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Use of Intravenous Immunoglobulin for Treatment of Neurological Conditions: A Systematic Review.

2004· article· en· W2980948123 on OpenAlexaff
Brian Hutton, Dean Fergusson, Michael Sharma, Alan Tinmouth, Kumanan Wilson, Paul C. Hébert

Bibliographic record

VenueBlood · 2004
Typearticle
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsMedicineClinical trialRandomized controlled trialPlaceboMeta-analysisExacerbationMEDLINESystematic reviewIntensive care medicinePediatricsInternal medicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

Abstract Purpose: Given the increasing use of intravenous immunoglobulin for various neurological conditions, its significant cost and the uncertainty pertaining to its benefits and harms, we conducted a systematic review of randomized controlled trials that compared intravenous immunoglobulin to other current therapies. Methods: A systematic search strategy of Medline (1966-June 2003) and the Cochrane Registry of Controlled Trials (June 2003 edition) was developed to identify randomised controlled trials. Two authors (BH, DF) independently reviewed all citations retrieved from the electronic search to identify all potentially relevant trials for this review. In cases where a unanimous decision could not be reached, a third party was consulted. To be eligible, studies had to be randomised controlled trials comparing intravenous immunoglobulin to either placebo or an active control and evaluating clinical outcomes. Measures of effect were calculated for each trial independently, and studies were pooled based on clinical and methodologic judgment as to its appropriateness. Fixed effects and random effects models were selected for each meta-analysis based on appraisal of the clinical homogeneity of patients across studies, as well as from testing for heterogeneity between studies. In circumstances where pooling of trials was inappropriate or not feasible, a qualitative discussion of the findings was developed. Results: Thirty-seven trials representing 14 conditions were identified. Results from meta-analysis suggest that intravenous immunoglobulin therapy is effective for the treatment of multiple sclerosis (pooled 1-year EDSS change −0.46, 95% CI [−0.92,0.01] in favor of IVIG; pooled change in annual exacerbation rate −0.82, 95% CI [−1.54, −0.11] in favor of IVIG; pooled odds of remaining exacerbation free 0.24, 95% CI [0.12, 0.50] in favor of IVIG ) and idiopathic chronic inflammatory demyelinating polyneuropathy (pooled change in disability score −0.67, 95% CI [−1.04, −0.30] in favor of IVIG; pooled odds of achieving treatment response 4.43, 95% CI [2.20, 8.91] in favor of IVIG). There was insufficient evidence to determine whether this therapy was more effective for Guillain-Barré Syndrome than plasma exchange (pooled change in disability score −0.11, 95% CI [−0.37,0.14]; pooled odds of improving by 1 or more grades on the Hughes disability scale 1.91, 95% CI [1.11, 3.28] in favor of IVIG; pooled odds of mortality 0.84, 95% CI [0.31, 2.29]). There was also insufficient evidence regarding paraprotein-associated chronic inflammatory demyelinating polyneuropathy and multifocal motor neuropathy. No evidence of benefit was observed for inclusion body myositis and myasthenia gravis. Based on evidence from lone randomised trials, there also exists evidence indicating that IVIG may be useful for treatment of dermatomyositis, stiff person syndrome and Lambert-Eaton Syndrome.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.279
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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