Long Covid autonomic syndrome and his impact on workability: results of observational prospective study and 1-year FU in patients admitted to hospital with COVID19
Bibliographic record
Abstract
Abstract Long-COVID19 has been recently associated with long-sick leave and unemployment. We will present recent data obtained by a prospective observational study conducted during the 2nd wave of the pandemic in Italy to assess the time course of Long-COVID19 autonomic syndrome in working age population and its impact on patient’s work ability. The patients were consecutively enrolled at the time of their hospital discharge and were followed-up for 1 year. Clinical data and work ability have been collected at 1, 6, and 12 months after hospital discharge in our out-patient clinic. Data on Long-COVID19 autonomic syndrome occurrence in working-age and the effects on work ability will be presented and discussed. Long-COVID19 autonomic syndrome occurred in one in three working-age people and was still evident 6 and 12 months after the acute infection resolution. This was associated with a significant reduction in the work ability. Timely recognition of long-COVID19 autonomic syndrome and its potential impact on work ability represents important steps in the prevention of long-term disabilities among active working adults.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".