The trends in cost associated with liver transplantation in the US: Analysis of weighted hospital data.

This study aims to evaluate recent annualized trends in the cost-burden of inpatient hospitalizations associated with liver transplantation (LT) in the US as stratified by patient demographics and medical characteristics. From 2016 to 2019 National Inpatient Sample was used to select patients who underwent LT, from which the weighted charge estimates were derived and converted to admission costs using inflation-adjusted charge-to-cost ratios. The adjusted values were stratified using select patient variables and graphed across the respective years to derive goodness-of-fit for each trend (expressed with R2 and p -values). From 2016 to 2019, the estimated total number of LT-related hospitalizations in the US were 6685, 7075, 7260, and 7815 cases respectively. There was a general increase in the total cost of LT-related hospitalizations over the years: $945.75, $1010.23, $1052.46, and $1143.84 in millions of dollars (0.98, 0.01). Furthermore, positive trends in total cost were observed in the following strata: patients aged 35-49 (0.92, 0.04) and above 65 (0.91, 0.05), Whites (0.99, 0.01), those with congestive heart failure (0.98, 0.01), ≥2 comorbidities (0.97, 0.02), hepatic encephalopathy (0.93, 0.04), and those with private insurance (0.93, 0.04), as well as LT performed in the Northeast (0.94, 0.03), Midwest (0.92, 0.04), and South (0.91, 0.04). Total cost associated with hepatitis C declined significantly (0.94, 0.03). With respect to mean costs, positive trends were observed in the following strata: those with other or cryptogenic liver disease (0.93, 0.03), ≥2 comorbidities (0.96, 0.02), and LT performed in the Northeast region (0.93, 0.04). The number of liver transplants performed in the US, as well as the associated costs, are rising. Given the apparent rising costs in specific patient populations, economic and public health policies must focus on cost containment within these groups to ensure appropriate usage of resources.

The Trends in Health Care Utilization and Costs Associated With Primary Liver Cancer: An Analysis of United States Hospitals Between 2016 and 2019.

BACKGROUND: Primary liver cancer (PLC) has placed an increasing economic and resource burden on the health care system of the United States. We attempted to quantify its epidemiology and associated costs using a national inpatient database. METHODS: Hospital discharge and insurance claims data from the National Inpatient Sample were used to conduct this analysis. Patients diagnosed with PLC (hepatocellular carcinoma or cholangiocarcinoma) were included in the study population, which was then stratified using patient demographics, comorbidities, degree of cancer spread, liver disease complications, and other descriptors. Trends were analyzed via regression curves for each of these strata from the years 2016 to 2019, with special attention to patterns in hospitalization incidence, inpatient mortality rate, total costs, and average per-capita costs. The resulting curves were evaluated using goodness-of-fit statistics and P-values. RESULTS: Aggregate hospitalization incidence, inpatient mortality rates, and total costs were found to significantly increase throughout the study period (P=0.002, 0.002, and 0.02, respectively). Relative to their demographic counterparts, males, White Americans, and those older than 65 years of age contributed the largest proportions of total costs. These population segments also experienced significant increases in total expenditure (P=0.04, 0.03, and 0.02, respectively). Admissions deemed to have multiple comorbidities were associated with progressively higher total costs throughout the study period (P=0.01). Of the categorized underlying liver diseases, only admissions diagnosed with alcoholic liver disease or nonalcoholic fatty liver disease saw significantly increasing total costs (P=0.006 and 0.01), although hepatitis C was found to be the largest contributor to total expenses. CONCLUSIONS: From 2016 to 2019, total costs, admission incidence, and inpatient mortality rates associated with PLC hospitalization increased. Strata-specific findings may be reflective of demographic shifts in the PLC patient populations, as well as changes in underlying chronic liver disease etiologies.

The Impact of Malnutrition on the Hospital and Infectious Outcomes of Patients Admitted With Alcoholic Hepatitis: 2011 to 2017 Analysis of US Hospitals.

GOALS: We specifically evaluate the effect of malnutrition on the infection risks of patients admitted with alcoholic hepatitis using a national registry of hospitalized patients in the United States. BACKGROUND: Malnutrition is a common manifestation of alcoholic hepatitis that affects patient outcomes. STUDY: 2011 to 2017 National Inpatient Sample was used to isolated patients with alcoholic hepatitis, stratified using malnutrition (protein-calorie malnutrition, sarcopenia, and weight loss/cachexia) and matched using age, gender, and race with 1:1 nearest neighbor matching method. Endpoints included mortality and infectious endpoints. RESULTS: After matching, there were 10,520 with malnutrition and 10,520 malnutrition-absent controls. Mortality was higher in the malnutrition cohort [5.02 vs. 2.29%, P<0.001, odds ratio (OR): 2.25, 95% confidence interval (CI): 1.93-2.63], as were sepsis (14.2 vs. 5.46, P<0.001, OR: 2.87, 95% CI: 2.60-3.18), pneumonia (10.9 vs. 4.63%, P<0.001, OR: 2.51, 95% CI: 2.25-2.81), urinary tract infection (14.8 vs. 9.01%, P<0.001, OR: 1.76, 95% CI: 1.61-1.91), cellulitis (3.17 vs. 2.18%, P<0.001, OR: 1.47, 95% CI: 1.24-1.74), cholangitis (0.52 vs. 0.20%, P<0.001, OR: 2.63, 95% CI: 1.59-4.35), and Clostridium difficile infection (1.67 vs. 0.91%, P<0.001, OR: 1.85, 95% CI: 1.44-2.37). In multivariate models, malnutrition was associated with mortality [P<0.001, adjusted odds ratio (aOR): 1.61, 95% CI: 1.37-1.90] and infectious endpoints: sepsis (P<0.001, aOR: 2.42, 95% CI: 2.18-2.69), pneumonia (P<0.001, aOR: 2.19, 95% CI: 1.96-2.46), urinary tract infection (P<0.001, aOR: 1.68, 95% CI: 1.53-1.84), cellulitis (P<0.001, aOR: 1.46, 95% CI: 1.22-1.74), cholangitis (P=0.002, aOR: 2.27, 95% CI: 1.36-3.80), and C. difficile infection (P<0.001, aOR: 1.89, 95% CI: 1.46-2.44). CONCLUSION: This study shows the presence of malnutrition is an independent risk factor of mortality and local/systemic infections in patients admitted with alcoholic hepatitis.

Malnutrition as a risk factor of adverse postoperative outcomes in patients undergoing hepatic resection: analysis of US hospitals.

Patients with liver cancer or space-occupying cysts suffer from malnutrition due to compression of gastric and digestive structures, liver and cancer-mediated dysmetabolism, and impaired nutrient absorption. As proportion of these patients requires removal of lesions through hepatic resection, it is important to evaluate the effects of malnutrition on post-hepatectomy outcomes. In our study approach, 2011-2017 National Inpatient Sample was used to isolate in-hospital hepatectomy cases, which were stratified using malnutrition (composite of malnutrition, sarcopenia and weight loss/cachexia). The malnutrition-absent controls were matched to cases using nearest neighbour propensity score matching method and compared with the following endpoints: mortality, length of stay, hospitalisation costs and postoperative complications. There were 2531 patients in total who underwent hepatectomy with matched number of controls from the database; following the match, malnutrition cohort (compared with controls) was more likely to experience in-hospital death (6·60 % v. 5·25 % P < 0·049, OR 1·27, 95 % CI 1·01, 1·61) and was more likely to have higher length of stay (18·10 d v. 9·32 d, P < 0·001) and hospitalisation costs ($278 780 v. $150 812, P < 0·001). In terms of postoperative complications, malnutrition cohort was more likely to experience bleeding (6·52 % v. 3·87 %, P < 0·001, OR 1·73, 95 % CI 1·34, 2·24), infection (6·64 % v. 2·49 %, P < 0·001, OR 2·79, 95 % CI 2·07, 3·74), wound complications (4·5 % v. 1·38 %, P < 0·001, OR 3·36, 95 % CI 2·29, 4·93) and respiratory failure (9·40 % v. 4·11 %, P < 0·001, OR 2·42, 95 % CI 1·91, 3·07). In multivariate analysis, malnutrition was associated with higher mortality (P < 0·028, adjusted OR 1·3, 95 % CI 1·03, 1·65). Thus, we conclude that malnutrition is a risk factor of postoperative mortality in patients undergoing hepatectomy.

The clinical impact of frailty on the postoperative outcomes of patients undergoing gastrectomy for gastric cancer: a propensity-score matched database study.

BACKGROUND: Frailty aggregates a composite of geriatric and elderly features that is classified into a singular syndrome; literature thus far has proven its influence over postoperative outcomes. In this study, we evaluate the effects of frailty following gastrectomy for gastric cancer. METHODS: 2011-2017 National Inpatient Sample was used to isolate patients with gastric cancer undergoing gastrectomy; from this, the Johns Hopkins ACG frailty criteria were applied to segregate frailty-present and absent populations. The case-controls were matched using propensity-score matching and compared to various endpoints. RESULTS: Post match, there were 1171 with and without frailty who were undergoing gastrectomy for gastric cancer. Those with frailty had higher mortality (6.83 vs 3.50% p < 0.001, OR 2.02 95% CI 1.37-2.97), length of stay (16.7 vs 12.0d; p < 0.001), and costs ($191,418 vs $131,367; p < 0.001); frail patients also had higher rates of complications including wound complications (3.42 vs 0.94% p < 0.001, OR 3.73 95% CI 1.90-7.31), infection (5.98 vs 3.67% p = 0.012, OR 1.67 95% CI 1.13-2.46), and respiratory failure (6.32 vs 3.84% p = 0.0084, OR 1.69 95% CI 1.15-2.47). In multivariate, those with frailty had higher mortality (p < 0.001, aOR 2.04 95% CI 1.38-3.01), length of stay (p < 0.001, aOR 1.40 95% CI 1.37-1.43), and costs (p < 0.001, aOR 1.46 95% CI 1.46-1.46). CONCLUSION: This study finding demonstrates the presence of frailty is an independent risk factor of adverse outcomes following gastrectomy; as such, it is important that these high-risk patients are stratified preoperatively and provided risk-averting procedures to alleviate their frailty-defining features.

Clinical frailty is a risk factor of adverse outcomes in patients with esophageal cancer undergoing esophagectomy: analysis of 2011-2017 US hospitals.

Frailty is an aggregate of medical and geriatric conditions that affect elderly and vulnerable patients; as frailty is known to affect postoperative outcomes, we evaluate the effects of frailty in patients undergoing esophageal resection surgery for esophageal cancer. 2011-2017 National Inpatient Sample was used to isolate younger (18 to <65) and older (65 or greater) patients undergoing esophagectomy for esophageal cancer, substratified using frailty (defined by Johns-Hopkins ACG frailty indicator) into frail patients and non-frail controls; the controls were 1:1 matched with frail patients using propensity score. Endpoints included mortality, length of stay (LOS), costs, discharge disposition, and postsurgical complications. Following the match, there were 363 and equal number controls in younger cohort; 383 and equal number controls in older cohort. For younger cohort, frail patients had higher mortality (odds ratio [OR] 3.14 95% confidence interval [CI] 1.39-7.09), LOS (20.5 vs. 13.6 days), costs ($320,074 vs. $190,235) and were likely to be discharged to skilled nursing facilities; however, there was no difference in postsurgical complications. In multivariate, frail patients had higher mortality (aOR 3.00 95%CI 1.29-6.99). In older cohort, frail patients had higher mortality (OR 1.96 95%CI 1.07-3.60), LOS (19.9 vs. 14.3 days), costs ($301,335 vs. $206,648) and were more likely to be discharged to short-term hospitals or skilled nursing facilities; the frail patients were more likely to suffer postsurgical respiratory failure (OR 2.03 95%CI 1.31-3.15). In multivariate, frail patients had higher mortality (aOR 1.93 95%CI 1.04-3.58). Clinical frailty adversely affects both younger and older patients undergoing esophagectomy for esophageal cancer.

The clinical impact of frailty on the postoperative outcomes of patients undergoing appendectomy: propensity score-matched analysis of 2011-2017 US hospitals.

BACKGROUND: The presence of clinical frailty can pose an escalated risk toward surgical outcomes including in cases that involve minimally invasive procedures. Given this premise, we evaluate the effects of frailty on post-appendectomy outcomes using a national in-hospital registry. METHODS: 2011-2017 National Inpatient Sample was used to isolate inpatient appendectomy cases; the population as stratified using Johns Hopkins ACG clinical frailty, expressed as either binary or ternary (prefrailty, frailty, and without frailty) indicators. The controls were matched to frailty-present groups using propensity score matching and compared to various endpoints, including mortality, length of stay (LOS), hospitalization costs, and postoperative complications. RESULTS: Post-match, there were 11,758 with and without frailty per binary; and 1236 frail, 10,522 pre-frail with respective equal number controls per ternary indicator. Using binary term, frail patients had higher mortality (4.22 vs 1.49% OR 2.92 95%CI 2.45-3.47), LOS (14.3 vs 5.35d p < 0.001), and costs ($160,700 vs $64,141 p < 0.001). In multivariate, frail patients had higher mortality (aOR 2.77 95%CI 2.32-3.31), as well as higher rates of postoperative complications. Using ternary term, frail patients had higher mortality (5.02 vs 2.27% OR 2.28 95%CI 1.45-3.59), LOS (18.9 vs 5.66 day p < 0.001) and costs ($200,517 vs $66,193 p < 0.001). In multivariate, frail patients had higher mortality (aOR 2.16 95%CI 1.35-3.43) and complications. Those with pre-frailty had higher mortality (4.12 vs 1.47% OR 2.88 95%CI 2.39-3.46), LOS (13.8 vs 5.34 day p < 0.001) and costs ($156,022 vs $63,772 p < 0.001). In multivariate, pre-frailty patients had higher mortality (aOR 2.79 95%CI 2.31-3.37) and complications. CONCLUSIONS: Frailty and prefrailty (using the ternary indicator) are associated with increased postoperative mortality and complication in patients who undergo appendectomy; given this finding, it is imperative that these vulnerable patients are identified early in the preoperative phase and are provided risk-modifying measures to ameliorate risks and optimize outcomes.

The impact of frailty on the postoperative outcomes of patients undergoing cholecystectomy: propensity score matched analysis of 2011-2017 US hospitals.

BACKGROUND: Frailty is an aggregate variable that encompasses debilitating geriatric conditions, which potentially affects postoperative outcomes. In this study, we evaluate the relationship between clinical frailty and post-cholecystectomy outcomes using a national registry of hospitalized patients. METHODS: 2011-2017 National Inpatient Sample database was used to identify patients who underwent cholecystectomy. Patients were stratified using the Johns Hopkins ACG frailty definition into binary (frailty and no-frailty) and tripartite frailty (frailty, prefrailty, no-frailty) indicators. The controls were matched to study cohort using 1:1 propensity score-matching and postoperative outcomes were compared. RESULTS: Post-match, using the binary term, frail patients (n = 40,067) had higher rates of mortality (OR 2.07 95%CI 1.90-2.25), length of stay, costs, and complications. In multivariate, frailty was associated with higher mortality (aOR 2.06 95%CI 1.89-2.24). When using tripartite frailty term, prefrail (n = 35,595) and frail (n = 4472) patients had higher mortality (prefrailty: OR 2.04 95%CI 1.86-2.23; frailty: OR 2.49 95%CI 1.99-3.13), length of stay, costs, and complications. In multivariate, prefrailty and frailty were associated with higher mortality (prefrailty: aOR 2.02 95%CI 1.84-2.21; frailty: aOR 2.54 95%CI 2.02-3.19). CONCLUSION: This study shows the presence of frailty (and prefrailty) is an independent risk factor of adverse postoperative outcomes in patients undergoing cholecystectomy.

The clinical impact of chronic liver disease in patients undergoing transcatheter and surgical aortic valve replacement: Systematic analysis of the 2011-2017 US hospital database.

OBJECTIVES: In this study, we use a national database to evaluate post-transcatheter (TAVR)/surgical aortic valve replacement (SAVR) outcomes stratified using chronic liver disease (CLD). BACKGROUND: In patients undergoing TAVR and SAVR, the surgical risks should be optimized; this includes evaluating hepatic diseases that may pose an operative risk. METHODS: 2011-2017 National Inpatient Sample was used to select in-hospital TAVR and SAVR cases, which were stratified according to CLD (cirrhosis, hepatitis B/C, alcoholic/fatty/nonspecific liver disease). The cases-controls were matched using propensity score matching and compared with various endpoints. RESULT: After matching for demographics and comorbidities, for TAVR, 606 and 1818 were with or without CLD; for SAVR, 1353 and 4059 were with and without CLD. In TAVR, there was no differences in mortality (2.81% vs. 2.75% OR 1.02 95% CI 0.58-1.78) or length of stay (6.29 vs. 6.44d p = 0.29), and CLD-present patients had marginally increased costs ($228,415 vs. $226,682 p = 0.048). There were no differences in complications. In multivariate, there was no difference in mortality (aOR 1.02 95% CI 0.58-1.79). In SAVR, CLD patients had higher mortality (7.98% vs. 3.23% OR 2.60 95% CI 2.00-3.38), length of stay (13.3 vs. 11.3 days p < 0.001), and costs ($273,487 vs. $238,097 p < 0.001). CLD patients also had increased respiratory failure (9.02% vs. 7.19% OR 1.28 95% CI 1.03-1.59) and bleeding (8.43% vs. 6.33% OR 1.36 95% CI 1.08-1.71). In multivariate, CLD had higher mortality (aOR 2.60 95% CI 2.00-3.38). CONCLUSION: CLD is associated with higher mortality and complications in patients undergoing SAVR; however, no correlation was found in patients undergoing TAVR.

GUESS-ing polygenic associations with multiple phenotypes using a GPU-based evolutionary stochastic search algorithm.

Genome-wide association studies (GWAS) yielded significant advances in defining the genetic architecture of complex traits and disease. Still, a major hurdle of GWAS is narrowing down multiple genetic associations to a few causal variants for functional studies. This becomes critical in multi-phenotype GWAS where detection and interpretability of complex SNP(s)-trait(s) associations are complicated by complex Linkage Disequilibrium patterns between SNPs and correlation between traits. Here we propose a computationally efficient algorithm (GUESS) to explore complex genetic-association models and maximize genetic variant detection. We integrated our algorithm with a new Bayesian strategy for multi-phenotype analysis to identify the specific contribution of each SNP to different trait combinations and study genetic regulation of lipid metabolism in the Gutenberg Health Study (GHS). Despite the relatively small size of GHS (n  =  3,175), when compared with the largest published meta-GWAS (n > 100,000), GUESS recovered most of the major associations and was better at refining multi-trait associations than alternative methods. Amongst the new findings provided by GUESS, we revealed a strong association of SORT1 with TG-APOB and LIPC with TG-HDL phenotypic groups, which were overlooked in the larger meta-GWAS and not revealed by competing approaches, associations that we replicated in two independent cohorts. Moreover, we demonstrated the increased power of GUESS over alternative multi-phenotype approaches, both Bayesian and non-Bayesian, in a simulation study that mimics real-case scenarios. We showed that our parallel implementation based on Graphics Processing Units outperforms alternative multi-phenotype methods. Beyond multivariate modelling of multi-phenotypes, our Bayesian model employs a flexible hierarchical prior structure for genetic effects that adapts to any correlation structure of the predictors and increases the power to identify associated variants. This provides a powerful tool for the analysis of diverse genomic features, for instance including gene expression and exome sequencing data, where complex dependencies are present in the predictor space.

PReMiuM: An R Package for Profile Regression Mixture Models Using Dirichlet Processes.

PReMiuM is a recently developed R package for Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vector to covariate data through cluster membership (Molitor, Papathomas, Jerrett, and Richardson 2010). The package allows binary, categorical, count and continuous response, as well as continuous and discrete covariates. Additionally, predictions may be made for the response, and missing values for the covariates are handled. Several samplers and label switching moves are implemented along with diagnostic tools to assess convergence. A number of R functions for post-processing of the output are also provided. In addition to fitting mixtures, it may additionally be of interest to determine which covariates actively drive the mixture components. This is implemented in the package as variable selection.

Exploring data from genetic association studies using Bayesian variable selection and the Dirichlet process: application to searching for gene × gene patterns.

We construct data exploration tools for recognizing important covariate patterns associated with a phenotype, with particular focus on searching for association with gene-gene patterns. To this end, we propose a new variable selection procedure that employs latent selection weights and compare it to an alternative formulation. The selection procedures are implemented in tandem with a Dirichlet process mixture model for the flexible clustering of genetic and epidemiological profiles. We illustrate our approach with the aid of simulated data and the analysis of a real data set from a genome-wide association study.

A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer.

BACKGROUND: A common characteristic of environmental epidemiology is the multi-dimensional aspect of exposure patterns, frequently reduced to a cumulative exposure for simplicity of analysis. By adopting a flexible Bayesian clustering approach, we explore the risk function linking exposure history to disease. This approach is applied here to study the relationship between different smoking characteristics and lung cancer in the framework of a population based case control study. METHODS: Our study includes 4658 males (1995 cases, 2663 controls) with full smoking history (intensity, duration, time since cessation, pack-years) from the ICARE multi-centre study conducted from 2001-2007. We extend Bayesian clustering techniques to explore predictive risk surfaces for covariate profiles of interest. RESULTS: We were able to partition the population into 12 clusters with different smoking profiles and lung cancer risk. Our results confirm that when compared to intensity, duration is the predominant driver of risk. On the other hand, using pack-years of cigarette smoking as a single summary leads to a considerable loss of information. CONCLUSIONS: Our method estimates a disease risk associated to a specific exposure profile by robustly accounting for the different dimensions of exposure and will be helpful in general to give further insight into the effect of exposures that are accumulated through different time patterns.

The differences in post-liver transplant outcomes of patients with autoimmune hepatitis who present with overlapping autoimmune liver diseases.

BACKGROUND: Patients with autoimmune hepatitis (AIH) may co-present with features of primary biliary cholangitis (PBC) or primary sclerosing cholangitis (PSC). Using a national transplant registry, the outcomes of patients with these autoimmune liver conditions were compared. METHODS: The UNOS-STAR registry was used to select a study population of AIH, PSC, and PBC liver transplant (LT) patients. Living and multi-organ transplant cases were excluded. Using the UNOS-registered diagnoses, the study population was subdivided into those with nonoverlapping autoimmune liver diseases and those with overlapping forms (e.g., AIH-PBC). Outcomes were compared, using endpoints such as all-cause mortality, graft failure, and organ-system specific causes of death. RESULTS: The main analysis featured 2048 entries, with 1927 entries having nonoverlapping AIH, 52 entries having PSC overlap, and 69 entries having PBC overlap. Patients with PBC overlap were more likely to have graft failure (adjusted hazard ratio [aHR] 3.46 95% CI 1.70-7.05), mortality secondary to respiratory causes (aHR 3.57 95% CI 1.23-10.43), and mortality secondary to recurrent disease (aHR 9.53 95% CI 1.85-49.09). Case incidence rates reflected these findings, expressed in events per 1000 person-years. For patients with PBC overlap and nonoverlapping AIH cases, respectively. Graft failure: 28.87 events vs. 9.42 events, mortality secondary to respiratory causes: 12.83 deaths vs. 3.77 deaths, mortality secondary to recurrent disease: 6.42 deaths vs. 1.26 deaths. Those with AIH-PSC overlap experienced a higher risk of death from graft infection (aHR 10.43 95% CI 1.08-100.37; case-incidence rate: 3.89 vs. 0.31 mortalities per 1000 person-years). Supplementary analysis showed similar findings, in which overlapping autoimmune conditions were associated with higher adverse outcome rates. CONCLUSION: Patients with AIH-PBC overlap have higher risk of mortality due to recurrent liver disease and respiratory causes, and patients with AIH-PSC overlap have higher risk of mortality due to graft infection. While further prospective studies are needed to clarify the underlying mechanisms related to these findings, our study characterizes the prognostic implications of AIH overlap on post-LT mortality and graft failure risks.

ESS++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration.

SUMMARY: ESS++ is a C++ implementation of a fully Bayesian variable selection approach for single and multiple response linear regression. ESS++ works well both when the number of observations is larger than the number of predictors and in the 'large p, small n' case. In the current version, ESS++ can handle several hundred observations, thousands of predictors and a few responses simultaneously. The core engine of ESS++ for the selection of relevant predictors is based on Evolutionary Monte Carlo. Our implementation is open source, allowing community-based alterations and improvements. AVAILABILITY: C++ source code and documentation including compilation instructions are available under GNU licence at http://bgx.org.uk/software/ESS.html.

The impact of cirrhosis on the postoperative outcomes of patients undergoing splenectomy: Propensity score matched analysis of the 2011-2017 US hospital database.

BACKGROUND & OBJECTIVE: While splenectomy is performed for various trauma and non-trauma indications, there is little information about the impact of cirrhosis on the post-splenectomy outcomes, despite the intricate physiological and vascular connection between the liver and the spleen. METHODS: 2011-2017 National Inpatient Sample was used to select patient cases who underwent the splenectomy procedure, who were further stratified using cirrhosis. The cirrhosis-absent controls were matched to the study cohort using propensity score matching with nearest neighbor matching method. Endpoints included mortality, length of stay, hospitalization costs, and postoperative complications. RESULTS: There were 675 patients with cirrhosis and 675 matched controls identified from the database. Cirrhosis cohort had higher mortality (20.0 vs 7.26%, p < 0.001, OR = 3.19, 95% CI = 2.26-4.52) and hospitalization costs ($210,716 vs $186,673, p = 0.003), but shorter length of stay (11.8 vs 12.5d, p = 0.04). In terms of complications, cirrhosis cohorts had higher postoperative bleeding (7.26 vs 4.3%, p = 0.027, OR = 1.74, 95% CI = 1.09-2.80) and shock (3.7 vs 1.04%, p = 0.002, OR = 3.67, 95% CI = 1.58-8.54), and were more likely to be discharged to short-term hospitals and home with home health care. On multivariate analysis, presence of cirrhosis resulted in higher mortality (p < 0.001, aOR = 3.30, 95% CI = 2.33-4.69). CONCLUSIONS: Cirrhosis is an independent risk factor of postoperative mortality in patients undergoing splenectomy; given this finding, further precautious and multidisciplinary care should be rendered in these at-risk patients with cirrhosis in the setting of splenectomy.

Effect of malnutrition on the postoperative outcomes of patients undergoing pancreatectomy for pancreatic cancer: Propensity score-matched analysis of 2011-2017 US hospitals.

BACKGROUND: Patients with pancreatic cancer suffer from metabolic dysregulation, which can manifest in clinical malnutrition. Because a portion of these patients require cancer-resective surgery, we evaluate the impact of malnutrition in patients undergoing pancreatic resection using a national database. METHODS: The 2011-2017 National Inpatient Sample was used to isolate cases of pancreatic resection (partial/total pancreatectomy and radical pancreaticoduodenectomy), which were stratified using malnutrition. A 1:1 nearest-neighbor propensity-score matching was applied to match the controls to the malnutrition cohort. End points include mortality, length of stay (LOS), hospitalization costs, and postoperative complications. RESULTS: Following the match, there were 2108 with malnutrition and an equal number without; from this, those with malnutrition had higher mortality (4.7% vs 3.04%; P = 0.007; odds ratio [OR], 1.57; 95% CI, 1.14-2.17), longer LOS, and higher costs. Regarding complications, malnourished patients had higher bleeding (5.41% vs 2.99%; P < 0.001; OR, 1.86; 95% CI, 1.36-2.54), wound complications (3.75% vs 1.57%; P < 0.001; OR, 2.45; 95% CI, 1.62-3.69), infection (7.83% vs 3.13%; P < 0.001; OR, 2.63; 95% CI, 1.96-3.52), and respiratory failure (7.45% vs 3.56%; P < 0.001; OR, 2.18; 95% CI, 1.65-2.89). In multivariate analyses, those with malnutrition had higher mortality (P = 0.008; adjust OR, 1.55; 95% CI, 1.12-2.14). CONCLUSION: Those with malnutrition had higher mortality and complications following pancreatic resection; given these findings, it is important that preoperative nutrition therapy is provided to minimize the surgical risks.

Identifying vulnerable populations through an examination of the association between multipollutant profiles and poverty.

Recently, concerns have centered on how to expand knowledge on the limited science related to the cumulative impact of multiple air pollution exposures and the potential vulnerability of poor communities to their toxic effects. The highly intercorrelated nature of exposures makes application of standard regression-based methods to these questions problematic due to well-known issues related to multicollinearity. Our paper addresses these problems by using, as its basic unit of inference, a profile consisting of a pattern of exposure values. These profiles are grouped into clusters and associated with a deprivation outcome. Specifically, we examine how profiles of NO(2)-, PM(2.5)-, and diesel- (road and off-road) based exposures are associated with the number of individuals living under poverty in census tracts (CT's) in Los Angeles County. Results indicate that higher levels of pollutants are generally associated with higher poverty counts, though the association is complex and nonlinear. Our approach is set in the Bayesian framework, and as such the entire model can be fit as a unit using modern Bayesian multilevel modeling techniques via the freely available WinBUGS software package, (1) though we have used custom-written C++ code (validated with WinBUGS) to improve computational speed. The modeling approach proposed thus goes beyond single-pollutant models in that it allows us to determine the association between entire multipollutant profiles of exposures with poverty levels in small geographic areas in Los Angeles County.

The clinical impact of paroxysmal arrhythmias on the hospital outcomes of patients admitted with cirrhosis: propensity score matched analysis of 2011-2017 US hospitals.

BACKGROUND: We evaluate the effects of paroxysmal arrhythmia on the hospital outcomes of patients admitted with cirrhosis. RESEARCH DESIGN AND METHODS: 2011-2017 National Inpatient Sample was used to isolate patients with decompensated/compensated cirrhosis, stratified by paroxysmal arrhythmia (supraventricular: PSVT and ventricular: PVT). The cohorts were matched using propensity-score matching and compared to mortality, length of stay, cost, and cardiac complications (cardioversion, cardiogenic shock, cardiac arrest, and ventricular fibrillation). RESULTS: In compensated cirrhosis, 2,453 had PSVT with matched controls; 5,274 had PVT with matched controls. Those with PSVT had higher mortality (aOR 1.55 95%CI 1.23-1.95) and higher rates of cardioversion and cardiogenic shock; likewise, those with PVT had higher mortality (aOR 2.41 95%CI 2.09-2.78) and higher rates of all complications. In decompensated cirrhosis, 1,598 had PSVT with matched controls; 4,178 had PVT with matched controls. Those with PSVT had higher mortality (aOR 1.57 95%CI 1.28-1.93) and higher rates of cardioversion, cardiogenic shock, cardiac arrest; those with PVT had higher mortality (aOR 2.25 95%CI 1.98-2.56) and higher rates of all complications. CONCLUSION: The findings from this study show that in either decompensated or compensated cohort, those with paroxysmal arrhythmias are at a higher risk of in-hospital mortality and adverse cardiac outcomes.

The clinical impact of malnutrition on the postoperative outcomes of patients undergoing gastrectomy for gastric cancer: Propensity score matched analysis of 2011-2017 hospital database.

BACKGROUND & AIMS: Malnutrition is a prominent feature of gastric cancer patients who suffer from gastric outlet obstruction, impaired peristalsis, and cancer-mediated disruptions in metabolic hemostasis. In this study, we systematically evaluate the impact of malnutrition on the postoperative outcome of patients with gastric cancer undergoing gastrectomy. METHODS: 2011-2017 National Inpatient Sample was used to isolate patients with gastric cancer who underwent gastrectomy, who were stratified using malnutrition. The malnutrition-present cohort was matched to the malnutrition-absent controls using 1:1 propensity score-matching analysis, and compared to the following endpoints: mortality, length of stay (LOS), hospitalization costs, and postoperative complications. RESULTS: 5309 were identified to have undergone gastric resection procedure for gastric cancer, from which there were 1044 with malnutrition and 1044 matched controls. Malnourished patients had higher mortality (6.80 vs 3.83% p = 0.003, OR 1.83 95% CI 1.23-2.73), LOS (17.2 vs 11.4 d p < 0.001), costs ($197,702 vs $124,133 p < 0.001), and were more often discharged to rehabilitation facilities. Malnourished patients had higher rates of wound complications (3.64 vs 1.25% p < 0.001, OR 3.00 95% CI 1.59-5.66), infection (6.90 vs 3.26% p < 0.001, OR 2.20 95% CI 1.45-3.34), and respiratory failure (6.80 vs 3.64% p = 0.002, OR 1.93 95% CI 1.29-2.89). In multivariate analysis, malnourished patients had higher rates of mortality (p = 0.002, aOR 1.87 95% CI 1.25-2.80), length of stay (p < 0.001, aOR 1.52 95% CI 1.48-1.55), costs (p < 0.001, aOR 1.61 95% CI 1.61-1.61) despite controlling for non-matched hospital variables. CONCLUSION: In this propensity score matched analysis, malnutrition is associated with increased postoperative mortality, LOS, and hospitalization costs in patients with gastric cancer undergoing gastric resection surgery.