The cost of lung transplantation in the United States: How high is too high?

Objectives: To identify patient and process factors that contribute to the high cost of lung transplantation (LTx) in the perioperative period, which may allow transplant centers to evaluate situations in which transplantation is most cost-effective to inform judicious resource allocation, avoid futile care, and reduce costs. Methods: The MarketScan Research databases were used to identify 582 privately insured patients undergoing single or bilateral LTx between 2013 and 2019. The patients were subdivided into groups by disease etiology using the United Network of Organ Sharing classification system. Multivariable generalized linear models using a gamma distribution with a log link were fit to examine the associations between the etiology of lung disease and costs during the index admission, 3 months before admission, and 3 months after discharge. Results: Our results indicate that the index admission contributed the most to the total transplantation costs compared to the 3 months before admission and after discharge. The regression-adjusted mean index hospitalization cost was 35% higher for patients with pulmonary vascular disease compared to those with obstructive lung disease ($527,156 vs $389,055). The use of extracorporeal membrane oxygenation, mechanical ventilation, and surgical complications in the post-transplantation period were associated with higher costs during the index admission. Surprisingly, age ≥55 was associated with lower costs during the index admission. Conclusions: This analysis identifies pivotal factors influencing the high cost of LTx, emphasizing the significant impact of the index admission, particularly for patients with pulmonary vascular disease. These insights offer transplant centers an opportunity to enhance cost-effectiveness through judicious resource allocation and service bundling, ultimately reducing overall transplantation costs.

RNA Binding Proteins that Mediate LPS-induced Alternative Splicing of the MyD88 Innate Immune Regulator.

Inflammation driven by Toll-like receptor (TLR) signaling pathways is required to combat infection. However, inflammation can damage host tissues; thus it is essential that TLR signaling ultimately is terminated to prevent chronic inflammatory disorders. One mechanism that terminates persistent TLR signaling is alternative splicing of the MyD88 signaling adaptor, which functions in multiple TLR signaling pathways. While the canonical long isoform of MyD88 (MyD88-L) mediates TLR signaling and promotes inflammation, an alternatively-spliced shorter isoform of MyD88 (MyD88-S) produces a dominant negative inhibitor of TLR signaling. MyD88-S production is induced by inflammatory agonists including lipopolysaccharide (LPS), and thus MyD88-S induction is thought to act as a negative feedback loop that prevents chronic inflammation. Despite the potential role that MyD88-S production plays in inflammatory disorders, the mechanisms controlling MyD88 alternative splicing remain unclear. Here, we identify two RNA binding proteins, SRSF1 and HNRNPU, that regulate LPS-induced alternative splicing of MyD88.

Spatially localized sparse approximations of deep features for breast mass characterization.

We propose a deep feature-based sparse approximation classification technique for classification of breast masses into benign and malignant categories in film screen mammographs. This is a significant application as breast cancer is a leading cause of death in the modern world and improvements in diagnosis may help to decrease rates of mortality for large populations. While deep learning techniques have produced remarkable results in the field of computer-aided diagnosis of breast cancer, there are several aspects of this field that remain under-studied. In this work, we investigate the applicability of deep-feature-generated dictionaries to sparse approximation-based classification. To this end we construct dictionaries from deep features and compute sparse approximations of Regions Of Interest (ROIs) of breast masses for classification. Furthermore, we propose block and patch decomposition methods to construct overcomplete dictionaries suitable for sparse coding. The effectiveness of our deep feature spatially localized ensemble sparse analysis (DF-SLESA) technique is evaluated on a merged dataset of mass ROIs from the CBIS-DDSM and MIAS datasets. Experimental results indicate that dictionaries of deep features yield more discriminative sparse approximations of mass characteristics than dictionaries of imaging patterns and dictionaries learned by unsupervised machine learning techniques such as K-SVD. Of note is that the proposed block and patch decomposition strategies may help to simplify the sparse coding problem and to find tractable solutions. The proposed technique achieves competitive performances with state-of-the-art techniques for benign/malignant breast mass classification, using 10-fold cross-validation in merged datasets of film screen mammograms.

With Comparable Outcomes, Should Early-Stage Lung Cancer Be a Contraindication to Lung Transplant?

BACKGROUND: Active primary lung malignancy remains a strong contraindication to lung transplantation (LTx). However, outcomes are unclear for patients with early-stage non-small cell lung cancer (NSCLC) who undergo LTx. We hypothesize that patients with early-stage NSCLC incidentally discovered in the explanted lungs have survival comparable to LTx recipients without incidental cancer identified. METHODS: We performed a single-center retrospective analysis of all LTx recipients from May 2007 to September 2021 with incidental cancer identified in the explanted lungs by pathologist report. Survival statistics were estimated using Kaplan-Meier analysis. RESULTS: Of the 1586 LTx performed, 23 patients (1.5%) were found to have incidental lung cancer in the explanted lungs. The most common indications for LTx were interstitial lung disease (n = 13) and chronic obstructive pulmonary disease (n = 7), and the most common histologic diagnosis was adenocarcinoma (n = 14). In the cohort with stage I disease (n = 9), the 1- and 5-year unadjusted Kaplan-Meier survival rates were 88.9% and 51.9%, respectively. The 1- and 5-year survival rates for transplant recipients without incidental cancer findings at LTx during this period were 86.7% and 59.4%, respectively, and did not differ significantly between the 2 strata (P = .96). CONCLUSIONS: Survival rates at 1 and 5 years were comparable between LTx recipients with incidentally noted pathologic stage I NSCLC and contemporary recipients without cancer. All cancer-related deaths occurred in recipients with incidentally noted advanced NSCLC. These results suggest that patients with pathologic stage I lung cancer at the time of transplant have outcomes comparable to those without cancer findings at the time of transplant.

Myelodysplastic neoplasm-associated U2AF1 mutations induce host defense defects by compromising neutrophil chemotaxis.

Myelodysplastic neoplasm (MDS) is a hematopoietic stem cell disorder that may evolve into acute myeloid leukemia. Fatal infection is among the most common cause of death in MDS patients, likely due to myeloid cell cytopenia and dysfunction in these patients. Mutations in genes that encode components of the spliceosome represent the most common class of somatically acquired mutations in MDS patients. To determine the molecular underpinnings of the host defense defects in MDS patients, we investigated the MDS-associated spliceosome mutation U2AF1-S34F using a transgenic mouse model that expresses this mutant gene. We found that U2AF1-S34F causes a profound host defense defect in these mice, likely by inducing a significant neutrophil chemotaxis defect. Studies in human neutrophils suggest that this effect of U2AF1-S34F likely extends to MDS patients as well. RNA-seq analysis suggests that the expression of multiple genes that mediate cell migration are affected by this spliceosome mutation and therefore are likely drivers of this neutrophil dysfunction.

Assessment of Gender Bias During Paramedic-Physician Handoffs.

Objective Gender bias against female physicians has been frequently demonstrated and associated with negative feelings toward their careers. Gender bias has also been demonstrated in prehospital clinical care. However, potential gender bias during paramedic-physician handoffs has not been studied. This study aimed to identify gender bias during interactions between prehospital personnel and emergency physicians at the time of patient handoff. Methods An observational study was conducted at an urban academic emergency department. Observers were trained to record information from paramedic-physician handoffs but were blind to the nature of the study. The primary outcome was to whom paramedics initially directed the focus of their handoff report based on physician gender, with secondary outcomes of to whom paramedics directed most of their report and whether they asked about further questions based on physician gender. Results There were 784 observed handoffs. There was no significant association between the gender of the physician and which physician received first attention (χ2 {1, N = 782} = 0.9736, p = 0.3238) or majority attention (χ2 {1, N = 780} = 1.9414, p = 0.1635). Paramedics were more likely to ask questions to male attendings than female attendings (χ2 {1, N = 784} = 4.4319, p = 0.0353). Conclusion We identified limited differences in communication based on gender between paramedics and physicians during emergency department patient handoffs.

A radio-detected type Ia supernova with helium-rich circumstellar material.

Type Ia supernovae (SNe Ia) are thermonuclear explosions of degenerate white dwarf stars destabilized by mass accretion from a companion star1, but the nature of their progenitors remains poorly understood. A way to discriminate between progenitor systems is through radio observations; a non-degenerate companion star is expected to lose material through winds2 or binary interaction3 before explosion, and the supernova ejecta crashing into this nearby circumstellar material should result in radio synchrotron emission. However, despite extensive efforts, no type Ia supernova (SN Ia) has ever been detected at radio wavelengths, which suggests a clean environment and a companion star that is itself a degenerate white dwarf star4,5. Here we report on the study of SN 2020eyj, a SN Ia showing helium-rich circumstellar material, as demonstrated by its spectral features, infrared emission and, for the first time in a SN Ia to our knowledge, a radio counterpart. On the basis of our modelling, we conclude that the circumstellar material probably originates from a single-degenerate binary system in which a white dwarf accretes material from a helium donor star, an often proposed formation channel for SNe Ia (refs. 6,7). We describe how comprehensive radio follow-up of SN 2020eyj-like SNe Ia can improve the constraints on their progenitor systems.

Understanding the Sensitivity of Grape Terpenes to Jasmonates Using In Vitro Culture and In Vivo Vineyard Experiments.

Terpene volatiles define the flavor of terpenic grape cultivars. However, grape terpene concentrations can vary 2- to 3-fold across seasons and vineyards, impacting vintage quality. The plant hormone methyl jasmonate (MeJA) stimulates grape terpene production but is expensive and can decrease berry weight and maturity. The synthetic jasmonate prohydrojasmon (PDJ) is cost-effective yet has not been evaluated on grape maturity and terpene production. Here, we performed in vitro (berry culture) and in vivo (vineyard) experiments using Gewürztraminer (Vitis vinifera L.) to evaluate the time- and concentration-dependent sensitivity of maturity parameters and terpene content to MeJA and PDJ. In vitro berry weight was reduced by high MeJA and PDJ concentration across timings. Terpenes were most sensitive to low MeJA concentration at veraison (increased 24-fold) in vitro. Moderate PDJ concentration applied at veraison doubled (increased twofold) terpene concentration in vivo without impacting berry weight or maturity. In conclusion, PDJ may provide a solution to mitigate seasonal variability in terpene production in terpenic grape cultivars.

Guide to the Female Student Athlete ECG: A Comprehensive Study of 3466 Young, Racially Diverse Athletes.

OBJECTIVES: The 12-lead electrocardiogram (ECG) is used in the preparticipation screening examination for athletes. Despite known differences in ECG findings by sex, only QTc prolongation is given a sex-specific threshold. We hypothesize that our large dataset-with diversity in age, race, and sport participation-can be utilized to improve ECG screening in female student athletes. METHODS: Computerized 12-lead ECGs were recorded and analyzed in female athletes who underwent preparticipation screening examination between June 2010 and September 2021. The quantitative, empirical 2017 international criteria for electrocardiographic interpretation were compared with either the 99th percentile in our cohort or the percentile that corresponded to the known disease prevalence. RESULTS: Of 3466 female athletes with ECGs as part of preparticipation screening examination, the 2017 international criteria classified 2.1% of athletes with at least one ECG abnormality requiring cardiological evaluation. Rates were similar across age, race/ethnicity, and sporting discipline. Using ranges based on our population, 2.7% of athletes would require additional workup. Surprisingly, ST depression up to 0.03 mV was a normal finding in this cohort. If RS voltage extremes were considered findings requiring follow-up, an additional 9.6% of the athlete population would be flagged using current definitions. This number decreases to 2.7% if using the 99th percentile in this cohort. CONCLUSION: These results highlight a difference in the reported prevalence of ECG abnormalities when comparing empirically derived thresholds to statistically derived ranges. Consideration of new metrics specific to the female athlete population has the potential to further refine athlete ECG screening.

Textbook outcome in lung transplantation: Planned venoarterial extracorporeal membrane oxygenation versus off-pump support for patients without pulmonary hypertension.

BACKGROUND: Planned venoarterial extracorporeal membrane oxygenation (VA ECMO) is increasingly used during bilateral orthotopic lung transplantation (BOLT) and may be superior to off-pump support for patients without pulmonary hypertension. In this single-institution study, we compared rates of textbook outcome between BOLTs performed with planned VA ECMO or off-pump support for recipients with no or mild pulmonary hypertension. METHODS: Patients with no or mild pulmonary hypertension who underwent isolated BOLT between 1/2017 and 2/2021 with planned off-pump or VA ECMO support were included. Textbook outcome was defined as freedom from intraoperative complication, 30-day reintervention, 30-day readmission, post-transplant length of stay >30 days, 90-day mortality, 30-day acute rejection, grade 3 primary graft dysfunction at 48 or 72 hours, post-transplant ECMO, tracheostomy within 7 days, inpatient dialysis, reintubation, and extubation >48 hours post-transplant. Textbook outcome achievement was compared between groups using multivariable logistic regression. RESULTS: Two hundred thirty-seven BOLTs were included: 68 planned VA ECMO and 169 planned off-pump. 14 (20.6%) planned VA ECMO and 27 (16.0%) planned off-pump patients achieved textbook outcome. After adjustment for prior BOLT, lung allocation score, ischemic time, and intraoperative transfusions, planned VA ECMO was associated with higher odds of textbook outcome than planned off-pump support (odds ratio 3.89, 95% confidence interval 1.58-9.90, p = 0.004). CONCLUSIONS: At our institution, planned VA ECMO for isolated BOLT was associated with higher odds of textbook outcome than planned off-pump support among patients without pulmonary hypertension. Further investigation in a multi-institutional cohort is warranted to better elucidate the utility of this strategy.

CarboGrove: a resource of glycan-binding specificities through analyzed glycan-array datasets from all platforms.

Glycan arrays continue to be the primary resource for determining the glycan-binding specificity of proteins. The volume and diversity of glycan-array data are increasing, but no common method and resource exist to analyze, integrate, and use the available data. To meet this need, we developed a resource of analyzed glycan-array data called CarboGrove. Using the ability to process and interpret data from any type of glycan array, we populated the database with the results from 35 types of glycan arrays, 13 glycan families, 5 experimental methods, and 19 laboratories or companies. In meta-analyses of glycan-binding proteins, we observed glycan-binding specificities that were not uncovered from single sources. In addition, we confirmed the ability to efficiently optimize selections of glycan-binding proteins to be used in experiments for discriminating between closely related motifs. Through descriptive reports and a programmatically accessible Application Programming Interface, CarboGrove yields unprecedented access to the wealth of glycan-array data being produced and powerful capabilities for both experimentalists and bioinformaticians.

Statins Are Associated With Increased Insulin Resistance and Secretion.

Objective: Statin treatment reduces the risk of atherosclerotic cardiovascular disease but is associated with a modest increased risk of type 2 diabetes, especially in those with insulin resistance or prediabetes. Our objective was to determine the physiological mechanism for the increased type 2 diabetes risk. Approach and Results: We conducted an open-label clinical trial of atorvastatin 40 mg daily in adults without known atherosclerotic cardiovascular disease or type 2 diabetes at baseline. The co-primary outcomes were changes at 10 weeks versus baseline in insulin resistance as assessed by steady-state plasma glucose during the insulin suppression test and insulin secretion as assessed by insulin secretion rate area under the curve (ISRAUC) during the graded-glucose infusion test. Secondary outcomes included glucose and insulin, both fasting and during oral glucose tolerance test. Of 75 participants who enrolled, 71 completed the study (median age 61 years, 37% women, 65% non-Hispanic White, median body mass index, 27.8 kg/m2). Atorvastatin reduced LDL (low-density lipoprotein)-cholesterol (median decrease 53%, P<0.001) but did not change body weight. Compared with baseline, atorvastatin increased insulin resistance (steady-state plasma glucose) by a median of 8% (P=0.01) and insulin secretion (ISRAUC) by a median of 9% (P<0.001). There were small increases in oral glucose tolerance test glucoseAUC (median increase, 0.05%; P=0.03) and fasting insulin (median increase, 7%; P=0.01). Conclusions: In individuals without type 2 diabetes, high-intensity atorvastatin for 10 weeks increases insulin resistance and insulin secretion. Over time, the risk of new-onset diabetes with statin use may increase in individuals who become more insulin resistant but are unable to maintain compensatory increases in insulin secretion.

Cultural Complications Curriculum: Applicability to Surgical Oncology Programs and Practices.

BACKGROUND: Recognizing the need to raise awareness of core diversity, equity, and inclusion (DEI) issues in the healthcare system, our previously developed Cultural Complications Curriculum aims to support institutions in reducing cultural error. As we continue program deployment, we discuss the opportunity to apply the Cultural Complications Curriculum to multidisciplinary audiences, such as in cancer programs. METHODS: We discuss applicability of the Cultural Complications Curriculum to cancer programs and practices, including how to tailor case discussions to oncology audiences. By emphasizing the unique characteristics of the multidisciplinary care environment and anticipating potential barriers to curriculum implementation, we demonstrate how the Cultural Complications Curriculum may support culture improvement across broad audiences. RESULTS: The successful application of the Cultural Complication Curriculum to multidisciplinary care programs will depend on appreciating differences in background knowledge, tailoring discussions to audience needs, and adapting material by incorporating new data and addressing emerging DEI issues. Multidisciplinary environments may require innovative approaches to education including virtual platforms, increased collaboration across centers and systems, and support from professional societies. In integrated care environments, like oncology, effective DEI discussions call for the engagement of a variety of medical specialties and departments. CONCLUSIONS: To meet the needs of an increasingly diverse patient population and workforce, our approach to DEI education must embrace the interdependent nature of care delivery. In oncology and other multidisciplinary care environments, application of the Cultural Complications Curriculum may be the first step to combating cultural error by engaging a broader demographic within our healthcare system.

Patterns of Community Violence Exposure among African American Adolescents Living in Low-Resourced Urban Neighborhoods.

African American adolescents living in neighborhoods with concentrated economic disadvantage are disproportionately exposed to community violence. This study builds upon previous research and examines patterns, severity, and chronicity of violence exposure, within a sample of African American adolescents living in low-resourced, urban neighborhoods (n = 327). The influence of both individual- and contextual-level factors on community violence exposure (CVE) is examined. Data were collected across four time points at 6-month intervals. Latent transition analysis identified three patterns of CVE at each time point: low witnessing and low victimization (LW-LV), high witnessing and low victimization (HW-LV), and high witnessing and high victimization (HW-HV), as well as transitions between each class. Although a stable LW-LV class membership over time was the most prevalent pattern, most adolescents experienced some change in exposure. Nearly one-third of the participants were classified in the HW-HV group at some point in time. Analyses on individual- and contextual-level factors revealed that more depressive symptoms, community problems (e.g., drugs, graffiti, noise), or community resources (e.g., schools, parks, recreational facilities) were associated with an increased likelihood of experiencing high levels of violent victimization. Implications for intervention and prevention of CVE are discussed.

Discriminative Localized Sparse Approximations for Mass Characterization in Mammograms.

The most common form of cancer among women in both developed and developing countries is breast cancer. The early detection and diagnosis of this disease is significant because it may reduce the number of deaths caused by breast cancer and improve the quality of life of those effected. Computer-aided detection (CADe) and computer-aided diagnosis (CADx) methods have shown promise in recent years for aiding in the human expert reading analysis and improving the accuracy and reproducibility of pathology results. One significant application of CADe and CADx is for breast cancer screening using mammograms. In image processing and machine learning research, relevant results have been produced by sparse analysis methods to represent and recognize imaging patterns. However, application of sparse analysis techniques to the biomedical field is challenging, as the objects of interest may be obscured because of contrast limitations or background tissues, and their appearance may change because of anatomical variability. We introduce methods for label-specific and label-consistent dictionary learning to improve the separation of benign breast masses from malignant breast masses in mammograms. We integrated these approaches into our Spatially Localized Ensemble Sparse Analysis (SLESA) methodology. We performed 10- and 30-fold cross validation (CV) experiments on multiple mammography datasets to measure the classification performance of our methodology and compared it to deep learning models and conventional sparse representation. Results from these experiments show the potential of this methodology for separation of malignant from benign masses as a part of a breast cancer screening workflow.