COMORBIDITIES IN CHILDREN WITH SPASTIC QUADRIPLEGIA
Bibliographic record
Abstract
Objectives: The objective of this study was to determine the the major comorbidites in patients with spastic quadriplegia. Methods: Medical records of patients with spastic quadriplegia from a single pediatric neurology practice over a 14 year period, were retrospectively and systematically reviewed. Variables examined included demographics, prenatal, perinatal, and postnatal risk factors, and investigations. Comorbidity analysis included hearing, vision, feeding, orthopedic abnormalities, learning disabilities, and epilepsy. Binomial logistic regression analyses will be applied to identify predictors of the comorbidities. Results: 100 patients with spastic quadriplegia were included in this study. 39% of patients were premature, 60% were term and 1 was unknown. 62.5% of patient were wheelchair dependent and had a groß motor function classification (GMFCS) of IV or V. 33% of patients were fed by nasogastric or gastric tube. Hearing loss occurred in 39% with 5% of patients requiring hearing aids or being completely deaf. Vision was abnormal in 71% with 18% having cortical blindness or optic atrophy. 44% of patients had epilepsy with 20% acquired, and 34% beginning in the neonatal period. 54.4% needed special education while only 12.2% of children went to a regular school with no extra help. At least 50% of patients needed orthopedic intervention. 31% had baclofen or botox treatments, and 6% had selective dorsal rhizotomies. Conclusion: The majority of patients with spastic quadriplegia are classified in GMFCS levels IV and V. The associated comorbidities of hearing loss, epilepsy, and the need for assisted feeding occur in almost half the patients. Abnormal vision, orthopedic abnormalities, and the need for special education is present in the majority of patients. Pending subgroup analyses include clinical factors predicting these comorbidities. Consultation and intervention by appropriate subspecialists should help optimize function and integration of these children into our society.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".