Impact of Extracorporeal Photopheresis on Blood Parameters of Atopic Dermatitis Patients
Bibliographic record
Abstract
BACKGROUND: Extracorporeal photopheresis (ECP) is a safe treatment modality with immunomodulatory effects. The latter may also explain efficacy of ECP in patients with atopic dermatitis (AD). OBJECTIVE: We aimed to assess various blood parameters of AD patients who underwent ECP over a maximum 1-year treatment period. METHODS: We performed a retrospective single-center chart review (clinical data, laboratory data) of adult patients with AD who had received for at least 3 ECP cycles, in part combined with other treatment modalities. RESULTS: We studied 60 patients with AD (85% extrinsic type, 15% intrinsic type) who had median number of 14 (4-23) ECP cycles within a maximum 1-year treatment. When compared with baseline, leukocytes and lymphocytes remained significantly decreased after 3-, 6-, 9-, and 12-month ECP ( P = 0.014 and P = 0.0012, respectively). A significant decline of eosinophils, as well as eosinophilic cationic protein levels, was observed after 3-, 6-, 9-, and 12-month ECPs ( P = 0.011 and P = 0.0017, respectively). Total serum immunoglobulin E (IgE), as well as lactate dehydrogenase, were significantly decreased at 3-, 6-, 9-, and 12-month evaluation compared with baseline ( P < 0.00001 and P = 0.00007, respectively). Patients with slight or marked improvement of AD after their ECP treatment period had significantly higher median baseline serum IgE levels than patients who did not respond to ECP ( P = 0.0023). CONCLUSIONS: Several laboratory parameters, including eosinophils, eosinophilic cationic protein, total serum IgE, and lactate dehydrogenase, which declined under ECP, are well-known disease biomarkers for AD patients. With normalization of the abovementioned laboratory parameters, a clinical response to ECP treatment was observed in almost two thirds of patients, confirming that ECP may be an effective combination treatment modality for AD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".