Murphree, Dennis H.

Abstract Background Preoperative risk scores facilitate patient selection, but postoperative risk scores may offer valuable information for predicting outcomes. We hypothesized that the postoperative Sequential Organ Failure Assessment (SOFA) score would predict mortality after left ventricular assist device (LVAD) implantation. Methods We retrospectively reviewed data from 294 continuous‐flow LVAD implantations performed at Mayo Clinic Rochester during 2007 to 2015. We calculated the EuroSCORE, HeartMate‐II Risk Score, and RV Failure Risk Score from preoperative data and the APACHE III and Post Cardiac Surgery (POCAS) risk scores from postoperative data. Daily, maximum, and mean SOFA scores were calculated for the first 5 postoperative days. The area under receiver‐operator characteristic curves (AUC) was calculated to compare the scoring systems' ability to predict 30‐day, 90‐day, and 1‐year mortality. Results For the entire cohort, mortality was 5% at 30 days, 10% at 90 days, and 19% at 1 year. The Day 1 SOFA score had better discrimination for 30‐day mortality (AUC 0.77) than the preoperative risk scores or the APACHE III and POCAS postoperative scores. The maximum SOFA score had the best discrimination for 30‐day mortality (AUC 0.86), and the mean SOFA score had the best discrimination for 90‐day mortality (AUC 0.82) and 1‐year mortality (AUC 0.76). Conclusions We observed that postoperative mean and maximum SOFA scores in LVAD recipients predict short‐term and intermediate‐term mortality better than preoperative risk scores do. However, because preoperative and postoperative risk scores each contribute unique information, they are best used in concert to predict outcomes after LVAD implantation.

Abstract Background Coronary microvascular dysfunction (CMD) is associated with an increased risk of cardiovascular morbidity and mortality. The current gold-standard comprehensive assessment of CMD is through a limited-access invasive catheterization lab procedure. Purposes We aimed to develop a point-of-care tool to assist clinical guidance in patients presenting with chest pain and/or an abnormal functional stress test and with non-obstructive coronary artery disease (NOCAD) based on demographic data and resting ECG waveforms. Methods This study included 1,893 NOCAD patients (<50% angiographic stenosis) who underwent CMD evaluation as well as a standard ECG up to 1 year prior. Microvascular endothelial-independent dysfunction was defined by abnormal coronary flow reserve (CFR) <2.5 in response to intracoronary adenosine administration. Microvascular endothelial dysfunction was defined by a maximal percent increase in coronary blood flow (%ΔCBF) ≤50% in response to intracoronary acetylcholine infusion. We trained algorithms to distinguish between the following outcomes: CFR ≤2.5, ΔCBF (%) ≤50, and the combination of both. Two classes of algorithms were trained, one depending on ECG waveforms as input, and another using tabular style clinical data. The optimal classification threshold was determined by maximizing Youden's J. Results Mean age was 51±12 years and 66% were females (n=1,257). AUC values ranged from 0.49 to 0.67 for all the outcomes. The best performance in our analysis was for the outcome CFR ≤2.5 via logistic regression on tabular variables. AUC and accuracy were 0.67 and 60%; while sensitivity and NPV were 70% and 85%. Specificity and PPV were 56% and 0.35%. When decreasing the threshold from the “optimal” one (24%) to 15%, sensitivity and NPV increased to 92% and 90% respectively, while specificity and PPV decreased to 25% and 29% respectively (Figure 2). Conclusion An AI-enabled algorithm may be able to assist clinical guidance by ruling out CMD in patients presenting with chest pain and/or an abnormal functional stress test. This algorithm needs to be prospectively validated in different cohorts. Funding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): The James Nutter Family & Maria Long Family Fellowship in Cardiovascular Research and Mayo Clinic Figure 1Figure 2

Abstract Aims The current gold standard comprehensive assessment of coronary microvascular dysfunction (CMD) is through a limited-access invasive catheterization lab procedure. We aimed to develop a point-of-care tool to assist clinical guidance in patients presenting with chest pain and/or an abnormal cardiac functional stress test and with non-obstructive coronary artery disease (NOCAD). Methods and results This study included 1893 NOCAD patients (<50% angiographic stenosis) who underwent CMD evaluation as well as an electrocardiogram (ECG) up to 1-year prior. Endothelial-independent CMD was defined by coronary flow reserve (CFR) ≤2.5 in response to intracoronary adenosine. Endothelial-dependent CMD was defined by a maximal percent increase in coronary blood flow (%ΔCBF) ≤50% in response to intracoronary acetylcholine infusion. We trained algorithms to distinguish between the following outcomes: CFR ≤2.5, %ΔCBF ≤50, and the combination of both. Two classes of algorithms were trained, one depending on ECG waveforms as input, and another using tabular clinical data. Mean age was 51 ± 12 years and 66% were females (n = 1257). Area under the curve values ranged from 0.49 to 0.67 for all the outcomes. The best performance in our analysis was for the outcome CFR ≤2.5 with clinical variables. Area under the curve and accuracy were 0.67% and 60%. When decreasing the threshold of positivity, sensitivity and negative predictive value increased to 92% and 90%, respectively, while specificity and positive predictive value decreased to 25% and 29%, respectively. Conclusion An artificial intelligence-enabled algorithm may be able to assist clinical guidance by ruling out CMD in patients presenting with chest pain and/or an abnormal functional stress test. This algorithm needs to be prospectively validated in different cohorts.

Background Impaired right ventricular (RV) pulmonary artery coupling has been associated with higher mortality in patients with chronic heart disease, but few studies have examined this metric in critically ill patients. We sought to evaluate the association between RV pulmonary artery coupling, defined by the ratio of tricuspid annular peak systolic tissue Doppler velocity (TASV)/estimated RV systolic pressure (RVSP), and mortality in cardiac intensive care unit patients. Methods and Results Using a database of unique cardiac intensive care unit admissions from 2007 to 2018, we included patients with TASV/RVSP ratio measured within 1 day of hospitalization. Hospital mortality was analyzed using multivariable logistic regression, and 1‐year mortality was analyzed using multivariable Cox proportional‐hazards analysis. We included 4259 patients with a mean age of 69±15 years (40.1% women). Admission diagnoses included acute coronary syndrome in 56%, heart failure in 52%, respiratory failure in 24%, and cardiogenic shock in 12%. The mean TASV/RVSP ratio was 0.31±0.14, and in‐hospital mortality occurred in 7% of patients. Higher TASV/RVSP ratio was associated with lower in‐hospital mortality (adjusted unit odds ratio, 0.68 per each 0.1‐unit higher ratio; 95% CI, 0.58–0.79; P <0.001) and lower 1‐year mortality among hospital survivors (adjusted unit hazard ratio, 0.83 per each 0.1‐unit higher ratio; 95% CI, 0.77–0.90; P <0.001). Stepwise decreases in hospital and 1‐year mortality were observed in each higher TASV/RVSP quintile. The TASV/RVSP ratio remained associated with mortality after adjusting for left ventricular systolic and diastolic function. Conclusions A low TASV/RVSP ratio is associated with increased short‐term and long‐term mortality among cardiac intensive care unit patients, emphasizing importance of impaired RV pulmonary artery coupling as a determinant of poor prognosis. Further study is required to determine whether interventions to optimize RV pulmonary artery coupling can improve outcomes.

Abstract Aims There are limited contemporary data on the use of initial fibrinolysis in ST-segment elevation myocardial infarction cardiogenic shock (STEMI-CS). This study sought to compare the outcomes of STEMI-CS receiving initial fibrinolysis vs. primary percutaneous coronary intervention (PPCI). Methods Using the National (Nationwide) Inpatient Sample from 2009 to 2017, a comparative effectiveness study of adult (&gt;18 years) STEMI-CS admissions receiving pre-hospital/in-hospital fibrinolysis were compared with those receiving PPCI. Admissions with alternate indications for fibrinolysis and STEMI-CS managed medically or with surgical revascularization (without fibrinolysis) were excluded. Outcomes of interest included in-hospital mortality, development of non-cardiac organ failure, complications, hospital length of stay, hospitalization costs, use of palliative care, and do-not-resuscitate status. Results During 2009–2017, 5297 and 110 452 admissions received initial fibrinolysis and PPCI, respectively. Compared with those receiving PPCI, the fibrinolysis group was more often non-White, with lower co-morbidity, and admitted on weekends and to small rural hospitals (all P &lt; 0.001). In the fibrinolysis group, 95.3%, 77.4%, and 15.7% received angiography, PCI, and coronary artery bypass grafting, respectively. The fibrinolysis group had higher rates of haemorrhagic complications (13.5% vs. 9.9%; P &lt; 0.001). The fibrinolysis group had comparable all-cause in-hospital mortality [logistic regression analysis: 28.8% vs. 28.5%; propensity-matched analysis: 30.8% vs. 30.3%; adjusted odds ratio 0.97 (95% confidence interval 0.90–1.05); P = 0.50]. The fibrinolysis group had comparable rates of acute organ failure, hospital length of stay, rates of palliative care referrals, do-not-resuscitate status use, and lesser hospitalization costs. Conclusions The use of initial fibrinolysis had comparable in-hospital mortality than those receiving PPCI in STEMI-CS in the contemporary era in this large national observational study.

Abstract Aims Early detection of aortic stenosis (AS) is becoming increasingly important with a better outcome after aortic valve replacement in asymptomatic severe AS patients and a poor outcome in moderate AS. We aimed to develop artificial intelligence-enabled electrocardiogram (AI-ECG) using a convolutional neural network to identify patients with moderate to severe AS. Methods and results Between 1989 and 2019, 258 607 adults [mean age 63 ± 16.3 years; women 122 790 (48%)] with an echocardiography and an ECG performed within 180 days were identified from the Mayo Clinic database. Moderate to severe AS by echocardiography was present in 9723 (3.7%) patients. Artificial intelligence training was performed in 129 788 (50%), validation in 25 893 (10%), and testing in 102 926 (40%) randomly selected subjects. In the test group, the AI-ECG labelled 3833 (3.7%) patients as positive with the area under the curve (AUC) of 0.85. The sensitivity, specificity, and accuracy were 78%, 74%, and 74%, respectively. The sensitivity increased and the specificity decreased as age increased. Women had lower sensitivity but higher specificity compared with men at any age groups. The model performance increased when age and sex were added to the model (AUC 0.87), which further increased to 0.90 in patients without hypertension. Patients with false-positive AI-ECGs had twice the risk for developing moderate or severe AS in 15 years compared with true negative AI-ECGs (hazard ratio 2.18, 95% confidence interval 1.90–2.50). Conclusion An AI-ECG can identify patients with moderate or severe AS and may serve as a powerful screening tool for AS in the community.

ABSTRACT Background: Recent data suggests improved outcomes among cardiac intensive care unit (CICU) patients treated with norepinephrine, especially patients with severe shock. We aimed to describe the association between norepinephrine and mortality in CICU patients with severe shock, defined as those requiring high-dose vasopressors (HDV). Materials and Results: We retrospectively evaluated Mayo Clinic CICU patients treated with vasopressors from 2007 to 2015. HDV was defined as a peak Cumulative Vasopressor Index of four for any vasopressor. Peak norepinephrine equivalent (NEE) dose was used to compare vasopressor doses. Multivariable logistic regression was used to determine predictors of hospital mortality. Results: We included 2,090 patients with a median age of 69 years (IQR 59–78), including 35% females; 44% of patients received HDV. Hospital mortality was higher among patients receiving HDV (42% vs. 16%, unadjusted OR 3.87, 95% CI 3.16–4.75, P < 0.01). On multivariable analysis in HDV patients, hospital mortality increased with rising peak NEE (adjusted OR 1.02 per 0.01 mcg/kg/min, 95% CI 1.01–1.02, P < 0.01) and the use of NE was associated with lower hospital mortality (adjusted OR 0.46, 95% CI 0.31–0.72, P < 0.01). After adjustment for illness severity, peak NEE and norepinephrine use were not associated with mortality among patients who did not require HDV. Conclusions: Mortality is high among CICU patients requiring HDV, and rises with increasing vasopressor requirements. Use of NE was associated with lower mortality among patients requiring HDV, but not among those without HDV, implying that patients with more severe shock may benefit from preferential use of NE.

Abstract Objective Access to palliative care (PC) is important for many patients with uncontrolled symptom burden from serious or complex illness. However, many patients who could benefit from PC do not receive it early enough or at all. We sought to address this problem by building a predictive model into a comprehensive clinical framework with the aims to (i) identify in-hospital patients likely to benefit from a PC consult, and (ii) intervene on such patients by contacting their care team. Materials and Methods Electronic health record data for 68 349 inpatient encounters in 2017 at a large hospital were used to train a model to predict the need for PC consult. This model was published as a web service, connected to institutional data pipelines, and consumed by a downstream display application monitored by the PC team. For those patients that the PC team deems appropriate, a team member then contacts the patient’s corresponding care team. Results Training performance AUC based on a 20% holdout validation set was 0.90. The most influential variables were previous palliative care, hospital unit, Albumin, Troponin, and metastatic cancer. The model has been successfully integrated into the clinical workflow making real-time predictions on hundreds of patients per day. The model had an “in-production” AUC of 0.91. A clinical trial is currently underway to assess the effect on clinical outcomes. Conclusions A machine learning model can effectively predict the need for an inpatient PC consult and has been successfully integrated into practice to refer new patients to PC.

AbstractBackgroundIntegrins are heterodimeric proteins composed of noncovalently linked ɑ and β subunits which are essential for a wide range of normal physiology and also play prominent roles in cancer. Here we tested whether integrin expression in diagnostic skin biopsies is associated with sentinel lymph node (SLN) metastasis.MethodsWe utilized a cohort of 854 consecutive patients with primary cutaneous melanoma to quantify the expression of β integrin subunits by reverse transcriptase quantitative PCR (RT‐qPCR). In addition, we quantified the expression of β3 integrin by immunohistochemistry (IHC) in a subset of 271 patients by H score. Outcome of interest was SLN biopsy metastasis within 90 days of melanoma diagnosis. Logistic regression analyses were used to develop models for the likelihood of SLN metastasis from molecular, clinical, and histologic variables.Resultsβ3 integrin expression quantified by IHC or RT‐qPCR was associated with SLN metastasis. β1, β5, β6, and β8 integrin expression was not associated with SLN metastasis. The incremental gain in performance of a predictive model which included β3 integrin expression as quantified by IHC in combination with established clinicopathologic variables (Breslow depth and patient age) was limited.Conclusionsβ3 integrin is the principal integrin subunit associated with sentinel lymph node biopsy (SLNb) metastasis in primary cutaneous melanoma. However, β3 integrin H score does not significantly improve models for the likelihood of SLN metastasis over Breslow depth and patient age.