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Record W2158402076 · doi:10.3171/ped.2004.101.2.0141

Measuring the health status of children with hydrocephalus by using a new outcome measure

2004· article· en· W2158402076 on OpenAlexaff
Abhaya V. Kulkarni, James M. Drake, Doron Rabin, Peter B. Dirks, Robin P. Humphreys, James T. Rutka

Bibliographic record

VenueJournal of Neurosurgery Pediatrics · 2004
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsSickKids FoundationUniversity of Toronto
Fundersnot available
KeywordsMedicineHydrocephalusMultivariate analysisAnalysis of varianceCohortPhysical therapyPediatricsSurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECT: In the preceding article, the authors described the Hydrocephalus Outcome Questionnaire (HOQ), a simple, reliable, and valid measure of health status in children with hydrocephalus. In the present study, they present their initial experience in using the HOQ to quantify the health status in a typical cohort of children with hydrocephalus. METHODS: The mothers of children with hydrocephalus completed the HOQ and, with the child's attending surgeon, provided a global rating of their children's health. An exploratory analysis was performed using a multivariate analysis of variance (ANOVA) to determine which variables might be associated with worse health status. The mothers of 80 children, ranging in age from 5 to 17 years, participated in the study. The mean HOQ Overall Health score was 0.68, a value estimated to be equivalent to a mean health utility score of 0.77. The global health ratings provided by the mothers and the surgeons were moderately correlated with the HOQ scores (Pearson correlations 0.58 and 0.57, respectively). Results of the multivariate ANOVA indicated that the presence of epilepsy was strongly associated with a worse health status (p < 0.0001, F-test). CONCLUSIONS: The health status of a typical sample of children with hydrocephalus was measured using the HOQ. The only consistently significant association with health status found was the presence of epilepsy.

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.

How this classification was reachedexpand

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.831

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.059
GPT teacher head0.281
Teacher spread0.222 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations57
Published2004
Admission routes1
Has abstractyes

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