The Swiss Narcolepsy Scale (SNS) and its short form (sSNS) for the discrimination of narcolepsy in patients with hypersomnolence: a cohort study based on the Bern Sleep–Wake Database

Disentangling the complex landscape of sleep-wake disorders with data-driven phenotyping: A study of the Bernese center

BACKGROUND AND PURPOSE

The diagnosis of sleep-wake disorders (SWDs) is challenging because of the existence of only few accurate biomarkers and the frequent coexistence of multiple SWDs and/or other comorbidities. The aim of this study was to assess in a large cohort of well-characterized SWD patients the potential of a data-driven approach for the identification of SWDs.

METHODS

We included 6958 patients from the Bernese Sleep Registry and 300 variables/biomarkers including questionnaires, results of polysomnography/vigilance tests, and final clinical diagnoses. A pipeline, based on machine learning, was created to extract and cluster the clinical data. Our analysis was performed on three cohorts: patients with central disorders of hypersomnolence (CDHs), a full cohort of patients with SWDs, and a clean cohort without coexisting SWDs.

RESULTS

A first analysis focused on the cohort of patients with CDHs and revealed four patient clusters: two clusters for narcolepsy type 1 (NT1) but not for narcolepsy type 2 or idiopathic hypersomnia. In the full cohort of SWDs, nine clusters were found: four contained patients with obstructive and central sleep apnea syndrome, one with NT1, and four with intermixed SWDs. In the cohort of patients without coexisting SWDs, an additional cluster of patients with chronic insomnia disorder was identified.

CONCLUSIONS

This study confirms the existence of clear clusters of NT1 in CDHs, but mainly intermixed groups in the full spectrum of SWDs, with the exception of sleep apnea syndromes and NT1. New biomarkers are needed for better phenotyping and diagnosis of SWDs.

REM sleep and muscle atonia in brainstem stroke: A quantitative polysomnographic and lesion analysis study

Important brainstem regions are involved in the regulation of rapid eye movement sleep. We hypothesized that brainstem stroke is associated with dysregulated rapid eye movement sleep and related muscle activity. We compared quantitative/qualitative polysomnography features of rapid eye movement sleep and muscle activity (any, phasic, tonic) between 15 patients with brainstem stroke (N = 46 rapid eye movement periods), 16 patients with lacunar/non-brainstem stroke (N = 40 rapid eye movement periods), 15 healthy controls (N = 62 rapid eye movement periods), and patients with Parkinson's disease and polysomnography-confirmed rapid eye movement sleep behaviour disorder. Further, in the brainstem group, we performed a magnetic resonance imaging-based lesion overlap analysis. The mean ratio of muscle activity to rapid eye movement sleep epoch in the brainstem group ("any" muscle activity 0.09 ± 0.15; phasic muscle activity 0.08 ± 0.14) was significantly lower than in the lacunar group ("any" muscle activity 0.17 ± 0.2, p < 0.05; phasic muscle activity 0.16 ± 0.19, p < 0.05), and also lower than in the control group ("any" muscle activity 0.15 ± 0.17, p < 0.05). Magnetic resonance imaging-based lesion analysis indicated an area of maximum overlap in the medioventral pontine region for patients with reduced phasic muscle activity index. For all groups, mean values of muscle activity were significantly lower than in the patients with Parkinson's disease and polysomnography-confirmed REM sleep behaviour disorder group ("any" activity 0.51 ± 0.26, p < 0.0001 for all groups; phasic muscle activity 0.42 ± 0.21, p < 0.0001 for all groups). For the tonic muscle activity in the mentalis muscle, no significant differences were found between the groups. In the brainstem group, contrary to the lacunar and the control groups, "any" muscle activity index during rapid eye movement sleep was significantly reduced after the third rapid eye movement sleep phase. This study reports on the impact of brainstem stroke on rapid eye movement atonia features in a human cohort. Our findings highlight the important role of the human brainstem, in particular the medioventral pontine regions, in the regulation of phasic muscle activity during rapid eye movement sleep and the ultradian distribution of rapid eye movement-related muscle activity.

Meningitis, meningoencephalitis and encephalitis in Bern: an observational study of 258 patients

Background

Depending on geographic location, causes of encephalitis, meningoencephalitis and meningitis vary substantially. We aimed to identify the most frequent causes, clinical presentation and long-term outcome of encephalitis, meningoencephalitis and meningitis cases treated in the Inselspital University Hospital Bern, Switzerland.

Methods

In this monocentric, observational study, we performed a retrospective review of clinical patient records for all patients treated within a 3-year period. Patients were contacted for a telephone follow-up interview and to fill out questionnaires, especially related to disturbances of sleep and wakefulness.

Results

We included 258 patients with the following conditions: encephalitis (18%), nonbacterial meningoencephalitis (42%), nonbacterial meningitis (27%) and bacterial meningoencephalitis/meningitis (13%). Herpes simplex virus (HSV) was the most common cause of encephalitis (18%); tick-borne encephalitis virus (TBEV) was the most common cause of nonbacterial meningoencephalitis (46%), enterovirus was the most common cause of nonbacterial meningitis (21%) and Streptococcus pneumoniae was the most common cause of bacterial meningoencephalitis/meningitis (49%). Overall, 35% patients remained without a known cause. After a median time of 16 months, 162 patients participated in the follow-up interview; 56% reported suffering from neurological long-term sequelae such as fatigue and/or excessive daytime sleepiness (34%), cognitive impairment and memory deficits (22%), headache (14%) and epileptic seizures (11%).

Conclusions

In the Bern region, Switzerland, TBEV was the overall most frequently detected infectious cause, with a clinical manifestation of meningoencephalitis in the majority of cases. Long-term neurological sequelae, most importantly cognitive impairment, fatigue and headache, were frequently self-reported not only in encephalitis and meningoencephalitis survivors but also in viral meningitis survivors up to 40 months after acute infection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02502-3.

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.

Recognizing the Symptom Spectrum of Narcolepsy to Improve Timely Diagnosis: A Narrative Review

Narcolepsy is a chronic sleep disorder with a strong negative impact on quality of life, especially when untreated. Diagnostic delay is a persistent problem, with obvious detrimental effects on patients. A diagnosis of narcolepsy may be delayed because of its broad symptom presentation which is much more encompassing than the classical "tetrad" of sleepiness, cataplexy, hallucinations, and sleep paralysis. Furthermore, symptoms can vary over time. Presentation of symptoms can also be markedly different between children and adults. Finally, common sleep-related comorbidities increase the risk of narcolepsy being masked by overlapping symptoms or treatment. In this review, we provide a detailed description of the broad and dynamic symptom spectrum of narcolepsy, with specific attention to the different manifestations in both adults and children. The overarching goal is to help not only sleep specialists, but general practitioners, pediatricians, and other caregivers with early recognition and prompt diagnosis of this severe but treatable disorder.

[Narcolepsy in adults: Definition, etiology and treatment]

Narcolepsy is a hypersomnolence disorder of central origin that presents with a disturbance of the wake-sleep regulation. Lead symptoms consist of excessive daytime sleepiness and cataplexy. Nowadays, two types of narcolepsy are distinguished. Type 1 narcolepsy, formerly known as narcolepsy with cataplexy, is based on hypocretin deficiency. The cause of type 2 narcolepsy, formerly known as narcolepsy without cataplexy, remains mainly unknown. A multimodal approach is necessary for diagnosis. The mean latency between the onset of disease and diagnosis in Europe ranges 14 years. Narcolepsy has a major impact on workability and quality of life. The management of narcolepsy is usually life-long and includes non-pharmacological approaches and a symptomatic pharmacological treatment.

Narcolepsy Severity Scale: a reliable tool assessing symptom severity and consequences

Study Objectives

To define clinically relevant Narcolepsy Severity Scale (NSS) score ranges, confirm its main performances and sensitivity to medications, and determine whether items need to be weighted.

Methods

One hundred and forty-three consecutive untreated and 238 treated adults with narcolepsy type 1 (NT1) completed the NSS, a 15-item self-administered questionnaire (score: 0–57) that assesses the severity and consequences of the five major narcolepsy symptoms such as daytime sleepiness, cataplexy, hallucinations, sleep paralysis, and disturbed nighttime sleep (DNS). They also completed the Epworth Sleepiness scale (ESS; daytime sleepiness), Beck Depression Inventory (BDI; depressive symptoms), and EQ5D (quality of life).

Results

The mean symptom number (4.3 vs 3.5), NSS total score (33.3 ± 9.4 vs 24.3 ± 10.2), and number of narcolepsy symptoms (five symptoms: 53.1% vs 24.8%; four symptoms: 26.6% vs 22.7%; three symptoms: 15.4% vs 32.4%; two symptoms: 4.9% vs 20.2%) were significantly different between untreated and treated patients (p &lt; 0.0001). DNS was often the third symptom (95.5 per cent). The symptom number was associated with diagnosis delay, age at onset, and ESS and BDI scores. Comparisons with ESS, BDI and EQ5D showed that NSS item weighting was not necessary to highlight between-group differences. Four NSS severity levels were defined (mild, moderate, severe, and very severe) with between-group differences related to treatment. The probability of having ESS ≥ 16, BDI ≥ 20, and EQ-5D &lt; 60 increased with the severity level.

Conclusion

NSS is valid, reliable, and responsive to treatment in patients with NT1, with four clinically relevant severity score ranges provided. NSS has adequate clinimetric properties for broadening its use for both clinic and research.