Is medical dissolution treatment for uric acid stones more cost-effective than surgical treatment? A novel, solo practice retrospective cost-analysis of medical vs. surgical therapy
Bibliographic record
Abstract
INTRODUCTION: Effective medical dissolution therapy (MDT) for uric acid stones is more cost-effective than surgical treatment; however, treatment failure may be associated with increased cost. We aimed to study the cost-effectiveness of MDT for uric acid stones vs. surgical management. METHODS: We performed a retrospective study within our institution of all patients receiving MDT for uric acid stones from 2008-2019. All patients had a known history of uric acid stones, urine pH ≤5.5, and <500 Hounsfield units on preoperative computed tomography (CT). The cost of treatment in the dissolution group was compared to the cost of primary surgical treatment in a theoretical matched cohort. Cost was estimated using local Medicare reimbursement scales. Statistical analysis was performed with SPSS Statistics. RESULTS: A total of 28 patients were identified, of which 18 were included in the study. Complete and partial dissolution occurred in six (33%) and four (22%) patients, respectively. Five (28%) patients developed symptoms and underwent ureteral stent placement. Ureteroscopy and percutaneous nephrolithotomy (PCNL) were each performed in three (17%) patients in whom dissolution treatment was not effective on followup CT. Following dissolution trial, six (33%) patients had residual stone burden requiring surgical intervention. The average cost of treatment, including surgeries, was $14 604 in the dissolution group vs. $17 680 in the surgical cohort. The average cost to achieve stone-free status in patients with complete, partial, or no response to dissolution were $1675, $10 124, and $21 584, respectively, while primary surgical treatment for the same patients would cost $15 037, $10 901, and $20 511, respectively. CONCLUSIONS: Successful MDT is highly cost-effective. Incomplete response to dissolution can stem from several reasons and contributes to higher costs and likely decreased quality of life.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".