An Analysis of Industry Payments Toward Physicians in the United States—Cryolipolysis
Bibliographic record
Abstract
Background: Cryolipolysis has emerged as a nonsurgical fat reduction alternative to liposuction. Industry payments may impact how physician authors view medical devices in the literature. Under-reporting financial conflicts of interest has raised concerns about full transparency between industry and physicians. Objectives: We aim to determine the impact industry payments to physicians have on the cryolipolysis literature and whether there is under-reporting of financial conflicts of interest in the literature. Methods: We collated all articles that cite the pivotal trial in the Food and Drug Administration approval of a cryolipolysis device. Articles were read independently and coded as favourable or neutral. A separate researcher screened the Centers for Medicare & Medicaid Services Open Payments database for direct or in-kind payments and recorded financial conflicts of interest. Results: A total of 19 articles met the inclusion criteria. This included 37 unique authors across multiple specialties. Eighteen (95%) published articles had at least one author who received industry payment. Payments totalled $1,476,564.16. Twelve (63%) articles were positive, and 7 (37%) neutral. Of the 31 authors who received payments, 11 (35%) did not report a conflict of interest. The majority of industry payments assessed were for consulting fees, which totalled $980,334.86 (66.4%). Conclusions: We found the majority of published opinions on cryolipolysis from the United States were written by physicians who received industry payments. We also found financial conflicts of interest around cryolipolysis devices are under-reported in the literature.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".