The Importance of Stone Retrieval in the Modern Management of Urolithiasis
Bibliographic record
Abstract
Background and Objectives World urolithiasis is increasing with a 70% increase in hospital admissions between 2000 and 2015. Stone analysis can allow for the identification of metabolic conditions and stone retrieval may decrease the need for follow-up imaging, reducing costs and patient radiation. This study aimed to see if introducing the UroPro © Stone catcher into our practise would increase stone retrieval thus increasing stone analysis rates and reducing the need for follow-up imaging. Methods Between November 2018 and July 2019 patients receiving ESWL or being conservatively managed for a ureteric stone were discharged with a Paramount Medical solutions UroPro © Stone Catcher. Both groups of patients were asked to complete a patient survey regarding the product. Results There were 27 patients recruited. 14 from SWL and 13 from acute admissions. 22 responses were received in total: 10 from acute admissions and 12 from ESWL. 5 patients were uncontactable. 30% (n=3) of the acute patients passed and caught a stone negating the need for further imaging. 30% (n=3) did not pass their stone and required either emergency or elective intervention. 1 patient passed his stone into the toilet whilst another had the stone in their bladder when they were taken to theatre. 20% (n=2) patients but did not catch their stone requiring follow-up imaging which revealed the stone had passed. In the ESWL group 16% (n=2) caught a fragment, the rest found they only passed dust. Stone analysis was performed in all 5 patients who returned a fragment. A total of 73% (n=16) of patients reported over 75% compliance with the stone catcher. 59% (n=13) reported that the stone catcher was easy to use whilst 27% (n=6) found it hard. When given a choice of sieving methods. Only 6 patients (27%) would opt to use the stone catcher with over half, 64% (n=14), preferring more traditional methods of sieving urine over the stone catcher. Conclusion The UroPro © stone catcher did increase the number of stones caught and sent for analysis. However, many patients preferred the older ‘sieving’ methods. Stone catchers retail at £5.50, therefore ‘sieving’ remains more cost-effective. Stone retrieval in any form remains advantageous as confirming stone passage saves the patient 0.5 to 2.8 mSv of radiation from follow-up imaging, the NHS circa £100 per unnecessary follow-up computed tomography (CT) scan and aids metabolic analysis. Over time both factors may be substantial. Therefore, emphasizing the benefits and importance to patients to sieve their urine regardless of the techniques is paramount in the modern management of urolithiasis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".