Abstract WP18: Association Of Quality Of Life Domains And Clinical Symptoms In Familial Cerebral Cavernous Malformation Patients
Bibliographic record
Abstract
Background: Familial cerebral cavernous malformation (FCCM) is characterized by multiple brain lesions at risk for intracranial hemorrhage (ICH) and neurological morbidity, affecting quality of life (QoL). PROMIS-29 is a QoL survey validated in some neurological diseases but has not yet been evaluated for FCCM. We aimed to assess whether PROMIS-29 health domains are associated with clinical symptoms in FCCM patients. Methods: PROMIS-29 surveys assessing seven QoL domains were completed by 198 FCCM patients >=18 years either at a baseline or follow-up visit in the Brain Vascular Malformation Consortium CCM study. Raw PROMIS-29 domain scores were converted to T scores that are standardized to a reference population with mean 50 and SD 10, and oriented so that higher scores are unfavorable. One-sample t-tests and p-values assessed whether mean T-scores were significantly different from 50 (p<0.05). Multivariable linear regression was used to test whether domain scores were associated with history of ICH, seizures, or headaches at time of survey, adjusting for age and sex. Results: Compared to a reference population, FCCM patients had significantly higher anxiety (52.7, 95% CI: 51.3-54.2, p<0.001), pain (52.5, 95% CI: 51.0-54.0, p=0.002), and physical functioning scores (52.0, 95% CI: 51.4-54.5, p<0.001), but lower social participation scores (46.9, 95% CI: 45.4-48.5, p<0.001). History of ICH and headaches were significantly associated with 4 domains each (all >3 points, p<0.05, Table), while seizures were not associated. Fatigue was the only affected domain in common. Conclusion: FCCM patients differed significantly from the reference population on anxiety, pain, physical functioning, and social participation domains. These same domains were significantly associated with history of ICH or headaches in patients. Further studies will determine whether changes in health domains are associated with changes in clinical symptoms.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".