Burnout in Stroke Patients Pre-and Post-COVID-19 Pandemic
Bibliographic record
Abstract
Background: Since the first appearance of COVID-19 numerous complications have been reported particularly within 1.48% of the population suffering from stroke. Maintaining positive mental health is crucial to modulate COVID-19 impacts involving burnout, depression, and anxiety. Objective: The aim of the current study was to investigate the consequences of the COVID-19 pandemic in Egypt on the level of burnout in stroke cases. Patients and methods: A total of 100 Egyptian stroke male and female cases participated in the study. Participants aged between 34 and 70 years old and their cognition score was >26 according to Montreal Cognitive Assessment (MOCA) scale. The Malach-Pines tool was used to measure burnout. Results: The mean scores of all items of the burnout scale increased significantly post COVID-19 in comparison with that of pre COVID-19 (P<0.001). The highest score was for “I've had it” with a mean score of 4.17 (SD 1.08) pre COVID-19, which increased significantly post COVID-19 to 5.98 (SD 0.97). The score of “I've had it” also increased significantly post COVID-19 in both age classes, duration of illness classes, and in females and males (P<0.001), also increase significantly post COVID-19 compared with that pre COVID-19 in subjects with high, medium, and low educational levels (P<0.001). Conclusion: Lockdown procedures related to the COVID-19 pandemic had a major impact on stroke cases whose post COVID-19 burnout levels had increased and led to worse management outcomes.
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How this classification was reachedexpand
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".