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Record W2606890798 · doi:10.17140/pnnoj-2-106

Burden of Illness for Neural Tube Defects: Canadian Perspective

2015· article· en· W2606890798 on OpenAlexaffabout
Gideon Koren, Floortje van Nooten, Randall Winnette, Paige Church, Radek Wasiak, Parvaneh Yazdani-Brojeni, Min Hua Jen, Dimitra Lambrelli, Mark Jeddi, Marion Kissner

Bibliographic record

VenuePediatrics and Neonatal Nursing - Open Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsBayer (Canada)Health Sciences CentreSunnybrook Health Science CentreHospital for Sick Children
Fundersnot available
KeywordsPerspective (graphical)Neural tubeTube (container)PsychologyMedicineIntensive care medicineComputer scienceMaterials scienceArtificial intelligenceBiologyComposite material

Abstract

fetched live from OpenAlex

Background: Neural Tube Defects (NTDs) are serious birth defects of which Spina Bifida (SB) is the most common.This paper aims to provide an estimate of the burden of illness for patients with SB and their caregivers in Canada, to assess the benefit of primary prevention.Methods: Individuals with NTDs were recruited through a hospital in Toronto.Using the clinic's database, individuals with SB and caregivers were screened to confirm eligibility.Data were collected using three types of questionnaires: sociodemographic, resource use and Quality of Life (QoL).Results: Of 310 questionnaires sent, 66 individuals with SB and 66 caregivers responded.Most individuals with SB had a lesion in the lumbar area.More than half had presence of hydrocephalus.In the past 10 years, hospitalisation was the most used health care resource and most visited a urologist in the previous year.Caregivers reported various health conditions resulting from their role as carer.QoL scores were standardised using a United States general population.Results demonstrated that individuals with SB are lower on the physical component score but better on the mental component score. Conclusions:The burden associated with individuals with SB in Canada is considerable.Our study highlights the need for primary prevention.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.043
GPT teacher head0.355
Teacher spread0.311 · 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 designOther design
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

Citations1
Published2015
Admission routes2
Has abstractyes

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