Detecting Polyneuropathy in Patients with Hereditary Transthyretin Amyloid Cardiomyopathy
Bibliographic record
Abstract
Background: Patients with hereditary transthyretin amyloid cardiomyopathy (hATTR-CM), can show neurologic signs that lead to the eventual onset of polyneuropathy (PN). Detection of PN among patients with hATTR-CM can identify candidates for disease-modifying therapies that could significantly reduce the incidence of mortality and morbidity for these complex patients. The purpose of this study is to determine the prevalence of PN among patients with hATTR-CM. Methods: Sixty patients with hATTR-CM were enrolled in this prospective study, from the Amyloidosis Clinic at the University Health Network in Toronto, Ontario, Canada. All patients (average age: 69.12 ± 11.82 years; 51.7% male; 48.3% female) were referred to neurology programs specialized in hATTR PN. Comprehensive neurologic assessments were conducted, including a physical examination and nerve conduction studies (NCSs). NCSs were performed on the upper and lower extremities. Results: Thirty patients (50.0%) displayed clinical and NCS abnormalities. Six patients (10.0%) did not display any neurologic abnormalities on the physical examination, but did have abnormalities on the NCSs, suggesting the presence of transthyretin-PN. The abnormalities on the NCSs were more indicative of sensory PN than of motor polyneuropathy. Twenty-four patients (40.0%) did not display any clinical or NCS abnormalities. Based on the systematic neurologic assessment, 36 patients in our study were identified as having a mixed hATTR phenotype, and they are to receive specific disease-modifying therapies, either patisiran or inotersen. Conclusion: Patients with hATTR-CM should be systematically referred to a specialized neurologist for routine assessment, especially patients who report neurologic symptoms (ie, numbness and burning sensation in extremities).
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".