The COVID Stones Collaborative: How has the Management of Ureteric Stones Changed During and After the COVID-19 Pandemic? Rationale and Study Protocol
Bibliographic record
Abstract
Background and objectives The coronavirus disease 2019 (COVID-19) pandemic is having a significant impact on healthcare delivery. As a result, management of patients with ureteric stones has likely been affected. We report our study protocol for the investigation of ureteric stone management during and after the COVID-19 pandemic. Material and methods The COVID Stones study is a multicenter national cohort study of the management and outcomes of patients with ureteric stones before, during, and after the COVID-19 pandemic in the United Kingdom. The study will consist of three data collection periods, pre-pandemic (“pre-COVID”), pandemic (“COVID”), and post-pandemic (“post-COVID”). This will allow quantification of what “normal” was, how this has changed, and to capture any persisting changes in management. The primary outcome evaluating the success rate of the initial treatment decision will be assessed following a 6-month follow-up from the time of first presentation and will be performed for each recruited patient from each of the three data collection periods. This will allow comparison between both management and outcomes before, during, and after the pandemic. Conclusions We anticipate that this study will lead to an increased understanding of the impact of the outcomes of emergency management of ureteric stones following changes in clinical practice due to the COVID-19 pandemic health provision restrictions.
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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 | 0.075 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.031 | 0.009 |
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".