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Record W3156242382 · doi:10.1093/asj/sjab176

Response to: Shockwave Therapy for the Prevention of Paradoxical Adipose Hyperplasia After Cryolipolysis: Myth or Reality?

2021· letter· en· W3156242382 on OpenAlexaff
Andreas Nikolis

Bibliographic record

VenueAesthetic Surgery Journal · 2021
Typeletter
Languageen
FieldMedicine
TopicBody Contouring and Surgery
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineAdipose tissueHyperplasiaSurgeryPathologyInternal medicine

Abstract

fetched live from OpenAlex

I would like to respond to the Letter to the Editor on the manuscript entitled “A Multicenter Evaluation of Paradoxical Adipose Hyperplasia Following Cryolipolysis for Fat Reduction and Body Contouring: A Review of 8658 Cycles in 2114 Patients.” 1,2 The author of the letter stipulates that the utilization of shockwave therapy has eliminated all cases of Paradoxical Adipose Hyperplasia (PAH) following CS in 2291 consecutive cycles. The author further attributes this to the combination treatment and more specifically to the anti-fibrosclerotic effect and decreased oxidative stress on post-cryolipolysis tissues.3 The observations are based on 30 patients satisfying inclusion criteria for their published review from a pool of 64 patients having 2 or greater cryolipolysis cycles followed by shockwave therapy. In the study, the author reported that 76.7% of patients found the therapy comfortable, 68.3% of patients were satisfied with the results, and 57.7% had their expectations met. The follow-up was a minimum of 12 weeks, but the mean follow-up was not reported for the group. Unfortunately, the challenge in interpreting the results resides in the following points: (1) less than 50% of patients treated (n = 64) were re-evaluated (n = 30) and of those re-evaluated, one-half were evaluated by email; and (2) the average length of follow-up is not mentioned, although the email and clinical follow-up at 3 months may not capture subtle changes initially present because a full-blown PAH picture may take more time to appear.3-6 In fact, the general recommendation is to avoid treating PAH cases until 12 months following cryolipolysis treatment, given the delayed presence of PAH and the uncertainty as to when the process arises and fully ends. Finally, the utilization of non-clinical follow-up is challenging. The patients who have historically been diagnosed with PAH largely assumed the treatment did not work and frequently believed the hypertrophy of a previously treated region was a result of slow weight gain. It would be beneficial to assess the reported 68.3% rate of “satisfaction” and 57.7% rate of “met expectations” following the treatment and evaluate why the numbers are on the lower side. A non-clinical or remote evaluation makes the diagnosis of PAH difficult, especially in light of the realization that many clinicians often have difficulty in making the initial diagnosis themselves unless they have either seen previous cases or the hypertrophy is truly exaggerated when combined with a clinical picture of minimal or small increase in weight compared with pretreatment weights. All in all, the concept put forth merits evaluation because the number of cycles in this center is significant without any obvious cases of PAH present; thus, I would urge the author to pursue a prospective clinical trial evaluating the 2 technologies with a 12-month follow-up, because anything we can do to prevent unwanted cases of PAH is very worthwhile. The author declared no potential conflicts of interest with respect to the research, authorship, and publication of this article. The author received no financial support for the research, authorship, and publication of this article.

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)0.001
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.037
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0370.023
Insufficient payload (model declined to judge)0.0050.003

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.

Opus teacher head0.056
GPT teacher head0.309
Teacher spread0.252 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2021
Admission routes1
Has abstractno

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