Op 16 januari 2022 overleed Bas Edixhoven, hoogleraar meetkunde aan de Universiteit Leiden. Naast zijn onderzoek en onderwijs was Bas betrokken bij vele internationale en nationale wiskunde... Show moreOp 16 januari 2022 overleed Bas Edixhoven, hoogleraar meetkunde aan de Universiteit Leiden. Naast zijn onderzoek en onderwijs was Bas betrokken bij vele internationale en nationale wiskunde-organisaties. In Nederland onder andere bij de commissie Onderzoek en de commissie Onderwijs van Platform Wiskunde Nederland, Mastermath, Wisk4all, DIAMANT, Vierkant voor Wiskunde, Compositio Mathematica, Indagationes Mathematicae, en de Bèta-lerarenkamer. Tevens was hij lid van de Koninklijke Nederlandse Akademie van Wetenschappen. Zijn nabije collega’s Robin de Jong, Jaap Top, Gerard van der Geer en René Schoof herdenken hem. Show less
Background: Aims of this study were to investigate the prevalence and incidence of catheter-related infection, identify risk factors, and determine the relation of catheter-related infection with... Show moreBackground: Aims of this study were to investigate the prevalence and incidence of catheter-related infection, identify risk factors, and determine the relation of catheter-related infection with mortality in critically ill COVID-19 patients. Methods: This was a retrospective cohort study of central venous catheters (CVCs) in critically ill COVID-19 patients. Eligible CVC insertions required an indwelling time of at least 48 hours and were identified using a full-admission electronic health record database. Risk factors were identified using logistic regression. Differences in survival rates at day 28 of follow-up were assessed using a log-rank test and proportional hazard model. Results: In 538 patients, a total of 914 CVCs were included. Prevalence and incidence of suspected catheter-related infection were 7.9% and 9.4 infections per 1,000 catheter indwelling days, respectively. Prone ventilation for more than 5 days was associated with increased risk of suspected catheter-related infection; odds ratio, 5.05 (95% confidence interval 2.12-11.0). Risk of death was significantly higher in patients with suspected catheter-related infection (hazard ratio, 1.78; 95% confidence interval, 1.25-2.53). Conclusions: This study shows that in critically ill patients with COVID-19, prevalence and incidence of suspected catheter-related infection are high, prone ventilation is a risk factor, and mortality is higher in case of catheter-related infection. Show less
Purpose: To assess, validate and compare the predictive performance of models for in-hospital mortality of COVID-19 patients admitted to the intensive care unit (ICU) over two different waves of... Show morePurpose: To assess, validate and compare the predictive performance of models for in-hospital mortality of COVID-19 patients admitted to the intensive care unit (ICU) over two different waves of infections. Our models were built with high-granular Electronic Health Records (EHR) data versus less-granular registry data. Methods: Observational study of all COVID-19 patients admitted to 19 Dutch ICUs participating in both the national quality registry National Intensive Care Evaluation (NICE) and the EHR-based Dutch Data Warehouse (hereafter EHR). Multiple models were developed on data from the first 24 h of ICU admissions from February to June 2020 (first COVID-19 wave) and validated on prospective patients admitted to the same ICUs between July and December 2020 (second COVID-19 wave). We assessed model discrimination, calibration, and the degree of relatedness between development and validation population. Coefficients were used to identify relevant risk factors. Results: A total of 1533 patients from the EHR and 1563 from the registry were included. With high granular EHR data, the average AUROC was 0.69 (standard deviation of 0.05) for the internal validation, and the AUROC was 0.75 for the temporal validation. The registry model achieved an average AUROC of 0.76 (standard deviation of 0.05) in the internal validation and 0.77 in the temporal validation. In the EHR data, age, and respiratory-system related variables were the most important risk factors identified. In the NICE registry data, age and chronic respiratory insufficiency were the most important risk factors. Conclusion: In our study, prognostic models built on less-granular but readily-available registry data had similar performance to models built on high-granular EHR data and showed similar transportability to a prospective COVID-19 population. Future research is needed to verify whether this finding can be confirmed for upcoming waves. Show less
Fleuren, L.M.; Dam, T.A.; Tonutti, M.; Bruin, D.P. de; Lalisang, R.C.A.; Gommers, D.; ... ; Dutch ICU Data Sharing Covid-19 Co 2021
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... Show moreIntroduction 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 (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure. Conclusion The most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records. Show less
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... Show moreBackground 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. Show less
Several prospective multigenerational studies have shown that crime runs in the family, while empirical research on the biological causes of crime has also established that low heart rate is... Show moreSeveral prospective multigenerational studies have shown that crime runs in the family, while empirical research on the biological causes of crime has also established that low heart rate is related to antisocial behavior. This study examines whether the intergenerational transmission of crime is moderated or mediated by a low heart rate of the son. Prospectively collected conviction data on 794 men from three consecutive generations of the Dutch Transfive dataset is used. Heart rates were measured around age 18, during the medical examination prior to the mandatory military service in the Dutch army. All analyses were conducted separately for violent and non-violent crime. Both paternal violence and low heart rate levels are associated with increased violent offending. Intergenerational transmission of violence was only found among families in which the son had a low heart rate, although the degree of transmission did not differ significantly from families in which the son had a high heart rate. No support was found for a mediating influence of low heart rates of criminals’ offspring on the intergenerational transmission of crime and violence. The results from this study underline the importance to focus on the interaction between biological risk factors and psychosocial risk factors for criminal behavior Show less
Background: Pediatric safety margins are generally based on data from adult studies; however, adult-based margins might be too large for children. The aim of this study was to quantify and compare... Show moreBackground: Pediatric safety margins are generally based on data from adult studies; however, adult-based margins might be too large for children. The aim of this study was to quantify and compare interfractional organ position variation in children and adults.Material and methods: For 35 children and 35 adults treated with thoracic/abdominal irradiation, 850 (range 5-30 per patient) retrospectively collected cone beam CT images were registered to the reference CT that was used for radiation treatment planning purposes. Renal position variation was assessed in three orthogonal directions and summarized as 3D vector lengths. Diaphragmatic position variation was assessed in the cranio-caudal (CC) direction only. We calculated means and SDs to estimate group systematic (sigma) and random errors (sigma) of organ position variation. Finally, we investigated possible correlations between organ position variation and patients' height.Results: Interfractional organ position variation was different in children and adults. Median 3D right and left kidney vector lengths were significantly smaller in children than in adults (2.8, 2.9mm vs. 5.6, 5.2mm, respectively; p<.05). Generally, the pediatric sigma and sigma were significantly smaller than in adults (p<.007). Overall and within both subgroups, organ position variation and patients' height were only negligibly correlated.Conclusions: Interfractional renal and diaphragmatic position variation in children is smaller than in adults indicating that pediatric margins should be defined differently from adult margins. Underlying mechanisms and other components of geometrical uncertainties need further investigation to explain differences and to appropriately define pediatric safety margins. Show less
Giesen, F. van der; Gaalen, F. van; Jong, R. de; Goeverden, M. van; Slootweg, H.; Vlieland, T.V. 2016
Background and purpose: To quantify renal and diaphragmatic interfractional motion in order to estimate systematic and random errors, and to investigate the correlation between interfractional... Show moreBackground and purpose: To quantify renal and diaphragmatic interfractional motion in order to estimate systematic and random errors, and to investigate the correlation between interfractional motion and patient-specific factors.Material and methods: We used 527 retrospective abdominal-thoracic cone beam CT scans of 39 childhood cancer patients (<18 years) to quantify renal motion relative to bony anatomy in the left-right (LR), cranio-caudal (CC) and anterior-posterior (AP) directions, and diaphragmatic motion in the CC direction only. Interfractional motion was quantified by distributions of systematic and random errors in each direction (standard deviations Sigma and sigma, respectively). Also, correlation between organ motion and height was analyzed.Results: Inter-patient organ motion varied widely, with the largest movements in the CC direction. Values of Sigma in LR, CC, and AP directions were 1.1, 3.8, 2.1 mm for the right, and 1.3, 3.0, 1.5 mm for the left kidney, respectively. The sigma in these three directions was 1.1, 3.1, 1.7 mm for the right, and 1.2, 2.9, 2.1 mm for the left kidney, respectively. For the diaphragm we estimated Sigma = 5.2 mm and sigma = 4.0 mm. No correlations were found between organ motion and height.Conclusions: The large inter-patient organ motion variations and the lack of correlation between motion and patient-related factors, suggest that individualized margin approaches might be required. (C) 2015 Elsevier Ireland Ltd. All rights reserved. Show less
Beurskens, F.J.; Diebolder, C.A.; Jong, R. de; Voorhorst, M.; Verploegen, S.; Strumane, K.; ... ; Parren, P.W.H.I. 2014
IMPORTANCE\nSelective decontamination of the digestive tract (SDD) and selective oropharyngeal decontamination (SOD) are prophylactic antibiotic regimens used in intensive care units (ICUs) and... Show moreIMPORTANCE\nSelective decontamination of the digestive tract (SDD) and selective oropharyngeal decontamination (SOD) are prophylactic antibiotic regimens used in intensive care units (ICUs) and associated with improved patient outcome. Controversy exists regarding the relative effects of both measures on patient outcome and antibiotic resistance.\nOBJECTIVE\nTo compare the effects of SDD and SOD, applied as unit-wide interventions, on antibiotic resistance and patient outcome.\nDESIGN, SETTING, AND PARTICIPANTS\nPragmatic, cluster randomized crossover trial comparing 12 months of SOD with 12 months of SDD in 16 Dutch ICUs between August 1, 2009, and February 1, 2013. Patients with an expected length of ICU stay longer than 48 hours were eligible to receive the regimens, and 5881 and 6116 patients were included in the clinical outcome analysis for SOD and SDD, respectively.\nINTERVENTIONS\nIntensive care units were randomized to administer either SDD or SOD.\nMAIN OUTCOMES AND MEASURES\nUnit-wide prevalence of antibiotic-resistant gram-negative bacteria. Secondary outcomes were day-28 mortality, ICU-acquired bacteremia, and length of ICU stay.\nRESULTS\nIn point-prevalence surveys, prevalences of antibiotic-resistant gram-negative bacteria in perianal swabs were significantly lower during SDD compared with SOD; for aminoglycoside resistance, average prevalence was 5.6% (95% CI, 4.6%-6.7%) during SDD and 11.8% (95% CI, 10.3%-13.2%) during SOD (P < .001). During both interventions the prevalence of rectal carriage of aminoglycoside-resistant gram-negative bacteria increased 7% per month (95% CI, 1%-13%) during SDD (P = .02) and 4% per month (95% CI, 0%-8%) during SOD (P = .046; P = .40 for difference). Day 28-mortality was 25.4% and 24.1% during SOD and SDD, respectively (adjusted odds ratio, 0.96 [95% CI, 0.88-1.06]; P = .42), and there were no statistically significant differences in other outcome parameters or between surgical and nonsurgical patients. Intensive care unit-acquired bacteremia occurred in 5.9% and 4.6% of the patients during SOD and SDD, respectively (odds ratio, 0.77 [95% CI, 0.65-0.91]; P = .002; number needed to treat, 77).\nCONCLUSIONS AND RELEVANCE\nUnit-wide application of SDD and SOD was associated with low levels of antibiotic resistance and no differences in day-28 mortality. Compared with SOD, SDD was associated with lower rectal carriage of antibiotic-resistant gram-negative bacteria and ICU-acquired bacteremia but a more pronounced gradual increase in aminoglycoside-resistant gram-negative bacteria.\nTRIAL REGISTRATION\ntrialregister.nlIdentifier: NTR1780. Show less
Welten, S.; Bastiaansen, T.; Jong, R. de; Vries, M. de; Peters, E.; Sheikh, S.; ... ; Nossent, Y. 2014
