Bibliographic record
Abstract
Objective: The prevalence of kidney stones in children is increasing.Consequently, the need to intervene surgically is also.However, clear indications for surgical intervention in pediatric nephrolithiasis are lacking.As a result, management of stones is currently based on patient preference and subjective assessment of whether it is feasible surgically to perform stone removal.We therefore set out to identify patient and stone characteristics that predict the necessity for surgery.Methods: A retrospective analysis of 63 pediatric renal stone patients presenting to the University of Alberta Hospital from 1990 to 2013 was performed.These 63 patients presented with a total of 143 stones.Univariate and multivariate analysis are being conducted to assess for patient and stone characteristics requiring surgical intervention.Results: Thus far, we have found that presentation with multiple bilateral stones is more common in individuals requiring surgery.Furthermore, the presence of a high creatinine and hypocitrituria were associated with surgical intervention.Conversely, surgery was less often performed in patients presenting with hypercalcemia and increased 1,25(OH) 2 D 3 .Stone characteristics associated with surgical intervention included large stone size, growth in stone size over time, movement in location, being present in the ureter and being composed of calcium oxalate.Conversely, small stones, composed of calcium phosphate, were more likely to pass without surgical intervention.Conclusion: Our study provides some individual and stone characteristics associated with surgical intervention.Hopefully, these observations can contribute to the establishment of guidelines for when a stone should be monitored and allowed to pass, as opposed to when a stone should be surgically removed before it requires emergency care.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.308 | 0.107 |
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".