Bibliographic record
Abstract
Letters18 February 2014Low-Level Laser Liposuction and HypertriglyceridemiaAlanna Weisman, MD and Gary F. Lewis, MDAlanna Weisman, MDFrom Toronto General Hospital, Toronto, Ontario, Canada.Search for more papers by this author and Gary F. Lewis, MDFrom Toronto General Hospital, Toronto, Ontario, Canada.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/L14-5004-3 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Background: Liposuction is the most common plastic surgery performed in the United States; however, it is invasive and associated with potential complications. Noninvasive liposuction is a rapidly growing industry, with 75 000 procedures done in the United States in 2012 and total expenditures estimated at $84 million (1). Various technologies are used to perform noninvasive liposuction, including radiofrequency ablation, cryotherapy, high-intensity focused ultrasonography, and low-level laser therapy (2). All of these technologies are described as having minimal complication rates.Objective: To report what we believe is the first case of severe hypertriglyceridemia induced by noninvasive liposuction.Case Report: We had been ...References1. The American Society for Aesthetic Plastic Surgery. Cosmetic Surgery National Data Bank. 2012. Accessed at www.surgery.org/sites/default/files/ASAPS-2012-Stats.pdf on 9 January 2014. Google Scholar2. Mulholland RS, Paul MD, Chalfoun C. Noninvasive body contouring with radiofrequency, ultrasound, cryolipolysis, and low-level laser therapy. Clin Plast Surg. 2011;38:503-20. [PMID: 21824546] CrossrefMedlineGoogle Scholar3. Caruso-Davis MK, Guillot TS, Podichetty VK, Mashtalir N, Dhurandhar NV, Dubuisson O, et al. Efficacy of low-level laser therapy for body contouring and spot fat reduction. Obes Surg. 2011;21:722-9. [PMID: 20393809] CrossrefMedlineGoogle Scholar4. Jackson RF, Roche GC, Wisler K. Reduction in cholesterol and triglyceride serum levels following low-level laser irradiation: a noncontrolled, nonrandomized pilot study. The American Journal of Cosmetic Surgery. 2010;27:177-84. Google Scholar5. Lewis GF, O'Meara NM, Soltys PA, Blackman JD, Iverius PH, Pugh WL, et al. Fasting hypertriglyceridemia in noninsulin-dependent diabetes mellitus is an important predictor of postprandial lipid and lipoprotein abnormalities. J Clin Endocrinol Metab. 1991;72:934-44. [PMID: 2005221] CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAuthors: Alanna Weisman, MD; Gary F. Lewis, MDAffiliations: From Toronto General Hospital, Toronto, Ontario, Canada.Disclosures: None disclosed. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=L13-1119. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics 18 February 2014Volume 160, Issue 4Page: 289-290KeywordsAdipocytesCholesterolPlastic surgeryRadiofrequency ablationRandomized trialsSerum triglyceridesSleep apneaTemperatureType 2 diabetesUltrasound imaging ePublished: 18 February 2014 Issue Published: 18 February 2014 Copyright & PermissionsCopyright © 2014 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".