Burden of Illness for Neural Tube Defects: Canadian Perspective
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".