Growth factor concentrations in platelet‐rich plasma for androgenetic alopecia: An intra‐subject, randomized, blinded, placebo‐controlled, pilot study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Platelet-rich plasma (PRP), processed from autologous peripheral blood, is used to treat androgenetic alopecia (AGA). OBJECTIVE: To determine the efficacy of PRP for hair growth promotion in AGA patients in a randomized, blinded, placebo-controlled, pilot clinical trial (NCT02074943). METHODS: The efficacy of an 8 week, five session, PRP treatment course was determined by measuring hair density and hair caliber changes in 10 AGA affected patients. For each PRP sample, the concentrations of selected growth factors were determined using a multiplex assay system. The clinical results were then correlated with the growth factor concentrations in PRP. RESULTS: At 16 weeks, 8 weeks after the last PRP injection, treated areas exhibited increased mean hair density (+12.76%) over baseline compared to placebo (+0.99%). Mean hair caliber decreased in both treated and placebo regions (-16.22% and -19.46%, respectively). Serial analysis of PRP significant variability in concentrations between patients. Overall, there was a positive correlation between GDNF concentration and hair density (P = .004). Trends, though not statistically significant, were also observed for FGF2 and VEGF. LIMITATIONS: Small sample size and lack of comparative cohorts receiving protocol variations limit confidence in the study data. CONCLUSIONS: This small pilot clinical trial suggests PRP treatment may be beneficial for AGA. However, the variable hair growth responses between patients indicate there is a significant opportunity to improve PRP therapy protocols for hair growth promotion. The variability in growth factor concentration in PRP suggests standardization of growth factors postprocessing might improve hair growth responses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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