A Randomized Trial of Aerobic Exercise and Sleep Quality in Lymphoma Patients Receiving Chemotherapy or No Treatments
Bibliographic record
Abstract
BACKGROUND: Patients with lymphoma experience sleep problems that may be managed with aerobic exercise but no previous study has examined this issue. METHODS: We randomized 122 patients with lymphoma to usual care (n = 62) or 12 weeks of supervised aerobic exercise training (AET; n = 60). Our primary sleep endpoint was global sleep quality assessed by the Pittsburgh Sleep Quality Index (PSQI). Secondary endpoints were the PSQI component scores. Planned subgroup analyses were also conducted. RESULTS: Intention-to-treat analyses indicated that AET resulted in a nonsignificant (P = 0.16) improvement in global sleep quality compared with usual care [mean group difference = -0.64; 95% confidence interval (CI), -1.56 to +0.27]. In planned subgroup analyses, statistically significant or borderline significant interactions were identified for type of lymphoma (P(interaction) = 0.006), current treatment status (P(interaction) = 0.036), time since diagnosis (P(interaction) = 0.010), body mass index (P(interaction) = 0.075), and baseline sleep quality (P(interaction) = 0.041). Specifically, AET improved global sleep quality in patients with lymphoma who had indolent non-Hodgkin lymphoma (P = 0.001), were receiving chemotherapy (P = 0.013), were <2 years post-diagnosis (P = 0.005), were obese (P = 0.025), and were poor sleepers at baseline (P = 0.007). CONCLUSIONS: AET did not significantly improve sleep quality in this heterogeneous sample of patients with lymphoma; however, clinically identifiable subgroups appeared to benefit. Future exercise trials targeting these responsive subgroups are needed to confirm these findings. IMPACT: If replicated in larger and more focused trials, aerobic exercise may be an attractive option to manage sleep dysfunction in patients with cancer because of its favorable safety profile and other documented health benefits.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 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".