ACCELERATED AGING AMONG ADULTS LIVING WITH CEREBRAL PALSY
Bibliographic record
Abstract
Abstract Cerebral Palsy (CP) is the most common pediatric-onset physical disability, with an estimated prevalence ranging from 2.6-3.1 cases per 1,000 live births in the United States. There is a lack of clinical follow-up for individuals with CP after they transition from pediatric to adult primary care, and insufficient surveillance to track patients with CP longitudinally. Despite the shortage of research to examine the natural history of CP and chronic disease trajectories in this population, a range of secondary conditions arise at an accelerated rate as compared to the adult population without CP, prompting the widespread notion and clinical hypothesis that patients with CP are prone to accelerated aging. These factors further worsen functional status and quality of life, as well as lead to decreased independence. Despite the well-established interrelationships between physical and mental health disorders in the non-CP older adult population, the extent to which, mechanisms underlying, and time course associated with the development of these chronic conditions among adults living with CP has received little empirical attention. The proposed course will build upon our ongoing work by highlighting new findings from three centers doing research pertaining to aging with CP, and will cover novel mechanisms of musculoskeletal pathophysiology in CP, risk factors of and unique CVD profiles among adults with CP, and new findings related to health trajectory differences of adults with CP from clinical and population-representative cohorts. We will also provide insights into the pathophysiologic mechanisms linking early frailty and long-term health outcomes among persons with CP.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".