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Does Patient History Influence Capsular Contracture? An Exploratory Analysis with Machine Learning.

Thomas M Johnstone¹, Daniel Najafali², Jennifer K Shah¹

¹Division of Plastic and Reconstructive Surgery, Stanford University School of Medicine, Stanford, CA, USA.

Aesthetic Plastic Surgery

|May 29, 2026

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This summary is machine-generated.

Administrative medical history alone has limited predictive power for identifying patients at risk of capsular contracture (CC) after breast procedures. While prior CC and irradiation were confirmed risk factors, they did not significantly improve prediction accuracy.

Area of Science:

Plastic Surgery
Medical Informatics
Machine Learning

Background:

Capsular contracture (CC) is a common complication following breast augmentation and reconstruction.
Predicting CC risk is challenging due to inconsistent risk factors across studies.
This study explores administrative medical history for CC risk prediction.

Purpose of the Study:

To evaluate the predictive utility of administrative medical history (ICD and CPT codes) for capsular contracture (CC) risk.
To identify reliable population-level predictors for CC development using machine learning.

Main Methods:

Utilized Merative MarketScan data (2003-2017) for breast augmentation/reconstruction patients.
Employed ICD codes for patient history and CPT codes for procedures.

Keywords:

Alloplastic reconstruction Artificial intelligence Breast Breast implants Breast reconstruction Capsular contracture Complications Contracture formation Implant Implant capsular contracture Implant-based reconstruction Machine learning Mammaplasty Outcomes prediction Postoperative complications Supervised machine learning

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Applied hyperparameter-tuned random forest and multivariable logistic regression models.

Main Results:

Included 112,489 patients; CC rate was 9.55%.
Random forest model achieved a 9.54% error rate.
Prior CC and irradiation were significant predictors, but their removal had minimal impact on model accuracy.

Conclusions:

Administrative medical history alone offers limited predictive value for CC.
Confirmed associations of prior CC and irradiation but found negligible incremental predictive contribution.
Current administrative data does not substantially enhance clinical prediction of CC risk.