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

Самоподобие массивов сетевых публикаций по компьютерной вирусологии

Описан подход к организации анализа потока тематических публикаций по компьютерной вирусологии, представленных в web-пространстве. Обоснована фрактальная природа информационных потоков, описаны основные алгоритмы, применяемые в процессе исследований, а также приведены прогнозные выводы на основе свойств персистентности временных рядов.Описано підхід до організації аналізу потоку тематичних публікацій з комп’ютерної вірусології, які наведені у web-просторі. Обґрунтовано фрактальну природу інформаційних потоків, описано основні алгоритми, що застосовуються в процесі досліджень, а також наведено прогнозні висновки на базі властивостей персистентності часових рядів.An approach to the organization of the analysis of a thematic publications stream on computer virology, submitted in web-space, is described. The fractal nature of information streams is proved, the basic algorithms used during researches are described and forecasts conclusions on the basis of persistent properties of time series are given

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.</p

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

Peer reviewedPublisher PD

Prognostic models versus single risk factor approach in first trimester selective screening for gestational diabetes mellitus: a prospective population-based multicentre cohort study

Objectives: To evaluate whether (1) first-trimester prognostic models for gestational diabetes mellitus (GDM) outperform the currently used single risk factor approach, and (2) a first-trimester random venous glucose measurement improves model performance. Design: Prospective population-based multicentre cohort. Setting: Thirty-one independent midwifery practices and six hospitals in the Netherlands. Population: Women recruited before 14 weeks of gestation without pre-existing diabetes. Methods: The single risk factor approach (presence of at least one risk factor: BMI ≥30 kg/m 2, previous macrosomia, history of GDM, positive first-degree family history of diabetes, non-western ethnicity) was compared with the four best performing models in our previously published external validation study (Gabbay-Benziv 2014, Nanda 2011, Teede 2011, van Leeuwen 2010) with and without the addition of glucose. Main outcome measures: Discrimination was assessed by c-statistics, calibration by calibration plots, added value of glucose by the likelihood ratio chi-square test, net benefit by decision curve analysis and reclassification by reclassification plots. Results: Of the 3723 women included, a total of 181 (4.9%) developed GDM. The c-statistics of the prognostic models were higher, ranging from 0.74 to 0.78 without glucose and from 0.78 to 0.80 with glucose, compared with the single risk factor approach (0.72). Models showed adequate calibration, and yielded a higher net benefit than the single risk factor approach for most threshold probabilities. Teede 2011 performed best in the reclassification analysis. Conclusions: First-trimester prognostic models seem to outperform the currently used single risk factor approach in screening for GDM, particularly when glucose was added as a predictor. Tweetable abstract: Prognostic models seem to outperform the currently used single risk factor approach in screening for gestational diabetes

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

Low dose aspirin in the prevention of recurrent spontaneous preterm labour - the APRIL study: A multicenter randomized placebo controlled trial

Background: Preterm birth (birth before 37 weeks of gestation) is a major problem in obstetrics and affects an estimated 15 million pregnancies worldwide annually. A history of previous preterm birth is the strongest risk factor for preterm birth, and recurrent spontaneous preterm birth affects more than 2.5 million pregnancies each year. A recent meta-analysis showed possible benefits of the use of low dose aspirin in the prevention of recurrent spontaneous preterm birth. We will assess the (cost-)effectiveness of low dose aspirin in comparison with placebo in the prevention of recurrent spontaneous preterm birth in a randomized clinical trial. Methods/design: Women with a singleton pregnancy and a history of spontaneous preterm birth in a singleton pregnancy (22-37 weeks of gestation) will be asked to participate in a multicenter, randomized, double blinded, placebo controlled trial. Women will be randomized to low dose aspirin (80 mg once daily) or placebo, initiated from 8 to 16 weeks up to maximal 36 weeks of gestation. The primary outcome measure will be preterm birth, defined as birth at a gestational age (GA) < 37 weeks. Secondary outcomes will be a composite of adverse neonatal outcome and maternal outcomes, including subgroups of prematurity, as well as intrauterine growth restriction (IUGR) and costs from a healthcare perspective. Preterm birth will be analyzed as a group, as well as separately for spontaneous or indicated onset. Analysis will be performed by intention to treat. In total, 406 pregnant women have to be randomized to show a reduction of 35% in preterm birth from 36 to 23%. If aspirin is effective in preventing preterm birth, we expect that there will be cost savings, because of the low costs of aspirin. To evaluate this, a cost-effectiveness analysis will be performed comparing preventive treatment with aspirin with placebo. Discussion: This trial will provide evidence as to whether or not low dose aspirin is (cost-) effective in reducing recurrence of spontaneous preterm birth. Trial registration: Clinical trial registration number of the Dutch Trial Register: NTR 5675. EudraCT-registration number: 2015-003220-31

Evaluation of low-dose aspirin in the prevention of recurrent spontaneous preterm labour (the APRIL study) : A multicentre, randomised, double-blinded, placebo-controlled trial

Funding: MdB, LV, TN, BM, MO and CdG received funding from ZonMw, The Dutch Organisation for Health Research and Development (grant number 836041006). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Thyroid-stimulating hormone and free thyroxine fail to predict the severity and clinical course of hyperemesis gravidarum : A prospective cohort study

Funding information: This prospective cohort study was supported by a research grant from North West Hospital Group, Alkmaar, the Netherlands (Grant number: 2013T085) and by a research grant from the Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam UMC, the Netherlands (Project number: 23346). ACKNOWLEDGMENTS We thank Dr. J.P. Bestwick (employed at Queen Mary University of London, London, UK) and Professor Dr. J.H. Lazarus (employed at Cardiff School of Medicine, Cardiff, UK) for providing TSH medians from their study in the UK. Dr. J.P. Bestwick and Professor Dr. Lazarus have nothing to disclose.Peer reviewedPublisher PD