Development and validation of a gonadotropin dose selection model for optimized ovarian stimulation in IVF/ICSI: an individual participant data meta-analysis.

Background: The ovarian response to gonadotropin stimulation varies widely among women, and could impact the probability of live birth as well as treatment risks. Many studies have evaluated the impact of different gonadotropin starting doses, mainly based on predictive variables like ovarian reserve tests (ORT) including anti-Müllerian hormone (AMH), antral follicle count (AFC), and basal follicle-stimulating hormone (bFSH). A Cochrane systematic review revealed that individualizing the gonadotropin starting dose does not affect efficacy in terms of ongoing pregnancy/live birth rates, but may reduce treatment risks such as the development of ovarian hyperstimulation syndrome (OHSS).

Physical activity, sedentary behaviour, and childhood asthma: a European collaborative analysis.

Objectives: To investigate the associations of physical activity (PA) and sedentary behaviour in early childhood with asthma and reduced lung function in later childhood within a large collaborative study.

Design: Pooling of longitudinal data from collaborating birth cohorts using meta-analysis of separate cohort-specific estimates and analysis of individual participant data of all cohorts combined.

Setting: Children aged 0-18 years from 26 European birth cohorts.

Did aetiology matter in illness duration and complications in patients presenting in primary care with acute respiratory tract infections early in the COVID-19 pandemic: An observational study in nine countries.

Background: Despite considerable research into COVID-19 sequelae, little is known about differences in illness duration and complications in patients presenting in primary care with symptoms of acute respiratory tract infections (RTI) that are and are not attributed to SARS-CoV-2 infection.

Objective: To explore whether aetiology impacted course of illness and prediction of complications in patients presenting in primary care with symptoms of RTI early in the COVID-19 pandemic.

Methods: Between April 2020-March 2021 general practitioners from nine European countries recruited consecutively contacting patients with RTI symptoms.

Sharing Medical Big Data While Preserving Patient Confidentiality in Innovative Medicines Initiative: A Summary and Case Report from BigData@Heart.

Sharing individual patient data (IPD) is a simple concept but complex to achieve due to data privacy and data security concerns, underdeveloped guidelines, and legal barriers. Sharing IPD is additionally difficult in big data-driven collaborations such as Bigdata@Heart in the Innovative Medicines Initiative, due to competing interests between diverse consortium members. One project within BigData@Heart, case study 1, needed to pool data from seven heterogeneous data sets: five randomized controlled trials from three different industry partners, and two disease registries.

Assessment of risk of ALS conferred by the GGGGCC hexanucleotide repeat expansion in among first-degree relatives of patients with ALS carrying the repeat expansion.

Objectives: We aimed to estimate the age-related risk of ALS in first-degree relatives of patients with ALS carrying the repeat expansion.

Methods: We included all patients with ALS carrying a repeat expansion in The Netherlands. Using structured questionnaires, we determined the number of first-degree relatives, their age at death due to ALS or another cause, or age at time of questionnaire.

Identifying multivariate disease trajectories and potential phenotypes of early knee osteoarthritis in the CHECK cohort.

Objective: To gain better understanding of osteoarthritis (OA) heterogeneity and its predictors for distinguishing OA phenotypes. This could provide the opportunity to tailor prevention and treatment strategies and thus improve care.

Design: Ten year follow-up data from CHECK (1002 early-OA subjects with first general practitioner visit for complaints ≤6 months before inclusion) was used.

Using self-supervised feature learning to improve the use of pulse oximeter signals to predict paediatric hospitalization.

: The success of many machine learning applications depends on knowledge about the relationship between the input data and the task of interest (output), hindering the application of machine learning to novel tasks. End-to-end deep learning, which does not require intermediate feature engineering, has been recommended to overcome this challenge but end-to-end deep learning models require large labelled training data sets often unavailable in many medical applications. In this study, we trained self-supervised learning (SSL) models for automatic feature extraction from raw photoplethysmography (PPG) obtained using a pulse oximeter, with the aim of predicting paediatric hospitalization.

Endometrial scratching in women undergoing IVF/ICSI: an individual participant data meta-analysis.

Background: In IVF/ICSI treatment, the process of embryo implantation is the success rate-limiting step. Endometrial scratching has been suggested to improve this process, but it is unclear if this procedure increases the chance of implantation and live birth (LB) and, if so, for whom, and how the scratch should be performed.

Objective And Rationale: This individual participant data meta-analysis (IPD-MA) aims to answer the question of whether endometrial scratching in women undergoing IVF/ICSI influences the chance of a LB, and whether this effect is different in specific subgroups of women.

Sex differences in the generalizability of randomized clinical trials in heart failure with reduced ejection fraction.

Aims: In order to understand how sex differences impact the generalizability of randomized clinical trials (RCTs) in patients with heart failure (HF) and reduced ejection fraction (HFrEF), we sought to compare clinical characteristics and clinical outcomes between RCTs and HF observational registries stratified by sex.

Methods And Results: Data from two HF registries and five HFrEF RCTs were used to create three subpopulations: one RCT population (n = 16 917; 21.7% females), registry patients eligible for RCT inclusion (n = 26 104; 31.

Development and Evaluation of a Simulation-Based Algorithm to Optimize the Planning of Interim Analyses for Clinical Trials in ALS.

Background And Objectives: Late-phase clinical trials for neurodegenerative diseases have a low probability of success. In this study, we introduce an algorithm that optimizes the planning of interim analyses for clinical trials in amyotrophic lateral sclerosis (ALS) to better use the time and resources available and minimize the exposure of patients to ineffective or harmful drugs.

Methods: A simulation-based algorithm was developed to determine the optimal interim analysis scheme by integrating prior knowledge about the success rate of ALS clinical trials with drug-specific information obtained in early-phase studies.

Using the embryo-uterus statistical model to predict pregnancy chances by using cleavage stage morphokinetics and female age: two centre-specific prediction models and mutual validation.

Background: The predictive capability of time-lapse monitoring (TLM) selection algorithms is influenced by patient characteristics, type and quality of data included in the analysis and the used statistical methods. Previous studies excluded DET cycles of which only one embryo implanted, introducing bias into the data. Therefore, we wanted to develop a TLM prediction model that is able to predict pregnancy chances after both single- and double embryo transfer (SET and DET).

Artificial intelligence to enhance clinical value across the spectrum of cardiovascular healthcare.

Artificial intelligence (AI) is increasingly being utilized in healthcare. This article provides clinicians and researchers with a step-wise foundation for high-value AI that can be applied to a variety of different data modalities. The aim is to improve the transparency and application of AI methods, with the potential to benefit patients in routine cardiovascular care.

Predicting pregnancy chances leading to term live birth in oligo/anovulatory women diagnosed with PCOS.

Research Question: Which patient features predict the time to pregnancy (TTP) leading to term live birth in infertile women diagnosed with polycystic ovary syndrome (PCOS)?

Design: Prospective cohort follow-up study was completed, in which initial standardized phenotyping was conducted at two Dutch university medical centres from January 2004 to January 2014. Data were linked to the Netherlands Perinatal Registry to obtain pregnancy outcomes for each participant. All women underwent treatment according to a standardized protocol, starting with ovulation induction as first-line treatment.

Long-term effectiveness of dual CFTR modulator treatment of cystic fibrosis.

Background: Although short-term efficacy of lumacaftor/ivacaftor and tezacaftor/ivacaftor is clearly established in clinical trials, data on long-term effectiveness is limited. This registry-based cohort study assessed real-world longitudinal outcomes of F508del-homozygous people with cystic fibrosis (pwCF) ≥12 years, up to 3 years after the introduction of dual cystic fibrosis transmembrane conductance regulator (CFTR) modulators.

Methods: Annual data (2010-2019) were retrieved from the Dutch Cystic Fibrosis Registry.

Blood pressure and the risk of rebleeding and delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage.

Introduction And Objective: Blood pressure is presumably related to rebleeding and delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (aSAH) and could serve as a target to improve outcome. We assessed the associations between blood pressure and rebleeding or DCI in aSAH-patients.

Materials And Methods: In this observational study in 1167 aSAH-patients admitted to the intensive care unit (ICU), adjusted hazard ratio's (aHR) were calculated for the time-dependent association of blood pressure and rebleeding or DCI.

Using Machine Learning Methods Incorporating Individual Reader Annotations to Classify Paediatric Chest Radiographs in Epidemiological Studies.

: Epidemiological studies that involve interpretation of chest radiographs (CXRs) suffer from inter-reader and intra-reader variability. Inter-reader and intra-reader variability hinder comparison of results from different studies or centres, which negatively affects efforts to track the burden of chest diseases or evaluate the efficacy of interventions such as vaccines. This study explores machine learning models that could standardize interpretation of CXR across studies and the utility of incorporating individual reader annotations when training models using CXR data sets annotated by multiple readers.

Efficacy and safety of switching from intravenous to oral antibiotics (amoxicillin-clavulanic acid) versus a full course of intravenous antibiotics in neonates with probable bacterial infection (RAIN): a multicentre, randomised, open-label, non-inferiority trial.

Background: Switching from intravenous antibiotic therapy to oral antibiotic therapy among neonates is not yet practised in high-income settings due to uncertainties about exposure and safety. We aimed to assess the efficacy and safety of early intravenous-to-oral antibiotic switch therapy compared with a full course of intravenous antibiotics among neonates with probable bacterial infection.

Methods: In this multicentre, randomised, open-label, non-inferiority trial, patients were recruited at 17 hospitals in the Netherlands.

Comparison of parent reported physician diagnosed asthma and general practitioner registration.

Objective: To compare parent reported physician diagnosed asthma from questionnaires for epidemiological purposes, to general practitioner (GP) recorded childhood asthma.

Methods: This study was embedded in the KOALA Birth Cohort Study with regular follow-up by ISAAC core questions on asthma in 2834 children in two different recruitment groups, with 'conventional' lifestyles or 'alternative' lifestyles. At age 11-13 years these data were linked to data extracted from GP records.

Individual treatment effect estimation in the presence of unobserved confounding using proxies: a cohort study in stage III non-small cell lung cancer.

Randomized Controlled Trials (RCT) are the gold standard for estimating treatment effects but some important situations in cancer care require treatment effect estimates from observational data. We developed "Proxy based individual treatment effect modeling in cancer" (PROTECT) to estimate treatment effects from observational data when there are unobserved confounders, but proxy measurements of these confounders exist. We identified an unobserved confounder in observational cancer research: overall fitness.

Dysplastic Recurrence After Successful Treatment for Early Barrett's Neoplasia: Development and Validation of a Prediction Model.

Background & Aims: The combination of endoscopic resection and radiofrequency ablation is the treatment of choice for eradication of Barrett's esophagus (BE) with dysplasia and/or early cancer. Currently, there are no evidence-based recommendations on how to survey patients after successful treatment, and most patients undergo frequent follow-up endoscopies. We aimed to develop and externally validate a prediction model for visible dysplastic recurrence, which can be used to personalize surveillance after treatment.

Smartphone detection of atrial fibrillation using photoplethysmography: a systematic review and meta-analysis.

Objectives: Timely diagnosis of atrial fibrillation (AF) is essential to reduce complications from this increasingly common condition. We sought to assess the diagnostic accuracy of smartphone camera photoplethysmography (PPG) compared with conventional electrocardiogram (ECG) for AF detection.

Methods: This is a systematic review of MEDLINE, EMBASE and Cochrane (1980-December 2020), including any study or abstract, where smartphone PPG was compared with a reference ECG (1, 3 or 12-lead).

Forskolin-induced organoid swelling is associated with long-term cystic fibrosis disease progression.

Rationale: Cystic fibrosis (CF) is a monogenic life-shortening disease associated with highly variable individual disease progression which is difficult to predict. Here we assessed the association of forskolin-induced swelling (FIS) of patient-derived organoids with long-term CF disease progression in multiple organs and compared FIS with the golden standard biomarker sweat chloride concentration (SCC).

Methods: We retrieved 9-year longitudinal clinical data from the Dutch CF Registry of 173 people with mutations in the cystic fibrosis transmembrane conductance regulator () gene.

Comparison of statistical methods for the analysis of recurrent adverse events in the presence of non-proportional hazards and unobserved heterogeneity: a simulation study.

Background: In preventive drug trials such as intermittent preventive treatment for malaria prevention during pregnancy (IPTp), where there is repeated treatment administration, recurrence of adverse events (AEs) is expected. Challenges in modelling the risk of the AEs include accounting for time-to-AE and within-patient-correlation, beyond the conventional methods. The correlation comes from two sources; (a) individual patient unobserved heterogeneity (i.