Insomnia, immunity, and infections in cancer patients: Results from a longitudinal study.
Bibliographic record
Abstract
BACKGROUND: Insomnia is very common in cancer patients receiving chemotherapy. Poor sleep is associated with immune alterations but the actual impact on health resulting from such immune changes has rarely been studied. The aim of this study was to evaluate, in women treated with chemotherapy for breast or gynecological cancer, the relationships between insomnia, immunity, and the occurrence of infections. METHOD: Fifty-two patients were assessed before chemotherapy (Time [T]1), on 4 occasions during the first 2 cycles of chemotherapy (i.e., on immunosuppression and recovery weeks; T2-T5), at posttreatment (T6), and at 3-month (T7) and 6-month (T8) follow-ups. A clinical interview was administered to assess insomnia (Insomnia Interview Schedule) and the occurrence of infections. Patients were categorized into 1 of these 3 subgroups on the basis of the insomnia interview at T1: good sleepers (GS), insomnia symptoms (SX), and insomnia syndrome (SYN). Finally, blood samples were collected at each time point (T1-T8) to measure several immune parameters (e.g., neutrophils, lymphocytes). RESULTS: Mixed-model analyses of covariance revealed that SYN patients at T1 had significantly lower counts of some blood cells after chemotherapy (T6) as compared to GS (i.e., total white blood cells and neutrophils) and as compared to GS and SX patients (i.e., total lymphocytes, CD3+ and CD4+ cells). At T8, SYN patients at T1 showed significantly lower lymphocytes, CD3+ and CD4+ counts as compared to SX patients. Finally, SYN patients at T1 were at a significantly higher risk of reporting infectious episodes at T5 as compared to SX patients. CONCLUSIONS: Although replication is warranted, these results suggest that prechemotherapy insomnia may potentiate the vulnerability to show immune alterations and develop infections due to chemotherapy during the cancer care trajectory. Overall, they further emphasize the need to provide effective treatments for sleep difficulties in patients undergoing chemotherapy. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".