Comorbidities and clinical determinants of outcome in children with spastic quadriplegic cerebral palsy
Bibliographic record
Abstract
The objective of this study was to determine the major comorbidities in patients with spastic quadriplegic (SQ) cerebral palsy (CP) and their possible clinical associations. Medical records of patients with SQ CP from a pediatric neurology practice over a 14-year period were retrospectively and systematically reviewed. Variables examined included demographics, prenatal, perinatal, and postnatal risk factors. Comorbidities documented included those involving hearing, vision, feeding status, and epilepsy. Binomial logistic regression analyses were applied to identify clinical associations of the comorbidities. Ninety-two children were included in this study of whom 39 were born preterm. Mean age of presentation was 2 months (SD 3.5) and males comprised 60% of the group. A total of 57% had a Gross Motor Function Classification Score (GMFCS) of Level IV or V. The four documented comorbidities occurred at a high frequency: 66 out of 83 children (80%) had a visual impairment with 13 (21%) having a substantial impairment; 37 out of 86 children (40%) had a hearing deficit; 43 out of 92 children (47%) had epilepsy; and 29 (33%) required assisted feeding. A GMFCS Level of IV or V and documented microcephaly was associated with the need for assisted feeding (odds ratio [OR] 8.1; 95% confidence interval [CI] 2.1-29.8, p=0.002 and OR 4.9, 95% CI 1.7-14.8, p=0.004 respectively). Epilepsy was associated with the occurrence of neonatal encephalopathy (OR 2.3, 95% CI 1.0-55; p=0.05), microcephaly (OR 4.9, 95% CI 1.6-14.8; p=0.004), periventricular leukomalacia (OR 7.4, 95% CI 1.6-35.0; p=0.012), and perinatal asphyxia (OR 3.6, 95% CI 1.5-8.9; p=0.005). There is a high frequency of comorbidity in the setting of SQ CP which can impact on quality of life and burdens of care. Few clinical associations of this burden appear, thus necessitating systematic programmatic follow-up of these children to facilitate early identification and intervention.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".