External validation and update of a prognostic model to predict mortality in hospitalized adults with RSV: A retrospective Dutch cohort study.

Respiratory syncytial virus (RSV) causes significant mortality in hospitalized adults. Prediction of poor outcomes improves targeted management and clinical outcomes. We externally validated and updated existing models to predict poor outcome in hospitalized RSV-infected adults. In this single center, retrospective, observational cohort study, we included hospitalized adults with respiratory tract infections (RTIs) and a positive polymerase chain reaction for RSV (A/B) on respiratory tract samples (2005-2018). We validated existing prediction models and updated the best discriminating model by revision, recalibration, and incremental value testing. We included 192 RSV-infected patients (median age 60.7 years, 57% male, 65% immunocompromised, and 43% with lower RTI). Sixteen patients (8%) died within 30 days. During hospitalization, 16 (8%) died, 30 (16%) were admitted to intensive care unit, 21 (11%) needed invasive mechanical ventilation, and 5 (3%) noninvasive positive pressure ventilation. Existing models performed moderately at external validation, with C-statistics 0.6 to 0.7 and moderate calibration. Updating to a model including lower RTI, chronic pulmonary disease, temperature, confusion and urea, increased the C-statistic to 0.76 (95% confidence interval, 0.61-0.91) to predict in-hospital mortality. In conclusion, existing models to predict poor prognosis among hospitalized RSV-infected adults perform moderately at external validation. A prognostic model may help to identify and treat RSV-infected adults at high-risk of death.

RSV hospitalization in infancy increases the risk of current wheeze at age 6 in late preterm born children without atopic predisposition.

Severe respiratory syncytial virus (RSV) infection during infancy is associated with ongoing respiratory morbidity. In a large birth cohort of 2210 healthy preterm infants born at 32-35 weeks of gestation, we aimed to determine the role of atopy in the link between RSV hospitalization and current wheeze at age 6. We defined current wheeze as parent-reported wheeze or the use of respiratory medication in the past 12 months. Based on a positive family history of atopic disease, we distinguished between children with and without atopic predisposition. Six-year follow-up data was obtained in 997/1559 (64%) children of which 102 (10.2%) children had been hospitalized with RSV during infancy. Current wheeze was present in 184/997 (18.6%) children. RSV hospitalization was an independent risk factor for current wheeze in children without atopic predisposition (aOR 4.05 [95% CI 1.22-12.52]) but not in children with this atopic background (aOR 1.50 [95% CI 0.81-2.71]).Conclusion: This is the largest published birth cohort demonstrating that in late preterm infants, atopic predisposition defines the relationship between RSV hospitalization and current wheeze. Future RSV prevention trials aiming to prevent ongoing respiratory symptoms should be analyzed separately for atopic status. What is Known: • RSV infection is responsible for a significant burden of disease in young children worldwide. • Severe RSV infection in early life is associated with asthmatic symptoms later in life. What is New: • This is the largest published birth cohort reporting about the role of atopic predisposition in the link between severe RSV infection and current wheeze at school age. • We show that RSV hospitalization in infancy is an independent risk factor for current wheeze in late preterm children without atopic predisposition at age 6. This was not seen in children with atopic predisposition.

Continuous glucose monitoring during diabetic pregnancy (GlucoMOMS): A multicentre randomized controlled trial.

AIM: Diabetes is associated with a high risk of adverse pregnancy outcomes. Optimal glycaemic control is fundamental and is traditionally monitored with self-measured glucose profiles and periodic HbA1c measurements. We investigated the effectiveness of additional use of retrospective continuous glucose monitoring (CGM) in diabetic pregnancies. MATERIAL AND METHODS: We performed a nationwide multicentre, open label, randomized, controlled trial to study pregnant women with type 1 or type 2 diabetes who were undergoing insulin therapy at gestational age < 16 weeks, or women who were undergoing insulin treatment for gestational diabetes at gestational age < 30 weeks. Women were randomly allocated (1:1) to intermittent use of retrospective CGM or to standard treatment. Glycaemic control was assessed by CGM for 5-7 days every 6 weeks in the CGM group, while self-monitoring of blood glucose and HbA1c measurements were applied in both groups. Primary outcome was macrosomia, defined as birth weight above the 90th percentile. Secondary outcomes were glycaemic control and maternal and neonatal complications. RESULTS: Between July 2011 and September 2015, we randomized 300 pregnant women with type 1 (n = 109), type 2 (n = 82) or with gestational (n = 109) diabetes to either CGM (n = 147) or standard treatment (n = 153). The incidence of macrosomia was 31.0% in the CGM group and 28.4% in the standard treatment group (relative risk [RR], 1.06; 95% CI, 0.83-1.37). HbA1c levels were similar between treatment groups. CONCLUSIONS: In diabetic pregnancy, use of intermittent retrospective CGM did not reduce the risk of macrosomia. CGM provides detailed information concerning glycaemic fluctuations but, as a treatment strategy, does not translate into improved pregnancy outcome.

Cost-effectiveness of laparoscopy as diagnostic tool before primary cytoreductive surgery in ovarian cancer.

OBJECTIVE: To evaluate the cost-effectiveness of a diagnostic laparoscopy prior to primary cytoreductive surgery to prevent futile primary cytoreductive surgery (i.e. leaving >1cm residual disease) in patients suspected of advanced stage ovarian cancer. METHODS: An economic analysis was conducted alongside a randomized controlled trial in which patients suspected of advanced stage ovarian cancer who qualified for primary cytoreductive surgery were randomized to either laparoscopy or primary cytoreductive surgery. Direct medical costs from a health care perspective over a 6-month time horizon were analyzed. Health outcomes were expressed in quality-adjusted life-years (QALYs) and utility was based on patient's response to the EQ-5D questionnaires. We primarily focused on direct medical costs based on Dutch standard prices. RESULTS: We studied 201 patients, of whom 102 were randomized to laparoscopy and 99 to primary cytoreductive surgery. No significant difference in QALYs (utility=0.01; 95% CI 0.006 to 0.02) was observed. Laparoscopy reduced the number of futile laparotomies from 39% to 10%, while its costs were € 1400 per intervention, making the overall costs of both strategies comparable (difference € -80 per patient (95% CI -470 to 300)). Findings were consistent across various sensitivity analyses. CONCLUSION: In patients with suspected advanced stage ovarian cancer, a diagnostic laparoscopy reduced the number of futile laparotomies, without increasing total direct medical health care costs, or adversely affecting complications or quality of life.

Pessary or Progesterone to Prevent Preterm delivery in women with short cervical length: the Quadruple P randomised controlled trial.

BACKGROUND: Preterm birth is in quantity and in severity the most important topic in obstetric care in the developed world. Progestogens and cervical pessaries have been studied as potential preventive treatments with conflicting results. So far, no study has compared both treatments. METHODS/DESIGN: The Quadruple P study aims to compare the efficacy of vaginal progesterone and cervical pessary in the prevention of adverse perinatal outcome associated with preterm birth in asymptomatic women with a short cervix, in singleton and multiple pregnancies separately. It is a nationwide open-label multicentre randomized clinical trial (RCT) with a superiority design and will be accompanied by an economic analysis. Pregnant women undergoing the routine anomaly scan will be offered cervical length measurement between 18 and 22 weeks in a singleton and at 16-22 weeks in a multiple pregnancy. Women with a short cervix, defined as less than, or equal to 35 mm in a singleton and less than 38 mm in a multiple pregnancy, will be invited to participate in the study. Eligible women will be randomly allocated to receive either progesterone or a cervical pessary. Following randomization, the silicone cervical pessary will be placed during vaginal examination or 200 mg progesterone capsules will be daily self-administered vaginally. Both interventions will be continued until 36 weeks gestation or until delivery, whichever comes first. Primary outcome will be composite adverse perinatal outcome of perinatal mortality and perinatal morbidity including bronchopulmonary dysplasia, intraventricular haemorrhage grade III and IV, periventricular leukomalacia higher than grade I, necrotizing enterocolitis higher than stage I, Retinopathy of prematurity (ROP) or culture proven sepsis. These outcomes will be measured up until 10 weeks after the expected due date. Secondary outcomes will be, among others, time to delivery, preterm birth rate before 28, 32, 34 and 37 weeks, admission to neonatal intensive care unit, maternal morbidity, maternal admission days for threatened preterm labour and costs. DISCUSSION: This trial will provide evidence on whether vaginal progesterone or a cervical pessary is more effective in decreasing adverse perinatal outcome in both singletons and multiples. TRIAL REGISTRATION: Trial registration number: NTR 4414 . Date of registration January 29th 2014.

Assessing variability in results in systematic reviews of diagnostic studies.

BACKGROUND: To describe approaches used in systematic reviews of diagnostic test accuracy studies for assessing variability in estimates of accuracy between studies and to provide guidance in this area. METHODS: Meta-analyses of diagnostic test accuracy studies published between May and September 2012 were systematically identified. Information on how the variability in results was investigated was extracted. RESULTS: Of the 53 meta-analyses included in the review, most (n=48; 91%) presented variability in diagnostic accuracy estimates visually either through forest plots or ROC plots and the majority (n=40; 75%) presented a test or statistical measure for the variability. Twenty-eight reviews (53%) tested for variability beyond chance using Cochran's Q test and 31 (58%) reviews quantified it with I(2). 7 reviews (13%) presented between-study variance estimates (τ(2)) from random effects models and 3 of these presented a prediction interval or ellipse to facilitate interpretation. Half of all the meta-analyses specified what was considered a significant amount of variability (n=24; 49%). CONCLUSIONS: Approaches to assessing variability in estimates of accuracy varied widely between diagnostic test accuracy reviews and there is room for improvement. We provide initial guidance, complemented by an overview of the currently available approaches.

Latent class models in diagnostic studies when there is no reference standard--a systematic review.

Latent class models (LCMs) combine the results of multiple diagnostic tests through a statistical model to obtain estimates of disease prevalence and diagnostic test accuracy in situations where there is no single, accurate reference standard. We performed a systematic review of the methodology and reporting of LCMs in diagnostic accuracy studies. This review shows that the use of LCMs in such studies increased sharply in the past decade, notably in the domain of infectious diseases (overall contribution: 59%). The 64 reviewed studies used a range of differently specified parametric latent variable models, applying Bayesian and frequentist methods. The critical assumption underlying the majority of LCM applications (61%) is that the test observations must be independent within 2 classes. Because violations of this assumption can lead to biased estimates of accuracy and prevalence, performing and reporting checks of whether assumptions are met is essential. Unfortunately, our review shows that 28% of the included studies failed to report any information that enables verification of model assumptions or performance. Because of the lack of information on model fit and adequate evidence "external" to the LCMs, it is often difficult for readers to judge the validity of LCM-based inferences and conclusions reached.

Incorporating quality assessments of primary studies in the conclusions of diagnostic accuracy reviews: a cross-sectional study.

BACKGROUND: Drawing conclusions from systematic reviews of test accuracy studies without considering the methodological quality (risk of bias) of included studies may lead to unwarranted optimism about the value of the test(s) under study. We sought to identify to what extent the results of quality assessment of included studies are incorporated in the conclusions of diagnostic accuracy reviews. METHODS: We searched MEDLINE and EMBASE for test accuracy reviews published between May and September 2012. We examined the abstracts and main texts of these reviews to see whether and how the results of quality assessment were linked to the accuracy estimates when drawing conclusions. RESULTS: We included 65 reviews of which 53 contained a meta-analysis. Sixty articles (92%) had formally assessed the methodological quality of included studies, most often using the original QUADAS tool (n = 44, 68%). Quality assessment was mentioned in 28 abstracts (43%); with a majority (n = 21) mentioning it in the methods section. In only 5 abstracts (8%) were results of quality assessment incorporated in the conclusions. Thirteen reviews (20%) presented results of quality assessment in the main text only, without further discussion. Forty-seven reviews (72%) discussed results of quality assessment; the most frequent form was as limitations in assessing quality (n = 28). Only 6 reviews (9%) further linked the results of quality assessment to their conclusions, 3 of which did not conduct a meta-analysis due to limitations in the quality of included studies. In the reviews with a meta-analysis, 19 (36%) incorporated quality in the analysis. Eight reported significant effects of quality on the pooled estimates; in none of them these effects were factored in the conclusions. CONCLUSION: While almost all recent diagnostic accuracy reviews evaluate the quality of included studies, very few consider results of quality assessment when drawing conclusions. The practice of reporting systematic reviews of test accuracy should improve if readers not only want to be informed about the limitations in the available evidence, but also on the associated implications for the performance of the evaluated tests.

Evaluating diagnostic accuracy in the face of multiple reference standards.

A universal challenge in studies that quantify the accuracy of diagnostic tests is establishing whether each participant has the disease of interest. Ideally, the same preferred reference standard would be used for all participants; however, for practical or ethical reasons, alternative reference standards that are often less accurate are frequently used instead. The use of different reference standards across participants in a single study is known as differential verification.Differential verification can cause severely biased accuracy estimates of the test or model being studied. Many variations of differential verification exist, but not all introduce the same risk of bias. A risk-of-bias assessment requires detailed information about which participants receive which reference standards and an estimate of the accuracy of the alternative reference standard. This article classifies types of differential verification and explores how they can lead to bias. It also provides guidance on how to report results and assess the risk of bias when differential verification occurs and highlights potential ways to correct for the bias.

Use of expert panels to define the reference standard in diagnostic research: a systematic review of published methods and reporting.

BACKGROUND: In diagnostic studies, a single and error-free test that can be used as the reference (gold) standard often does not exist. One solution is the use of panel diagnosis, i.e., a group of experts who assess the results from multiple tests to reach a final diagnosis in each patient. Although panel diagnosis, also known as consensus or expert diagnosis, is frequently used as the reference standard, guidance on preferred methodology is lacking. The aim of this study is to provide an overview of methods used in panel diagnoses and to provide initial guidance on the use and reporting of panel diagnosis as reference standard. METHODS AND FINDINGS: PubMed was systematically searched for diagnostic studies applying a panel diagnosis as reference standard published up to May 31, 2012. We included diagnostic studies in which the final diagnosis was made by two or more persons based on results from multiple tests. General study characteristics and details of panel methodology were extracted. Eighty-one studies were included, of which most reported on psychiatry (37%) and cardiovascular (21%) diseases. Data extraction was hampered by incomplete reporting; one or more pieces of critical information about panel reference standard methodology was missing in 83% of studies. In most studies (75%), the panel consisted of three or fewer members. Panel members were blinded to the results of the index test results in 31% of studies. Reproducibility of the decision process was assessed in 17 (21%) studies. Reported details on panel constitution, information for diagnosis and methods of decision making varied considerably between studies. CONCLUSIONS: Methods of panel diagnosis varied substantially across studies and many aspects of the procedure were either unclear or not reported. On the basis of our review, we identified areas for improvement and developed a checklist and flow chart for initial guidance for researchers conducting and reporting of studies involving panel diagnosis. Please see later in the article for the Editors' Summary.

What are Effective Strategies to Reduce Low-Value Care? An Analysis of 121 Randomized Deimplementation Studies.

BACKGROUND: Low-value care is healthcare leading to no or little clinical benefit for the patient. The best (combinations of) interventions to reduce low-value care are unclear. PURPOSE: To provide an overview of randomized controlled trials (RCTs) evaluating deimplementation strategies, to quantify the effectiveness and describe different combinations of strategies. METHODS: Analysis of 121 RCTs (1990-2019) evaluating a strategy to reduce low-value care, identified by a systematic review. Deimplementation strategies were described and associations between strategy characteristics and effectiveness explored. RESULTS: Of 109 trials comparing deimplementation to usual care, 75 (69%) reported a significant reduction of low-value healthcare practices. Seventy-three trials included in a quantitative analysis showed a median relative reduction of 17% (IQR 7%-42%). The effectiveness of deimplementation strategies was not associated with the number and types of interventions applied. CONCLUSIONS AND IMPLICATIONS: Most deimplementation strategies achieved a considerable reduction of low-value care. We found no signs that a particular type or number of interventions works best for deimplementation. Future deimplementation studies should map relevant contextual factors, such as the workplace culture or economic factors. Interventions should be tailored to these factors and provide details regarding sustainability of the effect.

Estimated impact of introduction of new diagnostic criteria for gestational diabetes mellitus.

BACKGROUND: Implementation of new diagnostic criteria for gestational diabetes mellitus (GDM) are still a subject of debate, mostly due to concerns regarding the effects on the number of women diagnosed with GDM and the risk profile of the women newly diagnosed. AIM: To estimate the impact of the World Health Organization (WHO) 2013 criteria compared with the WHO 1999 criteria on the incidence of gestational diabetes mellitus as well as to determine the diagnostic accuracy for detecting adverse pregnancy outcomes. METHODS: We retrospectively analyzed a single center Dutch cohort of 3338 women undergoing a 75 g oral glucose tolerance test where the WHO 1999 criteria to diagnose GDM were clinically applied. Women were categorized into four groups: non-GDM by both criteria, GDM by WHO 1999 only (excluded from GDM), GDM by WHO 2013 only (newly diagnosed) and GDM by both criteria. We compared maternal characteristics, pregnancy outcomes and likelihood ratios for adverse pregnancy outcomes. RESULTS: Retrospectively applying the WHO 2013 criteria increased the cohort incidence by 13.1%, from 19.3% to 32.4%. Discordant diagnoses occurred in 21.3%; 4.1% would no longer be labelled as GDM, and 17.2% were newly diagnosed. Compared to the non-GDM group, women newly diagnosed were older, had higher rates of obesity, higher diastolic blood pressure and higher rates of caesarean deliveries. Their infants were more often delivered preterm, large-for-gestational-age and were at higher risk of a 5 min Apgar score < 7. Women excluded from GDM were older and had similar pregnancy outcomes compared to the non-GDM group, except for higher rates of shoulder dystocia (4.3% vs 1.3%, P = 0.015). Positive likelihood ratios for adverse outcomes in all groups were generally low, ranging from 0.54 to 2.95. CONCLUSION: Applying the WHO 2013 criteria would result in a substantial increase in GDM diagnoses. Newly diagnosed women are at increased risk for pregnancy adverse outcomes. This risk, however, seems to be lower than those identified by the WHO 1999 criteria. This could potentially influence the treatment effect that can be achieved in this group. Evidence on treatment effects in newly diagnosed women is urgently needed.

Strategies to reduce the use of low-value medical tests in primary care: a systematic review.

BACKGROUND: It is recognised that medical tests are overused in primary care; however, it is unclear how best to reduce their use. AIM: To identify which strategies are effective in reducing the use of low-value medical tests in primary care settings. DESIGN AND SETTING: Systematic review. METHOD: The databases MEDLINE, EMBASE, and Rx for Change were searched (January 1990 to November 2019) for randomised controlled trials (RCTs) that evaluated strategies to reduce the use of low-value medical tests in primary care settings. Two reviewers selected eligible RCTs, extracted data, and assessed their risk of bias. RESULTS: Of the 16 RCTs included in the review, 11 reported a statistically significant reduction in the use of low-value medical tests. The median of the differences between the relative reductions in the intervention and control arms was 17% (interquartile range 12% to 24%). Strategies using reminders or audit/feedback showed larger reduction than those without these components (22% versus 14%, and 22% versus 13%, respectively) and patient-targeted strategies showed larger reductions than those not targeted at patients (51% versus 17%). Very few studies investigated the sustainability of the effect, adverse events, cost-effectiveness, or patient-reported outcomes related to reducing the use of low-value tests. CONCLUSION: This review indicates that it is possible to reduce the use of low-value medical tests in primary care, especially by using multiple components including reminders, audit/feedback, and patient-targeted interventions. To implement these strategies widely in primary care settings, more research is needed not only to investigate their effectiveness, but also to examine adverse events, cost-effectiveness, and patient-reported outcomes.

Defining asthma in children: how well do parents, doctors and spirometry agree?

BACKGROUND: Because diagnosing asthma in school-aged children is challenging, a variety of proxies for asthma are used in clinical practice and research settings as indicators of this disease. We aimed to provide insight into the agreement between various asthma indicators based on parental report, medical diagnosis and spirometry. METHODS: Children from the WHISTLER birth cohort performed spirometry and were followed up with parental ISAAC (International Study of Asthma and Allergies in Childhood) questionnaires about asthma at 5 and 8 years of age. Medical data were extracted from primary care records. We compared 15 asthma indicators based on parental report, medical diagnosis and spirometry using positive agreement, κ statistics and latent class cluster analysis. RESULTS: At 5 years of age, 1007 children completed a study visit, while 803 children visited at 8 years of age. Depending on the indicator, the responder and child's age, the asthma prevalence ranged from 0.2% to 26.6%. Cluster analysis revealed classes related to the presence of recent symptoms and a decreased lung function. Agreement between parents and doctors was generally low with κ coefficients ranging from 0.07 (recent wheeze) to 0.52 (recent asthma medication). Additionally, parental report showed to be sensitive to recall bias over time. CONCLUSIONS: Dependent on the asthma indicator, the responder and the age of the child, substantial differences in agreement were observed between commonly used indicators associated with asthmatic disease in school-aged children. Most agreement between parents and doctors was seen for objective and recent indicators such as the recent use of asthma medication. We advocate caution when literature with different asthma indicators is compared.

Forcing dichotomous disease classification from reference standards leads to bias in diagnostic accuracy estimates: A simulation study.

OBJECTIVES: The objective of this study was to study the impact of ignoring uncertainty by forcing dichotomous classification (presence or absence) of the target disease on estimates of diagnostic accuracy of an index test. STUDY DESIGN AND SETTING: We evaluated the bias in estimated index test accuracy when forcing an expert panel to make a dichotomous target disease classification for each individual. Data for various scenarios with expert panels were simulated by varying the number and accuracy of "component reference tests" available to the expert panel, index test sensitivity and specificity, and target disease prevalence. RESULTS: Index test accuracy estimates are likely to be biased when there is uncertainty surrounding the presence or absence of the target disease. Direction and amount of bias depend on the number and accuracy of component reference tests, target disease prevalence, and the true values of index test sensitivity and specificity. CONCLUSION: In this simulation, forcing expert panels to make a dichotomous decision on target disease classification in the presence of uncertainty leads to biased estimates of index test accuracy. Empirical studies are needed to demonstrate whether this bias can be reduced by assigning a probability of target disease presence for each individual, or using advanced statistical methods to account for uncertainty in target disease classification.

Detailed statistical analysis plan for the Dutch STRIDER (Sildenafil TheRapy In Dismal prognosis Early-onset fetal growth Restriction) randomised clinical trial on sildenafil versus placebo for pregnant women with severe early onset fetal growth restriction.

OBJECTIVE: The objective of the Dutch Sildenafil therapy in dismal prognosis early onset fetal growth restriction (STRIDER) randomised clinical trial is to assess the beneficial and harmful effects of sildenafil versus placebo on fetal and neonatal mortality in pregnant women with severe early-onset fetal growth restriction. The objective of this detailed statistical analysis plan is to minimize the risks of selective reporting and data-driven analysis. SETTING: The setting is 10 tertiary care hospitals and one secondary care hospital in The Netherlands. PARTICIPANTS: The participants will be 360 pregnant women with severe early-onset fetal growth restriction. INTERVENTIONS: The intervention is sildenafil 25 mg or placebo orally three times a day. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome is a composite of death or major neonatal morbidity assessed at hospital discharge. The secondary outcomes are neurodevelopmental impairment; mean scores of the Bayley III cognitive and motor assessment; the proportion of patients experiencing either preeclampsia or haemolysis, elevated liver enzymes, and low platelets syndrome; pulsatility index of uterine arteries, umbilical artery, and middle cerebral artery; birthweight; and gestational age at either delivery or intra-uterine death. RESULTS: A detailed statistical analysis is presented, including pre-defined exploratory outcomes and planned subgroup analyses. One interim analysis after 180 patients had completed the study was planned and a strategy to minimise the risks of type I errors due to repetitive testing is presented. During review of this manuscript the interim analysis was performed by the Data Safety Monitoring Board and early stopping of the trial was recommended. Final analyses will be conducted independently by two statistically qualified persons following the present plan. CONCLUSION: This pre-specified statistical analysis plan was written and submitted without knowledge of the unblinded data and updated after stopping of the trial at interim analysis. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02277132 . Registered on 29 September 2014. Original protocol for the study: doi: https://doi.org/10.5281/zenodo.56148.

Decision analytic modeling was useful to assess the impact of a prediction model on health outcomes before a randomized trial.

OBJECTIVE: To demonstrate how decision analytic models (DAMs) can be used to quantify impact of using a (diagnostic or prognostic) prediction model in clinical practice and provide general guidance on how to perform such assessments. STUDY DESIGN AND SETTING: A DAM was developed to assess the impact of using the HEART score for predicting major adverse cardiac events (MACE). Impact on patient health outcomes and health care costs was assessed in scenarios by varying compliance with and informed deviation (ID) (using additional clinical knowledge) from HEART score management recommendations. Probabilistic sensitivity analysis was used to assess estimated impact robustness. RESULTS: Impact of using the HEART score on health outcomes and health care costs was influenced by an interplay of compliance with and ID from HEART score management recommendations. Compliance of 50% (with 0% ID) resulted in increased missed MACE and costs compared with usual care. Any compliance combined with at least 50% ID reduced both costs and missed MACE. Other scenarios yielded a reduction in missed MACE at higher costs. CONCLUSION: Decision analytic modeling is a useful approach to assess impact of using a prediction model in practice on health outcomes and health care costs. This approach is recommended before conducting an impact trial to improve its design and conduct.

Study protocol for a randomised trial for atosiban versus placebo in threatened preterm birth: the APOSTEL 8 study.

INTRODUCTION: Preterm birth complicates >15 million pregnancies annually worldwide. In many countries, women who present with signs of preterm labour are treated with tocolytics for 48 hours. Although this delays birth, it has never been shown to improve neonatal outcome. In 2015, the WHO stated that the use of tocolytics should be reconsidered and that large placebo-controlled studies to evaluate the effectiveness of tocolytics are urgently needed. METHODS AND ANALYSIS: We designed an international, multicentre, randomised, double-blinded, placebo-controlled clinical trial. Women with threatened preterm birth (gestational age 30-34 weeks), defined as uterine contractions with (1) a cervical length of < 15 mm or (2) a cervical length of 15-30 mm and a positive fibronectin test or (3) in centres where cervical length measurement is not part of the local protocol: a positive fibronectin test or insulin-like growth factor binding protein-1 (Actim-Partus test) or (4) ruptured membranes, will be randomly allocated to treatment with atosiban or placebo for 48 hours. The primary outcome is a composite of perinatal mortality and severe neonatal morbidity. Analysis will be by intention to treat. A sample size of 1514 participants (757 per group) will detect a reduction in adverse neonatal outcome from 10% to 6% (alpha 0.05, beta 0.2). A cost-effectiveness analysis will be performed from a societal perspective. ETHICS AND DISSEMINATION: This study has been approved by the Research Ethics Committee (REC) of the Amsterdam University Medical Centres, location AMC, as well as the REC's in Dublin and the UK. The results will be presented at conferences and published in a peer-reviewed journal. Participants will be informed about the results. TRIAL REGISTRATION NUMBER: Nederlands Trial Register (Trial NL6469).