STUDY OF PERSISTENT COVID CASES IN HEALTH WORKERS
Bibliographic record
Abstract
Introduction: The COVID-19 disease presents an acute affectation that can continue in a sustained manner beyond 12 weeks from the onset of the initial symptoms, being called Persistent COVID (Post COVID, Long COVID). Objective: Assess the incidence of Persistent Covid that the workers at the Sant Joan de Reus Hospital and Reus-Baix Camp Primary Care (EDPSSJRBC) have presented, during the period from March 2020 to November 2022, predominant clinical, work impact. Methods: Descriptive observational study of active workers on 9/30/2022, who after COVID-19 developed Persistent Covid during 2020 to 2022. Study by survey of workers with COVID-19 with Persistent Covid symptoms and subsequent in-person evaluation through questionnaires, health examinations and complementary tests. Final assessment of work capacity against Persistent Covid in the context of the Health Surveillance of the Occupational Risk Prevention Service. Results: The profile of the worker affected by Persistent Covid in our study is characterized by: female sex, over 40 years of age, care work profile, with predominant symptoms of sleep disorder, memory disorder, difficulty concentrating, changes in mental status, mood, arthralgia, fatigue and headache. They presented abnormal results in the tests: Post COVID-19 Functional Scale, Insomnia Severity Index and Montreal Cognitive Assessment Test.Conclusions: Clinical impact of Persistent Covid of the workers in our study who improved over time and after cognitive rehabilitation treatments in the Cognitive Impairment Unit and regular physical exercise prescribed by the Sports Medicine Unit. Persistent Covid did not prevent the development of their work activity
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".