Publications by authors named "Hoogendoorn M"

Background: Acute myeloid leukemia (AML) is a malignancy of the bone marrow with a median age at diagnosis of 70 years. AML is difficult to treat, especially in older patients, among whom outcomes have historically been poor. Over the last two decades, a greater understanding of the molecular mechanisms of the pathology has led to the development of new drugs and multiple updates to treatment guidelines.

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Objective: To assess longitudinal associations with sudden cardiac arrest (SCA) of clinical characteristics recorded in primary care in people with type 2 diabetes (T2D), both with and without cardiovascular disease (CVD).

Research Design And Methods: We performed a case-control study, with SCA case subjects with T2D from the Amsterdam Resuscitation Studies (ARREST) registry of out-of-hospital resuscitation attempts in the Dutch Noord-Holland region (2010-2020) and up to five matched (age, sex, T2D, general practitioner [GP] practice) non-SCA control subjects. We collected relevant clinical measurements, medication use, and medical history from GPs' electronic health care records.

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The treatment of older patients with acute myeloid leukemia (AML) considered unfit for receiving intensive chemotherapy is challenging. Based on the hypothesis that addition of the broad tyrosine kinase inhibitor (TKI) midostaurin could improve the response to hypomethylating agents, irrespective of FLT3 gene mutational status, we conducted a randomized phase II multicenter study to assess the tolerability and efficacy of the addition of midostaurin to a 10-day schedule of decitabine in unfit (i.e.

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Purpose: To investigate health care utilization among patients with hematologic malignancies and its association with socioeconomic position (SEP) and compare health care utilization with a cancer-free population.

Methods: Patients with aggressive lymphoma, indolent lymphoma, or multiple myeloma (MM), diagnosed between 1999-2010 and 2015-2019, participated in longitudinal patient-reported outcome research, up to 11 years post-diagnosis. Questionnaires assessed health care utilization at the general practitioner (GP), medical specialist, and additional health care.

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With the increasing prevalence of comorbidity in an ageing population, it is crucial to better understand the impact of comorbidity on health-related quality of life (HRQoL) after lymphoma or multiple myeloma (MM) diagnosis. We included 261 newly diagnosed patients (67% response rate) diagnosed with lymphoma or MM between October 2020 and March 2023 in a longitudinal survey. The European Organisation for Research and Treatment of Cancer (EORTC) questionnaires were used to measure generic and disease-specific HRQoL.

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Introduction: Treatment in the intensive care unit (ICU) generates complex data where machine learning (ML) modelling could be beneficial. Using routine hospital data, we evaluated the ability of multiple ML models to predict inpatient mortality in a paediatric population in a low/middle-income country.

Method: We retrospectively analysed hospital record data from 0-59 months old children admitted to the ICU of Dhaka hospital of International Centre for Diarrhoeal Disease Research, Bangladesh.

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Background: Frailty in newly-diagnosed multiple myeloma (NDMM) patients is associated with treatment-related toxicity, which negatively affects health-related quality of life (HRQoL). Currently, data on changes in HRQoL of frail and intermediate-fit MM patients during active treatment and post-treatment follow-up are absent.

Methods: The HOVON123 study (NTR4244) was a phase II trial in which NDMM patients ≥ 75 years were treated with nine dose-adjusted cycles of Melphalan-Prednisone-Bortezomib (MPV).

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Article Synopsis
  • Research indicates that machine learning (ML) algorithms utilizing natural behavior data (like text, audio, and video) could enhance personalization in psychology and psychiatry, but there's a lack of a comprehensive review on this topic.
  • The systematic review analyzed 128 studies, predominantly focusing on predicting anxiety (87 studies) and posttraumatic stress disorder (41 studies), mostly published since 2019 in computer science journals, with a greater emphasis on text data.
  • While many studies showed promising predictive power, significant variations in quality and reporting standards exist, and further standardization and research in clinical settings are needed for effective application in mental health diagnostics.
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After a revision surgery, approximately 1-2 % of patients will develop a periprosthetic joint infection (PJI). During the revision surgery, the infected prosthesis is removed, a debridement is performed and a new or temporary spacer is placed. Additionally, patients are treated with antibiotics during and after the surgery.

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Article Synopsis
  • Reinforcement learning (RL) has potential in intensive care medicine due to the wealth of data and real-time decision-making needs, but trust and safety issues hinder its implementation for clinical support, particularly in optimizing ventilator settings for COVID-19 patients.
  • A novel method called cross off-policy evaluation (OPE) was developed to evaluate RL models, using a large dataset from Dutch ICUs and focusing on ventilator settings, with interim and final rewards based on gas exchange indices and patient outcomes.
  • The study found that while many RL policies performed well initially, almost half were deemed suboptimal under more rigorous evaluation, highlighting the importance of detailed clinical policy inspection and restrictions to ensure safety in patient care.
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Introduction: Temporal data has numerous challenges for deep learning such as irregularity of sampling. New algorithms are being developed that can handle these temporal challenges better. However, it is unclear how the performance ranges from classical non-temporal models to newly developed algorithms.

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Reinforcement Learning (RL) has recently found many applications in the healthcare domain thanks to its natural fit to clinical decision-making and ability to learn optimal decisions from observational data. A key challenge in adopting RL-based solution in clinical practice, however, is the inclusion of existing knowledge in learning a suitable solution. Existing knowledge from e.

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Purpose: To investigate the development in quality of ICU care over time using the Dutch National Intensive Care Evaluation (NICE) registry.

Materials And Methods: We included data from all ICU admissions in the Netherlands from those ICUs that submitted complete data between 2009 and 2021 to the NICE registry. We determined median and interquartile range for eight quality indicators.

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Article Synopsis
  • Reinforcement learning (RL) has potential applications in ICU settings for improving decision-making, and a systematic review was conducted to evaluate its impact on critically ill patients.
  • A total of 1,033 articles were screened, resulting in 18 journal articles and 18 conference papers focused on RL techniques; however, all studies only showed RL outperforming clinicians based on retrospective data.
  • The review concluded that while RL techniques reported better decision-making than clinicians, there were no studies proving actual improvements in patient outcomes, and there was a high risk of bias in the evaluation procedures.
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Background: Many older patients with acute myeloid leukaemia die or cannot undergo allogeneic haematopoietic stem-cell transplantation (HSCT) due to toxicity caused by intensive chemotherapy. We hypothesised that replacing intensive chemotherapy with decitabine monotherapy could improve outcomes.

Methods: This open-label, randomised, controlled, phase 3 trial was conducted at 54 hospitals in nine European countries.

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Objective: This work explores the perceptions of obstetrical clinicians about artificial intelligence (AI) in order to bridge the gap in uptake of AI between research and medical practice. Identifying potential areas where AI can contribute to clinical practice, enables AI research to align with the needs of clinicians and ultimately patients.

Design: Qualitative interview study.

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Objective: Congenital hypothyroidism (CH) is an inborn thyroid hormone (TH) deficiency mostly caused by thyroidal (primary CH) or hypothalamic/pituitary (central CH) disturbances. Most CH newborn screening (NBS) programs are thyroid-stimulating-hormone (TSH) based, thereby only detecting primary CH. The Dutch NBS is based on measuring total thyroxine (T4) from dried blood spots, aiming to detect primary and central CH at the cost of more false-positive referrals (FPRs) (positive predictive value (PPV) of 21% in 2007-2017).

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Purpose: Non-pharmacological interventions (NPIs) play an important role in the management of older people receiving homecare. However, little is known about how often specific NPIs are being used and to what extent usage varies between countries. The aim of the current study was to investigate the prevalence of NPIs in older homecare recipients in six European countries.

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With the introduction of targeted chemotherapy drugs, a new age of treatment for acute myeloid leukemia (AML) has begun. The promotion of the azacitidine+venetoclax combination regimen to first line of treatment in patients deemed ineligible for intensive chemotherapy marks the first of many novel combination regimens becoming part of national treatment guidelines. We review recent phase II and III clinical trials and conclude that these novel regimens offer significant increases in response rates, remission rates, and overall survival.

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Article Synopsis
  • The increasing use of AI in healthcare highlights the need for standardizing medical data from different electronic healthcare record (EHR) systems, as they often use varied naming conventions for the same concepts.
  • The study proposes an augmented intelligence method to align these different terminologies by predicting accurate medical concepts from raw EHR data, utilizing machine learning models trained on manually mapped data from multiple hospitals.
  • Results show that the initial model achieved a precision score of 0.744 and a recall score of 0.771 when applied to a large dataset, indicating promising effectiveness in concept mapping across diverse EHR systems.
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Objectives: Acquired missense mutations in the BCR::ABL1 kinase domain (KD) may cause tyrosine kinase inhibitor (TKI) treatment failure. Based on mutation-specific in vitro derived IC50-values, alternative TKI may be selected. We assessed clinical practice of BCR::ABL1 KD mutation testing, clinical response in relation to IC50-values, and clinical outcome of tested patients.

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Article Synopsis
  • The increasing number of older adults with complex chronic conditions (CCCs) poses challenges for care providers, as existing decision support systems are inadequate for addressing the complexities involved in their treatments.
  • This EU-funded project aims to develop advanced decision support systems using a vast pool of real-world data from over 51 million older adults across eight countries to improve health outcome predictions and evaluate treatment impacts.
  • Ethical guidelines have been followed for the study, which will disseminate findings through publications in peer-reviewed journals and share them with relevant stakeholders to enhance the quality of care for older persons with CCCs.
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Chronic lymphocytic leukemia (CLL)-related symptoms and morbidity related to the advanced age at diagnosis impairs the well-being of older adult patients. Therefore, it is essential to tailor treatment according to geriatric characteristics and aim for an improvement in health-related quality of life (HRQoL) as a primary treatment goal. In the HOVON139/GiVe trial, 12 cycles of fixed-duration venetoclax plus obinutuzumab (Ven-O) were shown to be effective and tolerable in FCR (fludarabine, cyclophosphamide, rituximab)-unfit patients with CLL (n = 67).

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