A systematic review of the incidence and prevalence of comorbidity in multiple sclerosis: Overview
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.
Bibliographic record
Abstract
BACKGROUND: Comorbidity is an area of increasing interest in multiple sclerosis (MS). OBJECTIVE: The objective of this review is to estimate the incidence and prevalence of comorbidity in people with MS and assess the quality of included studies. METHODS: We searched the PubMed, SCOPUS, EMBASE and Web of Knowledge databases, conference proceedings, and reference lists of retrieved articles. Two reviewers independently screened abstracts. One reviewer abstracted data using a standardized form and the abstraction was verified by a second reviewer. We assessed study quality using a standardized approach. We quantitatively assessed population-based studies using the I² statistic, and conducted random-effects meta-analyses. RESULTS: We included 249 articles. Study designs were variable with respect to source populations, case definitions, methods of ascertainment and approaches to reporting findings. Prevalence was reported more frequently than incidence; estimates for prevalence and incidence varied substantially for all conditions. Heterogeneity was high. CONCLUSION: This review highlights substantial gaps in the epidemiological knowledge of comorbidity in MS worldwide. Little is known about comorbidity in Central or South America, Asia or Africa. Findings in North America and Europe are inconsistent. Future studies should report age-, sex- and ethnicity-specific estimates of incidence and prevalence, and standardize findings to a common population.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it