Relationship between the Pittsburgh Sleep Quality Index and the Epworth Sleepiness Scale in a sleep laboratory referral population
Bibliographic record
Abstract
Prosanta Mondal,1 John A Gjevre,2 Regina M Taylor-Gjevre,3 Hyun J Lim11Department of Community Health and Epidemiology, 2Division of Respiratory, Critical Care and Sleep Medicine, 3Department of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, CanadaBackground: Sleep health questionnaires are often employed as a first assessment step for sleep pathology. The Epworth Sleepiness Scale (ESS) and the Pittsburgh Sleep Quality Index (PSQI) are two commonly employed questionnaire instruments. Aspects of sleep health may be measured differently depending on choice of instrument.Objectives: In a patient population at high risk for sleep disorders, referred for polysomnography (PSG), we evaluated the level of association between results from these two instruments. Questionnaire results were also compared with measured PSG parameters.Methods: Records of patients undergoing overnight PSG in the sleep laboratory between February–June 2011 were retrospectively reviewed for eligibility. Inclusion criteria were met by 236 patients. PSQI and ESS scores, demographic information, and PSG data were extracted from each record for analysis. Four subgroups based on normal/abnormal values for ESS and PSQI were evaluated for between-group differences.Results: Of 236 adult participants, 72.5% were male, the mean age was 52.9 years (13.9), mean body mass index (BMI) 34.4 kg/m2 (8.3), mean ESS 9.0 (4.8; range: 0–22), PSQI mean 8.6 (4.2; range: 2–19). The Pearson correlation coefficient was r = 0.13 (P = 0.05) for association between ESS and PSQI. Participants with an abnormal ESS were more likely to have an abnormal PSQI score (odds ratio 1.9 [1.1–3.6]; P = 0.03). Those with an abnormal ESS had higher BMI (P = 0.008) and higher apnea–hypopnea indexes (AHI) (P = 0.05). Differences between the four subgroups were observed for BMI and sex proportions, but not for AHI.Conclusions: We observed limited association between these two commonly used questionnaire instruments, the ESS and the PSQI. These two questionnaires appear to evaluate different aspects of sleep. In terms of clinical application, for global assessment of patients with sleep problems, care should be taken to include instruments measuring different facets of sleep health.Keywords: Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, polysomnography, sleep disorders
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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 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".