Search

Abstract Background Functional somatic symptoms (FSS), which commonly cannot be attributed to well-defined organic pathology, often co-occur with internalizing psychopathology and fluctuate throughout different life stages. We examined FSS courses throughout adolescence, and the association between preadolescent FSS, FSS severity and internalizing psychopathology at late adolescence. Methods Data from the Copenhagen Child Cohort (CCC2000) were utilized from assessments at ages 11–12 years (preadolescence; T0) and 16–17 years (late adolescence; T1). Self-report questionnaire and interview data on FSS, internalizing psychopathology, chronic medical conditions, and sociodemographic data from Danish national registers were available for 1285 youths. FSS courses were categorized into persistent (high FSS at T0 & T1), remission (high FSS only at T0), incident (high FSS only at T1) or no FSS (no FSS at T0 & T1). Multiple linear and multinomial logistic regressions were conducted to investigate the FSS/psychopathology association. Results 1.8% of adolescents fell into the persistent FSS course group throughout adolescence. Higher preadolescent FSS predicted FSS (b = 0.07, p

Autistic-like features and functional somatic symptoms (FSS) frequently co-occur. It remains unknown how autistic-like features and FSS affect each other and develop throughout adolescence. This study examined reciprocal relations between autistic-like features and FSS in adolescence. Participants were 2772 adolescents (52.5% male) from the Tracking Adolescents' Individual Lives Survey population and clinical cohort. Data from four waves were included, covering the ages between 11 and 19 years. Autistic-like features were measured using the Children's Social Behavior Questionnaire. FSS were assessed using the Youth Self Report and Adult Self Report, respectively. Using the random intercept cross-lagged panel model, a stable positive, moderately strong between-persons association was found between autistic-like features and FSS. No within-persons reciprocal effects from wave to wave were observed. Secondary analyses revealed a consistent relation with FSS for three different domains of autistic-like features (social and communication behaviors, repetitive behaviors, and self-regulatory behaviors), and highly similar interrelations in a subsample of adolescents with a clinical autism spectrum disorder diagnosis. In conclusion, the co-occurrence between autistic-like features and FSS is stable throughout adolescence. Clinicians working with adolescents with autistic-like features should be alert to the presence FSS, and vice versa.

Abstract The CoLab score was developed and externally validated to rule out COVID-19 among suspected patients presenting at the emergency department. We hypothesized a within-patient decrease in the CoLab score over time in an intensive care unit (ICU) cohort. Such a decrease would create the opportunity to potentially rule out the need for isolation when the infection is overcome. Using linear mixed-effects models, data from the Maastricht Intensive Care COVID (MaastrICCht) cohort were used to investigate the association between time and the CoLab score. Models were adjusted for sex, APACHE II score, ICU mortality, and daily SOFA score. The CoLab score decreased by 0.30 points per day (95% CI − 0.33 to − 0.27), independent of sex, APACHE II, and Mortality. With increasing SOFA score over time, the CoLab score decreased more strongly (− 0.01 (95% CI − 0.01 to − 0.01) additional decrease per one-point increase in SOFA score.) The CoLab score decreased in ICU patients on mechanical ventilation for COVID-19, with a one-point reduction per three days, independent of sex, APACHE II, and ICU mortality, and somewhat stronger with increasing multi-organ failure over time. This suggests that the CoLab score would decrease below a threshold where COVID-19 can be excluded.

Abstract Randomized controlled trials (RCTs) are the gold standard to establish the benefit-risk ratio of novel drugs. However, the evaluation of mature results often takes many years. We hypothesized that the addition of Bayesian inference methods at interim analysis time points might accelerate and enforce the knowledge that such trials may generate. In order to test that hypothesis, we retrospectively applied a Bayesian approach to the HOVON 132 trial, in which 800 newly diagnosed AML patients aged 18 to 65 years were randomly assigned to a “7 + 3” induction with or without lenalidomide. Five years after the first patient was recruited, the trial was negative for its primary endpoint with no difference in event-free survival (EFS) between experimental and control groups (hazard ratio [HR] 0.99, p = 0.96) in the final conventional analysis. We retrospectively simulated interim analyses after the inclusion of 150, 300, 450, and 600 patients using a Bayesian methodology to detect early lack of efficacy signals. The HR for EFS comparing the lenalidomide arm with the control treatment arm was 1.21 (95% CI 0.81–1.69), 1.05 (95% CI 0.86–1.30), 1.00 (95% CI 0.84–1.19), and 1.02 (95% CI 0.87–1.19) at interim analysis 1, 2, 3 and 4, respectively. Complete remission rates were lower in the lenalidomide arm, and early deaths more frequent. A Bayesian approach identified that the probability of a clinically relevant benefit for EFS (HR

Abstract Background Coronary artery calcification (CAC) is associated with poor outcome in critically ill patients. A deterioration in cardiac conduction and loss of myocardial tissue could be an underlying cause. Vectorcardiography (VCG) and cardiac biomarkers provide insight into these underlying causes. The aim of this study was to investigate whether a high degree of CAC is associated with VCG-derived variables and biomarkers, including high-sensitivity troponin-T (hs-cTnT) and N-terminal pro-B-type natriuretic peptide (NT-proBNP). Methods Mechanically ventilated coronavirus-19 (COVID-19) patients with an available chest computed tomography (CT) and 12-lead electrocardiogram (ECG) were studied. CAC scores were determined using chest CT scans. Patients were categorized into 3 sex-specific tertiles: low, intermediate, and high CAC. Daily 12 leads-ECGs were converted to VCGs. Daily hs-cTnT and NT-proBNP levels were determined. Linear mixed-effects regression models examined the associations between CAC tertiles and VCG variables, and between CAC tertiles and hs-cTnT or NT-proBNP levels. Results In this study, 205 patients (73.2% men, median age 65 years [IQR 57.0; 71.0]) were included. Compared to the lowest CAC tertile, the highest CAC tertile had a larger QRS area at baseline (6.65 µVs larger [1.50; 11.81], p = 0.012), which decreased during admission (− 0.27 µVs per day [− 0.43; − 0.11], p = 0.001). Patients with the highest CAC tertile also had a longer QRS duration (12.02 ms longer [4.74; 19.30], p = 0.001), higher levels of log hs-cTnT (0.79 ng/L higher [0.40; 1.19], p

Background Persistent somatic symptoms and functional disorders (PSS/FD) are complex conditions requiring collaboration between healthcare professionals. This is especially true at the interface between primary and secondary care interface. The current fragmentation of care is a major barrier to this, leading to poor experiences and outcomes and high costs for healthcare and society.Objectives The aim is to identify barriers and possible solutions for collaboration between primary and secondary care in patients with PSS/FD.Methods In two sessions, using the nominal group technique, a mix of primary and secondary care professionals identified barriers and possible solutions to collaboration between primary and secondary care in PSS/FD care. Barriers to collaboration were identified during session one, with potential solutions identified during session two in response to the top eight barriers. Each session ended with a voting round ranking the barriers and solutions.Results A total of 102 healthcare professionals participated in two sessions. In the first session, 55 participants provided a list of 22 barriers, while in the second session, 47 participants provided 18 possible solutions. The top barriers related to shared language and protocols, referral quality, expectations and responsibilities between healthcare professionals and patients, and time pressure. The top solutions identified related to general practitioners using electronic consultations with specialists and shared terminology with patients.Conclusion The identified barriers and possible solutions for collaboration between primary and secondary care need attention when considering collaboration in PSS/FD care and related settings, both in new and ongoing collaborations.

The meta-analytic-predictive (MAP) approach is a Bayesian method to incorporate historical controls in new trials that aims to increase the statistical power and reduce the required sample size. Here we investigate how to calculate the sample size of the new trial when historical data is available, and the MAP approach is used in the analysis. In previous applications of the MAP approach, the prior effective sample size (ESS) acted as a metric to quantify the number of subjects the historical information is worth. However, the validity of using the prior ESS in sample size calculation (i.e., reducing the number of randomized controls by the derived prior ESS) is questionable, because different approaches may yield different values for prior ESS. In this work, we propose a straightforward Monte Carlo approach to calculate the sample size that achieves the desired power in the new trial given available historical controls. To make full use of the available historical information to simulate the new trial data, the control parameters are not taken as a point estimate but sampled from the MAP prior. These sampled control parameters and the MAP prior based on the historical data are then used to derive the statistical power for the treatment effect and the resulting required sample size. The proposed sample size calculation approach is illustrated with real-life data sets with different outcomes from three studies. The results show that this approach to calculating the required sample size for the MAP analysis is straightforward and generic.

Summary: Extended food consumption during the rest period perturbs the phase relationship between circadian clocks in the periphery and the brain, leading to adverse health effects. Beyond the liver, how metabolic organs respond to a timed hypocaloric diet is largely unexplored. We investigated how feeding schedules impacted circadian gene expression in epididymal white and brown adipose tissue (eWAT and BAT) compared to the liver and hypothalamus. We restricted food to either daytime or nighttime in C57BL/6J male mice, with or without caloric restriction. Unlike the liver and eWAT, rhythmic clock genes in the BAT remained insensitive to feeding time, similar to the hypothalamus. We uncovered an internal split within the BAT in response to conflicting environmental cues, displaying inverted oscillations on a subset of metabolic genes without modifying its local core circadian machinery. Integrating tissue-specific responses on circadian transcriptional networks with metabolic outcomes may help elucidate the mechanism underlying the health burden of eating at unusual times.

Summary: Sex and gender-related factors are strongly associated with patients' illness trajectories, underscoring their essential role in epidemiological research and healthcare. Ignoring sex and gender in research and health inevitably results in inequities between women and men in terms of detection of disease, preventative measures, and effectiveness of treatment. Historical influences, including ideas of female inferiority and conservative notions of women's health only comprising reproductive health, reinforced the perceived irrelevance of sex and gender to health. Currently, these ideas are largely abandoned and epidemiology is becoming increasingly sensitive to sex. Gender-sensitivity, however, is lagging behind. This is potentially due to lacking knowledge and awareness about the relevance of both sex and gender to health and challenges in operationalizing gender in epidemiological research. Here, we thoroughly discuss the relevance of sex and gender to health, and pay special attention to the time, place, and culture-dependent embodiment of gender. We also discuss the operationalization of gender via composite gender scores in epidemiological studies. We argue to move beyond solely using these. Rather we should consider sex and gender in the initial stages of designing a study, to facilitate relevant, reproducible, and person-centric research.

Abstract Background Care for persistent somatic symptoms and functional disorders (PSS/FD) is often fragmented. Collaborative care networks (CCNs) may improve care quality for PSS/FD. Effectiveness likely depends on their functioning, but we lack a straightforward quality evaluation system. We therefore aimed to develop quality indicators to evaluate CCNs for PSS/FD. Method Using an online three-round modified Delphi process, an expert panel provided, selected and ranked quality indicators for CCNs in PSS/FD. Recruited experts were diverse healthcare professionals with relevant experience in PSS/FD care in the Netherlands. Results The expert panel consisted of 86 professionals representing 15 disciplines, most commonly physiotherapists, psychologists and medical specialists. 58% had more than 10 years experience in PSS/FD care. Round one resulted in 994 quotations, which resulted in 46 unique quality indicators. These were prioritised in round two and ranked in round three by the panel, resulting in a final top ten. The top three indicators were: “shared vision of care for PSS/FD”, “pathways tailored to the individual patient”, and “sufficiently-experienced caregivers for PSS/FD”. Conclusions The identified quality indicators to evaluate CCNs in the field of PSS/FD can be implemented in clinical practice and may be useful in improving services and when assessing effectiveness.

Abstract Background Eurotransplant liver transplant candidates are prioritized by Model for End-stage Liver Disease (MELD), a 90-day waitlist survival risk score based on the INR, creatinine and bilirubin. Several studies revised the original MELD score, UNOS-MELD, with transplant candidate data by modelling 90-day waitlist mortality from waitlist registration, censoring patients at delisting or transplantation. This approach ignores biomarkers reported after registration, and ignores informative censoring by transplantation and delisting. Methods We study how MELD revision is affected by revision from calendar-time cross-sections and correction for informative censoring with inverse probability censoring weighting (IPCW). For this, we revised UNOS-MELD on patients with chronic liver cirrhosis on the Eurotransplant waitlist between 2007 and 2019 (n = 13,274) with Cox models with as endpoints 90-day survival (a) from registration and (b) from weekly drawn calendar-time cross-sections. We refer to the revised score from cross-section with IPCW as DynReMELD, and compare DynReMELD to UNOS-MELD and ReMELD, a prior revision of UNOS-MELD for Eurotransplant, in geographical validation. Results Revising MELD from calendar-time cross-sections leads to significantly different MELD coefficients. IPCW increases estimates of absolute 90-day waitlist mortality risks by approximately 10 percentage points. DynReMELD has improved discrimination over UNOS-MELD (delta c-index: 0.0040, p

Abstract Background Although stimulating patients’ mobility is considered a component of fundamental nursing care, approximately 35% of hospitalized patients experience functional decline during or after hospital admission. The aim of this study is to assess mobility level and to identify factors affecting mobility status in hospitalized patients admitted in single-occupancy patient rooms (SPRs) on general wards. Methods Mobility level was quantified with the Johns Hopkins Highest Level of Mobility Scale (JH-HLM) and EQ-5D-3L. GENEActiv accelerometer data over 24 h were collected in a subset of patients. Data were analyzed using generalized ordinal logistic regression analysis. The STROBE reporting checklist was applied. Results Wearing pajamas during daytime, having pain, admission in an isolation room, and wearing three or more medical equipment were negatively associated with mobilization level. More than half of patients (58.9%) who were able to mobilize according to the EQ-5D-3L did not achieve the highest possible level of mobility according to the JH-HLM. The subset of patients that wore an accelerometer spent most of the day in sedentary behavior (median 88.1%, IQR 85.9–93.6). The median total daily step count was 1326 (range 22-5362). Conclusion We found that the majority of participating hospitalized patients staying in single-occupancy patient rooms were able to mobilize. It appeared, however, that most of the patients who are physically capable of walking, do not reach the highest possible level of mobility according to the JH-HLM scale. Nurses should take their responsibility to ensure that patients achieve the highest possible level of mobility.

Abstract We validated a Deep Embedded Clustering (DEC) model and its adaptation for integrating mixed datatypes (in this study, numerical and categorical variables). Deep Embedded Clustering (DEC) is a promising technique capable of managing extensive sets of variables and non-linear relationships. Nevertheless, DEC cannot adequately handle mixed datatypes. Therefore, we adapted DEC by replacing the autoencoder with an X-shaped variational autoencoder (XVAE) and optimising hyperparameters for cluster stability. We call this model “X-DEC”. We compared DEC and X-DEC by reproducing a previous study that used DEC to identify clusters in a population of intensive care patients. We assessed internal validity based on cluster stability on the development dataset. Since generalisability of clustering models has insufficiently been validated on external populations, we assessed external validity by investigating cluster generalisability onto an external validation dataset. We concluded that both DEC and X-DEC resulted in clinically recognisable and generalisable clusters, but X-DEC produced much more stable clusters.

Abstract Background Extra-hepatic vitamin K-status, measured by dephosphorylated uncarboxylated matrix Gla protein (dp-ucMGP), maintains vascular health, with high levels reflecting poor vitamin K status. The occurrence of extra-hepatic vitamin K deficiency throughout the disease of COVID-19 and possible associations with pulmonary embolism (PE), and mortality in intensive care unit (ICU) patients has not been studied. The aim of this study was to investigated the association between dp-ucMGP, at endotracheal intubation (ETI) and both ICU and six months mortality. Furthermore, we studied the associations between serially measured dp-ucMGP and both PE and mortality. Methods We included 112 ICU patients with confirmed COVID-19. Over the course of 4 weeks after ETI, dp-ucMGP was measured serially. All patients underwent computed tomography pulmonary angiography (CTPA) to rule out PE. Results were adjusted for patient characteristics, disease severity scores, inflammation, renal function, history of coumarin use, and coronary artery calcification (CAC) scores. Results Per 100 pmol/L dp-ucMGP, at ETI, the odds ratio (OR) was 1.056 (95% CI: 0.977 to 1.141, p = 0.172) for ICU mortality and 1.059 (95% CI: 0.976 to 1.059, p = 0.170) for six months mortality. After adjustments for age, gender, and APACHE II score, the mean difference in plasma dp-ucMGP over time of ICU admission was 167 pmol/L (95% CI: 4 to 332, p = 0.047). After additional adjustments for c-reactive protein, creatinine, and history of coumarin use, the difference was 199 pmol/L (95% CI: 50 to 346, p = 0.010). After additional adjustment for CAC score the difference was 213 pmol/L (95% CI: 3 to 422, p = 0.051) higher in ICU non-survivors compared to the ICU survivors. The regression slope, indicating changes over time, did not differ. Moreover, dp-ucMGP was not associated with PE. Conclusion ICU mortality in COVID-19 patients was associated with higher dp-ucMGP levels over 4 weeks, independent of age, gender, and APACHE II score, and not explained by inflammation, renal function, history of coumarin use, and CAC score. No association with PE was observed. At ETI, higher levels of dp-ucMGP were associated with higher OR for both ICU and six month mortality in crude and adjusted modes, although not statistically significantly.

Abstract Background Data on hyperglycemia and glucose variability in relation to diabetes mellitus, either known or unknown in ICU-setting in COVID-19, are scarce. We prospectively studied daily glucose variables and mortality in strata of diabetes mellitus and glycosylated hemoglobin among mechanically ventilated COVID-19 patients. Methods We used linear-mixed effect models in mechanically ventilated COVID-19 patients to investigate mean and maximum difference in glucose concentration per day over time. We compared ICU survivors and non-survivors and tested for effect-modification by pandemic wave 1 and 2, diabetes mellitus, and admission HbA1c. Results Among 232 mechanically ventilated COVID-19 patients, 21.1% had known diabetes mellitus, whereas 16.9% in wave 2 had unknown diabetes mellitus. Non-survivors had higher mean glucose concentrations (ß 0.62 mmol/l; 95%CI 0.20–1.06; ß 11.2 mg/dl; 95% CI 3.6–19.1; P = 0.004) and higher maximum differences in glucose concentrations per day (ß 0.85 mmol/l; 95%CI 0.37–1.33; ß 15.3; 95%CI 6.7–23.9; P = 0.001). Effect modification by wave, history of diabetes mellitus and admission HbA1c in associations between glucose and survival was not present. Effect of higher mean glucose concentrations was modified by pandemic wave (wave 1 (ß 0.74; 95% CI 0.24–1.23 mmol/l) ; (ß 13.3; 95%CI 4.3–22.1 mg/dl)) vs. (wave 2 (ß 0.37 (95%CI 0.25–0.98) mmol/l) (ß 6.7 (95% ci 4.5–17.6) mg/dl)). Conclusions Hyperglycemia and glucose variability are associated with mortality in mechanically ventilated COVID-19 patients irrespective of the presence of diabetes mellitus.

Providing adequate parental support is pivotal when treating excessive infant crying, but there are indications that parents may not feel supported by professional health care. This study investigated maternal satisfaction with health care and health care needs, comparing mothers of infants with (N = 110) and without a medical cause for the crying (N = 101). Hierarchical cluster analysis was used to detect patterns in health care needs. Dissatisfaction with health care (often related to feelings of not being taken seriously) was reported by 55.0%. Mothers of infants with a medical cause for the crying rated health care as more effective but were also more often dissatisfied with health care. Most mothers needed help both for the crying of their infant and their own well-being. The results suggest that offering effective reassurance to parents without downplaying the seriousness of the situation and being sensitive to the specific needs of each family is essential.

For predicting and improving the quality of essays, text analytic metrics (surface, syntactic, morphological, and semantic features) can be used to provide formative feedback to the students in higher education. In this study, the goal was to identify a sufficient number of features that exhibit a fair proxy of the scores given by the human raters via a data-driven approach. Using an existing corpus and a text analysis tool for the Dutch language, a large number of features were extracted. Artificial neural networks, Levenberg-Marquardt algorithm, and backward elimination were used to reduce the number of features automatically. Irrelevant features were eliminated based on the inter-rater agreement between predicted and human scores calculated using Cohen's kappa (?). The number of features in this study was reduced from 457 to 28 and grouped into different categories. The results reported in this article are an improvement over a similar previous study. First, the inter-rater reliability between the predicted scores and human raters was increased by tweaking the corpus for overfitting for average scores. The resulting maximum value of [Cohen's kappa] showed substantial agreement compared to moderate inter-rater reliability in the prior study. Second, instead of using a dedicated training and test set, the training and testing phases in the new experiments were performed using [Cohen's kappa]-fold cross validation on the corpus of texts. The approach presented in this research article is the first step toward our ultimate goal of providing meaningful formative feedback to the students for enhancing their writing skills and capabilities.

The meta-analytic-predictive (MAP) approach is a Bayesian meta-analytic method to synthesize and incorporate information from historical controls in the analysis of a new trial. Classically, only a single parameter, typically the intercept or rate, is assumed to vary across studies, which may not be realistic in more complex models. Analysis of covariance (ANCOVA) is often used to analyze trials with a pretest-posttest design, where both the intercept and the baseline effect (coefficient of the outcome at baseline) affect the estimated treatment effect. We extended the MAP approach to ANCOVA, to allow for variation in the intercept and the baseline effect across studies, and possibly also correlation between these parameters. The method was illustrated using data from the Alzheimer's Disease Cooperative Study (ADCS) and assessed with a simulation study. In the ADCS data, the proposed multivariate MAP approach yielded a prior effective sample size of 79 and 58 for the intercept and the baseline effect respectively and reduced the posterior standard deviation of the treatment effect by 12.6%. The result was robust to the choice of prior for the between-study variation. In the simulations, the proposed approach yielded power gains with a good control of the type I error rate. Ignoring the between-study correlation of the parameters or assuming no variation in the baseline effect generally led to less power gain. In conclusion, the MAP approach can be extended to a multivariate version for ANCOVA, which may improve the estimation of the treatment effect.

Abstract Background Despite preventive measures, the number of people with type 2 diabetes and obesity is increasing. Obesity increases morbidity and mortality in people with type 2 diabetes, making weight loss a cornerstone of treatment. We previously developed a very low energy diet (VLED) intervention that effectively reduced weight in people with type 2 diabetes in the long term. However, this intervention requires considerable time and manpower, which reduces the number of people who can benefit from it. eHealth offers more efficient solutions but has proven to be less effective than face-to-face interventions. Therefore, we want to investigate whether a blended version of our VLED intervention (in which face-to-face contact is partly replaced by an eHealth (mobile) application (E-VLED)) would be more cost-effective than the current face-to-face intervention. Methods We will conduct a randomised, controlled trial with non-inferiority design in patients with type 2 diabetes and obesity (BMI > 30 kg/m2), aged 18–75 years. The control group will receive the usual care VLED intervention, while the intervention group will receive the E-VLED intervention for 1 year, where face-to-face contact will be partly replaced by an eHealth (mobile) application. The main study endpoint is the difference in weight (% change) between the control and intervention group after 1 year, plus the difference between the total costs (euro) of the treatment in the control and intervention groups. The secondary aims are to investigate the effectiveness of the E-VLED diet intervention regarding cardiovascular risk factors, quality of life, patient satisfaction, compliance, and to study whether there is a difference in effectiveness in pre-specified subgroups. General linear models for repeated measurements will be applied for the statistical analysis of the data. Discussion We hypothesise that the E-VLED intervention will be equally effective compared to the usual care VLED but lower in costs due to less time invested by the dietician. This will enable to help more people with type 2 diabetes and obesity to effectively lose weight and improve their health-related quality of life. Trial registration Netherlands Trial Register, NL7832, registered on 26 June 2019.