Survival of Densely Packed Follicular Unit Grafts Using the Lateral Slit Technique
Bibliographic record
Abstract
BACKGROUND: The use of densely packed follicular unit grafts (>30 grafts/cm(2)) is a highly debated issue, with some claiming decreased survival rates. Those who perform dense packing routinely do not believe they have seen any impaired survival. However, no prior study has rigorously analyzed densely packed areas to assess survival rates. OBJECTIVE: In this study, the authors assessed the survivability of densely packed (>70 grafts/cm(2)) follicular unit grafts using the lateral slit technique. METHODS: This study was a strictly observational study in one patient. Several 1-cm(2) areas tattooed on the mid scalp were grafted at densities ranging from 23 to 72 grafts/cm(2) using the lateral slit technique. The area surrounding the observation sites was transplanted at a density of 30 to 40 grafts/cm(2). RESULTS: Examination of the most densely packed area (72 grafts/cm(2)) at 8 months posttransplant revealed that the number of implanted grafts showing growth was 98.6% whereas the least densely transplanted area (23 grafts/cm(2)) revealed a growth rate of 95.6%. CONCLUSION: This is the first study that demonstrates high growth rates in densely packed follicular units using the lateral slit technique, even at densities of 72 grafts/cm(2). These data are in contradistinction to previously performed studies using older methodologies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".