Comparative analysis of comorbidity indexes in implant-based breast reconstruction

Introduction: Recent studies have used comorbidity indexes to stratify postsurgical complication risk across multiple surgical fields, including plastic surgery. However, such studies are lacking in implant-based breast reconstruction (IBBR). Understanding how comorbidity scores affect postsurgical outcomes in IBBR can help identify patients who may require additional medical surveillance after surgery. Methods: We conducted a retrospective analysis of adult female patients who underwent IBBR between January 2017 and December 2022 using the Merative (TM) Marketscan (R) Research Databases. ICD-10 diagnosis codes were used to calculate patients' scores on four different comorbidity indexes. Chi-squared tests were performed for demographic analysis, and multivariable logistic regression controlling for demographic and surgical variables, was conducted to determine associations between comorbidity indexes and adverse outcomes. Results: Among 16,287 IBBR patients, 3145 (19.3%) experienced a complication within 90 days. On regression analysis, the Modified Frailty Index 5-Item (mFI-5) demonstrated the strongest associations with complications (odds ratio=1.25 [1.18, 1.32]), compared to the Charlson Comorbidity Index, Elixhauser Comorbidity Index, and Modified Frailty Index 11-Item. Further regression analysis revealed that four out of the five mFI-5 comorbidities were independent risk factors for postsurgical complications. Conclusion: This study highlights important associations between comorbidity indexes and adverse postoperative outcomes in IBBR. mFI-5 demonstrated superior performance in postoperative risk stratification compared to the other indexes analyzed. These findings suggest that using mFI-5 in clinical settings may help identify high comorbidity patients who may benefit from additional monitoring and prophylactic measures. Further research is needed to understand how to mitigate the increased postoperative complication risk in these patients. (c) 2024 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.