Incidence of Paradoxical Adipose Hyperplasia After Cryolipolysis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Paradoxical adipose hyperplasia (PAH) is a rare complication of cryolipolysis, characterized by an unexpected overgrowth of adipocytes in the treatment area. Emerging literature suggests that PAH may be underrecognized and underreported. Because of the increasing popularity of cryolipolysis for nonsurgical fat reduction, we sought to identify the overall incidence of PAH as well as the incidence by sex and treatment device, time to diagnosis, and any additional complications of cryolipolysis. In this systematic review and meta-analysis, databases (MEDLINE, Embase, CINAHL, Web of Science, Scopus, and CENTRAL) were searched from inception to May 11, 2025, for studies reporting on PAH incidence in cryolipolysis patients. The primary outcome was the literature-pooled PAH incidence, estimated using a nonpairwise generalized linear mixed model for meta-analysis. Secondarily, we descriptively reviewed treatment devices utilized, time to PAH diagnosis, and additional cryolipolysis complications. Twenty-eight studies encompassing 13,078 patients were included in the review. Low-certainty evidence suggested that the pooled incidence of PAH was 0.22% (95% CI, 0.10-0.47), with 29 cases identified (1 in 455 patients). Sex-based risk differences were not statistically significant. Only 4 studies reported sufficient follow-up duration (≥16 weeks). PAH cases were reported with various devices and applicators, and although 10 of the 29 PAH cases (34.5%) involved the CoolCore applicator, insufficient data precluded device-based meta-analysis. Overall, the incidence of PAH following cryolipolysis appears to be higher than manufacturer reports. These findings emphasize the need for comprehensive risk disclosure, improved awareness and adverse event reporting, risk factor identification, and further investigation into the pathogenesis of PAH. Level of Evidence: 3 (Therapeutic).
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.026 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".