Prenatal Spinal Evaluation and Functional Outcome of Patients Born with Myelomeningocele: Information for Improved Prenatal Counselling and Outcome Prediction
Bibliographic record
Abstract
OBJECTIVE: Prenatal ultrasonography can localize the level of the spinal cord malformation, allowing prediction of the potential postnatal neurological deficit and functional prognosis. METHODS: This study has two evaluations: (a) a retrospective prenatal review of 26 fetuses with spinal dysraphism (1987-1991), and (b) a follow-up descriptive study of patients (1971-1981) who underwent closure of the spinal lesion and ventricular shunting in the neonatal period. RESULTS: Prenatal ultrasound evaluation enabled the accurate definition of the last intact vertebral level which allows separation of fetuses into three functional groups (last intact level L2, L3-4, L5-sacral). Patterns of ambulation, urinary and bowel continence, and school performance vary according to level of spinal lesion and the neurological deficit. The need for ventricular shunts, the incidence of other spinal malformations and surgical interventions did not vary with the level of the spinal lesion. CONCLUSIONS: The functional outcome for patients with myelomeningocele is variable; however, distinct patterns emerge based on the level of spinal dysraphism and the resultant neurological deficit. By relating the level of the fetal spinal lesion to outcome data, more precise functional prognoses can be given to families.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".