Percutaneous Nerve Evaluation Test Versus Staged Test Trials for Sacral Neuromodulation: Sensitivity, Specificity, and Predictive Values of Each Technique
Bibliographic record
Abstract
PURPOSE: InterStim device is an U.S. Food and Drug Administration approved minimal invasive therapy for sacral neuromodulation for lower urinary tract dysfunction. Before InterStim implantation, a trial with the appropriate screening tests is required to determine patient therapy eligibility. There are two different techniques for patient screening: percutaneous nerve evaluation (PNE) test and staged test. Few studies have reported success and failure rates for each technique. However, test sensitivity and predictive values of either test have not been studied. The aim of our study was to determine the sensitivity and specificity of each test and to establish a decision algorithm for the most appropriate testing method to be used as a screening test. METHODS: This cross-sectional study was conducted from August 2009 to February 2012 and included patients with lower urinary tract dysfunction who participated in the stimulation test trial. Patients underwent PNE as the first stimulation test, while those who encountered technical difficulty during PNE or electrode migration underwent staged testing. RESULTS: A total of 213 patients, including 172 female and 41 male subjects, underwent PNE. The patients' diagnoses included refractory overactive bladder (47.9%), nonobstructive urinary retention (29.6%), and frequency urgency syndrome (22.1%). A total of 202 patients were screened with PNE and 10 patients with staged testing. Overall sensitivity of PNE was 87.3%, and it was 90% for staged test. PNE specificity was 98.5% as compared to 92.9% for staged test. Positive and negative predictive values for PNE were 99% and 82.1% and for staged test were 90% and 92.9%, respectively. CONCLUSIONS: PNE test has high specificity and positive predictive value. We recommend PNE, a simple office-based, less expensive procedure as the first option for screening.
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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 | 0.011 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".