Search

Abstract Reactivation of fetal hemoglobin expression alleviates the symptoms associated with β‐globinopathies, severe hereditary diseases with significant global health implications due to their high morbidity and mortality rates. The symptoms emerge following the postnatal transition from fetal‐to‐adult hemoglobin expression. Extensive research has focused on inducing the expression of the fetal γ‐globin subunit to reverse this switch and ameliorate these symptoms. Despite decades of research, only one compound, hydroxyurea, found its way to the clinic as an inducer of fetal hemoglobin. Unfortunately, its efficacy varies among patients, highlighting the need for more effective treatments. Erythroid cell lines have been instrumental in the pursuit of both pharmacological and genetic ways to reverse the postnatal hemoglobin switch. Here, we describe the first endogenously tagged fetal hemoglobin reporter cell line based on the adult erythroid progenitor cell line HUDEP2. Utilizing CRISPR‐Cas9‐mediated knock‐in, a bioluminescent tag was integrated at the HBG1 gene. Subsequent extensive characterization confirmed that the resulting reporter cell line closely mirrors the HUDEP2 characteristics and that the cells report fetal hemoglobin induction with high sensitivity and specificity. This novel reporter cell line is therefore highly suitable for evaluating genetic and pharmacologic strategies to induce fetal hemoglobin. Furthermore, it provides an assay compatible with high‐throughput drug screening, exemplified by the identification of a cluster of known fetal hemoglobin inducers in a pilot study. This new tool is made available to the research community, with the aspiration that it will accelerate the search for safer and more effective strategies to reverse the hemoglobin switch.

ObjectiveTo assess the separate and combined associations of maternal pre-pregnancy body mass index (BMI) and gestational weight gain with the risks of pregnancy complications and their population impact.DesignIndividual participant data meta-analysis of 39 cohorts.SettingEurope, North America, and Oceania.Population265 270 births.MethodsInformation on maternal pre-pregnancy BMI, gestational weight gain, and pregnancy complications was obtained. Multilevel binary logistic regression models were used.Main outcome measuresGestational hypertension, pre-eclampsia, gestational diabetes, preterm birth, small and large for gestational age at birth.ResultsHigher maternal pre-pregnancy BMI and gestational weight gain were, across their full ranges, associated with higher risks of gestational hypertensive disorders, gestational diabetes, and large for gestational age at birth. Preterm birth risk was higher at lower and higher BMI and weight gain. Compared with normal weight mothers with medium gestational weight gain, obese mothers with high gestational weight gain had the highest risk of any pregnancy complication (odds ratio 2.51, 95% CI 2.31- 2.74). We estimated that 23.9% of any pregnancy complication was attributable to maternal overweight/obesity and 31.6% of large for gestational age infants was attributable to excessive gestational weight gain.ConclusionsMaternal pre-pregnancy BMI and gestational weight gain are, across their full ranges, associated with risks of pregnancy complications. Obese mothers with high gestational weight gain are at the highest risk of pregnancy complications. Promoting a healthy pre-pregnancy BMI and gestational weight gain may reduce the burden of pregnancy complications and ultimately the risk of maternal and neonatal morbidity.Tweetable abstractPromoting a healthy body mass index and gestational weight gain might reduce the population burden of pregnancy complications.

Abstract Background For mechanically ventilated critically ill COVID-19 patients, prone positioning has quickly become an important treatment strategy, however, prone positioning is labor intensive and comes with potential adverse effects. Therefore, identifying which critically ill intubated COVID-19 patients will benefit may help allocate labor resources. Methods From the multi-center Dutch Data Warehouse of COVID-19 ICU patients from 25 hospitals, we selected all 3619 episodes of prone positioning in 1142 invasively mechanically ventilated patients. We excluded episodes longer than 24 h. Berlin ARDS criteria were not formally documented. We used supervised machine learning algorithms Logistic Regression, Random Forest, Naive Bayes, K-Nearest Neighbors, Support Vector Machine and Extreme Gradient Boosting on readily available and clinically relevant features to predict success of prone positioning after 4 h (window of 1 to 7 h) based on various possible outcomes. These outcomes were defined as improvements of at least 10% in PaO2/FiO2 ratio, ventilatory ratio, respiratory system compliance, or mechanical power. Separate models were created for each of these outcomes. Re-supination within 4 h after pronation was labeled as failure. We also developed models using a 20 mmHg improvement cut-off for PaO2/FiO2 ratio and using a combined outcome parameter. For all models, we evaluated feature importance expressed as contribution to predictive performance based on their relative ranking. Results The median duration of prone episodes was 17 h (11–20, median and IQR, N = 2632). Despite extensive modeling using a plethora of machine learning techniques and a large number of potentially clinically relevant features, discrimination between responders and non-responders remained poor with an area under the receiver operator characteristic curve of 0.62 for PaO2/FiO2 ratio using Logistic Regression, Random Forest and XGBoost. Feature importance was inconsistent between models for different outcomes. Notably, not even being a previous responder to prone positioning, or PEEP-levels before prone positioning, provided any meaningful contribution to predicting a successful next proning episode. Conclusions In mechanically ventilated COVID-19 patients, predicting the success of prone positioning using clinically relevant and readily available parameters from electronic health records is currently not feasible. Given the current evidence base, a liberal approach to proning in all patients with severe COVID-19 ARDS is therefore justified and in particular regardless of previous results of proning.

Rationale: Despite functional impairments, intensive care unit (ICU) survivors can perceive their quality of life as acceptable. Objectives: To investigate discrepancies between calculated health, based on self-reported physical, mental, and cognitive functioning and perceived health, 1 year after ICU admission. Methods: Data from an ongoing prospective multicenter cohort study, MONITOR-IC, were used. Patient-reported physical, mental, and cognitive functioning and perceived health (EuroQol visual analog scale; range, 0–100) 1 year post-ICU of patients admitted to 1 of 11 participating ICUs between July 2016 and September 2021 were analyzed. The relationship between functional outcomes and perceived health was modeled using linear regression. Calculated health for each patient was estimated using this model and compared with patients' perceived health, the difference reflecting a discrepancy. On the basis of a minimal clinically important difference of 8 points, three groups were defined: patients who rated their health better than calculated (positive discrepancy), patients who rated their health worse than calculated (negative discrepancy), and patients whose perceived health was concordant with their calculated health. Results: A total of 2,545 patients were analyzed, of whom 45.0% (n = 1,146) showed a discrepancy between calculated and perceived health. Patients with a negative discrepancy rated their health significantly lower (median, 50; interquartile range, 36–66) than patients with a positive discrepancy (median, 84; interquartile range, 75–90). Importantly, there were no significant differences in physical, mental, and cognitive functioning between patients with a negative versus positive discrepancy. Patients with a negative discrepancy had a higher education level and were more often unemployed. Conclusions: One year post-ICU, almost half of ICU survivors showed a discrepancy between calculated health and perceived health. [ABSTRACT FROM AUTHOR]

Author(s): Hidde Heesakkers [sup.1], Johannes G. van der Hoeven [sup.1], Stijn Corsten [sup.2], Inge Janssen [sup.3], Esther Ewalds [sup.4], Dominique Burgers-Bonthuis [sup.5], Thijs C. D. Rettig [sup.6], Crétien Jacobs [sup.7], [...], Purpose Long-term mental outcomes in family members of coronavirus disease 2019 (COVID-19) intensive care unit (ICU) survivors are unknown. Therefore, we assessed the prevalence of mental health symptoms, including associated risk factors, and quality of life (QoL) in family members of COVID-19 ICU survivors 3 and 12 months post-ICU. Methods A prospective multicentre cohort study in ICUs of ten Dutch hospitals, including adult family members of COVID-19 ICU survivors admitted between March 1, and July 1, 2020. Symptom prevalence rates of anxiety, depression (Hospital Anxiety and Depression Scale) and Post-Traumatic Stress Disorder (Impact of Event Scale-6), and QoL (Short Form-12) before ICU admission (baseline), and after 3 and 12 months were measured. Additionally, associations between family and patient characteristics and mental health symptoms were calculated. Results A total of 166 out of 197 (84.3%) included family members completed the 12-month follow-up of whom 46.1% and 38.3% had mental health symptoms 3 and 12 months post-ICU, respectively; both higher compared to baseline (22.4%) (p < 0.001). The mental component summary score of the SF-12 was lower at 12-month follow-up compared with baseline [mean difference mental component score: - 5.5 (95% confidence interval (CI) - 7.4 to - 3.6)]. Furthermore, 27.9% experienced work-related problems. Symptoms of anxiety (odds ratio (OR) 9.23; 95% CI 2.296-37.24; p = 0.002) and depression (OR 5.96; 95% CI 1.29-27.42; p = 0.02) prior to ICU admission were identified as risk factors for mental health symptoms after 12 months. Conclusion A considerable proportion of family members of COVID-19 survivors reported mental health symptoms 3 and 12 months after ICU admission, disrupting QoL and creating work-related problems.

Abstract Introduction Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. Methods We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. Results A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (

Abstract Background High-dose intravenous vitamin C directly scavenges and decreases the production of harmful reactive oxygen species (ROS) generated during ischemia/reperfusion after a cardiac arrest. The aim of this study is to investigate whether short-term treatment with a supplementary or very high-dose intravenous vitamin C reduces organ failure in post-cardiac arrest patients. Methods This is a double-blind, multi-center, randomized placebo-controlled trial conducted in 7 intensive care units (ICUs) in The Netherlands. A total of 270 patients with cardiac arrest and return of spontaneous circulation will be randomly assigned to three groups of 90 patients (1:1:1 ratio, stratified by site and age). Patients will intravenously receive a placebo, a supplementation dose of 3 g of vitamin C or a pharmacological dose of 10 g of vitamin C per day for 96 h. The primary endpoint is organ failure at 96 h as measured by the Resuscitation-Sequential Organ Failure Assessment (R-SOFA) score at 96 h minus the baseline score (delta R-SOFA). Secondary endpoints are a neurological outcome, mortality, length of ICU and hospital stay, myocardial injury, vasopressor support, lung injury score, ventilator-free days, renal function, ICU-acquired weakness, delirium, oxidative stress parameters, and plasma vitamin C concentrations. Discussion Vitamin C supplementation is safe and preclinical studies have shown beneficial effects of high-dose IV vitamin C in cardiac arrest models. This is the first RCT to assess the clinical effect of intravenous vitamin C on organ dysfunction in critically ill patients after cardiac arrest. Trial registration ClinicalTrials.gov NCT03509662. Registered on April 26, 2018. https://clinicaltrials.gov/ct2/show/NCT03509662 European Clinical Trials Database (EudraCT): 2017-004318-25. Registered on June 8, 2018. https://www.clinicaltrialsregister.eu/ctr-search/trial/2017-004318-25/NL

Abstract Background The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. Methods A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract–transform–load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. Results Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. Conclusions In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.

Abstract Background In well-resourced countries, comprehensive care programs have increased life expectancy of patients with sickle cell disease, with almost all infants surviving into adulthood. However, families affected by sickle cell disease are more likely to be economically disenfranchised because of their racial or ethnic minority status. As every individual child has the right to the highest attainable standard of health under the United Nations Convention on the Rights of the Child, it is essential to identify both barriers and facilitators with regard to the delivery of adequate healthcare. Optimal healthcare accessibility will improve healthcare outcomes for children with sickle cell disease and their families. Healthcare professionals in the field of sickle cell care have first-hand experience of the barriers that patients encounter when it comes to effective care. We therefore hypothesised that these medical professionals have a clear picture of what is necessary to overcome these barriers and which facilitators will be most feasible. Therefore, this study aims to map best practises and lessons learnt in order to attain more optimal healthcare accessibility for paediatric patients with sickle cell disease and their families. Methods Healthcare professionals working with young patients with sickle cell disease were recruited for semi-structured interviews. An interview guide was used to ensure the four healthcare accessibility dimensions were covered. The interviews were transcribed and coded. Based on field notes, initial codes were generated, to collate data (both barriers and solutions) to main themes (such as “transportation”, or “telecommunication”). Through ongoing thematic analysis, definitive themes were formulated and best practices were reported as recommendations. Quotations were selected to highlight or illustrate the themes and link the reported results to the empirical data. Results In 2019, 22 healthcare professionals from five different university hospitals in the Netherlands were interviewed. Participants included (paediatric) haematologists, nurses and allied health professionals. Six themes emerged, all associated with best practices on topics related to the improvement of healthcare accessibility for children with sickle cell disease and their families. Firstly, the full reimbursement of invisible costs made by caregivers. Secondly, clustering of healthcare appointments on the same day to help patients seeing all required specialists without having to visit the hospital frequently. Thirdly, organisation of care according to shared care principles to deliver specialised services as close as possible to the patient’s home without compromising quality. Fourthly, optimising verbal and written communication methods with special consideration for families with language barriers, low literacy skills, or both. Fifthly, improving the use of eHealth services tailored to users’ health literacy skills, including accessible mobile telephone contact between healthcare professionals and caregivers of children with sickle cell disease. Finally, increasing knowledge and interest in sickle cell disease among key stakeholders and the public to ensure that preventive and acute healthcare measures are understood and safeguarded in all settings. Conclusion This qualitative study describes the views of healthcare professionals on overcoming barriers of healthcare accessibility that arise from the intersecting vulnerabilities faced by patients with sickle cell disease and their families. The recommendations gathered in this report provide high-income countries with a practical resource to meet their obligations towards individual children under the United Nations Convention on the Rights of the Child.

OBJECTIVES:. As coronavirus disease 2019 is a novel disease, treatment strategies continue to be debated. This provides the intensive care community with a unique opportunity as the population of coronavirus disease 2019 patients requiring invasive mechanical ventilation is relatively homogeneous compared with other ICU populations. We hypothesize that the novelty of coronavirus disease 2019 and the uncertainty over its similarity with noncoronavirus disease 2019 acute respiratory distress syndrome resulted in substantial practice variation between hospitals during the first and second waves of coronavirus disease 2019 patients. DESIGN:. Multicenter retrospective cohort study. SETTING:. Twenty-five hospitals in the Netherlands from February 2020 to July 2020, and 14 hospitals from August 2020 to December 2020. PATIENTS:. One thousand two hundred ninety-four critically ill intubated adult ICU patients with coronavirus disease 2019 were selected from the Dutch Data Warehouse. Patients intubated for less than 24 hours, transferred patients, and patients still admitted at the time of data extraction were excluded. MEASUREMENTS AND MAIN RESULTS:. We aimed to estimate between-ICU practice variation in selected ventilation parameters (positive end-expiratory pressure, Fio2, set respiratory rate, tidal volume, minute volume, and percentage of time spent in a prone position) on days 1, 2, 3, and 7 of intubation, adjusted for patient characteristics as well as severity of illness based on Pao2/Fio2 ratio, pH, ventilatory ratio, and dynamic respiratory system compliance during controlled ventilation. Using multilevel linear mixed-effects modeling, we found significant (p ≤ 0.001) variation between ICUs in all ventilation parameters on days 1, 2, 3, and 7 of intubation for both waves. CONCLUSIONS:. This is the first study to clearly demonstrate significant practice variation between ICUs related to mechanical ventilation parameters that are under direct control by intensivists. Their effect on clinical outcomes for both coronavirus disease 2019 and other critically ill mechanically ventilated patients could have widespread implications for the practice of intensive care medicine and should be investigated further by causal inference models and clinical trials.

Abstract Objectives While physicians are often confronted with immunoglobulin A (IgA) deficiency in children with recurrent infections, the clinical relevance of this finding is unclear. Large‐scale studies examining the significance of IgA deficiency in children are hampered by differences in techniques for measuring IgA and the physiological increase of IgA with age. Both result in a variety of reference values used for diagnosing IgA deficiency. We propose a new laboratory‐independent method to accurately compare IgA measurements in children of varying ages. Methods We present a method to standardise IgA values for age and laboratory differences. We applied this method to a multicentre case–control study of children under the age of seven suffering from recurrent respiratory tract infections (rRTI, cases) and children who had IgA measured as part of coeliac disease screening (controls). We defined IgA deficiency as serum IgA measurements

First described in 1991, Yin Yang 1 (YY1) is a transcription factor that is ubiquitously expressed throughout mammalian cells. It regulates both transcriptional activation and repression, in a seemingly context-dependent manner. YY1 has a well-established role in the development of the central nervous system, where it is involved in neurogenesis and maintenance of homeostasis in the developing brain. In neurodevelopmental and neurodegenerative disease, the crucial role of YY1 in cellular processes in the central nervous system is further underscored. In this mini-review, we discuss the various mechanisms leading to the transcriptional activating and repressing roles of YY1, including its role as a traditional transcription factor, its interactions with cofactors and chromatin modifiers, the role of YY1 in the non-coding genome and 3D chromatin organization and the possible implications of the phase-separation mechanism on YY1 function. We provide examples on how these processes can be involved in normal development and how alterations can lead to various diseases.

Patients on P2Y12 inhibitors may still develop thrombosis or bleeding complications. Tailored antiplatelet therapy, based on platelet reactivity testing, might reduce these complications. Several tests have been used, but failed to show a benefit of tailored antiplatelet therapy. This could be due to the narrowness of current platelet reactivity tests, which are limited to analysis of platelet aggregation after stimulation of the adenosine diphosphate (ADP)-pathway. However, the response to ADP does not necessarily reflect the effect of P2Y12 inhibition on platelet function in vivo. Therefore, we investigated whether measuring platelet reactivity toward other physiologically relevant agonists could provide more insight in the efficacy of P2Y12 inhibitors. The effect of in vitro and in vivo P2Y12 inhibition on αIIbβ3-activation, P-selectin and CD63-expression, aggregate formation, release of alpha, and dense granules content was assessed after stimulation of different platelet activation pathways. Platelet reactivity measured with flow cytometry in 72 patients on P2Y12 inhibitors was compared to VerifyNow results. P2Y12 inhibitors caused strongly attenuated platelet fibrinogen binding after stimulation with peptide agonists for protease activated receptor (PAR)-1 and -4, or glycoprotein VI ligand crosslinked collagen-related peptide (CRP-xl), while aggregation was normal at high agonist concentration. P2Y12 inhibitors decreased PAR-agonist and CRP-induced dense granule secretion, but not alpha granule secretion. A proportion of P2Y12-inhibitor responsive patients according to VerifyNow, displayed normal fibrinogen binding assessed with flow cytometry after stimulation with PAR-agonists or CRP despite full inhibition of the response to ADP, indicating suboptimal platelet inhibition. Concluding, measurement of platelet fibrinogen binding with flow cytometry after stimulation of thrombin- or collagen receptors in addition to ADP response identifies different patients as nonresponders to P2Y12 inhibitors, compared to only ADP-induced aggregation-based assays. Future studies should investigate the value of both assays for monitoring on-treatment platelet reactivity.