The Relationship Between Cognitive Impairments and Sleep Quality Measures in Persistent Insomnia Disorder
Bibliographic record
Abstract
Erika CS Künstler,1,2 Peter Bublak,1 Kathrin Finke,1 Nicolas Koranyi,1 Marie Meinhard,1 Matthias Schwab,1,2 Sven Rupprecht1,2 1Department of Neurology, Jena University Hospital, Jena, Germany; 2Interdisciplinary Centre for Sleep and Ventilatory Medicine, Jena University Hospital, Jena, GermanyCorrespondence: Erika CS Künstler, Department of Neurology, Jena University Hospital, Am Klinikum 1, Jena, 07747, Germany, Tel +49 3641 9323525, Email Erika.Kuenstler@med.uni-jena.deStudy Objectives: Persistent insomnia disorder (pID) is linked to neurocognitive decline and increased risk of Alzheimer’s Disease (AD) in later life. However, research in this field often utilizes self-reported sleep quality data - which may be biased by sleep misperception - or uses extensive neurocognitive test batteries - which are often not feasible in clinical settings. This study therefore aims to assess whether a simple screening tool could uncover a specific pattern of cognitive changes in pID patients, and whether these relate to objective aspect(s) of sleep quality.Methods: Neurocognitive performance (Montreal Cognitive Assessment; MoCA), anxiety/depression severity, and subjective sleep quality (Pittsburgh Sleep Quality Index: PSQI; Insomnia Severity Index: ISI) data were collected from 22 middle-aged pID patients and 22 good-sleepers. Patients underwent overnight polysomnography.Results: Compared to good-sleepers, patients had lower overall cognitive performance (average: 24.6 versus 26.3 points, Mann–Whitney U = 136.5, p = < 0.006), with deficits in clock drawing and verbal abstraction. In patients, poorer overall cognitive performance correlated with reduced subjective sleep quality (PSQI: r(42) = − 0.47, p = 0.001; and ISI: r(42) = − 0.43, p = 0.004), reduced objective sleep quality (lower sleep efficiency: r(20) = 0.59, p = 0.004 and less REM-sleep: r(20) = 0.52, p = 0.013; and increased sleep latency: r(20) = − 0.57, p = 0.005 and time awake: r(20) = − 0.59, p = 0.004). Cognitive performance was not related to anxiety/depression scores.Conclusion: Using a simple neurocognitive screening tool, we found that pID patients showed cognitive deficiencies that related to both subjective/self-reported and objective/polysomnographic measures of sleep quality. Furthermore, these cognitive changes resembled those seen in preclinical non-amnestic AD, and thus could indicate incumbent neurodegenerative processes in pID. Interestingly, increased REM-sleep was correlated with better cognitive performance. However, whether REM-sleep is protective against neurodegeneration requires further investigation.Keywords: insomnia, sleep, neurodegeneration, Alzheimer’s disease, polysomnography, cognitive screening
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".