Sleep symptoms are essential features of long‐<scp>COVID</scp>– Comparing healthy controls with<scp>COVID</scp>‐19 cases of different severity in the international<scp>COVID</scp>sleep study (<scp>ICOSS‐II</scp>)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many people report suffering from post-acute sequelae of COVID-19 or "long-COVID", but there are still open questions on what actually constitutes long-COVID and how prevalent it is. The current definition of post-acute sequelae of COVID-19 is based on voting using the Delphi-method by the WHO post-COVID-19 working group. It emphasizes long-lasting fatigue, shortness of breath and cognitive dysfunction as the core symptoms of post-acute sequelae of COVID-19. In this international survey study consisting of 13,628 subjects aged 18-99 years from 16 countries of Asia, Europe, North America and South America (May-Dec 2021), we show that post-acute sequelae of COVID-19 symptoms were more prevalent amongst the more severe COVID-19 cases, i.e. those requiring hospitalisation for COVID-19. We also found that long-lasting sleep symptoms are at the core of post-acute sequelae of COVID-19 and associate with the COVID-19 severity when COVID-19 cases are compared with COVID-negative cases. Specifically, fatigue (61.3%), insomnia symptoms (49.6%) and excessive daytime sleepiness (35.8%) were highly prevalent amongst respondents reporting long-lasting symptoms after hospitalisation for COVID-19. Understanding the importance of sleep-related symptoms in post-acute sequelae of COVID-19 has a clinical relevance when diagnosing and treating long-COVID.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.001 | 0.007 |
| 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 it