Infectious Complications, Healthcare Resource Use, and Medical Costs Associated with Delays in Percutaneous Nephrolithotomy Among Patients with Stone Disease and Ureteral Stent Placement
Bibliographic record
Abstract
Purpose: The relationship between ureteral stent duration before percutaneous nephrolithotomy (PCNL) and infectious complications, admissions, imaging, and medical costs was evaluated. Materials and Methods: Patients who underwent PCNL within 6 months of ureteral stent placement were identified from commercial claims, categorized by time to treatment (0–30, 31–60, and >60 days), and followed 1-month post-PCNL. The effect of delayed treatment on inpatient admissions, infectious complications (pyelonephritis/sepsis), and imaging utilization was evaluated with logistic regression. A generalized linear model evaluated the effect of delayed treatment on medical costs. Results: Among 564 patients with PCNL and meeting the inclusion criteria (mean age 50; 55% female; 45% from South), mean (standard deviation) time to surgery was 48.8 (41.8) days. Less than half (44.3%; n = 250) underwent PCNL within 30 days of ureteral stent placement, 27.0% ( n = 152) between 31 and 60 days, and 28.7% ( n = 162) >60 days. Time to PCNL was significantly associated with inpatient admissions (>60 vs ≤30 days odds ratio [OR] 1.97, 95% confidence interval [CI] 1.29–3.01, p = 0.0016), infectious complications (>60 vs ≤30 days OR 2.43, 95% CI 1.55–3.81, p = 0.0001), imaging utilization (31–60 vs ≤30 days OR 1.56, 95% CI 1.02–2.38, p = 0.0383; >60 vs ≤30 days OR 2.01, 95% CI 1.31–3.06, p = 0.0012), and medical costs (31–60 vs ≤30 days OR 1.27, 95% CI 1.08–1.49, p = 0.0048; >60 vs ≤30 days OR 1.46, 95% CI 1.24–1.71, p < 0.0001). Conclusions: Compared with PCNL within 30 days, patients undergoing PCNL >30 days after ureteral stent placement had increased likelihood of infectious complications, resource use, and medical costs. These results may inform health care resource utilization and PCNL prioritization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".