A data management system for precision medicine.

Precision, or personalised medicine has advanced requirements for medical data management systems (MedDMSs). MedDMS for precision medicine should be able to process hundreds of parameters from multiple sites, be adaptable while remaining in sync at multiple locations, real-time syncing to analytics and be compliant with international privacy legislation. This paper describes the LogiqSuite software solution, aimed to support a precision medicine solution at the patient care (LogiqCare), research (LogiqScience) and data science (LogiqAnalytics) level.

Cautiously optimistic: paediatric critical care nurses' perspectives on data-driven algorithms in low-resource settings-a human-centred design study in Malawi.

Background: Paediatric critical care nurses face challenges in promptly detecting patient deterioration and delivering high-quality care, especially in low-resource settings (LRS). Patient monitors equipped with data-driven algorithms that monitor and integrate clinical data can optimise scarce resources (e.g.

Inhalation corticosteroids for COVID-19 - a real world data analysis on guideline adherence.

Background: The recommendation to consider prescribing inhalation corticosteroids to a subgroup of vulnerable COVID-19 patients was added to the Dutch medical guideline on November 11, 2021, and was also adopted by other countries during the pandemic.

Aim: To evaluate the adherence of general practitioners to this guideline, and whether real-world data quality is sufficient to study the effect of revised guidelines on prescribing behaviour.

Design & Setting: A retrospective cohort study using Dutch primary care data from the Extramural LUMC Academic Network database, containing patient data of 129 general practices in the Leiden - The Hague area.

Outcomes of female fertility preservation with cryopreservation of oocytes or embryos in the Netherlands: a population-based study.

Study Question: What are the reproductive outcomes of patients who cryopreserved oocytes or embryos in the context of fertility preservation in the Netherlands?

Summary Answer: This study shows that after a 10-year follow-up period, the utilization rate to attempt pregnancy using cryopreserved oocytes or embryos was 25.5% and the cumulative live birth rate after embryo transfer was 34.6% per patient.

The effect and implementation of the COVID Box, a remote patient monitoring system for patients with a COVID-19 infection in primary care: a matched cohort study.

At the onset of the COVID-19 pandemic, the pressure on hospitals increased tremendously. To alleviate this pressure, a remote patient monitoring system called the COVID Box was developed and implemented in primary care. The aim was to assess whether the COVID Box in primary care could reduce emergency department (ED) referrals due to a COVID-19 infection.

Availability of Evidence for Predictive Machine Learning Algorithms in Primary Care: A Systematic Review.

Importance: The aging and multimorbid population and health personnel shortages pose a substantial burden on primary health care. While predictive machine learning (ML) algorithms have the potential to address these challenges, concerns include transparency and insufficient reporting of model validation and effectiveness of the implementation in the clinical workflow.

Objectives: To systematically identify predictive ML algorithms implemented in primary care from peer-reviewed literature and US Food and Drug Administration (FDA) and Conformité Européene (CE) registration databases and to ascertain the public availability of evidence, including peer-reviewed literature, gray literature, and technical reports across the artificial intelligence (AI) life cycle.

Prediction of aneurysmal subarachnoid hemorrhage in comparison with other stroke types using routine care data.

Aneurysmal subarachnoid hemorrhage (aSAH) can be prevented by early detection and treatment of intracranial aneurysms in high-risk individuals. We investigated whether individuals at high risk of aSAH in the general population can be identified by developing an aSAH prediction model with electronic health records (EHR) data. To assess the aSAH model's relative performance, we additionally developed prediction models for acute ischemic stroke (AIS) and intracerebral hemorrhage (ICH) and compared the discriminative performance of the models.

Prediction of individual lifetime cardiovascular risk and potential treatment benefit: development and recalibration of the LIFE-CVD2 model to four European risk regions.

Aims: The 2021 European Society of Cardiology prevention guidelines recommend the use of (lifetime) risk prediction models to aid decisions regarding initiation of prevention. We aimed to update and systematically recalibrate the LIFEtime-perspective CardioVascular Disease (LIFE-CVD) model to four European risk regions for the estimation of lifetime CVD risk for apparently healthy individuals.

Methods And Results: The updated LIFE-CVD (i.

Patient and Staff Experience of Remote Patient Monitoring-What to Measure and How: Systematic Review.

Background: Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience-measuring methods and tools exists.

Objective: This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain.

Tailoring remote patient management in cardiovascular risk management for healthcare professionals using panel management: a qualitative study.

Background: While remote patient management (RPM) has the potential to assist in achieving treatment targets for cardiovascular risk factors in primary care, its effectiveness may vary among different patient subgroups. Panel management, which involves proactive care for specific patient risk groups, could offer a promising approach to tailor RPM to these groups. This study aims to (i) assess the perception of healthcare professionals and other stakeholders regarding the adoption and (ii) identify the barriers and facilitators for successfully implementing such a panel management approach.

Sex differences in clot, vessel and tissue characteristics in patients with a large vessel occlusion treated with endovascular thrombectomy.

Introduction: To improve our understanding of the relatively poor outcome after endovascular treatment (EVT) in women we assessed possible sex differences in baseline neuroimaging characteristics of acute ischemic stroke patients with large anterior vessel occlusion (LVO).

Patients And Methods: We included all consecutive patients from the MR CLEAN Registry who underwent EVT between 2014 and 2017. On baseline non-contrast CT and CT angiography, we assessed clot location and clot burden score (CBS), vessel characteristics (presence of atherosclerosis, tortuosity, size, and collateral status), and tissue characteristics with the Alberta Stroke Program Early Computed Tomography Score (ASPECTS).

A Digitally Enabled Combined Lifestyle Intervention for Weight Loss: Pilot Study in a Dutch General Population Cohort.

Background: Overweight and obesity rates among the general population of the Netherlands keep increasing. Combined lifestyle interventions (CLIs) focused on physical activity, nutrition, sleep, and stress management can be effective in reducing weight and improving health behaviors. Currently available CLIs for weight loss (CLI-WLs) in the Netherlands consist of face-to-face and community-based sessions, which face scalability challenges.

Development and Validation of a Prediction Model for Failure of the Transfemoral Approach of Endovascular Treatment for Large Vessel Occlusion Acute Ischemic Stroke.

Introduction: Extracranial vascular characteristics determine the accessibility of the large vessel intracranial occlusion for endovascular treatment (EVT) in acute ischemic stroke. We developed and validated a prediction model for failure of the transfemoral approach to aid clinical decision-making regarding EVT.

Methods: A prediction model was developed from data of patients included in the Dutch multicenter MR CLEAN Registry (March 18, 2014, until June 15, 2016) with penalized logistic regression.

Added Predictive Value of Female-Specific Factors and Psychosocial Factors for the Risk of Stroke in Women Under 50.

Background And Objectives: Female-specific factors and psychosocial factors may be important in the prediction of stroke but are not included in prediction models that are currently used. We investigated whether addition of these factors would improve the performance of prediction models for the risk of stroke in women younger than 50 years.

Methods: We used data from the Stichting Informatievoorziening voor Zorg en Onderzoek, population-based, primary care database of women aged 20-49 years without a history of cardiovascular disease.

Cardiovascular Risk Prediction in Men and Women Aged Under 50 Years Using Routine Care Data.

Background Prediction models for risk of cardiovascular events generally do not include young adults, and cardiovascular risk factors differ between women and men. Therefore, this study aimed to develop prediction models for first-ever cardiovascular event risk in men and women aged 30 to 49 years. Methods and Results We included patients aged 30 to 49 years without cardiovascular disease from a Dutch routine care database.

Sex differences in onset to hospital arrival time, prestroke disability, and clinical symptoms in patients with a large vessel occlusion: a MR CLEAN Registry substudy.

Background: Women have been reported to have worse outcomes after endovascular treatment (EVT), despite a similar treatment effect in non-clinical trial populations. We aimed to assess sex differences at hospital presentation with respect to workflow metrics, prestroke disability, and presenting clinical symptoms.

Methods: We included consecutive patients from the Multicentre Randomised Controlled Trial of Endovascular Treatment for Acute Ischaemic Stroke in The Netherlands (MR CLEAN) Registry (2014-2018) who received EVT for anterior circulation large vessel occlusion (LVO).

Developing Clinical Prediction Models Using Primary Care Electronic Health Record Data: The Impact of Data Preparation Choices on Model Performance.

Objective: To quantify prediction model performance in relation to data preparation choices when using electronic health records (EHR).

Study Design And Setting: Cox proportional hazards models were developed for predicting the first-ever main adverse cardiovascular events using Dutch primary care EHR data. The reference model was based on a 1-year run-in period, cardiovascular events were defined based on both EHR diagnosis and medication codes, and missing values were multiply imputed.

Combination of Radiological and Clinical Baseline Data for Outcome Prediction of Patients With an Acute Ischemic Stroke.

Background: Accurate prediction of clinical outcome is of utmost importance for choices regarding the endovascular treatment (EVT) of acute stroke. Recent studies on the prediction modeling for stroke focused mostly on clinical characteristics and radiological scores available at baseline. Radiological images are composed of millions of voxels, and a lot of information can be lost when representing this information by a single value.

Clarifying responsibility: professional digital health in the doctor-patient relationship, recommendations for physicians based on a multi-stakeholder dialogue in the Netherlands.

Background: Implementation of digital health (eHealth) generally involves adapting pre-established and carefully considered processes or routines, and still raises multiple ethical and legal dilemmas. This study aimed to identify challenges regarding responsibility and liability when prescribing digital health in clinical practice. This was part of an overarching project aiming to explore the most pressing ethical and legal obstacles regarding the implementation and adoption of digital health in the Netherlands, and to propose actionable solutions.

Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review.

While the opportunities of ML and AI in healthcare are promising, the growth of complex data-driven prediction models requires careful quality and applicability assessment before they are applied and disseminated in daily practice. This scoping review aimed to identify actionable guidance for those closely involved in AI-based prediction model (AIPM) development, evaluation and implementation including software engineers, data scientists, and healthcare professionals and to identify potential gaps in this guidance. We performed a scoping review of the relevant literature providing guidance or quality criteria regarding the development, evaluation, and implementation of AIPMs using a comprehensive multi-stage screening strategy.

Sex Differences in Presentation of Stroke: A Systematic Review and Meta-Analysis.

Background And Purpose: Women have worse outcomes than men after stroke. Differences in presentation may lead to misdiagnosis and, in part, explain these disparities. We investigated whether there are sex differences in clinical presentation of acute stroke or transient ischemic attack.