CSF Findings in Relation to Clinical Characteristics, Subtype, and Disease Course in Patients With Guillain-Barré Syndrome
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: To investigate CSF findings in relation to clinical and electrodiagnostic subtypes, severity, and outcome of Guillain-Barré syndrome (GBS) based on 1,500 patients in the International GBS Outcome Study. METHODS: Albuminocytologic dissociation (ACD) was defined as an increased protein level (>0.45 g/L) in the absence of elevated white cell count (<50 cells/μL). We excluded 124 (8%) patients because of other diagnoses, protocol violation, or insufficient data. The CSF was examined in 1,231 patients (89%). RESULTS: = 0.001). Patients with the Miller Fisher syndrome, distal predominant weakness, and normal or equivocal nerve conduction studies were more likely to have lower CSF protein levels. CSF cell count was <5 cells/μL in 1,005 patients (83%), 5-49 cells/μL in 200 patients (16%), and ≥50 cells/μL in 13 patients (1%). DISCUSSION: ACD is a common finding in GBS, but normal protein levels do not exclude this diagnosis. High CSF protein level is associated with an early severe disease course and a demyelinating subtype. Elevated CSF cell count, rarely ≥50 cells/μL, is compatible with GBS after a thorough exclusion of alternative diagnoses. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that CSF ACD (defined by the Brighton Collaboration) is common in patients with GBS.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".