Validation and modification of a predictive model of postresection hydrocephalus in pediatric patients with posterior fossa tumors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECT: Postresection hydrocephalus is observed in approximately 30% of pediatric patients with posterior fossa tumors. However, which patients will develop postresection hydrocephalus is not known. The Canadian Preoperative Prediction Rule for Hydrocephalus (CPPRH) was developed in an attempt to identify this subset of patients, allowing for the optimization of their care. The authors sought to validate and critically appraise the CPPRH. METHODS: The authors conducted a retrospective chart review of 99 consecutive pediatric patients who presented between 2002 and 2010 with posterior fossa tumors and who subsequently underwent resection. The data were then analyzed using bivariate and multivariate analyses, and a modified CPPRH (mCPPRH) was applied. RESULTS: Seventy-six patients were evaluated. Four variables were found to be significant in predicting postresection hydrocephalus: age younger than 2 years, moderate/severe hydrocephalus, preoperative tumor diagnosis, and transependymal edema. The mCPPRH produced observed likelihood ratios of 0.737 (95% CI 0.526-1.032) and 4.688 (95% CI 1.421-15.463) for low- and high-risk groups, respectively. CONCLUSIONS: The mCPPRH utilizes readily obtainable and reliable preoperative variables that together stratify children with posterior fossa tumors into high- and low-risk categories for the development of postresection hydrocephalus. This new predictive model will aid patient counseling and tailor the intensity of postoperative clinical and radiographic monitoring for hydrocephalus, as well as provide evidence-based guidance for the use of prophylactic CSF diversion.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it