Survival Tree Provides Individualized Estimates of Survival After Lung Transplant.

INTRODUCTION: Identifying contributors to lung transplant survival is vital in mitigating mortality. To enhance individualized mortality estimation and determine variable interaction, we employed a survival tree algorithm utilizing recipient and donor data. METHODS: United Network Organ Sharing data (2000-2021) were queried for single and double lung transplants in adult patients. Graft survival time <7 d was excluded. Sixty preoperative and immediate postoperative factors were evaluated with stepwise logistic regression on mortality; final model variables were included in survival tree modeling. Data were split into training and testing sets and additionally validated with 10-fold cross validation. Survival tree pruning and model selection was based on Akaike information criteria and log-likelihood values. Estimated survival probabilities and log-rank pairwise comparisons between subgroups were calculated. RESULTS: A total of 27,296 lung transplant patients (8175 single; 19,121 double lung) were included. Stepwise logistic regression yielded 47 significant variables associated with mortality. Survival tree modeling returned six significant factors: recipient age, length of stay from transplant to discharge, recipient ventilator duration post-transplant, double lung transplant, recipient reintubation post-transplant, and donor cytomegalovirus status. Eight subgroups consisting of combinations of these factors were identified with distinct Kaplan-Meier survival curves. CONCLUSIONS: Survival trees provide the ability to understand the effects and interactions of covariates on survival after lung transplantation. Individualized survival probability with this technique found that preoperative and postoperative factors influence survival after lung transplantation. Thus, preoperative patient counseling should acknowledge a degree of uncertainty given the influence of postoperative factors.

Association of individual surgeon volume and postoperative outcome in esophagomyotomy for achalasia.

BACKGROUND: Many surgical disciplines have demonstrated superior outcomes when procedures are performed at "high-volume". Esophagomyotomy is commonly performed for achalasia, however it's unclear what constitutes "high-volume" for this procedure, and if individual procedure volume and outcome are related. We identified physicians performing esophagomyotomy, stratified them by individual case volume, and examined their outcomes with the hypothesis that high-volume surgeons will be associated with improved outcomes as compared to low-volume surgeons. METHODS: The 2015-2019 Florida Agency for Health Care Administration (AHCA) inpatient dataset was queried for esophagomyotomy. Surgeons who performed ≥ 10 procedures during the study period were placed into the high-volume cohort, and those performing < 10 into the low-volume cohort. Groups were compared by length of stay, discharge disposition, and postoperative complications. Patient demographics were evaluated using student's t test and chi square test, p < 0.05 considered significant. RESULTS: Six hundred and sixty-two procedures performed by 135 surgeons were identified. The mean number of esophagomyotomies per surgeon was 4.9 (Range 1-147). The high-volume group (n = 12) performed 362 of the 662 procedures (55%), while the low-volume group (n = 123) performed the remaining 300 (45%). Patients of high-volume physicians had decreased length of stay (1.4 ± 0.8 days vs 4.9 ± 6.7 days, p = 0.01) and were more likely to be discharged to home following surgery (92.8% vs 86.0, p = 0.04). High volume physicians also had statistically significant differences in rates of urinary tract infection (1.4% vs 4.0%, p = 0.034), postoperative malnutrition (5.8% vs 11.0%, p = 0.015), and postoperative fluid and electrolyte disorders (5.5% vs 13.3%, p < 0.0001). CONCLUSION: Surgeons who perform higher volumes of esophagomyotomies are associated with decreased length of stay, higher likelihood of patient discharge to home, and decreased rates of some postoperative complications. This research should prompt further inquiry into defining what constitutes a high-volume center in foregut surgery and their role in improving patient outcomes.

Lower Socioeconomic Status Predicts Greater Obstacles to Care: Using Outpatient Cholecystectomy as a Model Cohort.

BACKGROUND: Patients with low socioeconomic status (SES) are disadvantaged in terms of access to health care. A novel metric for SES is the Distressed Communities Index (DCI). This study evaluates the effect of DCI on hospital choice and distance traveled for surgery. METHODS: A Florida database was queried for patients with symptomatic cholelithiasis or chronic cholecystitis who underwent an outpatient cholecystectomy between 2016 and 2019. Patients' DCI was compared with hospital ratings, comorbidities, Charlson Comorbidity Index, and distance traveled for surgery. Stepwise logistic regression was used to determine which factors most influenced distance traveled for surgery. RESULTS: There were 54,649 cases-81 open, 52,488 laparoscopic, and 2,080 robotic. There was no difference between surgical approach and patient's DCI group (p = 0.12). Rural patients traveled the farthest for surgery (avg 21.29 miles); urban patients traveled the least (avg 5.84 miles). Patients from distressed areas more often had surgery at one- or two-star hospitals than prosperous patients (61% vs 36.3%). Regression indicated distressed or at-risk areas predicted further travel for rural/small-town patients, while higher hospital ratings predicted further travel for suburban/urban patients. DISCUSSION: Compared to prosperous areas, patients from distressed areas have surgery at lower-rated hospitals, travel further if they live in rural/small-town areas, but travel less if they live in suburban areas. We postulate that farther travel in rural areas may be explained by a lack of health care resources in poor, rural areas, while traveling less in suburban areas may be explained by personal lack of resources for patients with low SES.

The continued financial effect of COVID: Increasing costs for non-elective major lower extremity amputations.

Background: The COVID-19 pandemic necessitated changes in processes of care, which significantly impacted surgical care. This study evaluated the impact of these changes on patient outcomes and costs for non-elective major lower extremity amputations (LEA). Methods: The 2019-2021 Florida Agency for Health Care Administration database was queried for adult patients who underwent non-elective major LEA. Per-patient inflation-adjusted costs were collected. Patient cohorts were established based on Florida COVID-19 mortality rates: COVID-heavy (CH) included nine months with the highest mortality, COVID-light (CL) included nine months with the lowest mortality, and pre-COVID (PC) included nine months before COVID (2019). Outcomes included in-hospital patient outcomes and hospitalization cost. Results: 6132 patients were included (1957 PC, 2104 CH, and 2071 CL). Compared to PC, there was increased patient acuity at presentation, but morbidity (31%), mortality (4%), and length of stay (median 12 [8-17] days) were unchanged during CH and CL. Additionally, costs significantly increased during the pandemic; median total cost rose 9%, room costs increased by 16%, ICU costs rose by 15%, and operating room costs rose by 15%. When COVID-positive patients were excluded, cost of care was still significantly higher during CH and CL. Conclusions: Despite maintaining pre-pandemic standards, as evidenced by unchanged outcomes, the pandemic led to increased costs for patients undergoing non-elective major LEA. This was likely due to increased patient acuity, resource strain, and supply chain shortages during the pandemic. Key message: While patient outcomes for non-elective major lower extremity amputations remained consistent during the COVID-19 pandemic, healthcare costs significantly increased, likely due to increased patient acuity and heightened pressures on resources and supply chains. These findings underscore the need for informed policy changes to mitigate the financial impact on patients and healthcare systems for future public health emergencies.

Is nonoperative management of appendicitis inferior in the COVID-19 era?

BACKGROUND: Previous studies on nonoperative management (NOM) of acute appendicitis (AA) indicated comparable outcomes to surgery, but the effect of COVID-19 infection on appendicitis outcomes remains unknown. Thus, we evaluate appendicitis outcomes during the COVID-19 pandemic to determine the effect of COVID-19 infection status and treatment modality. We hypothesized that active COVID-19 patients would have worse outcomes than COVID-negative patients, but that outcomes would not differ between recovered COVID-19 and COVID-negative patients. Moreover, we hypothesized that outcomes would not differ between nonoperative and operative management groups, regardless of COVID-19 status. METHODS: We queried the National COVID Cohort Collaborative from 2020 to 2023 to identify adults with AA who underwent operative or NOM. COVID-19 status was denoted as follows: COVID-negative, COVID-active, or COVID-recovered. Intention to treat was used for NOM. Propensity score-balanced analysis was performed to compare outcomes within COVID groups, as well as within treatment modalities. RESULTS: A total of 37,868 patients were included: 34,866 COVID-negative, 2,540 COVID-active, and 460 COVID-recovered. COVID-active and recovered less often underwent operative management. Unadjusted, there was no difference in mortality between COVID groups for operative management. There was no difference in rate of failure of NOM between COVID groups. Adjusted analysis indicated, compared with operative, NOM carried higher odds of mortality and readmission for COVID-negative and COVID-active patients. CONCLUSION: This study demonstrates higher odds of mortality among NOM of appendicitis and near equivalent outcomes for operative management regardless of COVID-19 status. We conclude that NOM of appendicitis is associated with worse outcomes for COVID-active and COVID-negative patients. In addition, we conclude that a positive COVID test or recent COVID-19 illness alone should not preclude a patient from appendectomy for AA. Surgeon clinical judgment of a patient's physiology and surgical risk should, of course, inform the decision to proceed to the operating room. LEVEL OF EVIDENCE: Therapeutic/Care Management; Level III.

Artificial Intelligence in Surgical Research: Accomplishments and Future Directions.

MINI-ABSTRACT: The study introduces various methods of performing conventional ML and their implementation in surgical areas, and the need to move beyond these traditional approaches given the advent of big data. OBJECTIVE: Investigate current understanding and future directions of machine learning applications, such as risk stratification, clinical data analytics, and decision support, in surgical practice. SUMMARY BACKGROUND DATA: The advent of the electronic health record, near unlimited computing, and open-source computational packages have created an environment for applying artificial intelligence, machine learning, and predictive analytic techniques to healthcare. The "hype" phase has passed, and algorithmic approaches are being developed for surgery patients through all stages of care, involving preoperative, intraoperative, and postoperative components. Surgeons must understand and critically evaluate the strengths and weaknesses of these methodologies. METHODS: The current body of AI literature was reviewed, emphasizing on contemporary approaches important in the surgical realm. RESULTS AND CONCLUSIONS: The unrealized impacts of AI on clinical surgery and its subspecialties are immense. As this technology continues to pervade surgical literature and clinical applications, knowledge of its inner workings and shortcomings is paramount in determining its appropriate implementation.

Expanded analysis for patients with acute cholecystitis indicates outcomes vary based on COVID-19 status and treatment modality.

BACKGROUND: The impact of different phases of COVID-19 infection on outcomes from acute calculous cholecystitis (ACC) is not well understood. Therefore, we examined outcomes of acute cholecystitis during the COVID-19 pandemic, comparing the effect of different treatment modalities and COVID-19 infection status. We hypothesized that patients with acute COVID-19 would have worse outcomes than COVID-negative patients, but there would be no difference between COVID-negative and COVID-recovered patients. METHODS: We used 2020-2023 National COVID Cohort Collaborative data to identify adults with ACC. Treatment (antibiotics-only, cholecystostomy tube, or cholecystectomy) and COVID-19 status (negative, active, or recovered) were collected. Treatment failure of nonoperative managements was noted. Adjusted analysis using a series of generalized linear models controlled for confounders (age, sex, body mass index, Charlson comorbidity index, severity at presentation, and year) to better assess differences in outcomes among treatment groups, as well as between COVID-19 groups. RESULTS: In total, 32,433 patients (skewed count) were included: 29,749 COVID-negative, 2112 COVID-active, and 572 (skewed count) COVID-recovered. COVID-active had higher rates of sepsis at presentation. COVID-negative more often underwent cholecystectomy. Unadjusted, COVID-active had higher 30-day mortality, 30-day complication, and longer length of stay than COVID-negative and COVID-recovered. Adjusted analysis revealed cholecystectomy carried lower odds of mortality for COVID-active and COVID-negative patients than antibiotics or cholecystostomy. COVID-recovered patients' mortality was unaffected by treatment modality. Treatment failure from antibiotics was more common for COVID-negative patients. CONCLUSION: Acute cholecystitis outcomes are affected by phase of COVID-19 infection and treatment modality. Cholecystectomy does not lead to worse outcomes for COVID-active and COVID-recovered patients than nonoperative treatments; thus, these patients can be considered for cholecystectomy if their physiology is not prohibitive.

Transition to Permitless Open Carry and Association with Firearm-Related Suicide.

BACKGROUND: Firearm-related death rates continue to rise in the US. As some states enact more permissive firearm laws, we sought to assess the relationship between a change to permitless open carry (PLOC) and subsequent firearm-related death rates, a currently understudied topic. STUDY DESIGN: Using state-level data from 2013 to 2021, we performed a linear panel analysis using a state fixed-effects model. We examined total firearm-related death, suicide, and homicide rates separately. If a significant association between OC law and death rate was found, we then performed a difference-in-difference (DID) analysis to assess for a causal relationship between changing to PLOC and increased death rate. For significant DID results, we performed confirmatory DID separating firearm and nonfirearm death rates. RESULTS: Nineteen states maintained a no OC or permit-required law, whereas 5 changed to permitless and 26 had a PLOC before 2013. The fixed-effects model indicated more permissive OC law that was associated with increased total firearm-related deaths and suicides. In DID, changing law to PLOC had a significant average treatment effect on the treated of 1.57 (95% CI 1.05 to 2.09) for total suicide rate but no significant average treatment effect for the total firearm-related death rate. Confirmatory DID results found a significant average treatment effect on the treated of 1.18 (95% CI 0.90 to 1.46) for firearm suicide rate. CONCLUSIONS: OC law is associated with total firearm-related death and suicide rates. Based on our DID results, changing to PLOC is indeed strongly associated with increased suicides by firearm.

COVID-Induced Alterations in Surgical Care and Outcomes in Perforated Diverticulitis.

BACKGROUND: COVID-19 caused healthcare systems to significantly alter processes of care. Literature on the pandemic's effect on healthcare processes and resulting surgical outcomes is lacking. This study aims to determine outcomes of open colectomy in patients with perforated diverticulitis during the pandemic. METHODS: Using CDC data, the highest and lowest COVID mortality rates were calculated and used to establish 9-month COVID-heavy (CH) and COVID-light (CL) timeframes, respectively. Nine-months of 2019 were assigned as pre-COVID (PC) control. Florida AHCA database was utilized for patient-level data. Primary outcomes were length of stay (LOS), morbidity, and in-hospital mortality. Stepwise regression with 10-fold cross-validation determined factors most impacting outcomes. A parallel analysis excluding COVID-positive patients was performed to differentiate COVID-infection from processes of care. RESULTS: There were 3862 patients in total. COVID-positive patients had longer LOS, more intensive care unit admissions, and higher morbidity and mortality. After excluding 105 COVID-positive patients, individual outcomes were not different per timeframe. Regression showed timeframe did not affect primary outcomes. DISCUSSION: Outcomes following colectomy for perforated diverticulitis were worse for COVID-positive patients. Despite increased stress on the healthcare system during the pandemic, major outcomes were unchanged for COVID-negative patients. Our results indicate that despite COVID-associated changes in processes of care, acute care surgery can still be performed in COVID-negative patients without increased mortality and minimal change in morbidity.

Recipient Survival after Orthotopic Liver Transplantation: Interpretable Machine Learning Survival Tree Algorithm for Patient-Specific Outcomes.

BACKGROUND: Elucidating contributors affecting liver transplant survival is paramount. Current methods offer crude global group outcomes. To refine patient-specific mortality probability estimation and to determine covariate interaction using recipient and donor data, we generated a survival tree algorithm, Recipient Survival After Orthotopic Liver Transplantation (ReSOLT), using United Network Organ Sharing (UNOS) transplant data. STUDY DESIGN: The UNOS database was queried for liver transplants in patients ≥18 years old between 2000 and 2021. Preoperative factors were evaluated with stepwise logistic regression; 43 significant factors were used in survival tree modeling. Graft survival of <7 days was excluded. The data were split into training and testing sets and further validated with 10-fold cross-validation. Survival tree pruning and model selection was achieved based on Akaike information criterion and log-likelihood values. Log-rank pairwise comparisons between subgroups and estimated survival probabilities were calculated. RESULTS: A total of 122,134 liver transplant patients were included for modeling. Multivariable logistic regression (area under the curve = 0.742, F1 = 0.822) and survival tree modeling returned 8 significant recipient survival factors: recipient age, donor age, recipient primary payment, recipient hepatitis C status, recipient diabetes, recipient functional status at registration and at transplantation, and deceased donor pulmonary infection. Twenty subgroups consisting of combinations of these factors were identified with distinct Kaplan-Meier survival curves (p < 0.001 among all by log rank test) with 5- and 10-year survival probabilities. CONCLUSIONS: Survival trees are a flexible and effective approach to understand the effects and interactions of covariates on survival. Individualized survival probability following liver transplant is possible with ReSOLT, allowing for more coherent patient and family counseling and prediction of patient outcome using both recipient and donor factors.

Association of state-level factors with rate of firearm-related deaths.

Background: Over 48,000 people died by firearm in the United States in 2021. Firearm violence has many inciting factors, but the full breadth of associations has not been characterized. We explored several state-level factors including factors not previously studied or insufficiently studied, to determine their association with state firearm-related death rates. Methods: Several state-level factors, including firearm open carry (OC) and concealed carry (CC) laws, state rank, partisan lean, urbanization, poverty rate, anger index, and proportion of college-educated adults, were assessed for association with total firearm-related death rates (TFDR). Secondary outcomes were firearm homicide (FHR) and firearm suicide rates (FSR). Exploratory data analysis with correlation plots and ANOVA was performed. Univariable and multivariable linear regression on the rate of firearm-related deaths was also performed. Results: All 50 states were included. TFDR and FSR were higher in permitless OC and permitless CC states. FHR did not differ based on OC or CC category. Open carry and CC were eliminated in all three regression models due to a lack of significance. Significant factors for each model were: 1) TFDR - partisan lean, urbanization, poverty rate, and state ranking; 2) FHR - poverty rate; 3) FSR - partisan lean and urbanization. Conclusions: Neither open nor concealed carry is associated with firearm-related death rates when socioeconomic factors are concurrently considered. Factors associated with firearm homicide and suicide differ and will likely require separate interventions to reduce firearm-related deaths. Key message: Neither open carry nor concealed carry law are associated with total firearm-related death rate, but poverty rate, urbanization, partisan lean, and state ranking are associated. When analyzing firearm homicide and suicide rates separately, poverty rate is strongly associated with firearm homicide rate, while urbanization and partisan lean are associated with firearm suicide rate.

Corrigendum to "Association of state-level factors with rate of firearm-related deaths" [Surg. Open Sci. vol. 14 (2023) 114-119].

[This corrects the article DOI: 10.1016/j.sopen.2023.07.011.].

Patient outcomes and cost in robotic emergency general surgery.

The use of robotic technology in general surgery continues to increase, though its utility for emergency general surgery remains under-studied. This study explores the current trends in patient outcomes and cost of robotic emergency general surgery (REGS). The Florida Agency for Healthcare Administration database (2018-2020) was queried for adult patients undergoing intra-abdominal emergency general surgery within 24 h of admission and linked to CMS Cost Reports/Hospital Compare, American Hospital Association, and Rand Corporation Hospital datasets. Patients from the four most common REGS procedures were propensity matched to laparoscopic equivalents for hospital cost analysis. A telephone survey was performed with the top 10 REGS hospitals to identify key qualities for successful REGS programs. 181 hospitals (119 REGS, 62 non-REGS) performed 60,733 emergency surgeries. Six-percent were REGS. The most common REGS were cholecystectomy, appendectomy, inguinal and ventral hernia repairs. Before and after propensity matching, total cost for these four procedures were significantly higher than their laparoscopic equivalents, which was due to higher surgical cost as the non-operative costs did not differ. There were no differences in mortality, individual complications, or length of stay for most of the four procedures. REGS volume significantly increased each year. The survey found that 8/10 hospitals have robotic-trained staff available 24/7. Although REGS volume is increasing in Florida, cost remains significantly higher than laparoscopy. Given higher costs and lack of significantly improved outcomes, further study should be undertaken to better inform which specific patient populations would benefit from REGS.

Nonelective coronary artery bypass graft outcomes are adversely impacted by Coronavirus disease 2019 infection, but not altered processes of care: A National COVID Cohort Collaborative and National Surgery Quality Improvement Program analysis.

Objective: The effects of Coronavirus disease 2019 (COVID-19) infection and altered processes of care on nonelective coronary artery bypass grafting (CABG) outcomes remain unknown. We hypothesized that patients with COVID-19 infection would have longer hospital lengths of stay and greater mortality compared with COVID-negative patients, but that these outcomes would not differ between COVID-negative and pre-COVID controls. Methods: The National COVID Cohort Collaborative 2020-2022 was queried for adult patients undergoing CABG. Patients were divided into COVID-negative, COVID-active, and COVID-convalescent groups. Pre-COVID control patients were drawn from the National Surgical Quality Improvement Program database. Adjusted analysis of the 3 COVID groups was performed via generalized linear models. Results: A total of 17,293 patients underwent nonelective CABG, including 16,252 COVID-negative, 127 COVID-active, 367 COVID-convalescent, and 2254 pre-COVID patients. Compared to pre-COVID patients, COVID-negative patients had no difference in mortality, whereas COVID-active patients experienced increased mortality. Mortality and pneumonia were higher in COVID-active patients compared to COVID-negative and COVID-convalescent patients. Adjusted analysis demonstrated that COVID-active patients had higher in-hospital mortality, 30- and 90-day mortality, and pneumonia compared to COVID-negative patients. COVID-convalescent patients had a shorter length of stay but a higher rate of renal impairment. Conclusions: Traditional care processes were altered during the COVID-19 pandemic. Our data show that nonelective CABG in patients with active COVID-19 is associated with significantly increased rates of mortality and pneumonia. The equivalent mortality in COVID-negative and pre-COVID patients suggests that pandemic-associated changes in processes of care did not impact CABG outcomes. Additional research into optimal timing of CABG after COVID infection is warranted.

Disparities in coronary artery bypass grafting between high- and low-volume surgeons and hospitals.

Background: High-volume surgeons and hospitals performing coronary artery bypass grafting have been associated with improved patient outcomes. However, patients of increased socioeconomic distress may have worse outcomes because of health care disparities. We sought to identify trends and outcomes in patients of elevated distress undergoing bypass grafting. Methods: The Florida Agency for Healthcare Administration administrative data set was merged with Centers for Medicare and Medicaid Services Physician and Hospital Compare and Economic Innovation Group Distressed Community Index data sets to build a comprehensive database. The data set was queried to identify patients undergoing coronary artery bypass procedures between 2016 and 2020. High- and low-volume hospitals and surgeons were compared. Patient and hospital demographics, comorbidities, length of stay, and postoperative complications were analyzed by χ2 and t test where appropriate. Results: A total of 41,571 coronary artery bypass grafting procedures were performed by 174 surgeons at 67 Florida hospitals. Low- and high-volume hospitals did not differ with respect to hospital ownership, overall star rating, national comparisons of mortality, readmission, or cost effectiveness. Patients from at-risk and distressed communities were more likely to undergo surgery at low-volume hospitals. Hospital length of stay was increased for low-volume hospitals (10.2 vs 9.4 days, P < .05). Postoperative complications including pneumonia, arrhythmia, respiratory failure, acute renal failure, shock, pleural effusion, and sepsis were more frequent at low-volume hospitals and for low-volume surgeons. Conclusion: High-volume hospitals and surgeons have improved postoperative outcomes and hospital length of stay when compared to low-volume hospitals and surgeons performing coronary artery bypass grafting. At-risk and distressed populations are more likely to undergo bypass surgery at low-volume hospitals, potentially contributing to worse patient outcome. Efforts should be made to mitigate the potential impact of low socioeconomic status to improve outcomes in this population.

Outcomes of Transcatheter and Surgical Aortic Valve Replacement in Distressed Socioeconomic Communities.

Objective Patients of low socioeconomic status have an increased risk of complications following cardiac surgery. We aimed to identify disparities in patients undergoing aortic valve replacement using the Distressed Communities Index (DCI), a comparative measure of community well-being. The DCI incorporates seven distinct socioeconomic indicators into a single composite score to depict the economic well-being of a community. Methods The Healthcare Cost and Utilization Project State Inpatient Database (HCUP-SID) for Florida and Washington was queried to identify patients undergoing surgical and transcatheter aortic valve replacement (surgical aortic valve replacement [SAVR], transcatheter aortic valve replacement [TAVR]) between 2012-2015. Patients undergoing TAVR and SAVR were propensity-matched and stratified based on the quintile of DCI score. A distressed community was defined as those in quintiles 4 and 5 (at-risk and distressed, respectively); a non-distressed community was defined as those in quintiles 1 and 2 (prosperous and comfortable, respectively). Outcomes following aortic valve replacement were compared across groups in distressed communities. Propensity score matching was used to balance baseline covariates between groups. Results A total of 27,591 patients underwent aortic valve replacement. After propensity matching, 5,331 patients were identified in each TAVR and SAVR group. Distressed TAVR patients had lower rates of postoperative pneumonia (7.6% vs. 3.8%, p<0.001), sepsis (3.6% vs. 1.9%, p<0.05), and cardiac complications (15.4% vs. 7.5%, p<0.001) when compared to highly distressed SAVR patients. When comparing distressed SAVR and TAVR and low distressed SAVR and TAVR groups, no significant difference was found in postoperative outcomes, except distressed TAVR experienced more cases of UTI. Conclusions Highly distressed TAVR patients had lower incidences of postoperative sepsis, pneumonia, and cardiac complications when compared to the highly distressed SAVR cohort. Patients undergoing TAVR in highly distressed communities had an increased incidence of postoperative urinary tract infection. DCI may be a useful adjunct to current risk scoring systems.

Predictive modeling of in-hospital mortality following elective surgery.

INTRODUCTION: The specific healthcare macroenvironment factors contributing to in-hospital mortality following elective surgery remain nuanced. We hypothesize an accurate global elective surgical mortality model can be created. METHODS: FL AHCA and Hospital Compare (2016-2019) were queried for in-hospital mortality following elective surgeries. Stepwise logistic regression with 47 patient and hospital factors was followed by gradient boosting machine (GBM) modeling describing the relative influence on risk for in-hospital mortality. Deceased and surviving patients were matched (1:2) to perform univariate analysis and logistic regression of significant factors. RESULTS: A total of 511,897 admissions, 2,266 patient deaths and 162 Florida hospitals were included. GBM factors (AUC 0.94) included post-operative patient and hospital factors. In the final regression model, patient age older than 70 years of age and hospital 5-star rating were significant (OR 2.87, 0.47, respectively). Hospitals rated 5-stars were protective of mortality. CONCLUSION: In-patient mortality following elective surgery is influenced by patient and hospital level factors. Efforts should be made to mitigate these risks or enhance those that are protective.

Elements of the care environment influence coronary artery bypass surgery readmission.

BACKGROUND: Coronary artery bypass grafting 30-day unplanned readmission is a focus for the CMS Hospital Readmissions Reduction Program. Awareness of the critical elements of the care delivery environment, including hospital infrastructure and patient clinical profiles that predispose toward readmission, is essential to proactively decrease readmissions. METHODS: The Healthcare Cost and Utilization Project-State Inpatient Database, American Hospital Association Annual Health Survey Database, and Healthcare Information Management Systems Society data sets were merged to create a single data set of patient- and hospital-level data from 8 states. Isolated coronary artery bypass grafting procedures were queried for all-cause 30-day readmission, and backwards stepwise logistic regression was performed. Readmission rate was then used to categorize hospitals into quartiles, and analysis focused on the hospitals with the lowest (Q1) and highest (Q4) readmission rates. Univariate analysis was performed comparing Q1 and Q4 hospitals. RESULTS: A total of 150,215 patients underwent isolated coronary artery bypass grafting with 23,244 (15.5%) readmitted patients among 903 hospitals. Model area under the curve was 0.709 (95% confidence interval, 0.702-0.716), with the top 3 readmission determinants related to discharge disposition. Compared to Q1, Q4 patients more often were female, were > 70 years of age, and had Medicare as a primary payor (P < .001). Low readmission rate hospitals were characterized by higher costs; not-for-profit status; having Joint Commission accreditation; and higher total admissions, operative volume, hospital/ICU beds, full-time physicians, nurses, and ancillary personnel (P < .001). CONCLUSION: Readmission after coronary artery bypass grafting is strongly influenced by discharge disposition. However, hospital factors such as scale, personnel, and ownership structure are significant contributors to readmission. Focus beyond patient factors to include the entire continuum of care is required to enhance outcomes, of which readmission is one surrogate measure.

Big Data Solutions for Controversies in Breast Cancer Treatment.

The digital world of data is expanding with an annual growth rate of 40%, and health care is among the fastest growing sector of the digital world with an annual growth rate of 48%. Rapid growth in technology has augmented data generation; for example, electronic health records produce huge amounts of patient-level data, whereas national registries capture information on numerous factors affecting health care delivery and patient outcomes. This big data can be utilized to improve health care outcomes. This review discusses relevant applications in breast cancer treatment.

Discharge timing: Does targeting an ideal length of stay for patients undergoing colectomy impact readmissions and costs of care?

INTRODUCTION: In colorectal surgery, enhanced recovery protocols reduce length-of-stay (LOS). Concerns remain about increased readmission rates. Using a predictive model targeting ideal LOS (iLOS), we evaluate the impact of discharge timing on readmission. METHODS: The HCUP-SID and AHA databases combined patient and hospital-level data from four states. Colectomy patients were stratified and propensity-matched based. We predicted iLOS using multivariate linear regression, created a discharge timing variable and used multivariate logistic regression to analyze 30-day and 90-day readmissions. RESULTS: Of 100,701 patients, 6903 (6.85%) were Lap-Left, 16,883 (16.77%) were Open-Left, 32,173 (31.95%) were Lap-Right, and 44,742 (44.43%) were Open-Right. Very early discharge (>4d before iLOS) and very late discharge (>4d after iLOS) were predictors of readmission in Lap- Left (p < 0.05) and Open-Right (p < 0.05). In Lap-Right, early discharge was a significant predictor of readmission (p < 0.01). CONCLUSION: Targeting using iLOS may optimize discharge timing after colectomy and avoid unplanned readmissions.