Actigraphic sleep detection: an artificial intelligence approach

Objective: Polysomnography is the gold standard for sleep monitoring, despite its many drawbacks: it is complex, costly and rather invasive. Medical-grade actigraphy represents an acceptably accurate alternative for the estimation of sleep patterns in normal, healthy adult populations and in patients suspected of certain sleep disorders. An increasing number of consumer-grade accelerometric devices populate the “quantified-self” market but the lack of validation significantly limits their reliability. Our aim was to prototype and validate a platform-free artificial neural network (ANN) based algorithm applied to a high performance, open source device (Axivity AX3), to achieve accurate actigraphic sleep detection. Methods: 14 healthy subjects (29.35 14.40 yrs, 7 females) were equipped for 13.3 2.58 h with portable polysomnography (pPSG), while wearing the Axivity AX3. The AX3 was set to record 3D accelerations at 100 Hz, with a dynamic range of 8 g coded at 10 bit. For the automatic actigraphy-based sleep detection, a 4 layer artificial neural network has been trained, validated and tested against the pPSG-based expert visual sleep-wake scoring. Results: When compared to the pPSG gold standard scoring, the ANN-based algorithm reached high concordance (85.3 0.06%), specificity (87.3 0.04%) and sensitivity (84.6 0.1%) in the detection of sleep over 30-sec epochs. Moreover there were no statistical differences between pPSG and actigraphy-based Total Sleep Time and Sleep Efficiency measurements (Wilcoxon test). Conclusions: The high concordance rate between ANN-actigraphy scoring and the standard visual pPSG one suggests that this approach could represent a viable method for collecting objective sleep-wake data using a high performance, open source actigraph

Usefulness of a simple sleep-deprived EEG protocol for epilepsy diagnosis in de novo subjects.

OBJECTIVE: In case series concerning the role of EEG after sleep deprivation (SD-EEG) in epilepsy, patients' features and protocols vary dramatically from one report to another. In this study, we assessed the usefulness of a simple SD-EEG method in well characterized patients. METHODS: Among the 963 adult subjects submitted to SD-EEG at our Center, in the period 2003-2010, we retrospectively selected for analysis only those: (1) evaluated for suspected epileptic seizures; (2) with a normal/non-specific baseline EEG; (3) still drug-free at the time of SD-EEG; (4) with an MRI analysis; (5) with at least 1year follow-up. SD-EEG consisted in SD from 2:00 AM and laboratory EEG from 8:00 AM to 10:30 AM. We analyzed epileptic interictal abnormalities (IIAs) and their correlations with patients' features. RESULTS: Epilepsy was confirmed in 131 patients. SD-EEG showed IIAs in 41.2% of all patients with epilepsy, and a 91.1% specificity for epilepsy diagnosis; IIAs types observed during SD-EEG are different in generalized versus focal epilepsies; for focal epilepsies, the IIAs yield in SD-EEG is higher than in second routine EEG. CONCLUSIONS: This simple SD-EEG protocol is very useful in de novo patients with suspected seizures. SIGNIFICANCE: This study sheds new light on the role of SD-EEG in specific epilepsy populations

Controversial issues on EEG after sleep deprivation for the diagnosis of epilepsy

EEG after sleep deprivation (SD-EEG) is widely used in many epilepsy centers as an important tool in the epilepsy diagnosis process. However, after more than 40 years of use, there are a number of issues which still need to be clarified concerning its features and role. In particular, the many scientific papers addressing its role in epilepsy diagnosis often differ remarkably from each other in terms of the type of patients assessed, their description and study design. Furthermore, also the length and the type of EEG performed after SD, as well as the length of SD itself, vary dramatically from one study to another. In this paper we shortly underscore the abovementioned differences among the different reports, as well as some interpretations of the findings obtained in the different studies. This analysis emphasizes, if needed, how SD-EEG still represents a crucial step in epilepsy diagnosis, and how additional, controlled studies might further shape its precise diagnostic/prognostic role

Prevalence of sleep disruption and determinants of sleepiness in a cohort of Italian hospital physicians: The PRESOMO study

Nightshift work can cause daytime somnolence and decreased alertness, and can increase risk of medical errors, occupational injuries and car accidents. We used a structured questionnaire, including the Epworth Sleepiness Scale (ESS), to assess the prevalence and the determinants of sleep disruption in 268 Italian University hospital physicians from Cagliari (N = 57), Milan (N = 180) and Pisa (N = 31), who participated in the multicentre study on the prevalence of sleep disturbance among hospital physicians (PRESOMO); 198 of them (74%) were engaged in nightshift work. We explored the association between history of nightshift work and poor sleep quality and daytime somnolence with multivariate logistic regression, adjusting by personal and lifestyle covariates. Age, female gender, taking medication interfering with sleep and an elevated ESS score were significant predictors of poor sleep quality and daytime somnolence. Nightshift work was associated with a higher prevalence of unrestful sleep (84% versus 70%; odds ratio [OR] = 2.4, 95% confidence interval [CI] 1.18-5.05) and daytime dozing (57% versus 35%; OR = 1.9, 95% CI 1.03-3.64), with an upward trend by years of engagement in nightshift work for both conditions (p = .043 and 0.017, respectively), and by number of nightshifts/year for unrestful sleep (p = .024). Such an association was not detected with the ESS scale. Our results suggest that nightshift work significantly affects sleep quality and daytime somnolence in hospital physicians, who might underestimate their daytime dozing problem, when asked to subjectively scale it

Sleep in Frontotemporal Dementia is Equally or Possibly More Disrupted, and at an Earlier Stage, When Compared to Sleep in Alzheimer's Disease

Background: Conversely to other neurodegenerative diseases (i.e., Alzheimer's disease, AD), sleep in frontotemporal dementia (FTD) has not been studied adequately. Although some evidence exists that sleep-wake disturbances occur in FTD, very little is known regarding sleep macrostructure and/or primary sleep disorders. Objective: To investigate these issues in this population and compare them to similar issues in AD and in healthy elderly (HE). Methods: Twelve drug-naïve behavioral-variant FTD (bvFTD) patients (7 men/5 women) of mean age 62.5 ± 8.6 years were compared to seventeen drug-naïve AD patients (9 men/8 women) of mean age 69.0 ± 9.9 years and twenty drug-naïve HE (12 men/8 women) of mean age 70.2 ± 12.5 years. All participants were fully assessed clinically, through a sleep questionnaire, an interview, and video-polysomnography recordings. Results: The two patient groups were comparably cognitively impaired. However, compared to FTD patients, the AD patients had a statistically significant longer disease duration. Overall, the sleep profile was better preserved in HE. Sleep complaints did not differ considerably between the two patient groups. Sleep parameters and sleep macrostructure were better preserved in AD compared to FTD patients, regardless of primary sleep disorders, which occurred equally in the two groups. Conclusions: With respect to AD, FTD patients had several sleep parameters similarly or even more affected by neurodegeneration, but in a much shorter time span. The findings probably indicate a centrally originating sleep deregulation. Since in FTD patients sleep disturbances may be obvious from an early stage of their disease, and possibly earlier than in AD patients, physicians and caregivers should be alert for the early detection and treatment of these symptoms

Daytime sleepiness in de novo untreated patients with epilepsy.

The aims of our study were to evaluate excessive daytime sleepiness in a group of de novo untreated people with epilepsy using a comprehensive and standardized approach, including subjective evaluation and neurophysiological and performance tests, and to compare these results with those obtained in a control group. Forty-seven patients with epilepsy (17 affected by primary generalized epilepsy and 30 by partial epilepsy), with a new epilepsy diagnosis and never treated, and 44 controls underwent Multiple Sleep Latency Test (preceded by nocturnal polysomnography), simple/complex visual reaction times, and Epworth Sleepiness Scale evaluation. Newly diagnosed and drug-free patients with epilepsy did not differ from controls in any of the tests performed to evaluate daytime sleepiness. In clinical practice, daytime sleepiness is a well-known and frequent complaint of patients with epilepsy, but different mechanisms and causes, such as associated psychiatric or sleep disorders, nocturnal seizures, sleep fragmentation, and antiepileptic drugs, must be taken into account. Excessive daytime sleepiness should not be considered an unavoidable consequence of epilepsy. Thus, a complete diagnostic work-up in patients with epilepsy and sleepiness should be undertaken whenever possible

Sleep Complaints, Sleep and Breathing Disorders in Myotonic Dystrophy Type 2

PURPOSE OF REVIEW: To update the current knowledge concerning sleep complaints and breathing disorders in myotonic dystrophy type 2 (DM2) and to better understand if sleep and breathing symptoms may add a further clinical definition of DM2. RECENT FINDINGS: Although DM2 has been poorly evaluated, the most relevant sleep disorders are sleep-disordered breathing (SDB) (37.5-66.7%) and restless legs syndrome (RLS) (50-60%). Excessive daytime somnolence (EDS) is not consistent with SDB, and a large percentage of patients with sleep complaints (58-69%) report pain. In addition, respiratory dysfunctions are reported in 6 to 15% of DM2 patients, albeit few data are available regarding pulmonary restriction, hypoventilation, and non-invasive ventilation (NIV). SDB, RLS, and pain may contribute to sleep fragmentation and EDS in DM2. In addition, few studies report hypoventilation and pulmonary restriction, although there are no studies at all on NIV, except for limited clinical experiences. These findings suggest performing a careful pulmonary examination and NIV when required. Furthermore, sleep studies and respiratory evaluation should be recommended if OSA or respiratory muscle dysfunctions are suspected. A large polysomnographic study should be performed to clarify the link between sleep disorders, pain, and sleep disruption in DM2

Clinical and dopaminergic imaging characteristics of the FARPRESTO cohort of trial-ready idiopathic rapid eye movement sleep behavior patients

Introduction: Idiopathic/isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is considered the prodromal stage of alpha-synucleinopathies. Thus, iRBD patients are the ideal target for disease-modifying therapy. The risk FActoRs PREdictive of phenoconversion in iRBD Italian STudy (FARPRESTO) is an ongoing Italian database aimed at identifying risk factors of phenoconversion, and eventually to ease clinical trial enrollment of well-characterized subjects.Methods: Polysomnography-confirmed iRBD patients were retrospectively and prospectively enrolled. Baseline harmonized clinical and nigrostriatal functioning data were collected at baseline. Nigrostriatal functioning was evaluated by dopamine transporter-single-photon emission computed tomography (DaT-SPECT) and categorized with visual semi-quantification. Longitudinal data were evaluated to assess phenoconversion. Cox regressions were applied to calculate hazard ratios.Results: 365 patients were enrolled, and 289 patients with follow-up (age 67.7 & PLUSMN; 7.3 years, 237 males, mean follow-up 40 & PLUSMN; 37 months) were included in this study. At follow-up, 97 iRBD patients (33.6%) phenoconverted to an overt synucleinopathy. Older age, motor and cognitive impairment, constipation, urinary and sexual dysfunction, depression, and visual semi-quantification of nigrostriatal functioning predicted phenoconversion. The remaining 268 patients are in follow-up within the FARPRESTO project.Conclusions: Clinical data (older age, motor and cognitive impairment, constipation, urinary and sexual dysfunction, depression) predicted phenoconversion in this multicenter, longitudinal, observational study. A standardized visual approach for semi-quantification of DaT-SPECT is proposed as a practical risk factor for phenoconversion in iRBD patients. Of note, non-converted and newly diagnosed iRBD patients, who represent a trial-ready cohort for upcoming disease-modification trials, are currently being enrolled and followed in the FARPRESTO study. New data are expected to allow better risk characterization

Clinical characteristics of a large cohort of patients with narcolepsy candidate for pitolisant: a cross-sectional study from the Italian PASS Wakix® Cohort

Introduction Narcolepsy is a chronic and rare hypersomnia of central origin characterized by excessive daytime sleepiness and a complex array of symptoms as well as by several medical comorbidities. With growing pharmacological options, polytherapy may increase the possibility of a patient-centered management of narcolepsy symptoms. The aims of our study are to describe a large cohort of Italian patients with narcolepsy who were candidates for pitolisant treatment and to compare patients' subgroups based on current drug prescription (drug-naive patients in whom pitolisant was the first-choice treatment, switching to pitolisant from other monotherapy treatments, and adding on in polytherapy). Methods We conducted a cross-sectional survey based on Italian data from the inclusion visits of the Post Authorization Safety Study of pitolisant, a 5-year observational, multicenter, international study. Results One hundred ninety-one patients were enrolled (76.4% with narcolepsy type 1 and 23.6% with narcolepsy type 2). Most patients (63.4%) presented at least one comorbidity, mainly cardiovascular and psychiatric. Pitolisant was prescribed as an add-on treatment in 120/191 patients (62.8%), as switch from other therapies in 42/191 (22.0%), and as a first-line treatment in 29/191 (15.2%). Drug-naive patients presented more severe sleepiness, lower functional status, and a higher incidence of depressive symptoms. Conclusion Our study presents the picture of a large cohort of Italian patients with narcolepsy who were prescribed with pitolisant, suggesting that polytherapy is highly frequent to tailor a patient-centered approach