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Purpose <p>Narcolepsy type 1 (NT1) and insufficient sleep syndrome (ISS) both present with excessive daytime sleepiness (EDS) and may fulfill the diagnostic criteria on the multiple sleep latency test (MSLT); therefore, differential diagnosis is often difficult. This study examined whether sleep spindle (SS) indices obtained from overnight polysomnography (PSG) performed before the MSLT are useful for distinguishing NT1 from ISS with false-positive MSLT findings.</p> Methods <p>We retrospectively analyzed 23 patients aged 10–30 years (14 with NT1 and 9 with ISS) who underwent PSG and MSLT at Kurume University Hospital between January 2015 and December 2023. Diagnoses were established according to the International Classification of Sleep Disorders, 3rd Edition. SS density, duration, and amplitude were quantified from C3/C4 derivations using (1) visual scoring and (2) automated detection. Group comparisons were performed using the Mann–Whitney U test. Receiver operating characteristic (ROC) analysis was used to evaluate discriminatory performance for variables showing significant between-group differences.</p> Results <p>Visual scoring showed no significant between-group differences in SS indices. Automated detection identified significant between-group differences in two fast SS indices derived from C3: duration during stage N2 and density during non-rapid eye movement sleep. No significant differences were found in C4 or in slow or unclassified SS. ROC analysis of C3 fast SS duration during stage N2 showed moderate discriminatory performance, with an area under the curve of 0.754. At the optimal cutoff value of 996.77 ms, sensitivity was 85.7% and specificity was 66.7%.</p> Conclusions <p>Automated SS quantification identified between-group differences that were not apparent on visual scoring. This may reflect inclusion, by automated detection, of sigma-rich electroencephalographic activity not captured as SS by visual scoring. Quantitative evaluation of SS by automated detection from a single-night PSG may complement the MSLT and help distinguish NT1 from ISS in patients with EDS and false-positive MSLT findings.</p>

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A retrospective exploratory study of sleep spindles as an adjunctive diagnostic marker for narcolepsy type 1: a comparison with insufficient sleep syndrome

  • 期刊论文

  • 发表日期：

    2026年5月4日

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  • Yuuki Hyodo,
  • Hiroshi Hiejima,
  • Takao Kato,
  • Satoshi Mizuki,
  • Minoru Takii,
  • Haruka Yokoyama,
  • Yuuki Fujii,
  • Touma Koura,
  • Nozomu Kotorii,
  • Mitsunari Habukawa,
  • Naohisa Uchimura,
  • Motohiro Ozone

摘要

Purpose

Narcolepsy type 1 (NT1) and insufficient sleep syndrome (ISS) both present with excessive daytime sleepiness (EDS) and may fulfill the diagnostic criteria on the multiple sleep latency test (MSLT); therefore, differential diagnosis is often difficult. This study examined whether sleep spindle (SS) indices obtained from overnight polysomnography (PSG) performed before the MSLT are useful for distinguishing NT1 from ISS with false-positive MSLT findings.

Methods

We retrospectively analyzed 23 patients aged 10–30 years (14 with NT1 and 9 with ISS) who underwent PSG and MSLT at Kurume University Hospital between January 2015 and December 2023. Diagnoses were established according to the International Classification of Sleep Disorders, 3rd Edition. SS density, duration, and amplitude were quantified from C3/C4 derivations using (1) visual scoring and (2) automated detection. Group comparisons were performed using the Mann–Whitney U test. Receiver operating characteristic (ROC) analysis was used to evaluate discriminatory performance for variables showing significant between-group differences.

Results

Visual scoring showed no significant between-group differences in SS indices. Automated detection identified significant between-group differences in two fast SS indices derived from C3: duration during stage N2 and density during non-rapid eye movement sleep. No significant differences were found in C4 or in slow or unclassified SS. ROC analysis of C3 fast SS duration during stage N2 showed moderate discriminatory performance, with an area under the curve of 0.754. At the optimal cutoff value of 996.77 ms, sensitivity was 85.7% and specificity was 66.7%.

Conclusions

Automated SS quantification identified between-group differences that were not apparent on visual scoring. This may reflect inclusion, by automated detection, of sigma-rich electroencephalographic activity not captured as SS by visual scoring. Quantitative evaluation of SS by automated detection from a single-night PSG may complement the MSLT and help distinguish NT1 from ISS in patients with EDS and false-positive MSLT findings.