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BackgroundPatients with ST-elevation myocardial infarction (STEMI) complicated by an out-of-hospital-cardiac-arrest (OHCA) may vary widely in their probability of dying. Large variation in mortality may have implications for current national efforts to benchmark operator and hospital mortality rates for coronary angiography. We aimed to build a risk-adjustment model of in-hospital mortality among OHCA survivors with concurrent STEMI.MethodsWithin the Cardiac Arrest Registry to Enhance Survival (CARES), we included adults with OHCA and STEMI who underwent emergent angiography within 2 hours of hospital arrival between January 2013 and December 2019. Using multivariable logistic regression to adjust for patient and cardiac arrest factors, we developed a risk-adjustment model for in-hospital mortality and examined variation in patients' predicted mortality.ResultsOf 2,999 patients (mean age 61.2 ± 12.0, 23.1% female, 64.6% white), 996 (33.2%) died during their hospitalization. The final risk-adjustment model included higher age (OR per 10-year increase, 1.50 [95% CI: 1.39-1.63]), unwitnessed OHCA (OR, 2.51 [1.99-3.16]), initial non-shockable rhythm [OR, 5.66 [4.52-7.13]), lack of sustained pulse for > 20 minutes (OR, 2.52 [1.88-3.36]), and longer resuscitation time (increased with each 10-minute interval) (c-statistic = 0.804 with excellent calibration). There was large variability in predicted mortality: median, 25.2%, inter-quartile-range: 14.0% to 47.8%, 10th-90th percentile: 8.2 % to 74.1%.ConclusionsIn a large national registry, we identified 5 key predictors for mortality in patients with STEMI and OHCA and found wide variability in mortality risk. Our findings suggest that current national benchmarking efforts for coronary angiography, which simply adjusts for the presence of OHCA, may not adequately capture patient case-mix severity.

BackgroundHealth status outcomes are increasingly being promoted as measures of health care quality, given their importance to patients. In heart failure (HF), an American College of Cardiology/American Heart Association Task Force proposed using the proportion of patients with preserved health status as a quality measure but not as a performance measure because risk adjustment methods were not available.MethodsWe built risk adjustment models for alive with preserved health status and for preserved health status alone in a prospective registry of outpatients with HF with reduced ejection fraction across 146 US centers between December 2015 and October 2017. Preserved health status was defined as not having a ≥5-point decrease in the Kansas City Cardiomyopathy Questionnaire Overall Summary score at 1 year. Using only patient-level characteristics, hierarchical multivariable logistic regression models were developed for 1-year outcomes and validated using data from 1 to 2 years. We examined model calibration, discrimination, and variability in sites' unadjusted and adjusted rates.ResultsAmong 3932 participants (median age [interquartile range] 68 years [59-75], 29.7% female, 75.4% White), 2703 (68.7%) were alive with preserved health status, 902 (22.9%) were alive without preserved health status, and 327 (8.3%) had died by 1 year. The final risk adjustment model for alive with preserved health status included baseline Kansas City Cardiomyopathy Questionnaire Overall Summary, age, race, employment status, annual income, body mass index, depression, atrial fibrillation, renal function, number of hospitalizations in the past 1 year, and duration of HF (optimism-corrected C statistic=0.62 with excellent calibration). Similar results were observed when deaths were ignored. The risk standardized proportion of patients alive with preserved health status across the 146 sites ranged from 62% at the 10th percentile to 75% at the 90th percentile. Variability across sites was modest and changed minimally with risk adjustment.ConclusionsThrough leveraging data from a large, outpatient, observational registry, we identified key factors to risk adjust sites' proportions of patients with preserved health status. These data lay the foundation for building quality measures that quantify treatment outcomes from patients' perspectives.

IntroductionEvaluation of health status benefits, cost-effectiveness, and value of new heart failure therapies is critical for supporting their use. The Kansas City Cardiomyopathy Questionnaire (KCCQ) measures patients' heart failure-specific health status but does not provide utilities needed for cost-effectiveness analyses. We mapped the KCCQ scores to EQ-5D scores so that estimates of societal-based utilities can be generated to support economic analyses.MethodsUsing data from two US cohort studies, we developed models for predicting EQ-5D utilities (3L and 5L versions) from the KCCQ (23- and 12-item versions). In addition to predicting scores directly, we considered predicting the five EQ-5D health state items and deriving utilities from the predicted responses, allowing different countries' health state valuations to be used. Model validation was performed internally via bootstrap and externally using data from two clinical trials. Model performance was assessed using R2, mean prediction error, mean absolute prediction error, and calibration of observed vs. predicted values.ResultsThe EQ-5D-3L models were developed from 1000 health status assessments in 547 patients with heart failure and reduced ejection fraction (HFrEF), while the EQ-5D-5L model was developed from 3925 patients with HFrEF. For both versions, models predicting individual EQ-5D items performed as well as those predicting utilities directly. The selected models for the 3L had internally validated R2 of 48.4-50.5% and 33.7-45.6% on external validation. The 5L version had validated R2 of 57.7%.ConclusionMappings from the KCCQ to the EQ-5D can yield the estimates of societal-based utilities to support cost-effectiveness analyses when EQ-5D data are not available.

BackgroundHeart failure is a common and devastating complication of type 2 diabetes (T2D). Prompt recognition of heart failure may avert hospitalization, facilitate use of guideline-directed therapies, and impact choice of T2D medications. We sought to determine the rate and factors associated with heart failure documentation in T2D patients with evidence of volume overload requiring loop diuretics.MethodsDCR is an on-going, prospective US registry of outpatient T2D patients from > 5000 cardiology, endocrinology, and primary care clinicians (current analysis used data from 2013-2019). Among T2D patients receiving loop diuretics, we examined the rate of chart documentation of heart failure. We used a 3-level hierarchical logistic regression model (patients nested within physician within practice) to examine factors associated with heart failure diagnosis.ResultsAmong 1,322,640 adults with T2D, 225,125 (17.0%) were receiving a loop diuretic, of whom 91,969 (40.9%) had documentation of heart failure. Male sex, lower body mass index, atrial fibrillation, chronic kidney disease, and coronary artery disease were associated with greater odds of heart failure diagnosis. After accounting for patient factors, patients seen by cardiologists were the most likely to have HF documented followed by PCPs and then endocrinologists.ConclusionsAmong US outpatients with T2D, 17% of patients had evidence of volume overload-defined by loop diuretic prescription-of whom fewer than half had a clinical diagnosis of heart failure. While there may be non-heart failure indications for loop diuretics, our data suggest that a substantial proportion of T2D patients may have unrecognized heart failure and therefore could be missing opportunities for targeted therapies that could alter the clinical course of heart failure.

Inhibition of soluble epoxide hydrolase (sEH, EPHX2) elicits potent cardiovascular protective effects in preclinical models of ischemic cardiovascular disease (CVD), and genetic polymorphisms in EPHX2 have been associated with developing ischemic CVD in humans. However, it remains unknown whether EPHX2 variants are associated with prognosis following an ischemic CVD event. We evaluated the association between EPHX2 p.Lys55Arg and p.Arg287Gln genotype with survival in 667 acute coronary syndrome (ACS) patients. No association with p.Arg287Gln genotype was observed (P = 0.598). Caucasian EPHX2 Arg55 carriers (Lys/Arg or Arg/Arg) had a significantly higher risk of 5-year mortality (adjusted hazard ratio [HR] 1.61, 95% confidence interval [CI] 1.01-2.55, P = 0.045). In an independent population of 2712 ACS patients, this association was not replicated (adjusted HR 0.92, 95% CI 0.70-1.21, P = 0.559). In a secondary analysis, Caucasian homozygous Arg55 allele carriers (Arg/Arg) appeared to exhibit a higher risk of cardiovascular mortality (adjusted HR 2.60, 95% CI 1.09-6.17). These results demonstrate that EPHX2 p.Lys55Arg and p.Arg287Gln polymorphisms do not significantly modify survival after an ACS event. Investigation of other sEH metabolism biomarkers in ischemic CVD appears warranted.

ObjectivesThe Stroke-Thrombolytic Predictive Instrument (Stroke-TPI) predicts the probability of good and bad outcomes with and without recombinant tissue plasminogen activator (rtPA). We sought to rebuild and externally validate a simpler Stroke-TPI to support implementation in routine clinical care.MethodsUsing the original derivation cohort of 1,983 patients from a combined database of randomized clinical trials (NINDS [National Institute of Neurological Disorders and Stroke] 1 and 2; ATLANTIS [Alteplase Thrombolysis for Acute Noninterventional Therapy in Ischemic Stroke] A and B; and ECASS [European Cooperative Acute Stroke Study] II), we simplified the Stroke-TPI by reducing variables and interaction terms and by exploring simpler (3- and 8-item) stroke severity scores. External validation was performed in the ECASS III trial (n = 821).ResultsThe following 6 variables were most predictive of good outcomes: age, systolic blood pressure, diabetes, stroke severity, symptom onset to treatment time, and rtPA therapy. Treatment effect modifiers included onset to treatment time and systolic blood pressure. For the models predicting a bad outcome (modified Rankin Scale [mRS] score ≥5), significant variables included age, stroke severity, and serum glucose. rtPA therapy did not change the risk of a poor outcome. Compared with models using the full NIH Stroke Scale, models using the 3-item severity score showed similar discrimination and excellent calibration. External validation on ECASS III showed similar performance (C statistics 0.75 [mRS score ≤1] and 0.80 [mRS score ≤2]).ConclusionA simpler model using a 3-item stroke severity score, instead of the 15-item NIH Stroke Scale, has similar prognostic value and may be easier to use in routine care. Future studies are needed to test whether it can improve process and clinical outcomes.

Simple Summary: There is limited literature on sample adequacy for molecular testing and genomic sequencing for pancreatic ductal adenocarcinoma obtained via EUS fine-needle aspiration (FNA) versus EUS fine-needle biopsy (FNB). Thus, we aimed to compare these two modalities regarding sample adequacy for molecular testing and genomic sequencing. In this retrospective chart review study, we analyzed all patients with pancreatic ductal adenocarcinoma who underwent EUS at Saint Luke's Hospital, Kansas City, MO, from 1 January 2018, to 31 December 2021. A rapid on-site evaluation was performed for all cases by cytotechnologists. We found that out of 1417 EUS procedures, 132 patients underwent EUS-guided biopsies. The mean number of passes required for FNB and FNA was similar. However, EUS-FNB, under rapid on-site specimen evaluation guidance, was superior to FNA in obtaining adequate samples for molecular testing. In addition, tumor surface area and tumor cellularity are essential parameters in determining sample adequacy for molecular testing, regardless of the tissue acquisition modality. Background and Aims: There is limited literature on sample adequacy for molecular testing in pancreatic ductal adenocarcinoma obtained via endoscopic ultrasound (EUS) fine-needle aspiration (FNA) versus EUS fine-needle biopsy (FNB). We aimed to compare these two modalities regarding sample adequacy for molecular and genomic sequencing. Methods: We reviewed all patients with pancreatic ductal adenocarcinoma who underwent EUS at Saint Luke's Hospital from 2018 to 2021. The patients were categorized based on the method of EUS tissue acquisition, specifically FNA or FNB. A comprehensive evaluation was conducted for all cases by cytotechnologists. Results: Out of 132 patients who underwent EUS-guided biopsies, 76 opted for FNA, 48 opted for FNB, and 8 opted for a combination of both. The average number of passes required for FNB and FNA was 2.58 ± 1.06 and 2.49 ± 1.07, respectively (p = 0.704), indicating no significant difference. Interestingly, 71.4% (35) of FNB-obtained samples were deemed adequate for molecular testing, surpassing the 32.1% (26) adequacy observed with FNA (p < 0.001). Additionally, 46.4% (26) of FNB-obtained samples were considered adequate for genomic testing, a notable improvement over the 23.8% (20) adequacy observed with FNA (p = 0.005). Conclusion: Although the number of passes required for cytologic diagnosis did not differ significantly between EUS-FNB and EUS-FNA, the former demonstrated superiority in obtaining samples adequate for molecular testing. Tumor surface area and cellularity were crucial parameters in determining sample adequacy for molecular testing, irrespective of the chosen tissue acquisition modality. [ABSTRACT FROM AUTHOR]

This paper draws on three case studies which show feasible and economic results in meeting net zero carbon emissions targets through Smart Local Energy Systems (SLES) in different localities across England, exploring opportunities to utilise waste heat from industry. They are based on the GreenSCIES model for which the blueprint was developed in London, Study 1. It consists of a fifth generation (5G) ambient loop district heat network using waste heat from a data centre, integrated with electric vehicle charging, storage and solar PV. The network includes decentralised heat pumps and allows for (i) heat sharing between buildings and (ii) applications for heat recovery from local sources. Study 2 is based on a heat network with waste heat from a foundry and some cooling supply and heat storage in the aquifer. Study 3 explored waste heat from a glassworks and considered mine workings for providing heat storage. These SLES projects illustrate how to integrate local waste heat sources in 3G and 4G heat networks, adapting the original GreenSCIES concept, providing pathways towards net zero carbon for a diverse range of urban locations with different waste heat sources, and further demonstrate the importance of collaboration between researchers, local government and industry. [ABSTRACT FROM AUTHOR]

Health disparities by socioeconomic status (SES) exist for many outcomes, including patients' subjective health status after myocardial infarction (MI). The Reserve Capacity Model (RCM), a theoretical means to understand such disparities, was tested to examine the possible mediating effects of cognitive-emotional factors on the association between SES and health status. Data from 2,348 post-MI patients in PREMIER were used. Indicators of SES were collected during hospitalization via personal interviews, while participants completed measures of stress and reserves at 1 month, depressive symptoms at 6 months, and health status at 1 year through telephone interviews. Structural equation model results provide partial support for the RCM, as cognitive-emotional factors partially mediated the association between SES and mental health status. For physical health status, results supported direct rather than indirect effects of SES. Findings suggest psychosocial interventions with patients of low SES will have their greatest effects on appraisals of psychological health status. Keywords Socioeconomic status * Health status disparities * Myocardial infarction * Depressive symptoms * Cognitive-emotional factors, Introduction Cardiovascular disease (CVD) is the leading cause of death in the United States. It is estimated that one American dies from CVD every 39 seconds, and that 33.6% of [...]