Validation of Appropriate Use Criteria for Coronary Computed Tomographic Angiography for Chest Pain Evaluation in a Tertiary Care Emergency Room.

PURPOSE: Appropriate use criteria (AUC) defines the appropriateness of imaging procedures for specific clinical scenarios to promote evidence-based utilization and improve cost-effective care. The goal of this study was to assess the diagnostic yield and downstream health care resource utilization according to the AUC categorization for coronary computed tomography angiography (CCTA) in emergency department (ED) patients presenting with chest pain. MATERIALS AND METHODS: A total of 789 consecutive patients in the ED with chest pain and no known coronary artery disease (CAD) who underwent CCTA were classified as appropriate, uncertain, or inappropriate use according to the 2010 AUC. We abstracted index and 30-day data from the electronic medical record to determine diagnostic yield (rate of obstructive CAD and revascularization) and health care resource utilization (downstream stress test and 30-d hospital return rate). RESULTS: Rates of appropriate, uncertain, and inappropriate utilization were 48.4%, 48.8%, and 2.8%. Among appropriate, uncertain, and inappropriate classifications, rates of obstructive CAD were 9%, 8%, and 32% (P=0.002); rates of revascularization were 3%, 1%, and 36% (P<0.001); downstream stress test utilization rates were 5% versus 5% versus 14% (P=0.17), and 30-day hospital return rates were 6% versus 6% versus 5% (P>0.99), respectively. CONCLUSIONS: Appropriate and uncertain uses were associated with low diagnostic yield compared with inappropriate use; however, our findings do not demonstrate differences between appropriate use categories with respect to downstream health care resource utilization. Further studies are needed to define the role of AUC for CCTA in the ED setting.

Comparing the Modified History, Electrocardiogram, Age, Risk Factors, and Troponin Score and Coronary Artery Disease Consortium Model for Predicting Obstructive Coronary Artery Disease and Cardiovascular Events in Patients With Acute Chest Pain.

The objective of this study was to compare the History, Electrocardiogram, Age, Risk factors, and Troponin (HEART) score and clinical coronary artery disease (CAD) consortium (CADC) model for predicting obstructive CAD (≥50% stenosis on coronary computed tomographic angiography) and 30-day major adverse cardiovascular events (MACE, composite of acute myocardial infarction, revascularization, and mortality). We studied 1981 patients with no known CAD who presented with acute chest pain and had negative initial troponin and electrocardiogram. Chest pain was classified as typical, atypical, and nonanginal and used to score the history component of the modified HEART score. The C-statistic for predicting obstructive CAD was 0.747 [95% confidence interval (CI), 0.712-0.783] for the HEART score and 0.792 (95% CI, 0.762-0.823) for the CADC model (P = 0.0005). The C-statistic for predicting 30-day MACE was 0.820 (95% CI, 0.774-0.864) for the HEART score and 0.850 (95% CI, 0.800-0.891) for the CADC model (P = 0.11). Among the 48.3% of patients for whom the CADC model predicted ≤5% probability of obstructive CAD, the observed 30-day MACE was 0.6%; among the 48.9% of patients for whom the HEART score was ≤2, the 30-day MACE was 0.6%. In conclusion, the CADC model was more effective at predicting obstructive CAD compared to the HEART score. The HEART score and CADC model were equally effective to safely identify low-risk patients by achieving <1% missed 30-day MACE.

Validity of Coronary Artery Disease Consortium Models for Predicting Obstructive Coronary Artery Disease & Cardiovascular Events in Patients with Acute Chest Pain Considered for Coronary Computed Tomographic Angiography.

Although the majority of acute chest pain patients are diagnosed with noncardiac chest pain after noninvasive testing, identifying these low-risk patients before testing is challenging. The objective of this study was to validate the coronary artery disease (CAD) consortium models for predicting obstructive CAD and 30-day major adverse cardiovascular events (MACE) in acute chest pain patients considered for coronary computed tomography angiogram, as well as to determine the pretest probability threshold that identifies low-risk patients with <1% MACE. We studied 1,981 patients with no known CAD and negative initial troponin and electrocardiogram. We evaluated CAD consortium models (basic: age, sex, and chest pain type; clinical: basic + diabetes, hypertension, dyslipidemia, and smoking; and clinical + coronary calcium score [CAC] models) for prediction of obstructive CAD (≥50% stenosis on coronary CT angiogram) and 30-day MACE (Acute Myocardial Infarction, revascularization, and mortality). The C-statistic for predicting obstructive CAD was 0.77 (95% confidence interval [CI] 0.73 to 0.77) for the basic, 0.80 (95% CI 0.77 to 0.80) for the clinical, and 0.88 (95% CI 0.85 to 0.88) for the clinical + CAC models. The C-statistic for predicting 30-day MACE was 0.82 (95% CI 0.77 to 0.87) for the basic, 0.84 (95% CI 0.79 to 0.88) for the clinical, and 0.87 (95% CI 0.83 to 0.91) for the clinical + CAC models. In 47.3% of patients for whom the clinical model predicted ≤5% probability for obstructive CAD, the observed 30-day MACE was 0.53% (95% CI 0.07% to 0.999%); in the 66.9% of patients for whom the clinical + CAC model predicted ≤5% probability, the 30-day MACE was 0.75% (95% CI 0.29% to 1.22%). We propose a chest pain evaluation algorithm based on these models that classify 63.3% of patients as low risk with 0.56% (95% CI 0.15% to 0.97%) 30-day MACE. In conclusion, CAD consortium models have excellent diagnostic and prognostic value for acute chest pain patients and can safely identify a significant proportion of low-risk patients by achieving <1% missed 30-day MACE.

Computer-aided analysis of 64- and 320-slice coronary computed tomography angiography: a comparison with expert human interpretation.

Routine use of CCTA to triage Emergency Department (ED) chest pain can reduce ED length of stay while providing accurate diagnoses. We evaluated the effectiveness of using Computer Aided Diagnosis in the triage of low to intermediate risk emergency chest pain patients with Coronary Computed Tomographic Angiography (CCTA). Using 64 and 320 slice CT scanners, we compared the diagnostic capability of computer aided diagnosis to human readers in 923 ED patients with chest pain. We calculated sensitivity, specificity, Positive Predictive Value and Negative Predictive Value for cases performed on each scanner. We calculated the area under the Receiver Operator Curve (ROC) comparing results for the two scanners to Computer Aided Diagnosis performance as compared to the human reader. We examined index and 30 Day outcomes by diagnosis for each scanner and the human reader. 60% of cases could be triaged by the computer. Sensitivity was approximately 85% for both scanners, with specificity at 50.6% for the 64 slice and at 56.5% for the 320 slice scanner (per person measures). The NPV was 97.8 and 97.1 for the 64 and 320 slice scanners, respectively. Results for the four major vessels were similar with negative predictive values ranging from 97 to 100%. The ROC for Computer Aided Diagnosis for the 64 and 320 Slice Scanners, using the human reader as the gold standard was 0.6794 and 0.7097 respectively. The index and 30 day outcomes were consistent for the human reader and Computer Aided Diagnosis interpretation. Although Computer Aided Diagnosis with CCTA cannot serve completely as a substitute for human reading, it offers excellent potential as a triage tool in busy EDs.

Advanced Imaging Reduces Cost Compared to Standard of Care in Emergency Department of Triage of Acute Chest Pain.

OBJECTIVE: To evaluate medical costs of novel therapies in complex medical settings using registry data. DATA SOURCE/STUDY SETTING: Primary data, from 2008 to 2010. We used patient registry data to evaluate cost and quality performance of coronary computed tomography angiography (CCTA) in triaging chest pain patients in our tertiary care emergency department and to model financial performance under Medicare's two midnight rule. STUDY DESIGN: Using generalized linear modeling, we retrospectively compared estimated expenditures for evaluation of low-to-intermediate-risk chest pain for demographic and medically risk matched samples of 894 patients each, triaged with CCTA or local standard of care (SOC) using Medicare reimbursement as a proxy. DATA COLLECTION/EXTRACTION METHODS: Predefined data elements were downloaded from the hospital mainframe into the CCTA registry, where they were validated and maintained electronically. PRINCIPLE FINDINGS: We found that predicted standard of care costs were 2.5 times higher on the initial visit and 1.98 times higher over 30 days (p < .001) than those using CCTA. Predicted cost was 1.6 times higher when we applied our two midnight rule model (p < .001). CONCLUSION: Rapid assessment of treatment using registry data is a promising means of analyzing cost performance in complex health care environments.

Associations between routine coronary computed tomographic angiography and reduced unnecessary hospital admissions, length of stay, recidivism rates, and invasive coronary angiography in the emergency department triage of chest pain.

OBJECTIVES: This study was designed to assess the effects on resource utilization of routine coronary computed tomographic angiography (CCTA) in triaging chest pain patients in the emergency department (ED). BACKGROUND: The routine use of CCTA for ED evaluation of chest pain is feasible and safe. METHODS: We conducted a retrospective multivariate analysis of data from two risk-matched cohorts of 894 ED patients presenting with chest pain to assess the impact of CCTA versus standard evaluation on admissions rate, length of stay, major adverse cardiovascular event rates, recidivism rates, and downstream resource utilization. RESULTS: The overall admission rate was lower with CCTA (14% vs. 40%; p < 0.001). Standard evaluation was associated with a 5.5-fold greater risk for admission (odds ratio [OR]: 5.53; p < 0.001). Expected ED length of stay with standard evaluation was about 1.6 times longer (OR: 1.55; p < 0.001). There were no differences in the rates of death and acute myocardial infarction within 30 days of the index visit between the two groups. The likelihood of returning to the ED within 30 days for recurrent chest pain was 5 times greater with standard evaluation (OR: 5.06; p = 0.022). Standard evaluation was associated with a 7-fold greater likelihood of invasive coronary angiography without revascularization (OR: 7.17; p < 0.001), while neither group was significantly more likely to receive revascularization (OR: 2.06; p = 0.193). The median radiation dose with CCTA was 5.88 mSv (n = 1039; confidence interval: 5.2 to 6.4). CONCLUSIONS: The routine use of CCTA in ED evaluation of chest pain reduces healthcare resource utilization.

Design of a functional membrane protein by engineering a heme-binding site in glycophorin A.

We have designed a functional model membrane protein by engineering a bis-Histidine heme-binding site into a natural membrane protein, glycophorin A (GpA), structurally characterized by the dimerization of a single transmembrane helix. Out of the 32 residues comprising the transmembrane helix of GpA, five amino acids were mutated; the resulting protein, ME1, has been characterized in dodecyl phosphocholin (DPC) micelles by UV-vis, CD spectroscopy, gel electrophoresis, and analytical ultracentrifugation. ME1 binds heme with sub-micromolar affinity and maintains the highly helical secondary structure and dimeric oligomerization state of GpA. The ME1-Heme complex exhibits a redox potential of -128 +/- 2 mV vs SHE, indicating that the heme resides in a hydrophobic environment and is well shielded from the aqueous phase. Moreover, ME1 catalyzes the hydrogen peroxide dependent oxidation of organic substrates such as TMB (2,2',5,5'-tetramethyl-benzidine). This protein may provide a useful framework to investigate how the protein matrix tunes the cofactor properties in membrane proteins.