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Record W6957796277 · doi:10.60692/qsy1r-eyv43

Serum insulin-like growth factor 1 (IGF-1) in multiple sclerosis: relation to cognitive impairment and fatigue

2018· article· en· W6957796277 on OpenAlexaboutno aff

Bibliographic record

VenueGreater South Information System · 2018
Typearticle
Languageen
FieldMedicine
TopicBiomedical and Chemical Research
Canadian institutionsnot available
Fundersnot available
KeywordsMultiple sclerosisCognitive impairmentCognitionAffect (linguistics)Chronic fatigue syndromeCorrelationPathogenesisMyelin

Abstract

fetched live from OpenAlex

Multiple sclerosis (MS) is a chronic demyelinating central nervous system (CNS) disease. Changes in insulin growth factor 1 (IGF-1) input to the brain can affect survival of myelin and CNS cells. The study aims to investigate the relation of serum IGF-1 levels with cognitive impairment and fatigue in MS patients.This study was conducted on 46 MS patients and 46 healthy controls. All participants were subjected to clinical assessment, serum IGF-1 levels, expanded disability status scale (EDSS), modified fatigue impact scale (MFIS), and Montreal cognitive assessment (MoCA) scale.There was no significant difference between patients and controls regarding serum IGF-1 levels (P = 0.19). However, low serum levels of IGF-1 have significantly greater odds for fatigue (P = 0.002) and cognitive impairment (P < 0.001). Also, serum IGF-1 levels have a significant negative correlation with MFIS (r = - 0.701 and P < 0.001) and a significant positive correlation with MoCA scale (r = + 0.84 and P < 0.001).The results, specifically that low levels of serum IGF-1 was associated with cognitive impairment and fatigue in MS, suggest that IGF-I may be involved in the pathogenesis of cognitive deficits and fatigue in MS disease.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.001

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 head0.092
GPT teacher head0.271
Teacher spread0.179 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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