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OBJECTIVE: To create a novel comorbidity score tailored for surgical database research. SUMMARY BACKGROUND DATA: Despite their use in surgical research, the Elixhauser (ECI) and Charlson Comorbidity Indices (CCI) were developed nearly four decades ago utilizing primarily non-surgical cohorts. METHODS: Adults undergoing 62 operations across 14 specialties were queried from the 2019 National Inpatient Sample (NIS) using International Classification of Diseases, 10th Revision (ICD-10) codes. ICD-10 codes for chronic diseases were sorted into Clinical Classifications Software Refined (CCSR) groups. CCSR with non-zero feature importance across four machine learning algorithms predicting in-hospital mortality were used for logistic regression; resultant coefficients were used to calculate the Comorbid Operative Risk Evaluation (CORE) score based on previously validated methodology. Areas under the receiver operating characteristic (AUROC) with 95% Confidence Intervals (CI) were used to compare model performance in predicting in-hospital mortality for the CORE score, ECI, and CCI. Validation was performed using the 2016-2018 NIS, combined 2018-2019 Florida and New York State Inpatient Databases (SID), and 2016-2022 institutional data. RESULTS: 699,155 records from the 2019 NIS were used for model development. The CORE score better predicted in-hospital mortality compared to the ECI within the NIS (0.90, 95%CI:0.90-0.90 vs. 0.84, 95%CI:0.84-0.84), SID (0.91, 95%CI:0.90-0.91 vs. 0.86, 95%CI:0.86-0.87), and institutional (0.88, 95%CI:0.87-0.89 vs. 0.84, 95%CI:0.83-0.85) databases (all P<0.001). Likewise, it outperformed the CCI for the NIS (0.76, 95%CI:0.76-0.76), SID (0.78, 95%CI:0.77-0.78), and institutional (0.62, 95%CI:0.60-0.64) cohorts (all P<0.001). CONCLUSIONS: The CORE score may better predict in-hospital mortality after surgery due to comorbid diseases in outcome-based research.
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INTRODUCTION: Immediate breast reconstruction (IBR) following mastectomy has been shown to improve quality of life and partially mitigate the adverse psychological impacts associated with the procedure. The present study examined hospital-based and patient-level disparities in utilization and outcomes of IBR following mastectomy. METHODS: All female adult hospitalizations with a diagnosis of breast cancer undergoing mastectomy were identified in the 2016 to 2020 National Inpatient Sample. Safety-net hospitals (SNH) were defined as those in the top quartile of all Medicaid or self-pay admissions. Patients who underwent mastectomy at SNH comprised the SNH cohort (others: Non-SNH). Multivariable models were developed to examine the impact of SNH status and patient factors on rates of IBR. RESULTS: Of an estimated 127,740 hospitalizations, 28,330 (22.2%) were treated at SNH. The proportion of patients receiving IBR increased from 46.7% in 2016 to 51.7% in 2020 (nptrend<.001). Compared to others, SNH were younger (57.9 ± 13.5 vs 58.3 ± 13.5 years) and less commonly White (45.6 vs 69.9%) (all P < .001). Additionally, SNH were more likely to receive unilateral mastectomy (67.1 vs 55.2%) but less frequently underwent IBR (37.7 vs 51.5%) (all P < .001). After adjustment, Black and Asian race, SNH, and bilateral mastectomy were associated with decreased odds of IBR. Increasing IBR hospital volume did not eliminate the observed racial disparity at non-SNH or SNH. CONCLUSION: There are disparities in rates of IBR following mastectomy attributable to SNH status. Future work is needed to ensure all patients have access to reconstructive care irrespective of payer status or the hospital at which they receive care.