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Record W1985235854 · doi:10.1177/135245850000600509

Multiple sclerosis, disease modifying treatments and depression: a critical methodological review

2000· review· en· W1985235854 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMultiple Sclerosis Journal · 2000
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsDepression (economics)MoodPsychiatryDiseasePsychologyClinical psychologyMood disordersMultiple sclerosisMajor depressive disorderPlaceboMedicineAnxietyAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Major depression affects one in two patients with multiple sclerosis (MS) during the course of their lifetime. This adds to the morbidity associated with the disorder and may contribute to an increased mortality rate because of suicide. Over the past few years, with the advent of disease modifying treatments for MS, a new concern with respect to mood has arisen, namely the possibility that some of these drugs may have depression as a clinically significant side effect. OBJECTIVE: To ascertain whether disease modifying treatments in MS are associated with the development of depression or the worsening of a depressive illness. METHODOLOGY: A MEDLINE and PSYCHLIT search focusing on depression and disease modifying treatments going back to 1993 (the publication date of the results of the first randomised, placebo controlled trial). The methodology pertaining to the assessment of depression is critically reviewed. Furthermore, a critical summary is provided of treatment modalities for the depressed MS patient. RESULTS: There are conflicting data that depression may occur with some disease modifying drugs, particularly interferon beta-1b. However, all studies reveal limitations with respect to the assessment of mood. Some reports, despite omitting details of how mentation was assessed, still comment on the presence or absence of depression. Others suffer from one or more of the following shortcomings: a failure to assess premorbid risk factors for mood disorder; a reliance on one question to assess depression; the utilisation of self report mood rating scales of questionable validity; neglecting to distinguish depression as a symptom from depression as a syndrome (i.e. major depression as defined by the DMS-1V). CONCLUSIONS: Given the many methodological pitfalls inherent in all studies to date, it is premature to conclude that disease modifying drugs are associated with depression. Evidence suggests that treatment of depression, irrespective of a putative association with a disease modifying agent, is frequently effective. This applies to pharmacotherapy or psychotherapy, although the former may be preferred should depression arise during a course of treatment with a disease modifying agent. Multiple Sclerosis (2000) 6 343 - 348

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
gptMetaresearchMeta-epidemiology (broad)
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.003
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.558
GPT teacher head0.466
Teacher spread0.092 · 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