Dream Activity in Narcoleptic Patients During the COVID-19 Lockdown in Italy

Some studies highlighted that patients with narcolepsy type-1 (NT1) experience high lucid dream frequency, and this phenomenon has been associated with a creative personality. Starting from the well-known “pandemic effect” on sleep and dreaming, we presented a picture of dream activity in pharmacologically treated NT1 patients during the Italian lockdown. Forty-three NT1 patients completed a web-survey during Spring 2021 and were compared with 86 matched-controls. Statistical comparisons revealed that: (a) NT1 patients showed greater sleepiness than controls; (b) controls showed higher sleep disturbances than NT1 patients, and this result disappeared when the medication effect in NT1 was controlled; (c) NT1 patients reported higher lucid dream frequency than controls. Focusing on dreaming in NT1 patients, we found that (a) nightmare frequency was correlated with female gender, longer sleep duration, higher intrasleep wakefulness; (b) dream recall, nightmare and lucid dream frequency were positively correlated with sleepiness. Comparisons between low and high NT1 lucid dreamers showed that patients more frequently experiencing lucid dreams reported a greater influence of dreaming during wakefulness, especially concerning problem-solving and creativity. Overall, our results are consistent with previous studies on pandemic dreaming carried out on healthy subjects. Moreover, we confirmed a link between lucidity and creativity in NT1 patients. Considering the small sample size and the cross-sectional design, our findings cannot provide a causal relationship between lucid dreams and the COVID-19 lockdown. Nevertheless, they represent a first contribution to address future studies on this issue, suggesting that some stable characteristics could interact with changes provoked by the pandemic.

823 Apparent seizure activity in a 9 year old female presenting as hypnopompic hallucinations

Introduction The presence of hypnopompic hallucinations raises concerns for narcolepsy. However, sleep-related hallucinations may occur in other settings. Dreams at sleep-wake transitions may be difficult for patients to differentiate from sleep-related hallucinations. Sleep-related hallucinations are predominantly visual, although they can be auditory, tactile and/or kinetic. However, they are generally not olfactory in nature. Report of case(s) Here we present a case of a 9-year-old female with a history of tonsillectomy and adenoidectomy, ADHD, ODD, nocturnal enuresis, nocturia, aggressive behaviors and emotional outbursts who presented with EDS, frequent nocturnal awakenings, involuntary dozing, prolonged naps and a one year duration of hypnopompic hallucinations. Initially, the hallucinations occurred 2–3 times per week, but then decreased in frequency to 2–3 times per month. The frequency of episodes apparently decreased after tonsillectomy. She states that she wakes up and sees dots, and “she looks scary” when she looks at herself. She describes a variety of hallucinations including: seeing dots (including her mother being covered in dots), a cupcake, a strange woman walking, her hands looking strange--they had enlarged or hearing noises (a single loud bang). Pertinent physical exam findings included: BMI 66th percentile, Mallampati score 2/4, and a mildly enlarged tongue. The polysomnogram demonstrated mild obstructive sleep apnea by pediatric criteria, and, most notably, demonstrated an EEG with spike and wave formations in the central and frontal leads bilaterally. These were seen during NREM sleep and most prominently during sleep-wake transitions. There was also a more focal brief run of a regular 2 Hz rhythm in the central and frontal leads bilaterally. A referral was placed to Pediatric Neurology who ordered a full EEG which is pending at this time. Conclusion Sleep-related hallucinations may occur in narcolepsy, other sleep disorders, a mental disorder, a medical disorder, a medication effect or secondary to substance use. This case suggests that seizure activity may present as hypnopompic hallucinations as well. Support (if any):

0484 How Much Improvement in Subject-Reported Sleep Onset Latency is Needed for Patients to Report a Positive Impact of Their Insomnia Medication?

Introduction How much improvement would be considered meaningful from the patient perspective is not well defined. In SUNRISE-2 (NCT02952820; E2006-G000-303), using the Patient Global Impression-Insomnia version (PGI-I), subjects rated how treatment impacted subjective (sleep diary-based) sleep onset latency (sSOL; Question2; positive, neutral, and negative) relative to before starting treatment. Meaningful change can thus be determined based on the change from baseline (CFB) in subjects with a positive score. Methods SUNRISE-2 (n=949, full analysis set) was a Phase 3, 12-month, double-blind, global study in subjects age ≥18y with insomnia disorder. Subjects received PBO (N=318), LEM 5mg (LEM5, N=316) or LEM 10mg (LEM10, N=315) for 6 months. At the end of Month 6, PBO subjects were rerandomized to LEM5 or LEM10; LEM5 and LEM10 subjects continued at the same dose for 6 more months. The ranges of median CFB in sSOL (minutes) at 6 months were examined in response to PGI-I Item 2. Results At 6 months, subjects reporting positive medication effect (PBO, n=110; LEM5, n=178; LEM10, n=159) showed median CFB in sSOL from -17.5 to -32.1 minutes across treatment groups. In subjects reporting neutral effect (PBO, n=49; LEM5, n=28; LEM10, n=27), median CFB in sSOL ranged from -10.4 to -25.6 minutes across treatment groups. In subjects reporting negative medication effect (PBO, n=82; LEM5, n=34; LEM10, n=32), median CFB in sSOL ranged from -8.6 to -10.4 minutes across treatment groups. The PBO group provided the smallest numbers for each response category range. Conclusion Subjects reporting positive medication effect on PGI-I Item 2, i.e. decreased time to fall asleep, had corresponding changes from baseline in sSOL ranging from -17.5 to -32.1 minutes. Thus, this range may represent a clinically meaningful improvement as perceived by patient-subjects, and may be useful to clinicians in determining whether a treatment regimen is working for their patients. Support Eisai Inc.

Clinical associations of an updated medication effect score for measuring diabetes treatment intensity

Objectives The medication effect score reflects overall intensity of a diabetes regimen by consolidating dosage and potency of agents used. Little is understood regarding how medication intensity relates to clinical factors. We updated the medication effect score to account for newer agents and explored associations between medication effect score and patient-level clinical factors. Methods Cross-sectional analysis of baseline data from a randomized controlled trial involving 263 Veterans with type 2 diabetes and hemoglobin A1c levels ≥8.0% (≥7.5% if under age 50). Medication effect score was calculated for all patients at baseline, alongside additional measures including demographics, comorbid illnesses, hemoglobin A1c, and self-reported psychosocial factors. We used multivariable regression to explore associations between baseline medication effect score and patient-level clinical factors. Results Our sample had a mean age of 60.7 ( SD = 8.2) years, was 89.4% male, and 57.4% non-White. Older age and younger onset of diabetes were associated with a higher medication effect score, as was higher body mass index. Higher medication effect score was significantly associated with medication nonadherence, although not with hemoglobin A1c, self-reported hypoglycemia, diabetes-related distress, or depression. Discussion We observed several expected associations between an updated medication effect score and patient-level clinical factors. These associations support the medication effect score as an appropriate measure of diabetes regimen intensity in clinical and research contexts.