Reply: The Optimal Management of Electrodiagnostic Studies during <scp>COVID</scp>‐19 Outbreak
Bibliographic record
Abstract
We thank Dr. Vinciguerra for her letter. She correctly points out that a pandemic is an evolving situation, rather than a static one, and recommendations may not apply to all time points during the pandemic. She describes an earlier pandemic scenario, which she terms the “contingency standard of care,” in which there are still sufficient resources to perform electrodiagnostic studies (EDX). It is in this situation that the coronavirus disease (COVID) guidance document applies most readily.1 She also points to a second pandemic scenario, which she terms the “crisis standard of care,” where medical resources, including staffing, are not available to carry out EDX studies. Dr. Vinciguerra stratifies the availability of resources and their effect on EDX testing in her letter. We did not address resource availability in our guidance document, although it is clearly a driver of the ability to perform EDX or other testing.1 Our intention was to provide recommendations regarding patient selection for EDX testing to clinicians during the time of the pandemic. However, in such a scenario where resources are unavailable or must be directed toward critical care, most, if not all, EDX studies may have to be postponed. Clinicians will have to rely on the clinical features and other diagnostic testing that may be available, accepting more diagnostic uncertainty before deciding on empiric treatment in acute situations, such as suspected Guillain Barre syndrome or myasthenic crisis. The “possibly urgent” category in our guidance document may also have to be handled similarly.1 Resumption of EDX will depend on the subsequent availability of resources and will vary by location. Charles Kassardjian has received honoraria or serve on an advisory board for Alexion, Akcea, Takeda, and Sanofi Genzyme. Urvi Desai has received honoraria for speaker bureau or advisory board participation from Alexion, Akcea, Stealth Biotherapeutics, and CSL Behring. Pushpa Narayanaswami has received grant support from the Patient Centered Outcomes Research Institute, Momenta Pharmaceuticals, provided consultation for Alexion, Momenta, and Argenx. We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".