Dataset Information

Association between Admission Hyperglycemia and Culprit Lesion Characteristics in Nondiabetic Patients with Acute Myocardial Infarction: An Intravascular Optical Coherence Tomography Study.

ABSTRACT: Background:Hyperglycemia is frequently observed in acute myocardial infarction (AMI). Diabetes mellitus (DM) patients and non-DM patients have different culprit lesion phenotypes and few data are available on non-DM patients with admission hyperglycemia. Therefore, we aimed to investigate the association between admission hyperglycemia and culprit lesion characteristics using optical coherence tomography (OCT) in AMI patients. Methods and Results:We consecutively enrolled 434 patients with AMI, and 277 patients were included in analysis: 65.7% (n = 182) non-DM patients and 34.3% (n = 95) DM patients. We measured acute blood glucose (ABG) and hemoglobin A1c to calculate the acute-to-chronic glycemic ratio (A/C). Then, we grouped non-DM patients into tertiles of A/C. OCT-based culprit lesion characteristics were compared across A/C tertiles in non-DM patients and between DM and non-DM patients. Non-DM patients had fewer lipid-rich plaques (52.7% versus 68.4%, p = 0.012) and thin-cap fibroatheroma (TCFA) (19.8% versus 34.7%, p = 0.006) than DM patients but similar prevalence of plaque rupture (47.3% versus 56.8%, p = 0.130). Non-DM patients with the highest A/C tertile had the highest prevalence of plaque rupture (p for?trend = 0.002), lipid-rich plaque (p for?trend = 0.001), and TCFA (p for?trend = 0.003). A/C > 1.22 but not ABG > 140?mg/dl predicted a high prevalence of plaque rupture, lipid-rich plaque, and TCFA in non-DM patients. Conclusions:In AMI patients without DM, admission hyperglycemia is associated with vulnerable culprit lesion characteristics, and A/C is a better predictor for vulnerable culprit plaque characteristics than ABG. These results call for a tailored evaluation and management of glucose metabolism in nondiabetic AMI patients. This trial is registered with NCT03593928.

SUBMITTER: Zhou J

PROVIDER: S-EPMC7327614 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Association between Admission Hyperglycemia and Culprit Lesion Characteristics in Nondiabetic Patients with Acute Myocardial Infarction: An Intravascular Optical Coherence Tomography Study.

Zhou Jinying J Sheng Zhaoxue Z Liu Chen C Zhou Peng P Li Jiannan J Chen Runzhen R Song Li L Zhao Hanjun H Yan Hongbing H

Journal of diabetes research 20200620

<h4>Background</h4>Hyperglycemia is frequently observed in acute myocardial infarction (AMI). Diabetes mellitus (DM) patients and non-DM patients have different culprit lesion phenotypes and few data are available on non-DM patients with admission hyperglycemia. Therefore, we aimed to investigate the association between admission hyperglycemia and culprit lesion characteristics using optical coherence tomography (OCT) in AMI patients.<h4>Methods and results</h4>We consecutively enrolled 434 pati ...[more]

PMID: 32685552

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Project description:BACKGROUND:Diabetes mellitus (DM) or pre-diabetes status is closely associated with features of vulnerable coronary lesions in patients with stable coronary heart disease or acute coronary syndrome. However, the association between duration of diabetes and the morphologies and features of vulnerable plaques has not been fully investigated in patients with acute myocardial infarction (AMI). METHODS:We enrolled a total of 279 patients who presented with AMI between March 2017 and March 2019 and underwent pre-intervention optical coherence tomography imaging of culprit lesions. Patients with DM were divided into two subgroups: a Short-DM group with DM duration of < 10 years and a Long-DM group with DM duration of ≥ 10 years. Baseline clinical data and culprit-plaque characteristics were compared between patients without DM (the non-DM group), those in the Short-DM group, and those in the Long-DM group. RESULTS:Patients with DM represented 34.1% of the study population (95 patients). The Short- and Long-DM groups included 64 (67.4%) and 31 patients (32.6%), respectively. Glycated hemoglobin A1c (HbA1c) levels were significantly higher in the Long-DM group than the Non- or Short-DM groups (8.4% [Long-DM] versus 5.7% [Non-DM] and 7.6% [Short-DM], P < 0.001). In addition, the highest prevalence of lipid-rich plaques, thin-cap fibroatheroma (TCFA), and plaque ruptures of culprit lesions were observed in the Long-DM group (lipid-rich plaques: 80.6% [Long-DM] versus 52.2% [Non-DM] and 62.5% [Short-DM], P = 0.007; TCFA: 41.9% [Long-DM] versus 19.6% [Non-DM] and 31.3% [Short-DM], P = 0.012; plaque rupture: 74.2% [Long-DM] versus 46.7% [Non-DM] and 48.4% [Short-DM], P = 0.017). The frequency of calcification was significantly higher among patients with DM than among those without (62.1% versus 46.2%, P = 0.016); however, no significant differences were found between the DM subgroups (61.3% [Long-DM] versus 62.5% [Short-DM], P = 0.999). CONCLUSIONS:Increased duration of DM combined with higher HbA1c levels influences culprit-plaque characteristics in patients with DM who suffer AMI. These findings might account for the higher risks of cardiac death in DM patients with long disease duration. Trial registration This study is registered at clinicaltrials.gov as NCT03593928.

Project description:Different culprit plaque phenotypes including plaque rupture (PR) and non-plaque rupture (NPR), and N-Terminal prohormone of brain natriuretic peptide (NT-proBNP) have been reported to influence clinical outcomes in patients with acute coronary syndrome (ACS). We aimed to investigate the prognostic implication of the peak and baseline values at admission for NT-proBNP for major adverse cardiovascular events (MACE) in ST-Segment Elevated Myocardial Infarction (STEMI) patients with different plaque phenotype. A total of 428 patients with STEMI undergoing optical coherence tomography (OCT) were enrolled and divided into four groups: PR/Tertile1-2 NT-proBNP (n = 132), PR/Tertile3 NT-proBNP (n = 65), NPR/Tertile1-2 NT-proBNP (n = 154), NPR/Tertlie3 NT-proBNP (n = 77). Baseline and Peak values of NT-proBNP were obtained in the admission period. The MACEs were defined as the composite of all-cause death, recurrence of myocardial infarction and stroke. High levels for peak NT-proBNP were significantly associated with a higher incidence of MACE and death (Log rank p = 0.037 and 0.0012, respectively). In the subgroup with NPR, a high level for peak NT-proBNP was significantly associated with higher incidence of death (Log rank p = 0.0022) but this association was not significant in the subgroup of PR (Log rank p = 0.24). Though plaque types were not associated with adverse event, the combination of NPR and a higher peak value for NT-proBNP indicated higher incidence of death compared with other groups (Log rank p = 0.0017). The area under the receiver operating characteristic curve for predicting death to evaluate the diagnostic value of the peak value for NT-proBNP and plaque types combined with traditional risk factors was 0.843 (95% CI: 0.805-0.876), which is superior to solely traditional risk factors: NRI (26.8% [95% CI: 0.4-53.1%], p = 0.046) and IDI (5.1% [95% CI: 1.0-9.2%], p = 0.016). STEMI patients with NPR and a high level for peak NT-proBNP showed higher incidence of death. The peak value of NT-proBNP in combination with plaque types can be used in risk stratification and prediction of death in patients with STEMI.

Project description:Thin-cap fibroatheroma (TCFA) is a prominent risk factor for plaque rupture. Intravascular optical coherence tomography (IVOCT) enables identification of fibrous cap (FC), measurement of FC thicknesses, and assessment of plaque vulnerability. We developed a fully-automated deep learning method for FC segmentation. This study included 32,531 images across 227 pullbacks from two registries (TRANSFORM-OCT and UHCMC). Images were semi-automatically labeled using our OCTOPUS with expert editing using established guidelines. We employed preprocessing including guidewire shadow detection, lumen segmentation, pixel-shifting, and Gaussian filtering on raw IVOCT (r,θ) images. Data were augmented in a natural way by changing θ in spiral acquisitions and by changing intensity and noise values. We used a modified SegResNet and comparison networks to segment FCs. We employed transfer learning from our existing much larger, fully-labeled calcification IVOCT dataset to reduce deep-learning training. Postprocessing with a morphological operation enhanced segmentation performance. Overall, our method consistently delivered better FC segmentation results (Dice: 0.837 ± 0.012) than other deep-learning methods. Transfer learning reduced training time by 84% and reduced the need for more training samples. Our method showed a high level of generalizability, evidenced by highly-consistent segmentations across five-fold cross-validation (sensitivity: 85.0 ± 0.3%, Dice: 0.846 ± 0.011) and the held-out test (sensitivity: 84.9%, Dice: 0.816) sets. In addition, we found excellent agreement of FC thickness with ground truth (2.95 ± 20.73 µm), giving clinically insignificant bias. There was excellent reproducibility in pre- and post-stenting pullbacks (average FC angle: 200.9 ± 128.0°/202.0 ± 121.1°). Our fully automated, deep-learning FC segmentation method demonstrated excellent performance, generalizability, and reproducibility on multi-center datasets. It will be useful for multiple research purposes and potentially for planning stent deployments that avoid placing a stent edge over an FC.

Dataset Information

Association between Admission Hyperglycemia and Culprit Lesion Characteristics in Nondiabetic Patients with Acute Myocardial Infarction: An Intravascular Optical Coherence Tomography Study.

Publications

Association between Admission Hyperglycemia and Culprit Lesion Characteristics in Nondiabetic Patients with Acute Myocardial Infarction: An Intravascular Optical Coherence Tomography Study.

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