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Treatment of Facial Lentigines in Peutz–Jeghers Syndrome With an Intense Pulsed Light Source

2002· article· en· W2065585269 on OpenAlexaff
B. Kent Remington, Todd Remington

Bibliographic record

VenueDermatologic Surgery · 2002
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineIntense pulsed lightDermatologyPeutz–Jeghers syndromeMucocutaneous zonePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Peutz-Jeghers syndrome is a hereditary condition characterized by distinctive mucocutaneous lentigines and intestinal hamartomatous polyposis. The cutaneous lesions may be cosmetically disfiguring and frequently present a therapeutic challenge. OBJECTIVE: To determine if intense pulsed light (IPL) is effective in treating facial lentigines in Peutz-Jeghers syndrome. METHODS: The IPL, utilizing a 590 nm cutoff filter, was used to treat facial lentigines in a 10-year-old girl with Peutz-Jeghers syndrome. RESULTS: A series of 12 treatment sessions, each to different facial regions, resulted in complete clearance of lentigines in the treated areas. Most of the lentigines resolved after a single treatment, with a few areas requiring a second treatment. CONCLUSION: In this case, treatment with IPL resulted in dramatic improvement of cosmetically disfiguring lentigines. To our knowledge, this is the first report of using IPL in Peutz-Jeghers syndrome.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.256
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations30
Published2002
Admission routes1
Has abstractyes

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