The evolution of percutaneous nephrolithotomy: Analysis of a single institution experience over 25 years
Bibliographic record
Abstract
INTRODUCTION: Over time, the incidence of nephrolithiasis has risen significantly, and patient populations have become increasingly complex. Our study aimed to determine the impact of changes in patient demographics on percutaneous nephrolithotomy (PCNL) outcomes. METHODS: A retrospective analysis of a prospectively collected database was carried out from 1990-2015. Patient demographics, comorbidities, stone and procedure characteristics were analyzed. Multivariate logistic regression was used to evaluate differences in operative duration, complications, stone-free rate, and length of stay. RESULTS: were analyzed; 47% of patients had comorbidities, including hypertension (22%), diabetes mellitus (14%), and cardiac disease (13%). Complication rate was 19%, including a 2% rate of major complications (Clavien grade III-V). There was a statistically significant increase in patient age, BMI, and comorbidities over time, which was correlated with an increased complication rate (odds ratio [OR] 1.15; p=0.010). The overall transfusion rate was 1.0% and remained stable (p=0.131). With time, both OR duration (mean Δ 16 minutes; p<0.001) and hospital length of stay (mean Δ 2.4 days; p<0.001) decreased significantly. Stone-free rate of 1873 patients with available three-month followup was 87% and decreased significantly over time (OR 1.09; p<0.001), but was correlated with an increased use of computed tomography (CT) scans for followup imaging. CONCLUSIONS: Despite an increasingly complex patient population, PCNL remains a safe and effective procedure with a high stone-free rate and low risk of complications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".