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Record W2399941035

Laser facial resurfacing: patient survey of recovery and results.

2000· article· en· W2399941035 on OpenAlexaff
Eugenie Brunner, Peter A. Adamson, John N. Harlock, David A.F. Ellis

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldMedicine
TopicDermatologic Treatments and Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineAcnePatient satisfactionSurgeryLaser treatmentLaserDentistryDermatology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine patient satisfaction with the postoperative recovery period and surgical outcome after facial laser resurfacing. DESIGN: Survey. PATIENTS: Patients who underwent facial laser resurfacing by two of the authors (PAA or DAFE) between 1995 and 1996. Questionnaires were completed by 47 of 100 patients. INTERVENTIONS: Facial laser resurfacing with the Sharplan CO2 laser and SilkTouch Scanner. MAIN OUTCOME MEASURES: Questionnaire. Statistical analysis was generated from a 5-point analogue scale. RESULTS: The overall side effects were moderate in severity, were well tolerated, and met the expectations of our patients. Redness was the most frequent side effect with an average duration of 3 months. Most patients returned to occupational and social activities at 2.5 weeks. Moderate lifestyle disruption was more frequent after full-face laser resurfacing than partial-face laser resurfacing. Excellent improvement was achieved for removal of fine wrinkles, improvement of skin quality, and sun-damaged skin. Good improvement was obtained for acne scarring and deep rhytids. Overall goals were attained in 89% of patients. CONCLUSIONS: Laser resurfacing produced excellent results for fine rhytids, skin quality, and sun-damaged skin. Return to social and occupational activities may occur early in recovery with the use of camouflage make-up. Patient education and close follow-up are necessary in the postoperative period.

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 score0.928
Threshold uncertainty score0.185

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 head0.053
GPT teacher head0.273
Teacher spread0.220 · 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

Citations8
Published2000
Admission routes1
Has abstractyes

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