Changes in self-reported hot flashes and their association with concurrent changes in insomnia symptoms among women with breast cancer
Bibliographic record
Abstract
In Brief Objective: The aim of this study was to assess longitudinally the relationship between hot flashes and insomnia symptoms in women receiving adjuvant treatments for breast cancer. Methods: Fifty-eight participants completed a 7-day daily diary assessing hot flashes, the Menopause-Specific Quality of Life Questionnaire, and the Insomnia Severity Index, before and after chemotherapy or radiotherapy and at a 3-month follow-up evaluation. Results: A first canonical correlation analysis (n = 55) revealed a marginally significant relationship between pretreatment versus posttreatment change scores in hot flashes and sleep (R = 0.39), and a second analysis (n = 51) showed a significant relationship between posttreatment and follow-up changes in hot flash activity and sleep (R = 0.59). Conclusions: These results show that increases in vasomotor symptoms occurring within the few months after the termination of initial adjuvant treatments for breast cancer are significantly associated with concurrent increases in insomnia symptoms and vice versa. Increases in hot flash severity and bother occurring within the few months following the termination of initial adjuvant treatments for breast cancer were significantly associated with concurrent increases in insomnia symptoms and vice versa. These relationships were not significant at posttreatment but were in the same direction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".