Reimagining durability of hydrocephalus treatment using conditional survival
Bibliographic record
Abstract
OBJECTIVE: Conditional survival incorporates the effect of time passed since an event to current data in an easy-to-understand, relevant format. Data from the Hydrocephalus Clinical Research Network (HCRN) registry were analyzed with conditional survival to improve patient and family counseling after hydrocephalus treatment. METHODS: Children with hydrocephalus who underwent first-time treatment by a single proximal catheter ventriculoperitoneal shunt (VPS) or endoscopic third ventriculostomy (ETV) with or without choroid plexus cauterization with at least 3 years of follow-up in the prospective HCRN registry (14 sites, April 24, 2008-December 31, 2020) were included. Those with nonperitoneal or multiple proximal catheters were excluded. The probability of failure-free survival at 3, 5, and 10 years was calculated as a function of time since surgery. RESULTS: Overall, 5782 patients were included (1609 with ETV, 4173 with VPS placement). The median time to censoring was 5.3 years. The overall respective 3-, 5-, and 10-year failure-free survival rates were 59%, 58%, and 57%, respectively, for ETV and 62%, 58%, and 54%, respectively, for VPS. If VPS failure had not occurred by 1 year postoperatively, the 3-, 5-, and 10-year failure-free survival rates were 85%, 79%, and 66%, respectively. If ETV failure had not occurred by 1 year, the 3-, 5-, and 10-year failure-free survival rates were 93%, 91%, and 86%, respectively. Conditional survival also varied by age and etiology. CONCLUSIONS: Patients who do not require revision surgery in the 1st year have an excellent chance of being revision free for an extended period. Conditional survival plots provided are intuitive and can be used in the counseling of North American patients with surgically treated hydrocephalus.
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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 | 0.019 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".