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Record W1969694488 · doi:10.1159/000120930

Model for the Cost Analysis of Shunted Hydrocephalic Children

2008· article· en· W1969694488 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePediatric Neurosurgery · 2008
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsHydrocephalusActivity-based costingMedicineShunt (medical)SurgeryPopulationFailure ratePediatricsIntensive care medicineStatisticsEconomicsAccountingMathematics

Abstract

fetched live from OpenAlex

This paper describes a model for forecasting the treatment costs for hydrocephalic patients with ventriculoperitoneal shunts. Modeling with institution-specific or reported failure rates allows the prediction of shunt failure in real and/or theoretical populations. The addition of costing factors (derived from hospitalization, operative and drug costs) to the model allows the derivation of partial or total cost estimates. The effects of varying the failure rate, infection rate, number of new patients, number of lost patients and costing factors can be simulated and measured. Basing this model on data from our institution, decreasing the rate of failure during the first year following shunt insertion or revision has the potential for greater cost savings over time than either decreasing the shunt infection rates or the duration of hospital stay. By combining shunt performance and financial data, an estimate of the cost of the treatment of a population with hydrocephalus, over time, can be derived. These data can be critical for institutional and program budgeting and serve as an estimate of the economic effects of treatment changes proposed in clinical trials.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.273
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it