Publications
Department of Medicine faculty members published more than 3,000 peer-reviewed articles in 2022.
2024
BACKGROUND
On legacy 2D positron emission tomography (PET) systems utilizing a 50 mL/min Rb-82 profile, test-retest precision of quantitative perfusion is ∼10%. It is unclear whether Rb-82 infusion rate significantly impacts quantitative perfusion and/or image quality on modern analog 3D PET-CT systems. We aimed to determine whether the Rb-82 infusion profile significantly impacts test-retest precision of quantitative perfusion, perfusion metrics, and/or image quality on a modern analog 3D PET-CT scanner.
METHODS
Ninety-eight volunteers from 3 distinct groups: healthy volunteers (Normals), patients with risk factors, and/or coronary disease (Clinicals) and patients with prior transmural myocardial infarctions (Infarcts), underwent cardiac stress testing on an analog 3D PET-CT. Participants received 3 consecutive resting scans and 2 consecutive stress scans, minutes apart, with two randomly assigned Rb-82 infusion profiles: 50 mL/min (fast [F]) and 20 mL/min (slow [S]). Perfusion metrics (resting (rMBF) and stress myocardial blood flow (sMBF)) were calculated using HeartSee software. Coefficients of variance (COV), repeatability (RC), MBF, and image quality metrics were compared.
RESULTS
rMBF correlated well between F and S profiles, with intraclass correlation coefficients (ICC) ranging .91-.93. sMBF was highly correlated between F and S profiles (ICC = .97). Fast and slow profiles were associated with similar same-day test-retest precision (COV 11.5% vs 11.3% (P = .77); RC 21.5% vs 22.6%, for F-F vs S-S). There were no clinically significant differences in MBF values between F and S profiles. Image quality metrics were similar between the 2 profiles.
CONCLUSIONS
There are no clinically significant differences in precision, perfusion metrics, or image quality between Rb-82 fast and slow infusions using a contemporary analog 3D PET-CT.
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2024
BACKGROUND
Although guidelines recommend low-density lipoprotein cholesterol (LDL-C) to be < 70 mg/dL in patients with atherosclerotic cardiovascular disease (ASCVD), the rate of achieving this goal remains suboptimal. We sought to understand real world contemporary practice patterns of LDL-C management in patients with ASCVD, and whether LDL-C testing influenced management across US health systems.
METHODS
A retrospective cohort study utilizing electronic medical record data from five health systems participating in the CardioHealth Alliance was performed on patients with an LDL-C measurement in 2021 and prior ASCVD. Multivariable regression modeling was used to determine the relationship of clinical factors with achievement of guideline directed LDL-C target. Changes in lipid lowering therapy (LLT) after LDL-C testing were also described.
RESULTS
Among 216,074 patients with ASCVD, 129,886 (60.1%) had uncontrolled LDL-C (i.e. ≥ 70 mg/dL). Compared with participants with controlled LDL-C (< 70 mg/dL), those with uncontrolled LDL-C were more frequently female (50.9% vs. 35.1%), or Black (13.7% vs. 10.3%), and less commonly had coronary artery disease as the form of vascular disease (73.0% vs. 83.5% %), heart failure (21.3% vs. 29.1% %), diabetes (34.1% vs. 48.2%), atrial fibrillation (19.3% vs. 26.1%), or chronic kidney disease (25.1% vs. 32.2%). In multivariable analyses, the factors most strongly associated with failure to achieve LDL-C control were female sex (RR 1.13 [95% CI 1.12-1.14] P < .001) and Black race (1.15 [1.14-1.17] P < .001). Among the 53,957 (41.5%) of those with uncontrolled LDL-C ≥70 mg/dL not on lipid lowering therapy (LLT) at baseline, only 21% were initiated on any LLT within 6 months of the uncontrolled LDL-C value.
CONCLUSIONS
Within 5 diverse large health systems in the CardioHealth Alliance, more than half of the patients with ASCVD had uncontrolled LDL-C with significant disparities based on sex and race at baseline. The vast majority were not initiated on any lipid lowering therapy within 6 months of an elevated test result indicating persistent gaps in care that will likely worsen health inequities in outcomes. This highlights the urgent need for implementation efforts to improve equitable care.
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