Infantile spasms: A U.S. consensus report
Bibliographic record
Abstract
The diagnosis, evaluation, and management of infantile spasms (IS) continue to pose significant challenges to the treating physician. Although an evidence-based practice guideline with full literature review was published in 2004, diversity in IS evaluation and treatment remains and highlights the need for further consensus to optimize outcomes in IS. For this purpose, a working group committed to the diagnosis, treatment, and establishment of a continuum of care for patients with IS and their families—the Infantile Spasms Working Group (ISWG)—was convened. The ISWG participated in a workshop for which the key objectives were to review the state of our understanding of IS, assess the scientific evidence regarding efficacy of currently available therapeutic options, and arrive at a consensus on protocols for diagnostic workup and management of IS that can serve as a guide to help specialists and general pediatricians optimally manage infants with IS. The overall goal of the workshop was to improve IS outcomes by assisting treating physicians with early recognition and diagnosis of IS, initiation of short duration therapy with a first-line treatment, timely electroencephalography (EEG) evaluation of treatment to evaluate effectiveness, and, if indicated, prompt treatment modification. Differences of opinion among ISWG members occurred in areas where data were lacking; however, this article represents a consensus of the U.S. approach to the diagnostic evaluation and treatment of IS.
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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 | 0.021 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".