The NECK trial: Effectiveness of anterior cervical discectomy with or without interbody fusion and arthroplasty in the treatment of cervical disc herniation;

The NECK trial: Effectiveness of anterior cervical discectomy with or without interbody fusion and arthroplasty in the treatment of cervical disc herniation; a double-blinded randomised controlled trial

COVID RADAR app; selfreported symptoms and behavior

Over a period of 2 years, a total of 280.000 Dutch inhabitants filled in a short questionnaire about Corona-related symptoms, behavior, vaccinationstatus and test result. In this dataset the postcode is deleted, because of privacy reasons. If researches would like to use the dataset with the postcode included, please contact u

Intra- and interindividual attack frequency variability of chronic cluster headache

BackgroundThe lack of knowledge about the intra- and interindividual attack frequency variability in chronic cluster headache complicates power and sample size calculations for baseline periods of trials, and consensus on their most optimal duration.MethodsWe analyzed the 12-week baseline of the ICON trial (occipital nerve stimulation in medically intractable chronic cluster headache) for: (i) weekly vs. instantaneous recording of attack frequency; (ii) intra-individual and seasonal variability of attack frequency; and (iii) the smallest number of weeks to obtain a reliable estimate of baseline attack frequency.ResultsWeekly median (14.4 [8.2–24.0]) and instantaneous (14.2 [8.0–24.5]) attack frequency recordings were similar (p = 0.20; Bland-Altman plot). Median weekly attack frequency was 15.3 (range 4.2–140) and highest during spring (p = 0.001) compared to the other seasons. Relative attack frequency variability decreased with increasing attack frequency (p = 0.010). We tabulated the weekly attack frequency estimation accuracies compared to, and the associated deviations from, the 12-week gold standard for different lengths of the observation period.ConclusionWeekly retrospective attack frequency recording is as good as instantaneous recording and more convenient. Attack frequency is highest in spring. Participants with ≥3 daily attacks show less attack frequency variability than those wit

Computational modelling of energy balance in individuals with Metabolic Syndrome

Abstract Background A positive energy balance is considered to be the primary cause of the development of obesity-related diseases. Treatment often consists of a combination of reducing energy intake and increasing energy expenditure. Here we use an existing computational modelling framework describing the long-term development of Metabolic Syndrome (MetS) in APOE3L.CETP mice fed a high-fat diet containing cholesterol with a human-like metabolic system. This model was used to analyze energy expenditure and energy balance in a large set of individual model realizations. Results We developed and applied a strategy to select specific individual models for a detailed analysis of heterogeneity in energy metabolism. Models were stratified based on energy expenditure. A substantial surplus of energy was found to be present during MetS development, which explains the weight gain during MetS development. In the majority of the models, energy was mainly expended in the peripheral tissues, but also distinctly different subgroups were identified. In silico perturbation of the system to induce increased peripheral energy expenditure implied changes in lipid metabolism, but not in carbohydrate metabolism. In silico analysis provided predictions for which individual models increase of peripheral energy expenditure would be an effective treatment. Conclusion The computational analysis confirmed that the energy imbalance plays an important role in the development of obesity. Furthermore, the model is capable to predict whether an increase in peripheral energy expenditure â for instance by cold exposure to activate brown adipose tissue (BAT) â could resolve MetS symptoms

Needs and perceptions regarding healthy eating among people at risk of food insecurity: a qualitative analysis

Abstract Background Healthy eating behaviour is an essential determinant of overall health. This behaviour is generally poor among people at risk of experiencing food insecurity, which may be caused by many factors including perceived higher costs of healthy foods, financial stress, inadequate nutritional knowledge, and inadequate skills required for healthy food preparation. Few studies have examined how these factors influence eating behaviour among people at risk of experiencing food insecurity. We therefore aimed to gain a better understanding of the needs and perceptions regarding healthy eating in this target group. Methods We conducted a qualitative exploration grounded in data using inductive analyses with 10 participants at risk of experiencing food insecurity. The analysis using an inductive approach identified four core factors influencing eating behaviour: Health related topics; Social and cultural influences; Influences by the physical environment; and Financial influences. Results Overall, participants showed adequate nutrition knowledge. However, eating behaviour was strongly influenced by both social factors (e.g. child food preferences and cultural food habits), and physical environmental factors (e.g. temptations in the local food environment). Perceived barriers for healthy eating behaviour included poor mental health, financial stress, and high food prices. Participants had a generally conscious attitude towards their financial situation, reflected in their strategies to cope with a limited budget. Food insecurity was mostly mentioned in reference to the past or to others and not to participants’ own current experiences. Participants were familiar with several existing resources to reduce food-related financial strain (e.g. debt assistance) and generally had a positive attitude towards these resources. An exception was the Food Bank, of which the food parcel content was not well appreciated. Proposed interventions to reduce food-related financial strain included distributing free meals, facilitating social contacts, increasing healthy food supply in the neighbourhood, and lowering prices of healthy foods. Conclusion The insights from this study increase understanding of factors influencing eating behaviour of people at risk of food insecurity. Therefore, this study could inform future development of potential interventions aiming at helping people at risk of experiencing food insecurity to improve healthy eating, thereby decreasing the risk of diet-related diseases

Supplementary Material for: Determinants of Advanced Bone Age in Childhood Obesity

Background: Childhood obesity is associated with advanced bone age (BA). Previous studies suggest that androgens, oestrogens, sex hormone-binding globulin, and insulin are responsible for this phenomenon, but results are contradictory and might be biased by confounders. We aim to elucidate this matter by applying a multivariate approach. Method: We performed a correlation analysis of BA standard deviation score (SDS) with age- and sex-specific SDS for androgens, oestrogens, and with indicators of insulin secretion derived from oral glucose tolerance testing, in a group of obese children. A multivariate analysis was performed to investigate which parameters were independently predictive of BA SDS. Results: In this cohort (n = 101; mean age 10.9 years; mean BA 11.8 years; mean BMI SDS 3.3), BMI SDS was significantly correlated to BA SDS (r = 0.55, p < 0.001). In a regression analysis in the total cohort (B = 0.27, p < 0.001) as well as in females (B = 0.34, p = 0.042), males (B = 0.31, p = 0.006), and pubertal children (B = 0.32, p = 0.046), dehydroepiandrosterone sulphate (DHEAS) showed a positive, independent association with BA SDS. No association with indicators of insulin secretion was found. Conclusion: BMI SDS is highly correlated to BA SDS in obese children. Increased DHEAS has a central role in advanced BA in obese children

Analyzing patient experiences using natural language processing: development and validation of the artificial intelligence patient reported experience measure (AI-PREM)

Abstract Background Evaluating patients’ experiences is essential when incorporating the patients’ perspective in improving healthcare. Experiences are mainly collected using closed-ended questions, although the value of open-ended questions is widely recognized. Natural language processing (NLP) can automate the analysis of open-ended questions for an efficient approach to patient-centeredness. Methods We developed the Artificial Intelligence Patient-Reported Experience Measures (AI-PREM) tool, consisting of a new, open-ended questionnaire, an NLP pipeline to analyze the answers using sentiment analysis and topic modeling, and a visualization to guide physicians through the results. The questionnaire and NLP pipeline were iteratively developed and validated in a clinical context. Results The final AI-PREM consisted of five open-ended questions about the provided information, personal approach, collaboration between healthcare professionals, organization of care, and other experiences. The AI-PREM was sent to 867 vestibular schwannoma patients, 534 of which responded. The sentiment analysis model attained an F1 score of 0.97 for positive texts and 0.63 for negative texts. There was a 90% overlap between automatically and manually extracted topics. The visualization was hierarchically structured into three stages: the sentiment per question, the topics per sentiment and question, and the original patient responses per topic. Conclusions The AI-PREM tool is a comprehensive method that combines a validated, open-ended questionnaire with a well-performing NLP pipeline and visualization. Thematically organizing and quantifying patient feedback reduces the time invested by healthcare professionals to evaluate and prioritize patient experiences without being confined to the limited answer options of closed-ended questions

Supplementary Material for: Dose-Titrated Vasopressin V2 Receptor Antagonist Improves Renoprotection in a Mouse Model for Autosomal Dominant Polycystic Kidney Disease

Background: In autosomal dominant polycystic kidney disease, renoprotective treatment with a vasopressin V2 receptor antagonist (V2RA) is given in a fixed dose (FD). Disease progression and drug habituation could diminish treatment efficacy. We investigated whether the renoprotective effect of the V2RA can be improved by dose titration of the V2RA aiming to maintain aquaresis at a high level. Methods: The V2RA OPC-31260 was administered to Pkd1-deletion mice in an FD (0.1%) or in a titrated dose (TD, up to 0.8% when drinking volume dropped). Total kidney weight (TKW) and cyst ratio were investigated and compared to non-treated Pkd1-deletion mice. Treatment was started early or late (21 or 42 days postnatal). Results: Water intake was significantly higher throughout the experiment in the TD compared to the FD group. FD treatment that was initiated early reduced TKW and cyst ratio but lost its renoprotective effect later during the experiment. In contrast, TD treatment was able to maintain the renoprotective effect. TD treatment, however, was also associated with a higher early termination rate in comparison with FD treatment. Late start of treatment (FD or TD) did not show a renoprotective effect. Conclusions: Titration of a V2RA aimed to maintain aquaresis at a high level showed a better renoprotective effect compared to FD administration. However, this treatment regimen was poorly tolerated and did not overcome treatment unresponsiveness when started later in the disease

Supplementary Material for: The Impact of Depressive Disorder Symptoms and Subtypes on 6-Year Incidence of Somatic Diseases

Medicin

Noninvasive detection of soft tissue sarcoma using volatile organic compounds in exhaled breath: a pilot study supplementary figure 1

Noninvasive detection of soft tissue sarcoma using volatile organic compounds in exhaled breath: a pilot study supplementary figure