A qualitative co-design-based approach to identify sources of workplace-related distress and develop well-being strategies for cardiovascular nurses, allied health professionals, and physicians.

OBJECTIVE: Clinician distress is a multidimensional condition that includes burnout, decreased meaning in work, severe fatigue, poor work-life integration, reduced quality of life, and suicidal ideation. It has negative impacts on patients, providers, and healthcare systems. In this three-phase qualitative investigation, we identified workplace-related factors that drive clinician distress and co-designed actionable interventions with inter-professional cardiovascular clinicians to decrease their distress and improve well-being within a Canadian quaternary hospital network. METHODS: Between October 2021 and May 2022, we invited nurses, allied health professionals, and physicians to participate in a three-phase qualitative investigation. Phases 1 and 2 included individual interviews and focus groups to identify workplace-related factors contributing to distress. Phase 3 involved co-design workshops that engaged inter-professional clinicians to develop interventions addressing drivers of distress identified. Qualitative information was analyzed using descriptive thematic analysis. RESULTS: Fifty-one clinicians (24 nurses, 10 allied health professionals, and 17 physicians) participated. Insights from Phases 1 and 2 identified five key thematic drivers of distress: inadequate support within inter-professional teams, decreased joy in work, unsustainable workloads, limited opportunities for learning and professional growth, and a lack of transparent leadership communication. Phase 3 co-design workshops yielded four actionable interventions to mitigate clinician distress in the workplace: re-designing daily safety huddles, formalizing a nursing coaching and mentorship program, creating a value-added program e-newsletter, and implementing an employee experience platform. CONCLUSION: This study increases our understanding on workplace-related factors that contribute to clinician distress, as shared by inter-professional clinicians specializing in cardiovascular care. Healthcare organizations can develop effective interventions to mitigate clinician distress by actively engaging healthcare workers in identifying workplace drivers of distress and collaboratively designing tailored, practical interventions that directly address these challenges.

Prevalence and drivers of nurse and physician distress in cardiovascular and oncology programmes at a Canadian quaternary hospital network during the COVID-19 pandemic: a quality improvement initiative.

OBJECTIVES: To assess the prevalence and drivers of distress, a composite of burnout, decreased meaning in work, severe fatigue, poor work-life integration and quality of life, and suicidal ideation, among nurses and physicians during the COVID-19 pandemic. DESIGN: Cross-sectional design to evaluate distress levels of nurses and physicians during the COVID-19 pandemic between June and August 2021. SETTING: Cardiovascular and oncology care settings at a Canadian quaternary hospital network. PARTICIPANTS: 261 nurses and 167 physicians working in cardiovascular or oncology care. Response rate was 29% (428 of 1480). OUTCOME MEASURES: Survey tool to measure clinician distress using the Well-Being Index (WBI) and additional questions about workplace-related and COVID-19 pandemic-related factors. RESULTS: Among 428 respondents, nurses (82%, 214 of 261) and physicians (62%, 104 of 167) reported high distress on the WBI survey. Higher WBI scores (≥2) in nurses were associated with perceived inadequate staffing (174 (86%) vs 28 (64%), p=0.003), unfair treatment, (105 (52%) vs 11 (25%), p=0.005), and pandemic-related impact at work (162 (80%) vs 22 (50%), p<0.001) and in their personal life (135 (67%) vs 11 (25%), p<0.001), interfering with job performance. Higher WBI scores (≥3) in physicians were associated with perceived inadequate staffing (81 (79%) vs 32 (52%), p=0.001), unfair treatment (44 (43%) vs 13 (21%), p=0.02), professional dissatisfaction (29 (28%) vs 5 (8%), p=0.008), and pandemic-related impact at work (84 (82%) vs 35 (56%), p=0.001) and in their personal life (56 (54%) vs 24 (39%), p=0.014), interfering with job performance. CONCLUSION: High distress was common among nurses and physicians working in cardiovascular and oncology care settings during the pandemic and linked to factors within and beyond the workplace. These results underscore the complex and contextual aspects of clinician distress, and the need to develop targeted approaches to effectively address this problem.

Association Between the Incidence of Hospitalizations for Acute Cardiovascular Events, Weather, and Air Pollution.

Background: The incidence of hospitalizations for cardiovascular events has been associated with specific weather conditions and air pollution. A comprehensive model including the interactions between various environmental factors remains to be developed. Objectives: The purpose of this study was to develop a comprehensive model of the association between weather patterns and the incidence of cardiovascular events and use this model to forecast near-term spatiotemporal risk. Methods: We present a spatiotemporal analysis of the association between atmospheric data and the incidence rate of hospital admissions related to heart failure (922,132 episodes), myocardial infarction (521,988 episodes), and ischemic stroke (263,529 episodes) in ∼24 million people in Canada between 2007 and 2017. Our hierarchical Bayesian model captured the spatiotemporal distribution of hospitalizations and identified weather and air pollution-related factors that could partially explain fluctuations in incidence. Results: Models that included weather and air pollution variables outperformed models without those covariates for most event types. Our results suggest that environmental factors may interact in complex ways on human physiology. The impact of environmental factors was magnified with increasing age. The weather and air pollution variables included in our models were predictive of the future incidence of heart failure, myocardial infarction, and ischemic strokes. Conclusions: The increasing importance of environmental factors on cardiovascular events with increasing age raises the need for the development of educational materials for older patients to recognize environmental conditions where exacerbations are more likely. This model could be the basis of a forecasting system used for local, short-term clinical resource planning based on the anticipated incidence of events.

Colony stimulating factor-1 producing endothelial cells and mesenchymal stromal cells maintain monocytes within a perivascular bone marrow niche.

Macrophage colony stimulating factor-1 (CSF-1) plays a critical role in maintaining myeloid lineage cells. However, congenital global deficiency of CSF-1 (Csf1op/op) causes severe musculoskeletal defects that may indirectly affect hematopoiesis. Indeed, we show here that osteolineage-derived Csf1 prevented developmental abnormalities but had no effect on monopoiesis in adulthood. However, ubiquitous deletion of Csf1 conditionally in adulthood decreased monocyte survival, differentiation, and migration, independent of its effects on bone development. Bone histology revealed that monocytes reside near sinusoidal endothelial cells (ECs) and leptin receptor (Lepr)-expressing perivascular mesenchymal stromal cells (MSCs). Targeted deletion of Csf1 from sinusoidal ECs selectively reduced Ly6C- monocytes, whereas combined depletion of Csf1 from ECs and MSCs further decreased Ly6Chi cells. Moreover, EC-derived CSF-1 facilitated recovery of Ly6C- monocytes and protected mice from weight loss following induction of polymicrobial sepsis. Thus, monocytes are supported by distinct cellular sources of CSF-1 within a perivascular BM niche.

Factors associated with SARS-CoV-2 test positivity in long-term care homes: A population-based cohort analysis using machine learning.

BACKGROUND: SARS-Cov-2 infection rates are high among residents of long-term care (LTC) homes. We used machine learning to identify resident and community characteristics predictive of SARS-Cov-2 infection. METHODS: We linked 26 population-based health and administrative databases to identify the population of all LTC residents tested for SARS-Cov-2 infection in Ontario, Canada. Using ensemble-based algorithms, we examined 484 factors, including individual-level demographics, healthcare use, comorbidities, functional status, and laboratory results; and community-level characteristics to identify factors predictive of infection. Analyses were performed separately for January to April (early wave 1) and May to August (late wave 1). FINDINGS: Among 80,784 LTC residents, 64,757 (80.2%) were tested for SARS-Cov-2 (median age 86 (78-91) years, 30.6% male), of whom 10.2% of 33,519 and 5.2% of 31,238 tested positive in early and late wave 1, respectively. In the late phase (when restriction of visitors, closure of communal spaces, and universal masking in LTC were routine), regional-level characteristics comprised 33 of the top 50 factors associated with testing positive, while laboratory values and comorbidities were also predictive. The c-index of the final model was 0.934, and sensitivity was 0.887. In the highest versus lowest risk quartiles, the odds ratio for infection was 114.3 (95% CI 38.6-557.3). LTC-related geographic variations existed in the distribution of observed infection rates and the proportion of residents at highest risk. INTERPRETATION: Machine learning informed evaluation of predicted and observed risks of SARS-CoV-2 infection at the resident and LTC levels, and may inform initiatives to improve care quality in this setting. FUNDING: Funded by a Canadian Institutes of Health Research, COVID-19 Rapid Research Funding Opportunity grant (# VR4 172736) and a Peter Munk Cardiac Centre Innovation Grant. Dr. D. Lee is the Ted Rogers Chair in Heart Function Outcomes, University Health Network, University of Toronto. Dr. Austin is supported by a Mid-Career investigator award from the Heart and Stroke Foundation. Dr. McAlister is supported by an Alberta Health Services Chair in Cardiovascular Outcomes Research. Dr. Kaul is the CIHR Sex and Gender Science Chair and the Heart & Stroke Chair in Cardiovascular Research. Dr. Rochon holds the RTO/ERO Chair in Geriatric Medicine from the University of Toronto. Dr. B. Wang holds a CIFAR AI chair at the Vector Institute.

Ethical decision making during a healthcare crisis: a resource allocation framework and tool.

The COVID-19 pandemic has strained healthcare resources the world over, requiring healthcare providers to make resource allocation decisions under extraordinary pressures. A year later, our understanding of COVID-19 has advanced, but our process for making ethical decisions surrounding resource allocation has not. During the first wave of the pandemic, our institution uniformly ramped-down clinical activity to accommodate the anticipated demands of COVID-19, resulting in resource waste and inefficiency. In preparation for the second wave, we sought to make such ramp down decisions more prudently and ethically. We report the development of a tool that can be used to make fair and ethical decisions in times of resource scarcity. We formed an interprofessional team to develop and use this tool to ensure that a diverse range of stakeholder perspectives were represented in this development process. This team, called the clinical activity recovery team, established institutional objectives that were combined with well-established procedural values, substantive ethical principles and decision-making criteria by using a variation on the well-known accountability for reasonableness ethical framework. The result of this is a stepwise, semiquantitative, ethical decision tool that can be applied to resource allocation challenges in order to reach fair and ethically defensible decisions. This ethical decision tool can be applied in various contexts and may prove useful at both the institutional and the departmental level; indeed this is how it is applied at our centre. As the second wave of COVID-19 strains healthcare resources, this tool can help clinical leaders to make fair decisions.

Predictors of mortality among long-term care residents with SARS-CoV-2 infection.

BACKGROUND: While individuals living in long-term care (LTC) homes have experienced adverse outcomes of SARS-CoV-2 infection, few studies have examined a broad range of predictors of 30-day mortality in this population. METHODS: We studied residents living in LTC homes in Ontario, Canada, who underwent PCR testing for SARS-CoV-2 infection from January 1 to August 31, 2020, and examined predictors of all-cause death within 30 days after a positive test for SARS-CoV-2. We examined a broad range of risk factor categories including demographics, comorbidities, functional status, laboratory tests, and characteristics of the LTC facility and surrounding community were examined. In total, 304 potential predictors were evaluated for their association with mortality using machine learning (Random Forest). RESULTS: A total of 64,733 residents of LTC, median age 86 (78, 91) years (31.8% men), underwent SARS-CoV-2 testing, of whom 5029 (7.8%) tested positive. Thirty-day mortality rates were 28.7% (1442 deaths) after a positive test. Of 59,702 residents who tested negative, 2652 (4.4%) died within 30 days of testing. Predictors of mortality after SARS-CoV-2 infection included age, functional status (e.g., activity of daily living score and pressure ulcer risk), male sex, undernutrition, dehydration risk, prior hospital contacts for respiratory illness, and duration of comorbidities (e.g., heart failure, COPD). Lower GFR, hemoglobin concentration, lymphocyte count, and serum albumin were associated with higher mortality. After combining all covariates to generate a risk index, mortality rate in the highest risk quartile was 48.3% compared with 7% in the first quartile (odds ratio 12.42, 95%CI: 6.67, 22.80, p < 0.001). Deaths continued to increase rapidly for 15 days after the positive test. CONCLUSIONS: LTC residents, particularly those with reduced functional status, comorbidities, and abnormalities on routine laboratory tests, are at high risk for mortality after SARS-CoV-2 infection. Recognizing high-risk residents in LTC may enhance institution of appropriate preventative measures.

Long-term mortality risk stratification of liver transplant recipients: real-time application of deep learning algorithms on longitudinal data.

BACKGROUND: Survival of liver transplant recipients beyond 1 year since transplantation is compromised by an increased risk of cancer, cardiovascular events, infection, and graft failure. Few clinical tools are available to identify patients at risk of these complications, which would flag them for screening tests and potentially life-saving interventions. In this retrospective analysis, we aimed to assess the ability of deep learning algorithms of longitudinal data from two prospective cohorts to predict complications resulting in death after liver transplantation over multiple timeframes, compared with logistic regression models. METHODS: In this machine learning analysis, model development was done on a set of 42 146 liver transplant recipients (mean age 48·6 years [SD 17·3]; 17 196 [40·8%] women) from the Scientific Registry of Transplant Recipients (SRTR) in the USA. Transferability of the model was further evaluated by fine-tuning on a dataset from the University Health Network (UHN) in Canada (n=3269; mean age 52·5 years [11·1]; 1079 [33·0%] women). The primary outcome was cause of death, as recorded in the databases, due to cardiovascular causes, infection, graft failure, or cancer, within 1 year and 5 years of each follow-up examination after transplantation. We compared the performance of four deep learning models against logistic regression, assessing performance using the area under the receiver operating characteristic curve (AUROC). FINDINGS: In both datasets, deep learning models outperformed logistic regression, with the Transformer model achieving the highest AUROCs in both datasets (p<0·0001). The AUROC for the Transformer model across all outcomes in the SRTR dataset was 0·804 (99% CI 0·795-0·854) for 1-year predictions and 0·733 (0·729-0·769) for 5-year predictions. In the UHN dataset, the AUROC for the top-performing deep learning model was 0·807 (0·795-0·842) for 1-year predictions and 0·722 (0·705-0·764) for 5-year predictions. AUROCs ranged from 0·695 (0·680-0·713) for prediction of death from infection within 5 years to 0·859 (0·847-0·871) for prediction of death by graft failure within 1 year. INTERPRETATION: Deep learning algorithms can incorporate longitudinal information to continuously predict long-term outcomes after liver transplantation, outperforming logistic regression models. Physicians could use these algorithms at routine follow-up visits to identify liver transplant recipients at risk for adverse outcomes and prevent these complications by modifying management based on ranked features. FUNDING: Canadian Donation and Transplant Research Program, CIFAR AI Chairs Program.

The psychological burden of waiting for procedures and patient-centred strategies that could support the mental health of wait-listed patients and caregivers during the COVID-19 pandemic: A scoping review.

BACKGROUND: Waiting for procedures delayed by COVID-19 may cause anxiety and related adverse consequences. OBJECTIVE: To synthesize research on the mental health impact of waiting and patient-centred mitigation strategies that could be applied in the COVID-19 context. METHODS: Using a scoping review approach, we searched 9 databases for studies on waiting lists and mental health and reported study characteristics, impacts and intervention attributes and outcomes. RESULTS: We included 51 studies that focussed on organ transplant (60.8%), surgery (21.6%) or cancer management (13.7%). Most patients and caregivers reported anxiety, depression and poor quality of life, which deteriorated with increasing wait time. The impact of waiting on mental health was greater among women and new immigrants, and those of younger age, lower socio-economic status, or with less-positive coping ability. Six studies evaluated educational strategies to develop coping skills: 2 reduced depression (2 did not), 1 reduced anxiety (2 did not) and 2 improved quality of life (2 did not). In contrast, patients desired acknowledgement of concerns, peer support, and periodic communication about wait-list position, prioritization criteria and anticipated procedure date. CONCLUSIONS: Findings revealed patient-centred strategies to alleviate the mental health impact of waiting for procedures. Ongoing research should explore how to optimize the impact of those strategies for diverse patients and caregivers, particularly in the COVID-19 context. PATIENT OR PUBLIC CONTRIBUTION: Six patients and four caregivers waiting for COVID-19-delayed procedures helped to establish eligibility criteria, plan data extraction and review a draft and final report.

Burnout and distress among physicians in a cardiovascular centre of a quaternary hospital network: a cross-sectional survey.

BACKGROUND: Burnout and distress have a negative impact on physicians and the treatment they provide. Our aim was to measure the prevalence of burnout and distress among physicians in a cardiovascular centre of a quaternary hospital network in Canada, and compare these outcomes to those for physicians at academic health science centres (AHSCs) in the United States. METHODS: We conducted a survey of physicians practising in a cardiovascular centre at 2 quaternary referral hospitals in Toronto, Ontario, between Nov. 27, 2018, and Jan. 31, 2019. The survey tool included the Well-Being Index (WBI), which measures fatigue, depression, burnout, anxiety or stress, mental and physical quality of life, work-life integration, meaning in work and distress; a score of 3 or higher indicated high distress. We also evaluated physicians' perception of the adequacy of staffing levels and of fair treatment in the workplace, and satisfaction with the electronic health record. We carried out standard univariate statistical comparisons using the χ2, Fisher exact or Kruskal-Wallis test as appropriate to perform univariate comparisons in the sample of respondents. We assessed the relation between a WBI score of 3 or higher and demographic characteristics. We compared univariate associations among WBI data for physicians at AHSCs in the US who completed the WBI to responses from our participants. RESULTS: The response rate to the survey was 84.1% (127/151). Of the 127 respondents, 83 (65.4%) reported burnout in the previous month, and 68 (53.5%) reported emotional problems. Sixty-nine respondents (54.3%) had a WBI score of 3 or higher. Respondents were more likely to have a WBI score of 3 or higher versus a score less than 3 if they perceived insufficient staffing levels (52/69 [75%] v. 26/58 [45%], p = 0.02) or unfair treatment (23/69 [33%] v. 8/58 [14%], p = 0.03), or were anesthesiologists (26/35 [74%] v. 43/92 [47%] for other specialists, p = 0.005). Compared to 21 594 physicians in practice at AHSCs in the US, our respondents had a higher mean WBI score (2.4 v. 1.8, p = 0.004) and reported a higher prevalence of burnout (65.4% v. 56.6%, p = 0.048). INTERPRETATION: Physicians in this study had high levels of burnout and distress, driven by the perception of inadequate staffing levels and being treated unfairly in the workplace. Addressing these institutional factors may improve physicians' work experience and patient outcomes.

Burnout and distress among nurses in a cardiovascular centre of a quaternary hospital network: a cross-sectional survey.

BACKGROUND: Burnout and distress have a negative impact on nurses and the treatment they provide. Our aim was to measure the prevalence of burnout and distress among nurses in a cardiovascular centre at 2 quaternary referral hospitals in Canada, and compare these outcomes to those for nurses at academic health science centres (AHSCs) in the United States. METHODS: We conducted a survey of nurses practising in a cardiovascular centre at 2 quaternary referral hospitals in Toronto, Ontario, between Nov. 27, 2018, and Jan. 31, 2019. The survey tool included the Well-Being Index (WBI), which measures fatigue, depression, burnout, anxiety or stress, mental and physical quality of life, work-life integration, meaning in work and distress; a score of 2 or higher on the WBI indicated high distress. We also evaluated nurses' perception of the adequacy of staffing levels and of fair treatment in the workplace, and satisfaction with the electronic health record. We carried out standard univariate statistical comparisons using the χ2, Fisher exact or Kruskal-Wallis test as appropriate to perform univariate comparisons in the sample of respondents. We assessed the relation between a WBI score of 2 or higher and demographic characteristics. We compared univariate associations among WBI data for nurses at AHSCs in the US who completed the WBI to responses from our participants. RESULTS: The response rate to the survey was 49.1% (242/493). Of the 242 respondents, 188 (77.7%) reported burnout in the previous month; 189 (78.1%) had a WBI score of 2 or higher, and 132 (54.5%) had a score of 4 or higher (indicative of severe distress). Ordinal multivariable analysis showed that lower WBI scores were associated with satisfaction with staffing levels (odds ratio [OR] 0.33, 95% confidence interval [CI] 0.16-0.69) and the perception of fair treatment in the workplace (OR 0.41, 95% CI 0.23-0.74). Higher proportions of our respondents than nurses at AHSCs in the US reported burnout (77.7% v. 60.5%, p < 0.001) and had a WBI score of 2 or higher (78.1% v. 57.0%) or 4 or higher (54.5% v. 32.0%) (both p < 0.001). INTERPRETATION: Although levels of burnout and distress were high among nurses, their perceptions of adequate staffing and fair treatment were associated with lower distress. Addressing inadequate staffing and unfair treatment may decrease burnout and other dimensions of distress among nurses, and improve their work experience and patient outcomes.

Burnout and distress among allied health care professionals in a cardiovascular centre of a quaternary hospital network: a cross-sectional survey.

BACKGROUND: Burnout and distress negatively affect the well-being of health care professionals and the treatment they provide. Our aim was to measure the prevalence of burnout and distress among allied health care staff at a cardiovascular centre of a quaternary hospital network in Canada, and compare outcomes to those for nonphysician employees in the United States. METHODS: We conducted a survey of allied health care staff, including physical, respiratory and occupational therapists, pharmacists, social workers, dietitians and speech-language pathologists, in a cardiovascular centre at 2 quaternary referral hospitals in Toronto, Ontario, between Nov. 27, 2018, and Jan. 31, 2019. The survey tool included the Well-Being Index (WBI), which measures fatigue, depression, burnout, anxiety or stress, quality of life, work-life integration, meaning in work and overall distress; a score of 2 or higher indicated high distress. We carried out standard univariate statistical comparisons using the χ2, Fisher exact or Kruskal-Wallis test as appropriate to perform univariate comparisons in the sample of respondents. We assessed the relation between a WBI score of 2 or higher and demographic characteristics. We compared univariate associations among WBI data for nonphysician employees in the US who completed the WBI to responses from our participants. RESULTS: The response rate to the survey was 86% (45/52). Thirty-three respondents (73%) reported experiencing burnout in the previous month, and 31 (69%) reported emotional problems. Compared to respondents who perceived fair treatment in the workplace, those who perceived unfair treatment (20 [44%]) were more likely to report emotional problems (17 [85%] v. 13 [54%], p = 0.05), to worry that work was hardening them emotionally (15 [75%] v. 8 [33%], p = 0.008), and to feel down, depressed or hopeless (12 [60%] v. 4 [17%], p = 0.005). Twenty-five respondents (56%) and 13 respondents (29%) reported WBI scores consistent with high (≥ 2) or severe (≥ 5) distress, respectively. Respondents were more likely to have a high WBI score if they perceived unfair treatment or inadequate staffing levels. Our respondents had a higher prevalence of burnout (73.3% v. 53.6%, p = 0.008) and a higher average WBI score (2.6 [SD 2.8] v. 1.7 [SD 2.6], p = 0.05) than 9096 nonphysician employees in the US. INTERPRETATION: The prevalence of burnout, emotional problems and distress was high among allied health care staff. Fair treatment in the workplace and adequate staffing may lower distress levels and improve the work experience of these health care professionals.

c-Myb Exacerbates Atherosclerosis through Regulation of Protective IgM-Producing Antibody-Secreting Cells.

Mechanisms that govern transcriptional regulation of inflammation in atherosclerosis remain largely unknown. Here, we identify the nuclear transcription factor c-Myb as an important mediator of atherosclerotic disease in mice. Atherosclerosis-prone animals fed a diet high in cholesterol exhibit increased levels of c-Myb in the bone marrow. Use of mice that either harbor a c-Myb hypomorphic allele or where c-Myb has been preferentially deleted in B cell lineages revealed that c-Myb potentiates atherosclerosis directly through its effects on B lymphocytes. Reduced c-Myb activity prevents the expansion of atherogenic B2 cells yet associates with increased numbers of IgM-producing antibody-secreting cells (IgM-ASCs) and elevated levels of atheroprotective oxidized low-density lipoprotein (OxLDL)-specific IgM antibodies. Transcriptional profiling revealed that c-Myb has a limited effect on B cell function but is integral in maintaining B cell progenitor populations in the bone marrow. Thus, targeted disruption of c-Myb beneficially modulates the complex biology of B cells in cardiovascular disease.

Comparison of cardiac surgery mortality reports using administrative and clinical data sources: a prospective cohort study.

BACKGROUND: Outcomes for coronary artery bypass surgery are of broadening interest, but the impact of data type on quality reporting has not been fully examined. We compared the performance of administrative and clinical data-based risk adjustment models at a tertiary-quaternary care hospital. METHODS: We used a prospective study design to test two risk adjustment models, one from administrative (Canadian Institute for Health Information [CIHI] Cardiac Care Quality Indicator) and one from clinical data (Society of Thoracic Surgeons), on cardiac surgical procedures performed between 2013 and 2016 (n = 1635). Our primary outcome was in-hospital mortality within 30 days of surgery. Model performance was established by comparing predicted and observed mortality, model calibration and handling of critical covariates. RESULTS: Observed mortality was 1.96%, which was the same as that predicted by the Society of Thoracic Surgeons model (1.96%), but significantly higher than that predicted by the CIHI model (1.03%). Despite both models having similar C statistics (0.756 CIHI; 0.758 Society of Thoracic Surgeons), the CIHI model showed significant underestimation of mortality among patients at higher risk. There was significant miscalibration of risk associated with 7 covariates: New York Heart Association class IV, congestive heart failure, ejection fraction less than 20%, atrial fibrillation, acute coronary insufficiency, cardiac compromise (shock, myocardial infarction < 24 h, intra-aortic balloon pump, cardiac resuscitation or preprocedure circulatory support) and creatinine concentration of 100 mg/dL or more. Together, these factors accounted for 84% of the difference in predicted mortality between the administrative and clinical models. INTERPRETATION: Risk prediction using administrative data underestimated risk of death, potentially inflating observed-to-predicted mortality ratios at hospitals with patients who are more ill. Caution is warranted when hospital reports of cardiac surgery outcomes are based on administrative data alone.

Self-renewing resident arterial macrophages arise from embryonic CX3CR1(+) precursors and circulating monocytes immediately after birth.

Resident macrophages densely populate the normal arterial wall, yet their origins and the mechanisms that sustain them are poorly understood. Here we use gene-expression profiling to show that arterial macrophages constitute a distinct population among macrophages. Using multiple fate-mapping approaches, we show that arterial macrophages arise embryonically from CX3CR1(+) precursors and postnatally from bone marrow-derived monocytes that colonize the tissue immediately after birth. In adulthood, proliferation (rather than monocyte recruitment) sustains arterial macrophages in the steady state and after severe depletion following sepsis. After infection, arterial macrophages return rapidly to functional homeostasis. Finally, survival of resident arterial macrophages depends on a CX3CR1-CX3CL1 axis within the vascular niche.

The in-hospital costs of treating high-risk patients with fenestrated and branched endografts.

OBJECTIVE: This study determined the 30-day morbidity and mortality and in-hospital costs of elective fenestrated (fEVAR) and branched (bEVAR) endovascular aneurysm repairs at a single academic institution and determined factors that influence them. METHODS: All elective fEVAR or bEVAR patients treated between November 2007 and March 2014 in a Canadian academic hospital were included. Procedural details, 30-day morbidity and mortality rates, and cost of hospitalization were analyzed. Nonparametric bootstrap analysis was used to compare means between groups and calculate confidence intervals (CIs). RESULTS: There were 84 consecutive fEVAR (n = 61) and bEVAR (n = 23) procedures. The 30-day mortality was 3.3% for fEVAR and 4.3% for bEVAR. Mean hospital stay was 7.2 ± 0.8 days for fEVAR and 12.6 ± 2.2 days for bEVAR. The mean cost of the index hospitalization was $57,000 for fEVAR and $91,000 for bEVAR. Device-related costs accounted for 55% of the total costs. The occurrence of intraoperative or postoperative events were used to further divide each of the fEVAR and bEVAR groups into "complicated hospitalization" (fEVAR, n = 10; bEVAR, n = 13) and "uncomplicated hospitalization" (fEVAR, n = 51; bEVAR, n = 10) groups. Device-related costs were not significantly different between the complicated and uncomplicated hospitalization groups (mean difference [95% CI] fEVAR: $3383 [-$3405 to $9809], P = .3; and bEVAR: $1930 [-$7892 to $11,288], P = .68). However, there were significant differences between the complicated and uncomplicated hospitalization groups in hospital length of stay (mean difference [95% CI] fEVAR: 8.1 [3.0-13.2] days, P = .001; and bEVAR: 10.8 [5.9-19.9] days, P = .002) and nondevice-related costs (mean difference [95% CI,] fEVAR: $25,843 [$11,689-$43,247], P = .001; and bEVAR; $20,326 [$9362-$36,615], P = .002). CONCLUSIONS: bEVAR and fEVAR are expensive interventions. Intraoperative adverse events and postoperative systemic complications dramatically increase costs and length of stay. Measures to minimize complications will reduce hospitalization costs and improve patient outcomes.

Pheochromocytoma in a Pregnant Woman With Prior Traumatic Aortic Injury.

BACKGROUND: Pheochromocytoma, a catecholamine-producing tumor seldom encountered in pregnancy, is often heralded by nonspecific symptoms and undue mortality with delayed diagnosis. The presence of an aortic pseudoaneurysm poses a management challenge given the risk of aortic rupture amplified by hypertensive events. CASE: A 30-year-old woman, gravida 3 para 1, presented at 23 6/7 weeks of gestation with vomiting, chest pain, and severe hypertension. Investigation revealed adrenal pheochromocytoma and pseudoaneurysm at the site of a previous aortic injury. Prazosin and phenoxybenzamine achieved α-blockade with subsequent addition of labetalol for ß-blockade. Concerns for aortic dissection led to endovascular aortic repair at 30 2/7 weeks of gestation. A female neonate was delivered by urgent cesarean delivery for persistent postprocedure fetal bradycardia. An adrenalectomy followed with near-immediate symptom resolution. Mother and neonate remain well. CONCLUSION: The case underscores the necessity of a meticulous approach to hypertension management and the pivotal role of diligent multidisciplinary collaboration to achieve a safe outcome.

Splenic metabolic activity predicts risk of future cardiovascular events: demonstration of a cardiosplenic axis in humans.

OBJECTIVES: This study sought to determine whether splenic activation after acute coronary syndrome (ACS) is linked to leukocyte proinflammatory remodeling and whether splenic activity independently predicts the risk of cardiovascular disease (CVD) events. BACKGROUND: Pre-clinical data suggest the existence of a cardiosplenic axis, wherein activation of hematopoietic tissues (notably in the spleen) results in liberation of proinflammatory leukocytes and accelerated atherosclerotic inflammation. However, it is presently unknown whether a cardiosplenic axis exists in humans and whether splenic activation relates to CVD risk. METHODS: (18)F-fluorodeoxyglucose ((18)FDG)-positron emission tomography (PET) imaging was performed in 508 individuals across 2 studies. In the first study, we performed FDG-PET imaging in 22 patients with recent ACS and 22 control subjects. FDG uptake was measured in spleen and arterial wall, whereas proinflammatory gene expression of circulating leukocytes was assessed by quantitative real-time polymerase chain reaction. In a second study, we examined the relationship between splenic tissue FDG uptake with subsequent CVD events during follow-up (median 4 years) in 464 patients who previously had undergone FDG-PET imaging. RESULTS: Splenic activity increased after ACS and was significantly associated with multiple indices of inflammation: 1) up-regulated gene expression of proinflammatory leukocytes; 2) increased C-reactive protein; and 3) increased arterial wall inflammation (FDG uptake). Moreover, in the second study, splenic activity (greater than or equal to the median) was associated with an increased risk of CVD events (hazard ratio [HR]: 3.3; 95% confidence interval [CI]: 1.5 to 7.3; p = 0.003), which remained significant after adjustment for CVD risk factors (HR: 2.26; 95% CI: 1.01 to 5.06; p = 0.04) and for arterial FDG uptake (HR: 2.68; 95% CI: 1.5 to 7.4; p = 0.02). CONCLUSIONS: Our findings demonstrate increased splenic metabolic activity after ACS and its association with proinflammatory remodeling of circulating leukocytes. Moreover, we observed that metabolic activity of the spleen independently predicted risk of subsequent CVD events. Collectively, these findings provide evidence of a cardiosplenic axis in humans similar to that shown in pre-clinical studies.