COVID19 on U.S. and canadian neurologists' therapeutic approach to multiple sclerosis: A survey of knowledge, attitudes, and practices
Bibliographic record
Abstract
Background: There have been >1 8 million cases of Sars-CoV-2 (Covid19) in the USA and >100,000 deaths reported as of June 2020 Immunosuppression is reported as a risk factor for developing Covid19 Amidst this pandemic and declared national emergency in the USA, with a parallel response in Canada, neuroimmunologists are making important decisions and adjudicating complex situations of risk for their patients living with MS No synthesized study of North American neuroimmunologists' perceptions has been conducted Objectives: To report the experiences, opinions, and decisionmaking of U S and Canadian neuroimmunologists as they relate to the treatment of patients with multiple sclerosis (MS) during the Covid19 pandemic of 2020 Methods: A new survey instrument was designed and distributed electronically Invitations were sent via a known panel of MS neurologists and to publicly available e-mail addresses of MS-focused U S and Canadian neurologists, April 14-May 3, 2020 Inclusion criteria included treating at least 10 MS patients in the prior 6 months Results: 243 respondents (average 197 MS patients seen in the prior 6 months (i e pre-Covid19);average practice duration 16 years;92% USA, 8% Canada;5% rural, 17% small city, 38% large city, 40% highly urbanized) met our inclusion criteria MS patient volume dropped by 79% on average (from 53 to 11 patients per month) during the time of Covid19 23% of neurologists were aware of patients self-discontinuing a DMT due to fear of Covid19 with 43% estimated to be doing so against medical advice 65% of respondents reported deferring >=1 doses of a disease modifying therapy (DMT) (49%), changing the dosing interval (34%), changing to home infusions (20%), switching a DMT (9%), and discontinuing DMTs altogether (8%) due to Covid19 Changes in DMT administration were most common among the higher-efficacy therapies alemtuzumab, cladribine, ocrelizumab, rituximab, and natalizumab;however, 35% of neurologists reported making no changes to DMT prescribing 98% of respondents expressed worry about their patients contracting Covid19 and 78% expressed the same degree of worry about themselves >50% reported believing that high-efficacy DMTs prolong viral shedding of SARS-CoV-2 and that B-cell therapies might prevent protective vaccine effects Accelerated pace of telemedicine was identified as a major shift in practice Conclusions: Reported prescribing changes and practice disruptions due to Covid19 may be temporary but are likely to have a long-lasting influence on MS patients and their care
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".