A re-evaluation of the Endoscopic Third Ventriculostomy Success Score: a Hydrocephalus Clinical Research Network study
Bibliographic record
Abstract
OBJECTIVE: The Hydrocephalus Clinical Research Network (HCRN) conducted a prospective study 1) to determine if a new, better-performing version of the Endoscopic Third Ventriculostomy Success Score (ETVSS) could be developed, 2) to explore the performance characteristics of the original ETVSS in a modern endoscopic third ventriculostomy (ETV) cohort, and 3) to determine if the addition of radiological variables to the ETVSS improved its predictive abilities. METHODS: From April 2008 to August 2019, children (corrected age ≤ 17.5 years) who underwent a first-time ETV for hydrocephalus were included in a prospective multicenter HCRN study. All children had at least 6 months of clinical follow-up and were followed since the index ETV in the HCRN Core Data Registry. Children who underwent choroid plexus cauterization were excluded. Outcome (ETV success) was defined as the lack of ETV failure within 6 months of the index procedure. Kaplan-Meier curves were constructed to evaluate time-dependent variables. Multivariable binary logistic models were built to evaluate predictors of ETV success. Model performance was evaluated with Hosmer-Lemeshow and Harrell's C statistics. RESULTS: Seven hundred sixty-one children underwent a first-time ETV. The rate of 6-month ETV success was 76%. The Hosmer-Lemeshow and Harrell's C statistics of the logistic model containing more granular age and etiology categorizations did not differ significantly from a model containing the ETVSS categories. In children ≥ 12 months of age with ETVSSs of 50 or 60, the original ETVSS underestimated success, but this analysis was limited by a small sample size. Fronto-occipital horn ratio (p = 0.37), maximum width of the third ventricle (p = 0.39), and downward concavity of the floor of the third ventricle (p = 0.63) did not predict ETV success. A possible association between the degree of prepontine adhesions on preoperative MRI and ETV success was detected, but this did not reach statistical significance. CONCLUSIONS: This modern, multicenter study of ETV success shows that the original ETVSS continues to demonstrate good predictive ability, which was not substantially improved with a new success score. There might be an association between preoperative prepontine adhesions and ETV success, and this needs to be evaluated in a future large prospective study.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".