The Preventable Shunt Revision Rate: A Multicenter Evaluation
Bibliographic record
Abstract
BACKGROUND: The Preventable Shunt Revision Rate (PSRR) was recently introduced as a novel quality metric. OBJECTIVE: To evaluate the PSRR across multiple centers and determine associated variables. METHODS: Nine participating centers in North America provided at least 2 years of consecutive shunt operations. Index surgery was defined as new shunt implantation, or revision of an existing shunt. For any index surgery that resulted in a reoperation within 90-days, index surgery information (demographic, clinical, and procedural) was collected and a decision made whether the failure was potentially preventable. The 90-day shunt failure rate and PSRR were calculated per institution and combined. Bivariate analyses were performed to evaluate individual effects of each independent variable on preventable shunt failure followed by a final multivariable model using a backward model selection approach. RESULTS: A total of 5092 shunt operations were performed; 861 failed within 90 days of index operation, resulting in a 16.9% combined 90-day shunt failure rate and 17.6% median failure rate (range, 8.7%-26.9%). Of the failures, 307 were potentially preventable (overall and median 90-day PSRR, 35.7% and 33.9%, respectively; range, 16.1%-55.4%). The most common etiologies of avoidable failure were infection (n = 134, 44%) and proximal catheter malposition (n = 83, 27%). Independent predictors of preventable failure (P < .05) were lack of endoscopy (odds ratio [OR] = 2.26), recent shunt infection (OR = 3.65), shunt type (OR = 2.06) and center. CONCLUSION: PSRR is variable across institutions, but can be 50% or higher. While the PSRR may never reach zero, this study demonstrates that overall about a third of early failures are potentially preventable.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".