MétaCan
Menu
Back to cohort
Record W1500585454 · doi:10.1371/journal.pone.0128139

Depressive Symptoms are the Main Predictor for Subjective Sleep Quality in Patients with Mild Cognitive Impairment—A Controlled Study

2015· article· en· W1500585454 on OpenAlexaboutno aff
Stefan Seidel, Peter Dal‐Bianco, Eleonore Pablik, Nina Müller, Claudia Schadenhofer, Claus Lamm, Gerhard Klösch, Doris Moser, Stefanie J. Klug, Gisela Pußwald, Eduard Auff, Johann Lehrner

Bibliographic record

VenuePLoS ONE · 2015
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
Fundersnot available
KeywordsPittsburgh Sleep Quality IndexEpworth Sleepiness ScaleMedicineInternal medicineMontreal Cognitive AssessmentBeck Depression InventoryNeuropsychologyDepression (economics)Effects of sleep deprivation on cognitive performancePhysical therapyCognitionSleep qualityCognitive impairmentPsychiatryPolysomnographyDiseaseAnxiety

Abstract

fetched live from OpenAlex

OBJECTIVE: Controlled data on predictors of subjective sleep quality in patients with memory complaints are sparse. To improve the amount of comprehensive data on this topic, we assessed factors associated with subjective sleep quality in patients from our memory clinic and healthy individuals. METHODS: Between February 2012 and August 2014 patients with mild cognitive impairment (MCI) and subjective cognitive decline (SCD) from our memory clinic and healthy controls were recruited. Apart from a detailed neuropsychological assessment, the subjective sleep quality, daytime sleepiness and depressive symptoms were assessed using the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS) and the Beck Depression Inventory (BDI-II). RESULTS: One hundred fifty eight consecutive patients (132 (84%) MCI patients and 26 (16%) SCD patients) and 75 healthy controls were included in the study. Pairwise comparison of PSQI scores showed that non-amnestic MCI (naMCI) patients (5.4 ± 3.5) had significantly higher PSQI scores than controls (4.3 ± 2.8, p = .003) Pairwise comparison of PSQI subscores showed that naMCI patients (1.1 ± 0.4) had significantly more "sleep disturbances" than controls (0.9 ± 0.5, p = .003). Amnestic MCI (aMCI) (0.8 ± 1.2, p = .006) and naMCI patients (0.7 ± 1.2, p = .002) used "sleep medication" significantly more often than controls (0.1 ± 0.6) Both, aMCI (11.5 ± 8.6, p < .001) and naMCI (11.5 ± 8.6, p < .001) patients showed significantly higher BDI-II scores than healthy controls (6.1 ± 5.3). Linear regression analysis showed that the subjective sleep quality was predicted by depressive symptoms in aMCI (p < .0001) and naMCI (p < .0001) patients as well as controls (p < .0001). This means, that more depressive symptoms worsened subjective sleep quality. In aMCI patients we also found a significant interaction between depressive symptoms and global cognitive function (p = .002). DISCUSSION: Depressive symptoms were the main predictor of subjective sleep quality in MCI patients and controls, but not in SCD patients. Better global cognitive function ameliorated the negative effect of depressive symptoms on the subjective sleep quality in aMCI patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.032
GPT teacher head0.285
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2015
Admission routes1
Has abstractyes

Explore more

Same venuePLoS ONESame topicSleep and related disordersFrench-language works237,207