Clinical evaluation of Morgellons disease in a cohort of North American patients
Bibliographic record
Abstract
Morgellons disease (MD) is a dermatological condition characterized by aberrant production of keratin and collagen fibers in skin. Although infection with Borrelia burgdorferi, the causative agent of Lyme disease (LD), has been associated with MD, relatively few studies have hitherto provided epidemiological evidence regarding this association. A cohort of 1000 seropositive North American LD patients was evaluated for the presence of MD. Patients were diagnosed with MD based on detection of microscopic fibers in skin lesions or under unbroken skin. Demographic and clinical features of MD patients were analyzed, and laboratory testing for tickborne coinfections and other infectious agents, was performed. Subjective and objective features of MD were analyzed using statistical methods. Of 1000 seropositive LD patients, 60 (6%) were diagnosed with MD. Of these 60 patients, 75% were female and 78% presented in the late disseminated stage of MD. All 60 patients (100%) were seropositive for B. burgdorferi infection. Tickborne coinfections in these patients included Babesia spp (62%), Bartonella and Rickettsia (25% each), Ehrlichia (15%) and i (10%). Helicobacter pylori was detected in 12% of MD patients. In all, 77% of MD patients had one or more coinfections. This study confirms recent findings that MD occurs in a limited subset of LD patients. The clinical and genetic determinants of MD in LD patients require further study.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".