Prospective Efficacy and Safety Study of an Innovative Kerascalp Hair Growth Serum in Mild-to-Moderate Alopecia in India: Regrowth Study
Bibliographic record
Abstract
BACKGROUND AND AIM: Male and female pattern baldness, commonly known as androgenetic alopecia is the most common type of alopecia, often predetermined genetically, which generally affects the scalp and is characterized by progressive terminal hair loss, known as miniaturization. This study aimed to assess the safety and efficacy of Kerascalp hair serum, a unique combination of esculin, ximenynic acid, and lauric acid, extracted from natural sources in subjects with mild to moderate androgenetic alopecia. METHODS: An open-label, single-arm clinical study was conducted on healthy males and females aged 18-60 years. Each subject applied the hair serum once daily for 90 days. The efficacy of hair serum was evaluated in terms of the following outcome variables: anagen and telogen ratio (A:T ratio), hair thickness, hair density, hair fall, and hair strength assessment. Subjects were assessed on day 0, day 30, day 60, day 90, and on follow-up day 120. RESULTS: Thirty subjects completed all assessment visits. After using the hair serum for 90 days, statistically significant (p<0.0001) improvement was observed in A:T ratio, hair density, hair thickness, and hair strength; a statistically significant reduction (p<0.0001) in hair fall was also observed. Moreover, improvement in general appearance of hair (in terms of hair volume and density) and scalp (in terms of itchiness, redness, roughness, and dryness) was recorded through dermatological assessment at each treatment visit and at follow-up visit compared to baseline. No adverse event was recorded during the study period, and on follow-up. CONCLUSIONS: The results of this clinical study suggest that a 90 days treatment with a phyto-ingredient-based Kerascalp hair serum is safe and effective in significantly improving A:T ratio, hair density, hair thickness, and hair strength, while reducing hair shedding. The improvement in the test parameters persists, even 30 days after stopping the usage of the serum.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".