A systematic review of morbidities suggestive of the multiple sclerosis prodrome
Bibliographic record
Abstract
The identification of a prodromal phase in multiple sclerosis (MS) could have major implications for earlier recognition and management of MS. The authors conducted a systematic review assessing studies of morbidities before, or at, MS onset or diagnosis.Areas covered: Two independent reviewers searched Medline, Embase, Psycinfo and CINAHL from inception to February 8th, 2019. To be eligible, studies had to be published in English and report the relative occurrence of at least one morbidity or symptom before, or at, MS onset or diagnosis among MS cases in comparison to a control group not known to have MS. Findings were narratively synthesized. Study quality was assessed using the Newcastle–Ottawa scale (NOS, maximum score 9).Expert opinion: Twenty-nine studies were included, which comprised 83,590 MS cases and 396,343 controls. Most were case-control studies (25/29), 8/29 were of high quality (NOS≥8) and 19/29 examined the period before MS symptom onset. Most studies assessing anxiety, depression, migraine and lower cognitive performance found these conditions to be more prevalent before MS onset or diagnosis relative to controls. There was limited evidence to implicate other conditions. Thus, there is evidence that anxiety, depression, migraine and lower cognitive performance form part of the MS prodrome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".