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Postsurgical Health‐related Quality of Life (HRQOL) in Children Following Hemispherectomy for Intractable Epilepsy

2007· article· en· W1983845178 on OpenAlexaff
Stephanie Griffiths, Elisabeth M. S. Sherman, Daniel J. Slick, Kim L. Eyrl, Mary Connolly, Paul Steinbok

Bibliographic record

VenueEpilepsia · 2007
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of British ColumbiaBC Children's HospitalAlberta Children's HospitalSimon Fraser University
Fundersnot available
KeywordsHemispherectomyMedicinePsychosocialQuality of life (healthcare)EpilepsyIntractable epilepsyPediatricsEpilepsy surgeryHealth related quality of lifePediatric epilepsyPopulationPsychiatryDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Health-related quality of life (HRQOL) is an important outcome measure in clinical research. Given the psychosocial and behavioral difficulties associated with pediatric epilepsy, evaluating HRQOL in this patient population is of particular importance. Though HRQOL has been examined in pediatric patients receiving focal resection or pharmacological (antiepileptic drug; AED) treatment, it has not been assessed in patients receiving hemispherectomy (HE) for intractable epilepsy. The current study evaluated HRQOL in a sample of pediatric HE cases (N=26) using previously validated questionnaires relative to surgical (N=30) and nonsurgical (N=84) comparison groups. Compared with focal resection and nonsurgical patients, parents of children who received HE reported similar levels of HRQOL. In surgical cases, worse HRQOL was correlated with residual seizure frequency. In both surgical and nonsurgical cases, female gender, higher AED load, and lower functional independence predicted worse HRQOL. Interestingly, HE status (i.e., having undergone HE) predicted fewer epilepsy-related limitations. Consistent with previous findings, AED load, in addition to lower functional abilities, appear particularly detrimental to life quality in pediatric epilepsy. HE, however, is not associated with increased risk for poor HRQOL. When considered in light of the multiple, significant risk factors for poor outcome associated with HE, children who undergo the procedure fare surprisingly well.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.358
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), 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

Citations48
Published2007
Admission routes1
Has abstractyes

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