in this study. Office BP did not differ between the various ACE or AT1R genotype groups. However, ambulatory BP and BP load were positively associated with the ACE I/D polymorphism. This was more apparent in men than in women. There were no differences in heart rate, BP variability, and amount of dipping. The AT1R A1166C polymorphism showed no consistent association with blood pressure (load). CONCLUSION: From these data we conclude that frequent measuring of blood pressure by ABPM is crucial to find an association of the ACE D allele with various aspects of blood pressure.