A Step Forward Toward the Understanding of the Long-Term Pathogenesis of Double Capsule Formation in Macrotextured Implants: A Prospective Histological Analysis
Bibliographic record
Abstract
BACKGROUND: Although increasingly reported in the literature, most plastic surgeons cannot define the etiology of double capsules. Often an incidental finding at implant exchange, double capsules are frequently associated with macrotextured devices. Several mechanisms have been proposed, including at the forefront that shearing causes a delamination of the periprosthetic capsule into a double capsule. OBJECTIVES: This study was designed to confirm the hypothesis that mechanical forces are involved in formation of double capsules by histological analysis. METHODS: A prospective analysis of consecutive implants with double capsules removed over 2 years was performed. Data collected at the time of surgery included Baker classification, reason for explant, implant manufacturer and style, and any presence of a seroma associated with the capsule. Specimens were sent for analysis by histology utilizing hematoxylin and eosin and alpha-smooth muscle actin staining techniques. RESULTS: Eight double capsules were collected for specimen analysis. All capsules demonstrated evidence of granulation tissue, alpha-smooth muscle actin positive myofibroblasts, and folds with embedded texture. Fibrosis surrounded weak areas with presence of layering and splitting, creating a potential space that is prone to separation. Tears and folds from granulomatous reaction are also present within the outer layer of the double capsule, which can only be explained by a mechanical shearing force as a pathogenic mechanism. CONCLUSIONS: Understanding the pathogenesis of double capsules may allow plastic surgeons to refine their indications for macrotextured implants while providing guidance to patients on avoidance of activities that produce shear-forces. The findings support the hypothesis that shearing forces delaminate the capsule into 2 separate distinct capsules.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".