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BACKGROUND: Expedited discharge following esophagectomy is controversial due to concerns for higher readmissions and financial burden. The present study aimed to evaluate the association of expedited discharge with hospitalization costs and unplanned readmissions following esophagectomy for malignant lesions. METHODS: Adults undergoing elective esophagectomy for cancer were identified in the 2014-2019 Nationwide Readmissions Database. Patients discharged by postoperative day 7 were considered Expedited and others as Routine. Patients who did not survive to discharge or had major perioperative complications were excluded. Multivariable regression models were constructed to assess association of expedited discharge with index hospitalization costs as well as 30- and 90-day non-elective readmissions. RESULTS: Of 9,886 patients who met study criteria, 34.6% comprised the Expedited cohort. After adjustment, female sex (adjusted odds ratio [AOR] 0.71, p = 0.001) and increasing Elixhauser Comorbidity Index (AOR 0.88/point, p

BACKGROUND: While insurance reimbursements allay a portion of costs associated with cardiac operations, uncovered and additional fees are absorbed by patients. An examination of financial toxicity (FT), defined as the burden of patient medical expenses on quality of life, is warranted. Therefore, the present study used a nationally representative database to demonstrate the association between insurance status and risk of financial toxicity (FT) among patients undergoing major cardiac operations. METHODS: Adults admitted for elective coronary artery bypass grafting (CABG) and isolated or concomitant valve operations were assessed using the 2016-2019 National Inpatient Sample. FT risk was defined as out-of-pocket expenditure >40% of post-subsistence income. Regression models were developed to determine factors associated with FT risk in insured and uninsured populations. To demonstrate the association between insurance status and risk of FT among patients undergoing major cardiac operations. RESULTS: Of an estimated 567,865 patients, 15.6% were at risk of FT. A greater proportion of uninsured patients were at risk of FT (81.3 vs. 14.8%, p

BackgroundSociodemographic disparities in atrial fibrillation (AF) management and thromboembolic prophylaxis have previously been reported, which may involve inequitable access to left atrial appendage occlusion (LAAO) during cardiac surgery. The present study aimed to evaluate the association of LAAO utilization with sex, race, and hospital region among patients with AF undergoing heart valve operations.MethodsAdults with AF undergoing valve replacement/repair in the 2012-2019 National Inpatient Sample were identified and stratified based on concurrent LAAO. Multivariable linear and logistic regressions were developed to identify factors associated with LAAO utilization. Mortality, complications including stroke and thromboembolism, hospitalization costs and length of stay (LOS) were secondarily assessed.ResultsOf 382,580 patients undergoing valve operations, 18.7% underwent concomitant LAAO. Over the study period, the proportion of female patients receiving LAAO significantly decreased from 44.8% to 38.9% (p

BackgroundEmergency general surgery (EGS) operations are associated with substantial risk of morbidity including postoperative respiratory failure (PRF). While existing risk models are not widely utilized and rely on traditional statistical methods, application of machine learning (ML) in prediction of PRF following EGS remains unexplored.ObjectiveThe present study aimed to develop ML-based prediction models for respiratory failure following EGS and compare their performance to traditional regression models using a nationally-representative cohort.MethodsNon-elective hospitalizations for EGS (appendectomy, cholecystectomy, repair of perforated ulcer, large or small bowel resection, lysis of adhesions) were identified in the 2016-18 Nationwide Readmissions Database. Factors associated with PRF were identified using ML techniques and logistic regression. The performance of XGBoost and logistic regression was evaluated using the receiver operating characteristic curve and coefficient of determination (R2). The impact of PRF on mortality, length of stay (LOS) and hospitalization costs was secondarily assessed using generalized linear models.ResultsOf 1,003,703 hospitalizations, 8.8% developed PRF. The XGBoost model exhibited slightly superior discrimination compared to logistic regression (0.900, 95% CI 0.899-0.901 vs 0.894, 95% CI 0.862-0.896). Compared to logistic regression, XGBoost demonstrated excellent calibration across all risk levels (R2: 0.998 vs 0.962). Congestive heart failure, neurologic disorders, and coagulopathy were significantly associated with increased risk of PRF. After risk-adjustment, PRF was associated with 10-fold greater odds (95% confidence interval (CI) 9.8-11.1) of mortality and incremental increases in LOS by 3.1 days (95% CI 3.0-3.2) and $11,900 (95% CI 11,600-12,300) in costs.ConclusionsLogistic regression and XGBoost perform similarly in overall classification of PRF risk. However, due to superior calibration at extremes of risk, ML-based models may prove more useful in the clinical setting, where probabilities rather than classifications are desired.

BackgroundExpedited discharge following esophagectomy is controversial due to concerns for higher readmissions and financial burden. The present study aimed to evaluate the association of expedited discharge with hospitalization costs and unplanned readmissions following esophagectomy for malignant lesions.MethodsAdults undergoing elective esophagectomy for cancer were identified in the 2014-2019 Nationwide Readmissions Database. Patients discharged by postoperative day 7 were considered Expedited and others as Routine. Patients who did not survive to discharge or had major perioperative complications were excluded. Multivariable regression models were constructed to assess association of expedited discharge with index hospitalization costs as well as 30- and 90-day non-elective readmissions.ResultsOf 9,886 patients who met study criteria, 34.6% comprised the Expedited cohort. After adjustment, female sex (adjusted odds ratio [AOR] 0.71, p = 0.001) and increasing Elixhauser Comorbidity Index (AOR 0.88/point, pConclusionExpedited discharge after esophagectomy was associated with decreased costs and unaltered readmissions. Prospective studies are necessary to robustly evaluate whether expedited discharge is appropriate for select patients undergoing esophagectomy.

BackgroundWhile insurance reimbursements allay a portion of costs associated with cardiac operations, uncovered and additional fees are absorbed by patients. An examination of financial toxicity (FT), defined as the burden of patient medical expenses on quality of life, is warranted. Therefore, the present study used a nationally representative database to demonstrate the association between insurance status and risk of financial toxicity (FT) among patients undergoing major cardiac operations.MethodsAdults admitted for elective coronary artery bypass grafting (CABG) and isolated or concomitant valve operations were assessed using the 2016-2019 National Inpatient Sample. FT risk was defined as out-of-pocket expenditure >40% of post-subsistence income. Regression models were developed to determine factors associated with FT risk in insured and uninsured populations. To demonstrate the association between insurance status and risk of FT among patients undergoing major cardiac operations.ResultsOf an estimated 567,865 patients, 15.6% were at risk of FT. A greater proportion of uninsured patients were at risk of FT (81.3 vs. 14.8%, pConclusionUninsured patients demonstrated higher FT risk after undergoing major cardiac operation. Hispanic race, longer lengths of stay, and combined CABG-valve operations were independently associated with increased risk of FT amongst the uninsured. Conversely, non-income factors did not impact FT risk in the insured cohort. Culturally-informed reimbursement strategies are necessary to reduce disparities in already financially disadvantaged populations.

BackgroundSociodemographic disparities in atrial fibrillation (AF) management and thromboembolic prophylaxis have previously been reported, which may involve inequitable access to left atrial appendage occlusion (LAAO) during cardiac surgery. The present study aimed to evaluate the association of LAAO utilization with sex, race, and hospital region among patients with AF undergoing heart valve operations.MethodsAdults with AF undergoing valve replacement/repair in the 2012-2019 National Inpatient Sample were identified and stratified based on concurrent LAAO. Multivariable linear and logistic regressions were developed to identify factors associated with LAAO utilization. Mortality, complications including stroke and thromboembolism, hospitalization costs and length of stay (LOS) were secondarily assessed.ResultsOf 382,580 patients undergoing valve operations, 18.7% underwent concomitant LAAO. Over the study period, the proportion of female patients receiving LAAO significantly decreased from 44.8% to 38.9% (pConclusionsFemale and Black patients had significantly lower odds while Midwest and Western hospitals had greater odds of LAAO utilization. Enhancing access to LAAO during valvular surgery is warranted to improve clinical and financial outcomes for patients with AF.

BackgroundEmergency general surgery (EGS) operations are associated with substantial risk of morbidity including postoperative respiratory failure (PRF). While existing risk models are not widely utilized and rely on traditional statistical methods, application of machine learning (ML) in prediction of PRF following EGS remains unexplored.ObjectiveThe present study aimed to develop ML-based prediction models for respiratory failure following EGS and compare their performance to traditional regression models using a nationally-representative cohort.MethodsNon-elective hospitalizations for EGS (appendectomy, cholecystectomy, repair of perforated ulcer, large or small bowel resection, lysis of adhesions) were identified in the 2016-18 Nationwide Readmissions Database. Factors associated with PRF were identified using ML techniques and logistic regression. The performance of XGBoost and logistic regression was evaluated using the receiver operating characteristic curve and coefficient of determination (R2). The impact of PRF on mortality, length of stay (LOS) and hospitalization costs was secondarily assessed using generalized linear models.ResultsOf 1,003,703 hospitalizations, 8.8% developed PRF. The XGBoost model exhibited slightly superior discrimination compared to logistic regression (0.900, 95% CI 0.899-0.901 vs 0.894, 95% CI 0.862-0.896). Compared to logistic regression, XGBoost demonstrated excellent calibration across all risk levels (R2: 0.998 vs 0.962). Congestive heart failure, neurologic disorders, and coagulopathy were significantly associated with increased risk of PRF. After risk-adjustment, PRF was associated with 10-fold greater odds (95% confidence interval (CI) 9.8-11.1) of mortality and incremental increases in LOS by 3.1 days (95% CI 3.0-3.2) and $11,900 (95% CI 11,600-12,300) in costs.ConclusionsLogistic regression and XGBoost perform similarly in overall classification of PRF risk. However, due to superior calibration at extremes of risk, ML-based models may prove more useful in the clinical setting, where probabilities rather than classifications are desired.

Background Treatment options for mitral regurgitation range from diuretic therapy, to surgical and interventional strategies including TMVR in high-risk surgical candidates. Frailty has been associated with inferior outcomes following hospitalizations for heart failure and in open cardiac surgery. Objective The purpose of the present study was to evaluate the impact of frailty on clinical outcomes and resource use following transcatheter mitral valve repair (TMVR). Methods Adults undergoing TMVR were identified using the 2016–2018 Nationwide Readmissions Database, and divided into Frail and Non-Frail groups. Frailty was defined using a derivative of the Johns Hopkins Adjusted Clinical Groups frailty indicator. Generalized linear models were used to assess the association of frailty with in-hospital mortality, complications, nonhome discharge, hospitalization costs, length of stay, and non-elective readmission at 90 days. Average marginal effects were used to quantify the impact of frailty on predicted mortality. Results Of 18,791 patients undergoing TMVR, 11.6% were considered frail. The observed mortality rate for the overall cohort was 2.2%. After adjustment, frailty was associated with increased odds of in-hospital mortality (AOR 1.8, 95% CI 1.2–2.6), corresponding to an absolute increase in risk of mortality of 1.1%. Frailty was associated with a 2.7-day (95% CI 2.1–3.2) increase in postoperative LOS, and $18,300 (95% CI 14,400–22,200) increment in hospitalization costs. Frail patients had greater odds (4.4, 95% CI 3.6–5.4) of nonhome discharge but similar odds of non-elective 90-day readmission. Conclusions Frailty is independently associated with inferior short-term clinical outcomes and greater resource use following TMVR. Inclusion of frailty into existing risk models may better inform choice of therapy and shared decision-making.