Defining Double Capsules: A Clinical and Histological Study
Bibliographic record
Abstract
BACKGROUND: Macrotextured breast implants are associated with double capsules. There is little agreement as to what defines double capsules, how they present, and whether different degrees of double capsule exist. OBJECTIVES: This study aimed to define double capsules and report an association between double-capsule type and degree of tissue adherence. METHODS: Consecutive aesthetic patients undergoing explantation of Biocell (Allergan, Inc., Irvine, CA) implants between May 2018 and November 2018 were included if they were found to have double capsules intraoperatively. Patient demographics, implant characteristics, explantation reason, implant adherence, and intraoperative findings were recorded. Both adherent and double capsules were histologically examined. Data were analyzed by descriptive statistics. RESULTS: Eleven patients had 22 Biocell implants explanted during the study period. The average explantation time was 8.0 years. Sixteen implants were found to have some degree of nonadherence, and all areas of nonadherence were associated with double-capsule formation. Double capsules were either partial or complete. The architecture of the inner layer of double capsules varied between an organized capsular layer and a thin area of nascent capsule. Histologically, all capsular specimens demonstrated an overall hypocellular fibrous capsule with scattered chronic inflammatory infiltrates. Synovial metaplasia was present in all capsule types and spaces/cracks in the capsule were disproportionately represented in partially adherent capsules. CONCLUSIONS: This is the first study to identify a clinical and pathological correlation between double capsules and failed tissue adherence. Double capsules represent a spectrum of inner capsule formation ranging between nascent capsular tissue to a mature inner capsular layer.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".