Automated CT Analysis of Body Composition as a Frailty Biomarker in Abdominal Surgery.

Importance: Prior studies demonstrated consistent associations of low skeletal muscle mass assessed on surgical planning scans with postoperative morbidity and mortality. The increasing availability of imaging artificial intelligence enables development of more comprehensive imaging biomarkers to objectively phenotype frailty in surgical patients. Objective: To evaluate the associations of body composition scores derived from multiple skeletal muscle and adipose tissue measurements from automated segmentation of computed tomography (CT) with the Hospital Frailty Risk Score (HFRS) and adverse outcomes after abdominal surgery. Design, Setting, and Participants: This retrospective cohort study used CT imaging and electronic health record data from a random sample of adults who underwent abdominal surgery at 20 medical centers within Kaiser Permanente Northern California from January 1, 2010, to December 31, 2020. Data were analyzed from April 1, 2022, to December 1, 2023. Exposure: Body composition derived from automated analysis of multislice abdominal CT scans. Main Outcomes and Measures: The primary outcome of the study was all-cause 30-day postdischarge readmission or postoperative mortality. The secondary outcome was 30-day postoperative morbidity among patients undergoing abdominal surgery who were sampled for reporting to the National Surgical Quality Improvement Program. Results: The study included 48 444 adults; mean [SD] age at surgery was 61 (17) years, and 51% were female. Using principal component analysis, 3 body composition scores were derived: body size, muscle quantity and quality, and distribution of adiposity. Higher muscle quantity and quality scores were inversely correlated (r = -0.42; 95% CI, -0.43 to -0.41) with the HFRS and associated with a reduced risk of 30-day readmission or mortality (quartile 4 vs quartile 1: relative risk, 0.61; 95% CI, 0.56-0.67) and 30-day postoperative morbidity (quartile 4 vs quartile 1: relative risk, 0.59; 95% CI, 0.52-0.67), independent of sex, age, comorbidities, body mass index, procedure characteristics, and the HFRS. In contrast to the muscle score, scores for body size and greater subcutaneous and intermuscular vs visceral adiposity had inconsistent associations with postsurgical outcomes and were attenuated and only associated with 30-day postoperative morbidity after adjustment for the HFRS. Conclusions and Relevance: In this study, higher muscle quantity and quality scores were correlated with frailty and associated with 30-day readmission and postoperative mortality and morbidity, whereas body size and adipose tissue distribution scores were not correlated with patient frailty and had inconsistent associations with surgical outcomes. The findings suggest that assessment of muscle quantity and quality on CT can provide an objective measure of patient frailty that would not otherwise be clinically apparent and that may complement existing risk stratification tools to identify patients at high risk of mortality, morbidity, and readmission.

Development and Validation of an Electronic Health Record-based Score for Triage to Perioperative Medicine.

OBJECTIVE: To develop an electronic health record-based risk model for perioperative medicine (POM) triage and compare this model with legacy triage practices that were based on clinician assessment. SUMMARY OF BACKGROUND DATA: POM clinicians seek to address the increasingly complex medical needs of patients prior to scheduled surgery. Identifying which patients might derive the most benefit from evaluation is challenging. METHODS: Elective surgical cases performed within a health system 2014- 2019 (N = 470,727) were used to develop a predictive score, called the Comorbidity Assessment for Surgical Triage (CAST) score, using split validation. CAST incorporates patient and surgical case characteristics to predict the risk of 30-day post-operative morbidity, defined as a composite of mortality and major NSQIP complications. Thresholds of CAST were then selected to define risk groups, which correspond with triage to POM appointments of different durations and modalities. The predictive discrimination CAST score was compared with the surgeon's assessments of patient complexity and the American Society of Anesthesiologists class. RESULTS: The CAST score demonstrated a significantly higher discrimination for predicting post-operative morbidity (area under the receiver operating characteristic curve 0.75) than the surgeon's complexity designation (0.63; P < 0.001) or the American Society of Anesthesiologists (0.65; P < 0.001) ( Fig. 1 ). Incorporating the complexity designation in the CAST model did not significantly alter the discrimination (0.75; P = 0.098). Compared with the complexity designation, classification based on CAST score groups resulted a net reclassification improvement index of 10.4% ( P < 0.001) ( Table 1 ). CONCLUSION: A parsimonious electronic health record-based predictive model demonstrates improved performance for identifying pre-surgical patients who are at risk than previously-used assessments for POM triage.

COVID-19 Vaccination and the Timing of Surgery Following COVID-19 Infection.

OBJECTIVE: To evaluate whether COVID-19 vaccination status or mode of anesthesia modified the temporal harms associated with surgery following coronavirus disease-2019 (COVID-19) infection. BACKGROUND: Surgery shortly after COVID-19 infection is associated with higher rates of complications, leading to recommendations to delay surgery following COVID-19 infection when possible. However, prior studies were based on populations with low or no prevalence of vaccination. METHODS: A retrospective cohort study of patients who underwent scheduled surgery in a health system from January 1, 2018 to February 28, 2022 (N=228,913) was performed. Patients were grouped by time of surgery relative to COVID-19 test positivity: 0 to 4 weeks after COVID-19 ("early post-COVID-19"), 4 to 8 weeks after COVID-19 ("mid post-COVID-19"), >8 weeks after COVID-19 ("late post-COVID-19"), surgery at least 30 days before subsequent COVID-19 ("pre-COVID-19"), and surgery with no prior or subsequent test positivity for COVID-19. RESULTS: Among patients who were not fully vaccinated at the time of COVID-19 infection, the adjusted rate of perioperative complications for the early post-COVID-19 group was significantly higher than for the pre-COVID-19 group (relative risk: 1.55; P =0.05). No significantly higher risk was identified between these groups for patients who were fully vaccinated (0.66; P =1.00), or for patients who were not fully vaccinated and underwent surgery without general anesthesia (0.52; P =0.83). CONCLUSIONS: Surgery shortly following COVID-19 infection was not associated with higher risks among fully vaccinated patients or among patients who underwent surgery without general anesthesia. Further research will be valuable to understand additional factors that modify perioperative risks associated with prior COVID-19 infection.

Decreasing trends in reintervention and readmission after endovascular aneurysm repair in a multiregional implant registry.

OBJECTIVE: As endovascular aortic aneurysm repair (EVAR) matures into its third decade, measures such as long-term reintervention and readmission have become a focus of quality improvement efforts. Within a large United States integrated health care system, we describe time trends in the rates of long-term reinterventions utilization measures. METHODS: Data from a United States multiregional EVAR registry was used to perform a descriptive study of 3891 adults who underwent conventional infrarenal EVAR for infrarenal abdominal aortic aneurysm between 2010 and 2019. Three-year follow-up was 96.7%. Outcomes included 1-, 3-, and 5-year graft revision (defined as a procedure involving placement of a new endograft component), secondary interventions (defined as a procedure necessary for maintenance of EVAR integrity [eg, coil embolization and balloon angioplasty/stenting]), conversion to open, interventions for type II endoleaks alone, and 90-day readmission. Crude cause-specific reintervention probabilities were calculated by operative year using the Aalen-Johansen estimator, with death as a competing risk and December 31, 2020 as the study end date. RESULTS: Excluding interventions for type II endoleak alone, 1-year secondary intervention incidence decreased from 5.9% for EVARs in 2010 to 2.0% in 2019 (P < .001) and 3-year incidence decreased from 7.2% to 3.6% from 2010 to 2017 (P = .03). The 3-year incidences of graft revision (mean incidence, 3.4%) and conversion to open remained fairly stable (mean incidence, 0.6%) over time. The 3-year incidence of interventions for type II endoleak alone also decreased from 3.4% in 2010 to 0.7% in 2017 (P = .01). Ninety-day readmission rates decreased from 19.3% for index EVAR in 2010 to 9.2% in 2019 (P = .03). CONCLUSIONS: Comprehensive data from a multiregional health care system demonstrates decreasing long-term secondary intervention and readmission rates over time in patients undergoing EVAR. These trends are not explained by evolving management of type II endoleaks and suggest improving graft durability, patient selection, or surgical technique. Further study is needed to define implant and anatomic predictors of different types of long-term reintervention.

Predicting early discharge and readmission following pancreaticoduodenectomy [S079].

INTRODUCTION: Implementing enhanced recovery after surgery (ERAS) protocols for major abdominal surgery has been shown to decrease length of stay (LOS) and postoperative complications, including mortality and readmission. Little is known to guide which patients undergoing pancreaticoduodenectomy (PD) should be eligible for ERAS protocols. METHODS AND PROCEDURES: A retrospective chart review of all PD performed from 2010 to 2018 within an integrated healthcare system was conducted. A predictive score that ranges from 0 to 4 was developed, with one point assigned to each of the following: obesity (BMI > 30), operating time > 400 min, estimated blood loss (EBL) > 400 mL, low- or high-risk pancreatic remnant (based on the presence of soft gland or small duct). Chi-squared tests and ANOVA were used to assess the relationship between this score and LOS, discharge before postoperative day 7, readmission, mortality, delayed gastric emptying (DGE), and pancreatic leak/fistula. RESULTS: 291 patients were identified. Mean length of stay was 8.5 days in those patients who scored 0 compared to 16.2 days for those who scored 4 (p = 0.001). 30% of patients who scored 0 were discharged before postoperative day 7 compared to 0% of those who scored 4 (p = 0.019). Readmission rates for patients who scored 0 and 4 were 12% and 33%, respectively (p = 0.017). Similarly, postoperative pancreatic fistula occurred in 2% versus 25% in these groups (p = 0.007). CONCLUSION: A simple scoring system using BMI, operating time, EBL, and pancreatic remnant quality can help risk-stratify postoperative PD patients. Those with lower scores could potentially be managed via an ERAS protocol. Patients with higher scores required longer hospitalizations, and adjunctive therapy such as medication and surgical technique to decrease risk of delayed gastric emptying and pancreatic fistula could be considered.

Comparison of Electronic Frailty Metrics for Prediction of Adverse Outcomes of Abdominal Surgery.

Importance: Electronic frailty metrics have been developed for automated frailty assessment and include the Hospital Frailty Risk Score (HFRS), the Electronic Frailty Index (eFI), the 5-Factor Modified Frailty Index (mFI-5), and the Risk Analysis Index (RAI). Despite substantial differences in their construction, these 4 electronic frailty metrics have not been rigorously compared within a surgical population. Objective: To characterize the associations between 4 electronic frailty metrics and to measure their predictive value for adverse surgical outcomes. Design, Setting, and Participants: This retrospective cohort study used electronic health record data from patients who underwent abdominal surgery from January 1, 2010, to December 31, 2020, at 20 medical centers within Kaiser Permanente Northern California (KPNC). Participants included adults older than 50 years who underwent abdominal surgical procedures at KPNC from 2010 to 2020 that were sampled for reporting to the National Surgical Quality Improvement Program. Main Outcomes and Measures: Pearson correlation coefficients between electronic frailty metrics and area under the receiver operating characteristic curve (AUROC) of univariate models and multivariate preoperative risk models for 30-day mortality, readmission, and morbidity, which was defined as a composite of mortality and major postoperative complications. Results: Within the cohort of 37 186 patients, mean (SD) age, 67.9 (female, 19 127 [51.4%]), correlations between pairs of metrics ranged from 0.19 (95% CI, 0.18- 0.20) for mFI-5 and RAI 0.69 (95% CI, 0.68-0.70). Only 1085 of 37 186 (2.9%) were classified as frail based on all 4 metrics. In univariate models for morbidity, HFRS demonstrated higher predictive discrimination (AUROC, 0.71; 95% CI, 0.70-0.72) than eFI (AUROC, 0.64; 95% CI, 0.63-0.65), mFI-5 (AUROC, 0.58; 95% CI, 0.57-0.59), and RAI (AUROC, 0.57; 95% CI, 0.57-0.58). The predictive discrimination of multivariate models with age, sex, comorbidity burden, and procedure characteristics for all 3 adverse surgical outcomes improved by including HFRS into the models. Conclusions and Relevance: In this cohort study, the 4 electronic frailty metrics demonstrated heterogeneous correlation and classified distinct groups of surgical patients as frail. However, HFRS demonstrated the highest predictive value for adverse surgical outcomes.

Resection of a giant mycotic left subclavian pseudoaneurysm.

Subclavian artery pseudoaneurysm due to intravenous drug use is a rare pathologic entity. A 6.6-cm left subclavian artery pseudoaneurysm immediately distal to the origin of the vertebral artery was discovered in a 39-year-old man with neck swelling, bacteremia, and a history of intravenous drug use. The pseudoaneurysm was resected through a median sternotomy and left supraclavicular incision, without reconstruction. This operative approach was opted for given the presence of infection and the ongoing intravenous drug use.

Pancreatic Neuroendocrine Tumor: Rationale for Centralization in an Integrated Health Care System.

OBJECTIVES: Given the complex surgical management and infrequency of pancreatic neuroendocrine tumor, we hypothesized that treatment at a center of excellence improves survival. METHODS: Retrospective review identified 354 patients with pancreatic neuroendocrine tumor treated between 2010 and 2018. Four hepatopancreatobiliary centers of excellence were created from 21 hospitals throughout Northern California. Univariate and multivariate analyses were performed. The χ2 test of clinicopathologic factors determined which were predictive for overall survival (OS). RESULTS: Localized disease was seen in 51% of patients, and metastatic disease was seen in 32% of patients with mean OS of 93 and 37 months, respectively (P < 0.001). On multivariate survival analysis, stage, tumor location, and surgical resection were significant for OS (P < 0.001). All stage OS for patients treated at designated centers was 80 and 60 months for noncenters (P < 0.001). Surgery was more common across stages at the centers of excellence versus noncenters at 70% and 40%, respectively (P < 0.001). CONCLUSIONS: Pancreatic neuroendocrine tumors are indolent but have malignant potential at any size with management often requiring complex surgeries. We showed survival was improved for patients treated at a center of excellence, where surgery was more frequently utilized.

Centralization of pancreatic cancer treatment within an integrated healthcare system improves overall survival.

BACKGROUND: Higher-volume centers for pancreatic cancer surgeries have been shown to have improved outcomes such as length of stay. We examined how centralization of pancreatic cancer care within a regional integrated healthcare system improves overall survival. METHODS: We conducted a retrospective study of 1621 patients treated for pancreatic cancer from February 2010 to December 2018. Care was consolidated into 4 Centers of Excellence (COE) in surgery, medical oncology, and other specialties. Descriptive statistics, bivariate analysis, Chi-square tests, and Kaplan-Meier analysis were performed. RESULTS: Neoadjuvant chemotherapy use rose from 10% to 31% (p < .001). The median overall survival (OS) improved by 3 months after centralization (p < .001), but this did not reach significance on multivariate analysis. CONCLUSIONS: Our results suggest that in a large integrated healthcare system, centralization improves overall survival and neoadjuvant therapy utilization for pancreatic cancer patients.

Many Neurology Readmissions Are Nonpreventable.

INTRODUCTION: Reducing unplanned hospital readmissions has become a national focus due to the Centers for Medicare and Medicaid Services' (CMS) penalties for hospitals with high rates. A first step in reducing unplanned readmission is to understand which patients are at high risk for readmission, which readmissions are planned, and how well planned readmissions are currently captured in comparison to patient-level chart review. METHODS: We examined all 5455 inpatient neurology admissions over a 2-year period to University of California San Francisco Medical Center and Johns Hopkins Hospital via chart review. We collected information such as patient age, procedure codes, diagnosis codes, all-payer diagnosis-related group, observed length of stay (oLOS), and expected length of stay. We performed multivariate logistic modeling to determine predictors of readmission. Discharge summaries were reviewed for evidence that a subsequent readmission was planned. RESULTS: A total of 353 (6.5%) discharges were readmitted within 30 days. Fifty-five (15.6%) of the 353 readmissions were planned, most often for a neurosurgical procedure (41.8%) or immunotherapy (23.6%). Only 8 of these readmissions would have been classified as planned using current CMS methodology. Patient age (odds ratio [OR] = 1.01 for each 10-year increase, P < .001) and estimated length of stay (OR = 1.04, P = .002) were associated with a greater likelihood of readmission, whereas index admission oLOS was not. CONCLUSIONS: Many neurologic readmissions are planned; however, these are often classified by current CMS methodology as unplanned and penalized accordingly. Modifications of the CMS lists for potentially planned neurological and neurosurgical procedures and for acute discharge neurologic diagnoses should be considered.

Community characteristics associated with where urgent care centers are located: a cross-sectional analysis.

OBJECTIVES: To determine the community characteristics associated with non-hospital-based urgent care centres wherever they are located. DESIGN: National cross-sectional study evaluating the association between non-hospital-based urgent care centers, and their demographic characteristics in a community, using descriptive statistics and multivariate logistic regressions. SETTING: Communities in the USA with non-hospital-based urgent care centers, as identified using a 2014 national database from the Urgent Care Association of America. PARTICIPANTS: 31,022 communities encompassing 6898 urgent care centers across the USA. PRIMARY AND SECONDARY OUTCOME MEASURES: Presence of a non-hospital-based urgent care center within a community. RESULTS: Communities with non-hospital-based urgent care centers are urban (75.7% with vs 22.2% without; p<0.001 across rural urban commuting area levels), and are located in areas with higher income levels (38.6% in highest quartile with vs 22.3% without; p<0.001 across quartiles) and higher levels of private insurance (29.6% in highest quartile with vs 23.9% without; p<0.001 across quartiles). CONCLUSIONS: While the growth of the urgent care industry may have other promising implications, policymakers should recognise that it may exacerbate disparities in access to acute care faced by poorer, uninsured patients, and may also have financial implications for providers that are providing overlapping services, such as emergency departments and primary care practices.

Access, quality, and costs of care at physician owned hospitals in the United States: observational study.

OBJECTIVE: To compare physician owned hospitals (POHs) with non-POHs on metrics around patient populations, quality of care, costs, and payments. DESIGN: Observational study. SETTING: Acute care hospitals in 95 hospital referral regions in the United States, 2010. PARTICIPANTS: 2186 US acute care hospitals (219 POHs and 1967 non-POHs). MAIN OUTCOME MEASURES: Proportions of patients using Medicaid and those from ethnic and racial minority groups; hospital performance on patient experience metrics, care processes, risk adjusted 30 day mortality, and readmission rates; costs of care; care payments; and Medicare market share. RESULTS: The 219 POHs were more often small (<100 beds), for profit, and in urban areas. 120 of these POHs were general (non-specialty) hospitals. Compared with patients from non-POHs, those from POHs were younger (77.4 v 78.4 years, P<0.001), less likely to be admitted through an emergency department (23.2% v. 29.0%, P<0.001), equally likely to be black (5.1% v 5.5%, P=0.85) or to use Medicaid (14.9% v 15.4%, P=0.75), and had similar numbers of chronic diseases and predicted mortality scores. POHs and non-POHs performed similarly on patient experience scores, processes of care, risk adjusted 30 day mortality, 30 day readmission rates, costs, and payments for acute myocardial infarction, congestive heart failure, and pneumonia. CONCLUSION: Although POHs may treat slightly healthier patients, they do not seem to systematically select more profitable or less disadvantaged patients or to provide lower value care.

Compensation of chief executive officers at nonprofit US hospitals.

IMPORTANCE: Hospital chief executive officers (CEOs) can shape the priorities and performance of their organizations. The degree to which their compensation is based on their hospitals' quality performance is not well known. OBJECTIVE: To characterize CEO compensation and examine its relation with quality metrics. DESIGN, SETTING, AND PARTICIPANTS: Retrospective observational study. Participants included 1877 CEOs at 2681 private, nonprofit US hospitals. MAIN OUTCOMES AND MEASURES: We used linear regression to identify hospital structural characteristics associated with CEO pay. We then determined the degree to which a hospital's performance on financial metrics, technologic metrics, quality metrics, and community benefit in 2008 was associated with CEO pay in 2009. RESULTS: The CEOs in our sample had a mean compensation of $595,781 (median, $404,938) in 2009. In multivariate analyses, CEO pay was associated with the number of hospital beds overseen ($550 for each additional bed; 95% CI, 429-671; P < .001), teaching status ($425,078 more at major teaching vs nonteaching hospitals; 95% CI, 315,238-534,918; P < .001), and urban location. Hospitals with high levels of advanced technologic capabilities compensated their CEOs $135,862 more (95% CI, 80,744-190,990; P < .001) than did hospitals with low levels of technology. Hospitals with high performance on patient satisfaction compensated their CEOs $51,706 more than did those with low performance on patient satisfaction (95% CI, 15,166-88,247; P = .006). We found no association between CEO pay and hospitals' margins, liquidity, capitalization, occupancy rates, process quality performance, mortality rates, readmission rates, or measures of community benefit. CONCLUSIONS AND RELEVANCE: Compensation of CEOs at nonprofit hospitals was highly variable across the country. Compensation was associated with technology and patient satisfaction but not with processes of care, patient outcomes, or community benefit.