Postfolate spina bifida lesion level change
Bibliographic record
Abstract
BACKGROUND: Spina bifida accounts for a large proportion of birth defects in the United States. Studies have evaluated the decrease in prevalence at birth after folate fortification of food grains, but little is known about neurologic functional changes related to fortification. This study assesses the functional level of lesions in the prefortification and postfortification eras. METHODS: Data were collected through retrospective review of medical records from a regional multispecialty clinic in Arizona. This study included individuals born between 1981-1995 (prefortification) and 1999-2013 (postfortification). Patients were included if they had a primary diagnosis of spina bifida with or without hydrocephalus. RESULTS: There was a significant difference in functional lesion level with an 85% reduction in thoracic level lesions in the postfortification era (p < .005). There were no differences in gender or ethnicity across eras; however, Hispanic ethnicity had a higher number of cases overall (51.7%). The most common lesion level in both eras was mid-lumbar, accounting for 35.7 and 34.4% of cases in the prefolate and postfolate eras, respectively. CONCLUSIONS: This study demonstrates a significant difference in the distribution of lesion level of spina bifida patients born in the postfortification era, based on neurologic function. Further research with a larger sample size is needed to determine if this observation holds true nationally.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".