Efficacy of long pulse neodymium-doped yttrium aluminium garnet 1064 laser permanent hair reduction treatment in skin types V and VI Nigerian patients
Bibliographic record
Abstract
Background: There are no studies examining the use, safety, efficacy, effective fluence and pulse duration of Laser hair reduction in Nigerians. This study aimed to document the safety, efficacy, effective fluence and pulse duration, and the number of Laser sessions to achieve permanent hair reduction. Methods: A retrospective review of Laser hair removal in 87 FitzPatrick skin type V and VI patients from January 2017 to August 2021 using the neodymium-doped yttrium aluminium garnet (Nd:Yag). The fluence (Joules/cm3), pulse duration (msecs), Laser site and interval between Laser sessions were documented. Data was summarized using frequencies and percentage proportion. Comparison of pulse duration, fluence, and the number of sessions between different body sites was tested using analysis of variance. Results: A total of 354 laser sessions were performed in 87 patients made up of 80 females and 7 males; mean age of 35.8±9.24 years. The face was the most frequently treated site (67.5% of the sessions). The mean number of laser sessions, pulse duration and fluence were 4.07±4.22, 19.38±1.48 (msec) and 18.22±1.29 (J/cm3) respectively. An average of 6 sessions was required to achieve permanent hair reduction: the face required a significantly lower number of sessions, p=0.043. Conclusions: The long pulse Nd:Yag 1064 laser is an effective and safe Laser for hair removal in skin types V and VI. The effective, safe pulse duration and fluence are 16 to 22 msec and 15 to 20 J/cm2 respectively. The face requires fewer number of Laser sessions.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".