Risk Stratification and Management of Acute Respiratory Failure in Patients With Neuromuscular Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Guillain-Barré syndrome (GBS) and myasthenia gravis (MG) are the most common causes of acute neuromuscular respiratory failure resulting in ICU admission. This synthetic narrative review summarizes the evidence for the prediction and management of acute neuromuscular respiratory failure due to GBS and MG. DATA SOURCES: We searched PubMed for relevant literature and reviewed bibliographies of included articles for additional relevant studies. STUDY SELECTION: English-language publications were reviewed. DATA EXTRACTION: Data regarding study methodology, patient population, evaluation metrics, respiratory interventions, and clinical outcomes were qualitatively assessed. DATA SYNTHESIS: No single tool has sufficient sensitivity and specificity for the prediction of acute neuromuscular respiratory failure requiring mechanical ventilation. Multimodal assessment, integrating history, examination maneuvers (single breath count, neck flexion strength, bulbar weakness, and paradoxical breathing) and pulmonary function testing are ideal for risk stratification. The Erasmus GBS Respiratory Insufficiency Score is a validated tool useful for GBS. Noninvasive ventilation can be effective in MG but may not be safe in early GBS. Airway management considerations are similar across both conditions, but dysautonomia in GBS requires specific attention. Extubation failure is common in MG, and early tracheostomy may be beneficial for MG. Prolonged ventilatory support is common, and good functional outcomes may occur even when prolonged ventilation is required. CONCLUSIONS: Multimodal assessments integrating several bedside indicators of bulbar and respiratory muscle function can aid in evidence-based risk stratification for respiratory failure among those with neuromuscular disease. Serial evaluations may help establish a patient's trajectory and to determine timing of respiratory intervention.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it