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Institution

Ochsner Medical Center

HealthcareNew Orleans, Louisiana, United States
About: Ochsner Medical Center is a healthcare organization based out in New Orleans, Louisiana, United States. It is known for research contribution in the topics: Population & Heart failure. The organization has 980 authors who have published 1159 publications receiving 49961 citations. The organization is also known as: Ochsner Hospital & Ochsner Foundation Hospital.


Papers
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Journal ArticleDOI
TL;DR: This meta‐analysis of randomized trials demonstrated no statistically significant difference in the incidence of MACE between patients who underwent trans‐ulnar or the trans‐radial cardiac catheterization.
Abstract: This meta-analysis of randomized trials demonstrated no statistically significant difference in the incidence of MACE between patients who underwent trans-ulnar or the trans-radial cardiac catheterization. No differences in arterial access time, fluoroscopy time, and contrast load between the two groups.

1 citations

Journal ArticleDOI
TL;DR: In this paper, the progression of mild hyperkalemia and the predictors of progression have not been well characterized using electronic medical records from the Research Action for Health Network (2012-2018).
Abstract: The progression of mild hyperkalemia and the predictors of progression have not been well characterized. In this study we aimed to characterize the progression of hyperkalemia and identify the risk factors for hyperkalemia progression. Adults with mild hyperkalemia (at least one serum potassium measure > 5.0 and ≤ 5.5 mEq/L) were identified using electronic medical records from the Research Action for Health Network (2012–2018). Progression to moderate-to-severe and progression to severe hyperkalemia were defined as the first occurrences of a serum potassium measure > 5.5 and > 6.0 mEq/L, respectively. Kaplan–Meier analyses were conducted to estimate progression rates for all patients and by pre-specified patient subgroups. Hazard ratios (HR) of moderate-to-severe and severe hyperkalemia progression were estimated using Cox models. Of 35,369 patients with mild hyperkalemia, 16.9% and 8.7% progressed to moderate-to-severe and severe hyperkalemia, respectively. Rates of hyperkalemia progression elevated with the severity of chronic kidney disease (CKD). The highest progression rates were seen in patients with CKD stage 5 (stage 5 vs. no CKD: moderate-to-severe, 50.2% vs. 12.0%; severe, 31.3% vs. 3.9%; p < 0.001). Higher progression rates were also observed in patients with heart failure, hypertension, and type II diabetes compared with patients without those conditions (all p < 0.001). The most prominent risk factors were CKD stage 5 (HR of progression to moderate-to-severe hyperkalemia, 3.32 [95% CI 3.03–3.64]; severe, 4.08 [3.55–4.69]), CKD stage 4 (2.19 [1.97–2.43], 2.28 [1.92–2.71]), CKD stage 3 (1.57 [1.46–1.68], 1.65 [1.46–1.87]), type I diabetes (1.37 [1.18–1.61], 1.54 [1.23–1.93]), and serum potassium (1.12 [1.10–1.15], 1.13 [1.10–1.17] per 0.1 mEq/L increase) (all p values < 0.05). Hyperkalemia progression rates increased significantly with CKD stage and were also higher among patients with higher baseline potassium level, heart failure, hypertension, and diabetes.

1 citations

Journal ArticleDOI
TL;DR: In this article , a multi-input and multiscale (MIMS) U-Net with a two-stage recurrent training strategy was proposed for the automatic vessel segmentation, which generated a refined prediction map with the following two training stages: (i) stage I coarsely segmented the major coronary arteries from preprocessed single-channel ICAs and generated the probability map of arteries; and during the stage II, a three-channel image consisting of the original pre-processed image, a generated probability map, and an edge-enhanced image generated from the pre-processing image was fed to the proposed MIMS U-net to produce the final segmentation result.
Abstract: Purpose: In stable coronary artery disease (CAD), reduction in mortality and/or myocardial infarction with revascularization over medical therapy has not been reliably achieved. Coronary arteries are usually extracted to perform stenosis detection. As such, developing accurate segmentation of vascular structures and quantification of coronary arterial stenosis in invasive coronary angiograms (ICA) is necessary. Approach: A multi-input and multiscale (MIMS) U-Net with a two-stage recurrent training strategy was proposed for the automatic vessel segmentation. The proposed model generated a refined prediction map with the following two training stages: (i) stage I coarsely segmented the major coronary arteries from preprocessed single-channel ICAs and generated the probability map of arteries; and (ii) during the stage II, a three-channel image consisting of the original preprocessed image, a generated probability map, and an edge-enhanced image generated from the preprocessed image was fed to the proposed MIMS U-Net to produce the final segmentation result. After segmentation, an arterial stenosis detection algorithm was developed to extract vascular centerlines and calculate arterial diameters to evaluate stenotic level. Results: Experimental results demonstrated that the proposed method achieved an average Dice similarity coefficient of 0.8329, an average sensitivity of 0.8281, and an average specificity of 0.9979 in our dataset with 294 ICAs obtained from 73 patients. Moreover, our stenosis detection algorithm achieved a true positive rate of 0.6668 and a positive predictive value of 0.7043. Conclusions: Our proposed approach has great promise for clinical use and could help physicians improve diagnosis and therapeutic decisions for CAD.

1 citations

Book ChapterDOI
01 Jan 2019
TL;DR: While the rarity of anal SCC precludes screening the population at large, groups at high risk for anal dysplasia and progression to invasive disease may derive benefit from focused screening programs, though the data supporting this are still evolving.
Abstract: Anal squamous cell carcinoma (SCC) is a relatively rare malignancy that in most cases is related to chronic infection from the human papillomavirus (HPV). The association with HPV infection places certain groups at high risk of developing precursor anal intraepithelial lesions and invasive cancer, including patients with chronic immunosuppression from human immunodeficiency virus (HIV) or other etiologies. The introductions of highly active antiretroviral therapy for HIV patients and of the HPV vaccine for adolescents have had a strong influence on the incidence of anal SCC over the past three decades, and this is likely to continue into the future as the full effect of HPV vaccines alters rates of HPV infection. While the rarity of anal SCC precludes screening the population at large, groups at high risk for anal dysplasia and progression to invasive disease may derive benefit from focused screening programs, though the data supporting this are still evolving. Finally, for those patients who are found to have high-grade squamous intraepithelial lesions, there are multiple topical and local ablative options for treatment. This chapter will discuss the incidence of anal SCC and how it has changed over time, risk factors for the development of invasive cancer, the pathogenesis of anal SCC, and the screening programs and treatment modalities available for anal dysplasia.

1 citations

Journal ArticleDOI
TL;DR: The rationale underpinning anesthesiologists' use of various perioperative strategies hypothesized to affect renal function in adult patients undergoing cardiac surgery, and identifying potentially renoprotective strategies for which patients would most value a detailed, evidence-based review of these strategies as discussed by the authors.

1 citations


Authors

Showing all 993 results

NameH-indexPapersCitations
Carl J. Lavie106113549318
Michael R. Jaff8244228891
Michael F. O'Rourke8145135355
Mandeep R. Mehra8064431939
Richard V. Milani8045423410
Christopher J. White7762125767
Bruce A. Reitz7433318457
Robert C. Bourge6927324397
Sana M. Al-Khatib6937717370
Hector O. Ventura6647816379
Andrew Mason6336015198
Aaron S. Dumont6038613020
Philip J. Kadowitz5537911951
David W. Dunn541958999
Lydia A. Bazzano5126713581
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
202223
2021120
2020117
2019102
201886