Post-COVID-19 syndrome among healthcare workers in Jordan
Why this work is in the frame
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Bibliographic record
Abstract
Background: Post-COVID-19 syndrome covers a wide range of new, recurring or ongoing health conditions, which can occur in anyone who has recovered from COVID-19. The condition may affect multiple systems and organs. Aims: To evaluate the frequency and nature of persistent COVID-19 symptoms among healthcare providers in Jordan. Methods: Post-COVID-19 syndrome refers to symptoms extending beyond 4-12 weeks. We conducted a historical cohort study among 140 healthcare staff employed at the National Center for Diabetes, Endocrinology and Genetics, Amman, Jordan. All of them had been infected with COVID-19 virus during March 2020 to February 2022. Data were collected through face-to-face interviews using a structured questionnaire. Results: Some 59.3% of the study population reported more than 1 persisting COVID-19 symptom, and among them 97.5%, 62.6% and 40.9% reported more than 1 COVID-19 symptom at 1-3, 3-6 and 6-12 months, respectively, after the acute phase of the infection. Post-COVID-19 syndrome was more prevalent among females than males (79.5% vs 20.5%) (P = 0.006). The most frequent reported symptom was fatigue. Females scored higher on the Fatigue Assessment Scale than males [23.26, standard deviation (SD) 8.00 vs 17.53, SD 5.40] (P < 0.001). No significant cognitive impairment was detected using the Mini-Mental State Examination and the Montreal Cognitive Assessment scales. Conclusion: More than half (59.3%) of the healthcare workers in our study reported post-COVID-19 syndrome. Further studies are needed to better understand the frequency and severity of the syndrome among different population groups.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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