Hemoglobin Levels and Serum C-Reactive Protein in Patients With Moderate to Severe Hidradenitis Suppurativa
Bibliographic record
Abstract
Introduction: Anemia of chronic inflammation is associated with many inflammatory diseases. Little is known about anemia in hidradenitis suppurativa (HS). This study aimed to review the levels of hemoglobin (Hb) and investigate its relationship with serum C-reactive protein (CRP) and disease severity in HS patients. Methods: This was a retrospective chart review of all HS patients from 2015 to 2017 with Hb and CRP blood work. Patient demographics, disease severity, and laboratory results were extracted. Data were analyzed descriptively. A linear regression model was used for the association between Hb and CRP. Two-tailed t-tests and one-way ANOVA were used to compare differences between sexes and disease severities. Results: Of the 25 patients included, 14 (56%) were female. The median age and disease duration of all patients were 41 years (range, 19-56 years) and 10 years (range, 1-40 years), respectively. The overall median CRP level was 11.5 mg/dL (range, 1-86.7 mg/dL). The median Hb levels for women and men were and 123.5 g/L (range, 90-142 g/L) and 152.0 g/L (range, 109-166 g/L), respectively. Anemia was found in 42.9% (6/14) of women and 27.3% (3/11) of men. There was an inverse relationship between Hb and CRP levels in both sexes (men: r = ‒0.88; P = .0006; women r = ‒0.65; P = .012). Conclusions: Anemia was prevalent in the HS population, and Hb levels inversely correlated with CRP. Physicians should be aware that anemia is common in inflammatory states, and that CRP could be a biomarker in patients with HS.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".