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Record W4403563718 · doi:10.1016/j.msard.2024.105943

Comorbidities and their association with outcomes in the multiple sclerosis population: A rapid review

2024· review· en· W4403563718 on OpenAlexafffundabout
Hanna A. Frank, Melissa Chao, Helen Tremlett, Ruth Ann Marrie, Lisa M. Lix, Kyla A. McKay, Fardowsa Yusuf, Feng Zhu, Mohammad Ehsanul Karim

Bibliographic record

VenueMultiple Sclerosis and Related Disorders · 2024
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsSt. Paul's HospitalVancouver Hospital and Health Sciences CentreUniversity of ManitobaHealth Sciences CentreManitoba HealthUniversity of British Columbia
FundersMultiple Sclerosis Society of Canada
KeywordsMedicineMultiple sclerosisAssociation (psychology)PopulationPsychiatryEnvironmental healthPsychotherapist

Abstract

fetched live from OpenAlex

INTRODUCTION: Multiple sclerosis (MS) has a high comorbidity burden. Despite known associations with adverse outcomes, a comprehensive evaluation of the specific associations between individual comorbidities and disability, treatment initiation, and mortality remains underexplored. This study aimed to review and summarize existing evidence on the association between comorbidities and these three MS outcomes. METHODS: A rapid review spanning the period from January 2002 to October 2023 was conducted following the Cochrane Rapid Review Methods Group recommendations. MEDLINE, Embase, and the grey literature were searched to identify studies examining the effects of comorbidities on disability, treatment initiation, and mortality among individuals with MS. Data extraction and risk of bias assessments were systematically performed, with the Newcastle-Ottawa scale and A MeaSurement Tool to Assess systematic Reviews (AMSTAR-2) criteria for observational studies and systematic reviews respectively. RESULTS: The review included 100 primary studies, encompassing 88 different comorbidities. Most study populations were between 60-80% female, with an average age of 30-45 years at study start. The majority of included studies were conducted in Europe, North America, and Asia (specifically the Middle East). Over half (66%) of specific comorbidity-outcome relationships were examined within a single study only, and just two studies examined treatment initiation as an outcome. Methods used to assess comorbidities and outcomes varied widely and included self-report measures, medical records and diagnostic codes, and standardized clinical assessments. Depression was consistently associated with greater disability (adjusted hazard ratio (aHR): 1.50-3.59) and mortality (aHR: 1.62-3.55). Epilepsy was similarly associated with increased disability (aOR: 1.13-1.77) and increased mortality (aHR: 2.23-3.85). Diabetes was generally associated with increased mortality (aHR: 1.39-1.47), but results for disability were inconsistent. Most other conditions were examined in one or two studies only or findings varied across studies, unable to collectively indicate a clear association. Although the anxiety-disability relationship was assessed by 24 studies, the findings varied in terms of the presence, direction, and strength of a possible association, requiring nuanced interpretation. CONCLUSIONS: This study identifies relationships between various comorbidities and three outcomes in MS, providing a foundation for future research and clinical guidelines. People with psychiatric, metabolic, and neurological conditions may be at a higher risk of MS disease progression and may therefore benefit from the targeted treatment of their comorbidities. Overall, comorbidities have varying associations with MS outcomes and individual associations require further exploration. However, there is evidence that some comorbidities indicate worse disability and higher mortality risk, and present barriers to initiating MS treatment, making the prevention and management of comorbidities an integral piece of MS patient care. PROTOCOL: The protocol for this rapid review was registered on PROSPERO (ID: CRD42023475565) and published on Protocol Exchange (https://doi.org/10.21203/rs.3.pex-2438/v1).

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.909
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.094
GPT teacher head0.313
Teacher spread0.219 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations15
Published2024
Admission routes3
Has abstractyes

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