Bidirectional relationship between sleep problems and long COVID: a longitudinal analysis of data from the COVIDENCE UK study
Bibliographic record
Abstract
BACKGROUND: Studies into the bidirectional relationship between sleep and long COVID have been limited by retrospective pre-infection sleep data and infrequent post-infection follow-up. We therefore used prospectively collected monthly data to evaluate how pre-infection sleep characteristics affect risk of long COVID and to track changes in sleep duration during the year after SARS-CoV-2 infection. METHODS: COVIDENCE UK is a prospective, population-based UK study of COVID-19 in adults. We included non-hospitalised participants with evidence of SARS-CoV-2 infection and used logistic regression to estimate adjusted ORs for the association between preinfection sleep characteristics and long COVID. We assessed post-infection sleep duration using multilevel mixed models. We collected sleep data from participants using a subset of questions from the Pittsburgh Sleep Quality Index. We defined long COVID as unresolved symptoms at least 12 weeks after infection. COVIDENCE UK is registered with ClinicalTrials.gov, NCT04330599. RESULTS: We included 3994 participants in our long COVID risk analysis, of whom 327 (8.2%) reported long COVID. We found an inverse relationship between pre-infection sleep quality and risk of long COVID (medium vs good quality: OR 1.37, 95% CI 1.04 to 1.81; medium-low vs good: 1.55, 1.12 to 2.16; low vs good: 1.94, 1.11 to 3.38). Greater variability in pre-infection sleep efficiency was also associated with long COVID when adjusted for infection severity (OR per percentage-point increase 1.07, 1.02 to 1.12). We assessed post-infection sleep duration in 6860 participants, observing a 0.11 hour (95% CI 0.09 to 0.14) increase in the first month after infection compared with pre-infection, with larger increases for more severe infections. After 1 month, sleep duration largely returned to pre-infection levels, although fluctuations in duration lasted up to 6 months after infection among people reporting long COVID. CONCLUSIONS: While poor-quality sleep before SARS-CoV-2 infection associates with increased risk of long COVID thereafter, changes in sleep duration after infection in these non-hospitalised cases were modest and generally quick to resolve. TRIAL REGISTRATION NUMBER: NCT04330599.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
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 | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".