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Record W2107287638 · doi:10.1080/14764170600719775

Pneumatic skin flattening (PSF): A novel technology for marked pain reduction in hair removal with high energy density lasers and IPLs

2006· article· en· W2107287638 on OpenAlexaboutno aff
Gary Lask, David Friedman, Monica Elman, Nathalie Fournier, Raphi Shavit, Michael Slatkine

Bibliographic record

VenueJournal of Cosmetic and Laser Therapy · 2006
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFlatteningHair removalLaserReduction (mathematics)Energy densitySurgeryDermatologyOpticsEngineering physicsAstronomy

Abstract

fetched live from OpenAlex

BACKGROUND: Intense pulsed light (IPL) aesthetic treatment, such as hair removal from large areas, is often very painful. The problems of pain and discomfort can be divided into two different phases: immediate acute pain and the long-term, milder, post-treatment discomfort also associated with erythema. The immediate acute pain is felt during each treatment pulse and can accumulate to an intolerable sensation after a few shots, resulting in the necessity of either using topical analgesic creams which have several limitations or else to considerably slow down the process and/or apply less efficient low-energy densities. The immediate pain is created by the stimulation of sensory nerves located near the basal layer of the epidermis and adjacent to the treated hair follicles. There is an interest in a technology which would significantly reduce acute pain and post-treatment erythema, without the necessity of lowering the energy density or speed of treatments. OBJECTIVES: To examine the advantages of pneumatic skin flattening (PSF) with negative pressure: (i) for the reduction or elimination of pain, without chilling the skin, during hair removal with high energy density IPLs and pulsed lasers; (ii) for the reduction of post-treatment erythema; and (iii) for the enhancement of hair removal. MATERIALS AND METHODS: We have removed hair from large areas such as legs and backs with a high-energy (42 J/cm2) pulsed diode laser and an IPL (15-20 J/cm2). Room temperature gel was applied to the skin before treatment. In all cases but one, skin was not chilled by external cooling devices. We utilized a vacuum chamber and a transparent sapphire window to generate deep negative pressure in the treatment site and flatten the skin against the window. The level of applied vacuum was in the 200-600 mmHg range. We have compared the level of pain (I-V according to a modified McGill Pain Questionnaire) and the efficacy of hair removal on a total of 40 treatment sites The results of the vacuum-assisted treatment sites were compared with the results on adjacent control areas, obtained without the application of vacuum. Post-treatment erythema was also compared. RESULTS AND CONCLUSIONS: PSF significantly reduces pain in all patients, even when higher (+30%) treatment energy levels are applied. Skin is well protected thermally by the conductive sapphire window. Post erythema and edema is considerably reduced, as well. Hair removal efficacy is preserved or enhanced. Treatment is faster and is uninterrupted by pain, without the necessity to apply topical anesthetic over a large area. Blood expulsion resulting from flattening the skin has also enabled the treatment of thin hair in light-skinned patients, using yellow and green wavelengths (540 nm cut-off filter) and short pulse durations with a higher efficacy than with the 650 nm cut-off filter.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.245
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations38
Published2006
Admission routes1
Has abstractyes

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