An approach to assessing immunoglobulin dependence in chronic inflammatory demyelinating inflammatory polyneuropathy
Bibliographic record
Abstract
Regular immunoglobulin treatment maintains strength and prevents disability in chronic inflammatory demyelinating polyneuropathy (CIDP). Discrimination between active disease, with optimum symptom control on treatment, and disease in remission not requiring treatment is essential for therapeutic decision-making and clinical trial design. To compare treatment cessation versus gradual dose reduction in assessment of disease activity (immunoglobulin dependence) in a cohort of stable CIDP patients on maintenance immunoglobulin treatment. An approach to restabilization of immunoglobulin-dependent individuals is also described. Retrospective review of IVIg cessation or gradual reduction in 33 patients with stable CIDP on maintenance IVIg. Demographic, clinical and treatment data were collected; clinical monitoring data were recorded prospectively as part of routine clinical practice. A total of 21/33 patients (62.6%) were immunoglobulin dependent, (gradual dose reduction:11, cessation:10). Mean change in Inflammatory Rasch-built Overall Disability Scale (I-RODS) (-15, standard deviation [SD] 16) and Medical Research Council Sum Score (MRC-SS) (-4, SD: 4) was clinically and statistically meaningful (>75% exceeded minimum clinically important differences). Mean time to deterioration was 5.0 (SD: 4.6) months, shorter in cessation group (3.5 months) than gradual reduction group (8.8 months). All patients were restabilized to previous baseline (M: 2.3, SD: 4.3 months), half within 1 week of retreatment. A total of 12 patients (37.4%) remained stable without treatment for ≥2 years (remission). A total of 50% were identified rapidly by cessation and 50% by gradual dose reduction requiring mean 4.8 (SD: 2.8) years follow-up and costing £113 623 per person Ig spend. No predictors of disease activity were identified. A treatment cessation trial with close clinical monitoring is an efficient, cost-effective and safe approach to assessing disease activity in CIDP.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".