Inter-database validation of a deep learning approach for automatic sleep scoring

[Abstract] Study objectives Development of inter-database generalizable sleep staging algorithms represents a challenge due to increased data variability across different datasets. Sharing data between different centers is also a problem due to potential restrictions due to patient privacy protection. In this work, we describe a new deep learning approach for automatic sleep staging, and address its generalization capabilities on a wide range of public sleep staging databases. We also examine the suitability of a novel approach that uses an ensemble of individual local models and evaluate its impact on the resulting inter-database generalization performance. Methods A general deep learning network architecture for automatic sleep staging is presented. Different preprocessing and architectural variant options are tested. The resulting prediction capabilities are evaluated and compared on a heterogeneous collection of six public sleep staging datasets. Validation is carried out in the context of independent local and external dataset generalization scenarios. Results Best results were achieved using the CNN_LSTM_5 neural network variant. Average prediction capabilities on independent local testing sets achieved 0.80 kappa score. When individual local models predict data from external datasets, average kappa score decreases to 0.54. Using the proposed ensemble-based approach, average kappa performance on the external dataset prediction scenario increases to 0.62. To our knowledge this is the largest study by the number of datasets so far on validating the generalization capabilities of an automatic sleep staging algorithm using external databases. Conclusions Validation results show good general performance of our method, as compared with the expected levels of human agreement, as well as to state-of-the-art automatic sleep staging methods. The proposed ensemble-based approach enables flexible and scalable design, allowing dynamic integration of local models into the final ensemble, preserving data locality, and increasing generalization capabilities of the resulting system at the same time

Computer-assisted analysis of polysomnographic recordings improves interscorer associated agreement and scoring times

Estudo iniciado no Haaglanden Medisch Centrum cunha política de coste neutral baixo o número de proxecto 2019-073.[Abstract]: Study objectives To investigate inter-scorer agreement and scoring time differences associated with visual and computer-assisted analysis of polysomnographic (PSG) recordings. Methods A group of 12 expert scorers reviewed 5 PSGs that were independently selected in the context of each of the following tasks: (i) sleep staging, (ii) scoring of leg movements, (iii) detection of respiratory (apneic-related) events, and (iv) of electroencephalographic (EEG) arousals. All scorers independently reviewed the same recordings, hence resulting in 20 scoring exercises per scorer from an equal amount of different subjects. The procedure was repeated, separately, using the classical visual manual approach and a computer-assisted (semi-automatic) procedure. Resulting inter-scorer agreement and scoring times were examined and compared among the two methods. Results Computer-assisted sleep scoring showed a consistent and statistically relevant effect toward less time required for the completion of each of the PSG scoring tasks. Gain factors ranged from 1.26 (EEG arousals) to 2.41 (leg movements). Inter-scorer kappa agreement was also consistently increased with the use of supervised semi-automatic scoring. Specifically, agreement increased from = 0.76 to K = 0.80 (sleep stages), = 0.72 to K = 0.91 (leg movements), = 0.55 to K = 0.66 (respiratory events), and = 0.58 to = 0.65 (EEG arousals). Inter-scorer agreement on the examined set of diagnostic indices did also show a trend toward higher Interclass Correlation Coefficient scores when using the semi-automatic scoring approach. Conclusions Computer-assisted analysis can improve inter-scorer agreement and scoring times associated with the review of PSG studies resulting in higher efficiency and overall quality in the diagnosis sleep disorders. © 2022 Alvarez-Estevez, Rijsman. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Xunta de Galicia;ED431H 2020/10Xunta de Galicia; ED431G 2019/0

Increased prevalence of restless legs syndrome in patients with Crohn’s disease

OBJECTIVE: To determine (a) the incidence of restless legs syndrome (RLS) in patients with Crohn's disease (CD), (b) whether and how the occurrence and severity of RLS is related to severity of CD, and (c) how RLS influences the quality of life of CD patients.BASIC METHODS: We carried out a cross-sectional questionnaire study in a random selection of 144 CD patients and 80 controls. Differences were calculated using a χ-test (categorical data), an independent T-test (continuous data, normal distribution), or a Mann-Whitney U-test (continuous data, non-normal distribution). Logistic regression analysis was carried out to establish the relation between CD and RLS after adjusting for risk factors.MAIN RESULTS: The prevalence of RLS was 25.7% (37/144) in CD patients compared with 12.5% (10/80) in the control group (P=0.02). CD patients using caffeine and patients with arthralgias had a higher risk for RLS. A higher score on the modified Harvey Bradshaw Index and CD-related surgery were also associated with a higher risk for RLS. CD-related surgery was also associated with a more severe course of RLS. Patients and controls with RLS had a lower score on 'physical functioning', one of the subcategories of the RAND-36 quality-of-life questionnaire.PRINCIPAL CONCLUSION: RLS occurs more frequently in patients with CD compared with healthy individuals. A more severe course of CD seems to be associated with a higher risk for RLS. The presence of RLS has a negative influence on quality of life, mainly interfering with physical activities of daily lif

Periodic limb movement disorder and restless legs syndrome in dialysis patients

BACKGROUND: Sleep disturbances, in particular restless legs or limb movements, during the night are often reported by uremic patients. However, polysomnography (PSG) studies have never been carried out to confirm the actual occurrence of these disorders and the association with other objective and self-reported sleep-wake data. METHODS: Forty-eight participants were subjected to a 2-day PSG. These data on sleep including periodic limb movements, which are associated with restless legs, were correlated with clinical observations, quality of sleep-wake and life questionnaires, and with biochemical and neurographical measures. RESULTS: Restless legs syndrome (RLS) was observed in 58.3% of the patients and periodic limb movement disorder (PLMD) occurred in 70.8% of the patients. PLMD was revealed polysomnographically in almost 90% of the RLS patients. Patients with both PLMD and RLS had significantly poorer sleep quality than those with neither disorder or with PLMD alone, both in terms of self-reported data and the PSG. Quality of life was significantly worse in patients with RLS and PLMD compared to those patients with neither disorder. PLMD patients also tended to have a lower quality of life. All other metabolic measures and the results of a nerve conduction test were not correlated with RLS and/or PLMD. CONCLUSION: There was a high prevalence of severe RLS and PLMD in the present sample of uraemia patients. Nearly all RLS patients had severe PLMD. RLS (in combination with PLMD) in dialysis is associated with poor sleep quality, insomnia complaints, depression and emotional distress. Our results suggest that PLMD per se is also clinically relevant

The impact of a multimodal intervention on emergency department crowding and patient flow

Objective: The objective of this study is to assess the impact of a multimodal intervention on emergency department (ED) crowding and patient flow in a Dutch level 1 trauma center. Methods: In this cross-sectional study, we compare ED crowding and patient flow between a 9-month pre-intervention period and a 9-month intervention period, during peak hours and overall (24/7). The multimodal intervention included (1) adding an emergency nurse practitioner (ENP) and (2) five medical specialists during peak hours to the 24/7 available emergency physicians (EPs), (3) a Lean programme to improve radiology turnaround times, and (4) extending the admission offices' openings hours. Crowding is measured with the modified National ED OverCrowding Score (mNEDOCS). Furthermore, radiology turnaround times, patients' length of stay (LOS), proportion of patients leaving without being seen (LWBS) by a medical provider, and unscheduled representations are assessed. Results: The number of ED visits were grossly similar in the two periods during peak hours (15,558 ED visits in the pre-intervention period and 15,550 in the intervention period) and overall (31,891 ED visits in the pre-intervention period vs. 32,121 in the intervention period). During peak hours, ED crowding fell from 18.6% (pre-intervention period) to 3.5% (intervention period), radiology turnaround times decreased from an average of 91 min (interquartile range 45-256 min) to 50 min (IQR 30-106 min., p < 0.001) and LOS reduced with 13 min per patient from 167 to 154 min (p < 0.001). For surgery, neurology and cardiology patients, LOS reduced significantly (with 17 min, 25 min, and 8 min. respectively), while not changing for internal medicine patients. Overall, crowding, radiology turnaround times and LOS also decreased. Less patients LWBS in the intervention period (270 patients vs. 348 patients, p < 0.001) and less patients represented unscheduled within 1 week after the initial ED visit: 864 (2.7%) in the pre-intervention period vs. 645 (2.0%) patients in the intervention period, p < 0.001. Conclusions: In this hospital, a multimodal intervention successfully reduces crowding, radiology turnaround times, patients' LOS, number of patients LWBS and the number of unscheduled return visits, suggesting improved ED processes. Further research is required on total costs of care and long-term effects

The effects of Psychotropic drugs On Developing brain (ePOD) study: methods and design

BACKGROUND: Animal studies have shown that methylphenidate (MPH) and fluoxetine (FLX) have different effects on dopaminergic and serotonergic system in the developing brain compared to the developed brain. The effects of Psychotropic drugs On the Developing brain (ePOD) study is a combination of different approaches to determine whether there are related findings in humans. METHODS/DESIGN: Animal studies were carried out to investigate age-related effects of psychotropic drugs and to validate new neuroimaging techniques. In addition, we set up two double-blind placebo controlled clinical trials with MPH in 50 boys (10-12 years) and 50 young men (23-40 years) suffering from ADHD (ePOD-MPH) and with FLX in 40 girls (12-14 years) and 40 young women (23-40 years) suffering from depression and anxiety disorders (ePOD-SSRI). Trial registration numbers are: Nederlands Trial Register NTR3103 and NTR2111. A cross-sectional cohort study on age-related effects of these psychotropic medications in patients who have been treated previously with MPH or FLX (ePOD-Pharmo) is also ongoing. The effects of psychotropic drugs on the developing brain are studied using neuroimaging techniques together with neuropsychological and psychiatric assessments of cognition, behavior and emotion. All assessments take place before, during (only in case of MPH) and after chronic treatment. DISCUSSION: The combined results of these approaches will provide new insight into the modulating effect of MPH and FLX on brain development