Effects of first year COVID-19 pandemic on urology practice in three major Arab Countries: Sub-Analysis of a survey by Arab association of urology research group
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The World Health Organization (WHO) declared the coronavirus disease-19 (COVID-19) pandemic on March 11, 2020. The health care system faced tremendous challenges in providing ethical and high-quality care. The impact of COVID-19 on urological practices varied widely worldwide, including in Arab countries. This study aimed to compare the influence of the COVID-19 pandemic on urology practice in Egypt, the KSA, and the UAE during the first year of the pandemic. METHODS: This sub-analysis assessed the demographics and COVID-19's effects on urological practice in terms of adjustments to hospital policy, including outpatient consultations, the management of elective and urgent surgical cases, and the continuation of education across the three countries. The availability of personal protective equipment (PPE) and urologists' emotional, physical, and verbal intimidation during COVID-19 were also compared. RESULTS: Regarding the impact on hospital policy, consultations replaced by telemedicine were significantly higher in the KSA (36.15%), followed by the UAE (33.3%), then Egypt (10.4%) (P = 0.008). Elective cases requiring ICU admission were 65.1% in Egypt, 45.2% in the KSA, and 58.2% in the UAE and were performed only in high-risk patients. PPE was freely available in 20.8% of the Egyptian hospitals compared to 83.3% in the KSA and 81.8% in the UAE. Online courses were significantly higher in Egypt (70.8%), followed by the UAE (53%) and the KSA (41.7%) (P = 0.02). Emotional intimidation was higher than verbal intimidation, representing 80%, 75.9%, and 76% in the UAE, KSA, and Egypt, respectively. CONCLUSION: This sub-analysis outlined significant hospital policy changes across the three Arab countries. Exposure to emotional, verbal, and physical intimidation was observed. The development of teleconsultations and online platforms for educational purposes was observed.
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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 | 0.002 |
| 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".