Not All Breast Implants Are Equal: A 13-Year Review of Implant Longevity and Reasons for Explantation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Augmentation mammaplasty is the most common aesthetic procedure. Textured implants control implant position and have improved capsular contracture rates; however, the impact of texturing on longevity and clinical findings at explantation is unclear. METHODS: All cases of explantation between January of 2005 and April of 2017 from an aesthetic practice were reviewed retrospectively. Patient demographics, implant characteristics, time to explantation, and clinical presentation and intraoperative findings at explantation were analyzed. RESULTS: Five hundred thirty-nine breast implants were explanted during the study period: 249 saline, 147 smooth gel, 123 Biocell, and 20 other nonaggressively textured breast implants. Average time from placement to explantation was 7.5, 5.6, 4.9, and 4.0 years for saline, other textured, smooth gel, and Biocell implants, respectively (p = 3.25e-08). The percentage of implants removed associated with implant performance failure was 50.3, 57.4, 75.0, and 85.4 percent for smooth gel, saline, other textured, and Biocell implants, respectively (p = 7.25e-09). In addition, 21.1 percent of Biocell implants versus 1.4 percent of all other implants presented with pain (p = 2.71e-15). Forty-five Biocell implants had double capsules; this phenomenon was not observed with any other implant type (p = 5.85e-37). Seven Biocell implants had late seromas, compared to three late seromas with any other implant type (p = 0.0013). CONCLUSIONS: Here, the authors provide evidence that Biocell implants have the shortest time to explantation and the highest proportion of implants associated with implant performance failure. This information should complement the informed consent process when selecting an appropriate implant.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it