Association between pyoderma gangrenosum and autoimmune connective tissue disorders: A systematic review
Why this work is in the frame
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Bibliographic record
Abstract
Pyoderma gangrenosum (PG) is a neutrophilic dermatosis that may result in painful cutaneous ulcers and can be challenging to manage.1 PG is frequently associated with underlying systemic disorders, particularly hematologic dyscrasias and inflammatory bowel disease (IBD).1, 2 PG has also been associated with autoimmune connective tissue disorders (AI-CTD), but its characteristics are not well documented. Hence, we sought to perform a systematic literature review to characterize the epidemiology, clinical characteristics, and management of patients with concomitant PG and AI-CTD. Following PRISMA guidelines, EMBASE, MEDLINE, and CENTRAL were searched from inception to July 23, 2023. AI-CTDs of interest include systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), antiphospholipid syndrome (APS), Sjögren syndrome (SS), scleroderma (Scl), and overlap syndrome (OS). Primary studies with original data for patients 18 years or older with an established diagnosis of AI-CTD were included. Non-English studies were excluded. Study quality and bias assessments were performed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) scale. Of the initial 702 articles identified in the search, 78 met the inclusion criteria and comprised 48 case reports, 21 case series, 6 cohort studies, and 3 case–control studies. A total of 234 patients were included, with a mean age of 57.3 years (range: 18–92). A majority occurred in females (76%) (Table 1). Lower legs (52.2%) were the most common site of PG involvement, followed by thigh/hips (18.7%), arms (11.0%), torso (9.9%), head/neck (3.3%), and mucous membranes (4.9%). The most prevalent AI-CTD associated with PG was RA (85.9%, n = 201), followed by SLE (12.0%, n = 28), Scl (1.3%, n = 3), APS (0.4%, n = 1), and SS (0.4%, n = 1). Six patients (2.6%) had OS. The mean treatment duration for PG was 39 weeks and included systemic corticosteroids (n = 65), calcineurin inhibitors (n = 21), tumor necrosis factor (TNF)-alpha inhibitors (n = 14), antibiotics (n = 19), purine antagonists (n = 18), interleukin (IL)-1 receptor antagonists (n = 3), dapsone (n = 7), cyclophosphamide (n = 7) and Janus kinase (JAK) inhibitors (n = 2) (Table 1). Treatment type did not vary significantly with AI-CTD. There were 88 patients (37.6%) with complete resolution and 12 patients (5.1%) with recurrences. Two deaths (0.9%) were reported prior to PG resolution due to other comorbidities, one of which was sepsis. This review is limited by study heterogeneity, reporting bias, and low-quality studies, as the majority were case reports. The pathogenesis of PG and AI-CTD both result from autoreactive T-cells and aberrant proinflammatory cytokine production, including IL-1, IL-17, IL-36, and TNF-alpha, among others.2, 3 Hence, both conditions often require long courses of immunosuppressants that come with inherent risks, yet evidence-based guidelines remain sparse. IL-36 is the key cytokine responsible for perpetuating neutrophilic inflammation in PG.4, 5 Spesolimab, a novel IL-36 receptor antagonist, may be a promising and safer off-label option given its targeted mechanism of action, but further studies are necessary. In conclusion, our review found that RA is the predominant AI-CTD associated with PG, the lower extremities are the most common sites of PG involvement, and females with concomitant AI-CTD represented a majority of PG cases in a 3:1 ratio. We propose an algorithm for working up patients with a new diagnosis of PG for suspected AI-CTD (Figure 1). Clinicians managing patients with a new onset of PG on the lower extremities should acknowledge this association and consider further workup for underlying AI-CTD, especially for RA in females when hematologic disorders or IBD have been ruled out. We would like to thank Ms. Risa Shorr, MLIS, Librarian at The Ottawa Hospital, for assisting with the literature search query. Data is available on request from the authors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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