Frequency and characteristics of cancer-related drowsiness (CRD or excessive daytime sleepiness) in patients with advanced cancer: Results of a prospective survey at a tertiary cancer center.
Bibliographic record
Abstract
131 Background: CRD is extremely distressing but treatable symptom to the advanced cancer patients (ACP). There are limited studies to evaluate the frequency and characteristics of CRD. The aim of this study was to identify the frequency, and factors associated with severity of CRD. Secondary aim was to determine the screening performance Edmonton Symptom Assessment Scale (ESAS)-drowsiness item against the Epworth Sleepiness Scale (ESS). Methods: We prospectively assessed 180 consecutive ACP at a tertiary cancer hospital. After obtaining signed consent, the patients completed ESAS, Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI); ESS (≥10 diagnostic of CRD), Hospital Anxiety Depression Scale (HADS), STOP-Bang Screening Scale (SBS), and Screening tool for RLS. We determined epidemiological performance, spearman correlations, regression analysis, receiver operated characteristics of CRD. Results: Of the180 patients assessed, 51% were female, CRD was found in 50% ACP, median scores(IQR) ESS: 11(7-14); ESAS- drowsiness item was 5 (2-6); PSQI was 8(5-11); ISI (13 (5-19); SBS 3(2-4); HADS-D 6(3-10). Sleep apnea was found in 61%; and RLS in 38%. ESAS-D was associated with other ESAS items[r, p-value] Sleep (0.38, < 0.0001); pain (0.3, < 0.0001); fatigue(0.51, < 0.0001); depression(0.39, < 0.0001); anxiety(0.44, < 0.0001); shortness of breath(0.32, < 0.0001); anorexia(0.36, < 0.0001), FWB(0.41, < 0.0001), and ESS (0.24, 0.001), Opioid dose [MEDD] (0.19, 0.01). Multivariate analysis found no independent predictors except ISI (OR 2.35; 0.036), ESAS Fatigue (OR 9.08, <0.0001), ESAS Anxiety (3.0, 0.009); feeling of well-being (OR 2.27, p=0.04). An ESAS- drowsiness cut-off score of ≥ 3(of 10) resulted in a sensitivity and specificity of 81% and 32% and of 70% and 44% in the training and validation samples, respectively. Conclusions: Clinically significant CRD was associated with increased fatigue, anxiety, sleep disturbance and worse feeling of well-being. These symptoms should be routinely assessed and treated in ACP with CRD. ESAS-drowsiness score of ≥3 of 10 is most useful for screening CRD.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".