International survey on the implementation of the European and American guidelines on disorders of consciousness
Bibliographic record
Abstract
Diagnostic, prognostic, and therapeutic procedures for patients with prolonged disorders of consciousness (pDoCs) vary significantly across countries and clinical settings, likely due to organizational factors (e.g., research vs. non-academic hospitals), expertise and availability of resources (e.g., financial and human). Two international guidelines, one from the European Academy of Neurology (EAN) and one from the American Academy of Neurology (AAN) in collaboration with the American Congress of Rehabilitation Medicine (ACRM) and the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR), were developed to facilitate consistent practice among professionals working with this challenging patient population. While the recommendations of both guidelines agree in principle, it remains an open issue how to implement them into clinical practice in the care pathway for patients with pDoCs. We conducted an online survey to explore health professional clinical practices related to the management of patients with pDoCs, and compare said practices with selected recommendations from both the guidelines. The survey revealed that while some recommendations are being followed, others are not and/or may require more honing/specificity to enhance their clinical utility. Particular attention should be given to the implementation of a multimodal assessment of residual consciousness, to the detection and treatment of pain, and to the impact of restrictions imposed by COVID-19 pandemics on the involvement of patients' families/representatives.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".