Analysis of the direct economic impact of smoking-related hospitalizations in Italy.

INTRODUCTION: Tobacco-related diseases have a substantial economic impact in terms of medical expenses, loss of productivity, and premature death. Tobacco use is estimated to be responsible for more than 90000 deaths each year in Italy. We aimed to evaluate the annual direct economic impact on the National Health System of hospitalizations attributable to tobacco smoking in Italy. METHODS: We analyzed data from all the hospitalizations of patients aged ≥30 years that occurred in Italy for 12 selected tobacco-related diseases, during 2018. These diseases included oropharyngeal cancer, esophageal cancer, gastric cancer, lung cancer, pancreatic cancer, bladder cancer, laryngeal cancer, ischemic heart disease, stroke, diseases of arteries, arterioles, and capillaries, pneumonia and influenza, and chronic obstructive pulmonary disease. We obtained information on 984322 hospital discharge records, including each hospitalization's direct costs. Using relative risk estimates from the scientific literature, we computed the population attributable fraction for various tobacco-related diseases to estimate the economic impact attributable to tobacco smoking. RESULTS: One-third of all hospitalizations occurred in 2018 in Italy among people aged ≥30 years for 12 tobacco-related diseases were found to be attributable to smoking, accounting for a total cost of €1.64 billion. Among the diseases considered, those with the highest expenditures attributable to tobacco smoking were ischemic heart disease, cerebrovascular disease, and lung cancer, accounting for €556 million, €290 million, and €229 million, respectively. CONCLUSIONS: Tobacco has a substantial economic impact in Italy, accounting for around 6% of the total cost of hospitalizations in 2018. This figure is expected to be largely underestimated due to several conservative assumptions adopted in the statistical analyses. It is imperative to prioritize comprehensive tobacco control measures to counteract the huge healthcare costs due to tobacco smoking.

Continuous care during labor by maternity care assistants in the Netherlands vs care-as-usual: a randomized controlled trial.

BACKGROUND: Continuous support during labor has many benefits including lower use of obstetrical interventions. However, implementation remains limited. Insights into birth outcomes and peripartum costs are essential to assess whether continuous care by a maternity care assistant is a potentially (cost) effective program to provide for all women. OBJECTIVE: Continuous care during labor, provided by maternity care assistants, will reduce the use of epidural analgesia and peripartum costs owing to a reduction in interventions. STUDY DESIGN: This was a randomized controlled trial comparing continuous support during labor (intervention group) with care-as-usual (control group) with prespecified intention-to-treat and per-protocol analyses. The primary outcome was epidural analgesia use. The secondary outcomes were use of other analgesia, referrals from midwife- to obstetrician-led care, modes of birth, hospital stay, sense of control (evaluated with the Labor Agentry Scale), maternal and neonatal adverse outcomes and peripartum costs. Data were collected using questionnaires. Anticipating incomplete adherence to providing continuous care, both intention-to-treat and per-protocol analyses were planned. Peripartum costs were estimated using a healthcare perspective. Mean costs per woman and cost differences between the intervention and control group were calculated. RESULTS: The population consisted of 1076 women with 54 exclusions and 30 discontinuations, leaving 992 women to be analyzed (515 continuous care and 477 care-as-usual). Intention-to-treat analyses showed statistically nonsignificant differences between the intervention and control group for epidural use (relative risk, 0.88; 95% confidence interval, 0.74-1.04; P=.14) and peripartum costs (mean difference, € 185.83; 95% confidence interval, -€ 204.22 to € 624.54). Per-protocol analyses showed statistically significant decreases in epidural analgesia (relative risk, 0.64; 95% confidence interval, 0.48-0.84; P=.001), other analgesia (relative risk, 0.59; 95% confidence interval, 0.37-0.94; P=.02), cesarean deliveries (relative risk, 0.53; 95% confidence interval, 0.29-0.95; P=.03) and increase in spontaneous vaginal births (relative risk, 1.09; 95% confidence interval, 1.01-1.18; P=.001) in the intervention group, but difference in total peripartum costs remained statistically nonsignificant (mean difference, € 246.55; 95% confidence interval, -€ 539.14 to € 13.50). CONCLUSION: If the provision of continuous care given by maternity care assistants during labor can be secured, continuous care leads to more vaginal births and less epidural use, pain medication, and cesarean deliveries while not leading to a difference in peripartum costs compared with care-as-usual.

Restrictive versus liberal fluid administration strategy (REFILL study) in postpartum hemorrhage and its effects on thromboelastometry (ROTEM®) values: a randomized, controlled trial.

OBJECTIVE: Current obstetric guidelines for postpartum hemorrhage (PPH) vary in fluid resuscitation management. This study aimed to evaluate the effect of fluid management on coagulation parameters in early PPH. METHODS: We performed a multicenter, randomized trial. Women who had 500 mL of blood loss in the third stage of labor were randomized to receive a restrictive fluid administration strategy or a liberal fluid administration strategy. A rotational thromboelastometry panel was performed in 72 patients. We evaluated within-group and between-group differences in the EXTEM clotting time (CT), EXTEM amplitude at 10 minutes (A10), INTEM CT, and FIBTEM A10. We also evaluated the mean fibrinogen concentration, activated partial thromboplastin time, and partial thromboplastin time in the total study population (n = 249). RESULTS: There were no significant differences in hemostatic parameters between the groups after correction for baseline values. CONCLUSIONS: In women with PPH <1500 mL, there is no clinically relevant effect of a restrictive or liberal fluid administration strategy on thromboelastometric hemostatic and regular coagulation parameters.

Which first-trimester risk assessment method for preeclampsia is most suitable? A model-based impact study.

BACKGROUND: Low-dose aspirin treatment reduces the risk of preeclampsia among high-risk pregnant women. Internationally, several first-trimester risk-calculation methods are applied. OBJECTIVE: This study aimed to assess the costs and benefits of different first-trimester preeclampsia risk estimation algorithms: EXPECT (an algorithmic prediction model based on maternal characteristics), National Institute for Health and Care Excellence (a checklist of risk factors), and the Fetal Medicine Foundation (a prediction model using additional uterine artery Doppler measurement and laboratory testing) models, coupled with low-dose aspirin treatment, in comparison with no risk assessment. STUDY DESIGN: We constructed a decision analytical model estimating the number of cases of preeclampsia with each strategy and the costs of risk assessment for preeclampsia and early aspirin treatment, expressed in euros (€) in a hypothetical population of 100,000 women. We performed 1-way sensitivity analyses to assess the impact of adherence rates on model outcomes. RESULTS: Application of the EXPECT, National Institute for Health and Care Excellence, and Fetal Medicine Foundation models results in respectively 1.98%, 2.55%, and 1.90% of the women developing preeclampsia, as opposed to 3.00% of women in the case of no risk assessment. Overall, the net financial benefits of the EXPECT, National Institute for Health and Care Excellence, and Fetal Medicine Foundation models relative to no risk assessment are €144, €43, and €38 per patient, respectively. The respective percentages of women receiving aspirin treatment are 18.6%, 10.2%, and 6.0% for the 3 risk assessment methods. CONCLUSION: The EXPECT and Fetal Medicine Foundation model are comparable with regard to numbers of prevented preeclampsia cases, and both are superior to the National Institute for Health and Care Excellence model and to no risk assessment. EXPECT is less resource-demanding and results in the highest cost savings, but also requires the highest number of women to be treated with aspirin. When deciding which strategy is preferable, cost savings and easier use have to be weighed against the degree of overtreatment, although low-dose aspirin has no clear disadvantages during pregnancy.

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.

Associations Between Late-Onset Preeclampsia and the Use of Calcium-Based Antacids and Proton Pump Inhibitors During Pregnancy: A Prospective Cohort Study.

Purpose: Preeclampsia is a leading cause of maternal morbidity and mortality. Calcium-based antacids and proton pump inhibitors (PPIs) are commonly used during pregnancy to treat symptoms of gastroesophageal reflux disease. Both have been hypothesized to reduce the risk of preeclampsia. We determined associations of calcium-based antacid and PPI use during pregnancy with late-onset preeclampsia (≥34 weeks of gestation), taking into account dosage and timing of use. Patients and Methods: We included 9058 pregnant women participating in the PRIDE Study (2012-2019) or The Dutch Pregnancy Drug Register (2014-2019), two prospective cohorts in The Netherlands. Data were collected through web-based questionnaires and obstetric records. We estimated risk ratios (RRs) for late-onset preeclampsia for any use and trajectories of calcium-based antacid and PPI use before gestational day 238, and hazard ratios (HRs) for time-varying exposures after gestational day 237. Results: Late-onset preeclampsia was diagnosed in 2.6% of pregnancies. Any use of calcium-based antacids (RR 1.2 [95% CI 0.9-1.6]) or PPIs (RR 1.4 [95% CI 0.8-2.4]) before gestational day 238 was not associated with late-onset preeclampsia. Use of low-dose calcium-based antacids in gestational weeks 0-16 (<1 g/day; RR 1.8 [95% CI 1.1-2.9]) and any use of PPIs in gestational weeks 17-33 (RR 1.6 [95% CI 1.0-2.8]) seemed to increase risks of late-onset preeclampsia. We did not observe associations between late-onset preeclampsia and use of calcium-based antacids (HR 1.0 [95% CI 0.6-1.5]) and PPIs (HR 1.4 [95% CI 0.7-2.9]) after gestational day 237. Conclusion: In this prospective cohort study, use of calcium-based antacids and PPIs during pregnancy was not found to reduce the risk of late-onset preeclampsia.

Predicting COVID-19 prognosis in the ICU remained challenging: external validation in a multinational regional cohort.

OBJECTIVES: Many prediction models for coronavirus disease 2019 (COVID-19) have been developed. External validation is mandatory before implementation in the intensive care unit (ICU). We selected and validated prognostic models in the Euregio Intensive Care COVID (EICC) cohort. STUDY DESIGN AND SETTING: In this multinational cohort study, routine data from COVID-19 patients admitted to ICUs within the Euregio Meuse-Rhine were collected from March to August 2020. COVID-19 models were selected based on model type, predictors, outcomes, and reporting. Furthermore, general ICU scores were assessed. Discrimination was assessed by area under the receiver operating characteristic curves (AUCs) and calibration by calibration-in-the-large and calibration plots. A random-effects meta-analysis was used to pool results. RESULTS: 551 patients were admitted. Mean age was 65.4 ± 11.2 years, 29% were female, and ICU mortality was 36%. Nine out of 238 published models were externally validated. Pooled AUCs were between 0.53 and 0.70 and calibration-in-the-large between -9% and 6%. Calibration plots showed generally poor but, for the 4C Mortality score and Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC) score, moderate calibration. CONCLUSION: Of the nine prognostic models that were externally validated in the EICC cohort, only two showed reasonable discrimination and moderate calibration. For future pandemics, better models based on routine data are needed to support admission decision-making.

Emerging Role of Carotid MRI for Personalized Ischemic Stroke Risk Prediction in Patients With Carotid Artery Stenosis.

Rupture of a vulnerable carotid plaque is an important cause of ischemic stroke. Prediction models can support medical decision-making by estimating individual probabilities of future events, while magnetic resonance imaging (MRI) can provide detailed information on plaque vulnerability. In this review, prediction models for medium to long-term (>90 days) prediction of recurrent ischemic stroke among patients on best medical treatment for carotid stenosis are evaluated, and the emerging role of MRI of the carotid plaque for personalized ischemic stroke prediction is discussed. A systematic search identified two models; the European Carotid Surgery Trial (ECST) medical model, and the Symptomatic Carotid Atheroma Inflammation Lumen stenosis (SCAIL) score. We critically appraised these models by means of criteria derived from the CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modeling Studies) and PROBAST (Prediction model Risk Of Bias ASsessment Tool). We found both models to be at high risk of bias. The ECST model, the most widely used model, was derived from data of large but relatively old trials (1980s and 1990s), not reflecting lower risks of ischemic stroke resulting from improvements in drug treatment (e.g., statins and anti-platelet therapy). The SCAIL model, based on the degree of stenosis and positron emission tomography/computed tomography (PET/CT)-based plaque inflammation, was derived and externally validated in limited samples. Clinical implementation of the SCAIL model can be challenging due to high costs and low accessibility of PET/CT. MRI is a more readily available, lower-cost modality that has been extensively validated to visualize all the hallmarks of plaque vulnerability. The MRI methods to identify the different plaque features are described. Intraplaque hemorrhage (IPH), a lipid-rich necrotic core (LRNC), and a thin or ruptured fibrous cap (TRFC) on MRI have shown to strongly predict stroke in meta-analyses. To improve personalized risk prediction, carotid plaque features should be included in prediction models. Prediction of stroke in patients with carotid stenosis needs modernization, and carotid MRI has potential in providing strong predictors for that goal.

Restrictive versus liberal fluid resuscitation strategy, influence on blood loss and hemostatic parameters in mild obstetric hemorrhage: An open-label randomized controlled trial. (REFILL study).

BACKGROUND: Evidence for optimal hemostatic resuscitation in postpartum hemorrhage (PPH) is lacking. Liberal fluid administration may result in acidosis, hypothermia and coagulopathy. OBJECTIVE: We hypothesize that in early PPH a restrictive fluid administration results in less progression to moderate PPH. STUDY DESIGN: In four Dutch hospitals we recruited women of 18 years and over, and more than 24 weeks pregnant. Exclusion criteria were: anticoagulant therapy, known coagulation disorders, pre-eclampsia, antenatal diagnosis of abnormally adhesive placenta, and a contraindication for liberal fluid therapy. We blindly randomized participants at 500 mL and ongoing blood loss in the third stage of labor between restrictive fluid administration (clear fluids 0.75-1.0 times the volume of blood lost) and liberal fluid administration (clear fluids 1.5-2.0 times the volume of blood lost). The primary outcome was progression to more than 1000 mL blood loss. Analyses were according to the intention-to-treat principle. RESULTS: From August 2014 till September 2019, 5190 women were informed of whom 1622 agreed to participate. A total of 252 women were randomized of which 130 were assigned to the restrictive group and 122 to the liberal group. In the restrictive management group 51 of the 130 patients (39.2%) progressed to more than 1000 mL blood loss versus 61 of the 119 patients (51.3%) in the liberal management group (difference, -12.0% [95%-CI -24.3% to 0.3%], p = 0.057). There was no difference in the need for blood transfusion, coagulation parameters, or in adverse events between the groups. CONCLUSIONS: Although a restrictive fluid resuscitation in women with mild PPH could not been proven to be superior, it does not increase the need for blood transfusion, alter coagulation parameters, or cause a rise in adverse events. It can be considered as an alternative treatment option to liberal fluid resuscitation. TRIAL REGISTRATION: NTR3789.

Perinatal factors related to pregnancy and childbirth satisfaction: a prospective cohort study.

BACKGROUND: Satisfaction of pregnancy and childbirth is an important quality measure of maternity care. Satisfaction questionnaires generally result in high scores. However, it has been argued that dissatisfaction relies on a different construct. In response to a worldwide call for obstetric care that is more woman-centered, we identified and described the contributors to suboptimal satisfaction with pregnancy and childbirth. METHODS: A prospective subcohort of 739 women from a larger cohort (Expect Study I, n = 2614) received a pregnancy and childbirth satisfaction questionnaire. Scores were transformed to a binary outcome whereby a score <100 points corresponded with less satisfied women. We performed a multiple logistic regression analysis to define independent perinatal factors related to suboptimal satisfaction. RESULTS: Decreased perceived personal well-being, antenatal anxiety, and obstetrician-led care during labor were all independently associated with suboptimal pregnancy and childbirth satisfaction. No difference in satisfaction was found between antenatal care led by a midwife or an obstetrician, but midwife-led antenatal care reduced the odds of suboptimal satisfaction compared to women who were transferred to an obstetrician in the antenatal period. Antenatal anxiety was experienced by 25% of all women and is associated with decreased satisfaction scores. DISCUSSION: Screening and treatment of women suffering from anxiety might improve pregnancy and childbirth satisfaction, but further research is necessary. Women's birthing experience may improve by reducing unnecessary secondary obstetric care.

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.

External validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysis.

BACKGROUND: Pre-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. METHODS: IPD 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. RESULTS: Of 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%. CONCLUSIONS: The 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 REGISTRATION: PROSPERO ID: CRD42015029349 .

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

OBJECTIVE: To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease. DESIGN: Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. DATA SOURCES: PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. STUDY SELECTION: Studies that developed or validated a multivariable covid-19 related prediction model. DATA EXTRACTION: At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). RESULTS: 37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models. CONCLUSION: Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. SYSTEMATIC REVIEW REGISTRATION: Protocol https://osf.io/ehc47/, registration https://osf.io/wy245. READERS' NOTE: This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

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.

Calcium intake from diet and supplement use during early pregnancy: the Expect study I.

PURPOSE: Adequate calcium intake during pregnancy is of major importance for the health of both mother and fetus. Up to date, evidence on the prevalence of inadequate calcium intake among pregnant women is sparse for Western countries, and it is unknown to what extent inadequate dietary calcium intake is adequately balanced by supplement use. The objective of this study was to estimate calcium intake from diet and supplement use during the early pregnancy in The Netherlands. METHODS: As part of the Expect cohort study, 2477 pregnant women (8-16 weeks of gestation) completed an online questionnaire including questions on baseline characteristics, the use of calcium containing supplements, and a short food-frequency questionnaire (FFQ). Intake data were used to calculate median calcium intakes from diet, from supplements, and combined, and to compare these values with currently accepted requirement levels. RESULTS: Forty-two percent of the pregnant women had a total calcium intake below the estimated average requirement of 800 mg/day. Median (interquartile range) calcium intake was 886 (611-1213) mg/day. Calcium or multivitamin supplements were used by 64.8% of the women at 8 weeks of gestation, with a median calcium content of 120.0 (60.0-200.0) mg/day. Prenatal vitamins were the most often used supplements (60.6%). CONCLUSIONS: Forty-two percent of Dutch pregnant women have an inadequate calcium intake. Supplements are frequently used, but most do not contain sufficient amounts to correct this inadequate intake.

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.