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1. Artificial intelligence-based preventive, personalized and precision medicine for cardiovascular disease/stroke risk assessment in rheumatoid arthritis patients: a narrative review

Author

Al-Maini, Mustafa, Maindarkar, Mahesh, Kitas, George D., Khanna, Narendra N., Misra, Durga Prasanna, Johri, Amer M., Mantella, Laura, Agarwal, Vikas, Sharma, Aman, Singh, Inder M., Tsoulfas, George, Laird, John R., Faa, Gavino, Teji, Jagjit, Turk, Monika, Viskovic, Klaudija, Ruzsa, Zoltan, Mavrogeni, Sophie, Rathore, Vijay, Miner, Martin, Kalra, Manudeep K., Isenovic, Esma R., Saba, Luca, Fouda, Mostafa M., and Suri, Jasjit S.

Published
2023
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7. Prediction of cardiovascular events in rheumatoid arthritis using risk age calculations: evaluation of concordance across risk age models

Author

Wibetoe, Grunde, Sexton, Joseph, Ikdahl, Eirik, Rollefstad, Silvia, Kitas, George D, van Riel, Piet, Gabriel, Sherine, Kvien, Tore K, Douglas, Karen, Sandoo, Aamer, Arts, Elke E, Wållberg-Jonsson, Solveig, Dahlqvist, Solbritt Rantapää, Karpouzas, George, Dessein, Patrick H, Tsang, Linda, El-Gabalawy, Hani, Hitchon, Carol A, Pascual-Ramos, Virginia, Contreas-Yañes, Irazu, Sfikakis, Petros P, González-Gay, Miguel A, Colunga-Pedraz, Iris J, Galarza-Delgado, Dionicio A, Azpiri-Lopez, Jose Ramon, Crowson, Cynthia S, and Semb, Anne Grete

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Cardiovascular, Rheumatoid Arthritis, Heart Disease, Autoimmune Disease, Prevention, Arthritis, Aging, Inflammatory and immune system, Good Health and Well Being, Adult, Age Factors, Aged, Arthritis, Rheumatoid, Cardiovascular Diseases, Female, Humans, Male, Middle Aged, Risk Assessment, Risk Factors, Cardiovascular risk age, Vascular age, Cardiovascular disease, Risk factors, Rheumatoid arthritis, Immunology, Public Health and Health Services, Arthritis & Rheumatology, Clinical sciences
Abstract

BackgroundIn younger individuals, low absolute risk of cardiovascular disease (CVD) may conceal an increased risk age and relative risk of CVD. Calculation of risk age is proposed as an adjuvant to absolute CVD risk estimation in European guidelines. We aimed to compare the discriminative ability of available risk age models in prediction of CVD in rheumatoid arthritis (RA). Secondly, we also evaluated the performance of risk age models in subgroups based on RA disease characteristics.MethodsRA patients aged 30-70 years were included from an international consortium named A Trans-Atlantic Cardiovascular Consortium for Rheumatoid Arthritis (ATACC-RA). Prior CVD and diabetes mellitus were exclusion criteria. The discriminatory ability of specific risk age models was evaluated using c-statistics and their standard errors after calculating time until fatal or non-fatal CVD or last follow-up.ResultsA total of 1974 patients were included in the main analyses, and 144 events were observed during follow-up, the median follow-up being 5.0 years. The risk age models gave highly correlated results, demonstrating R2 values ranging from 0.87 to 0.97. However, risk age estimations differed > 5 years in 15-32% of patients. C-statistics ranged 0.68-0.72 with standard errors of approximately 0.03. Despite certain RA characteristics being associated with low c-indices, standard errors were high. Restricting analysis to European RA patients yielded similar results.ConclusionsThe cardiovascular risk age and vascular age models have comparable performance in predicting CVD in RA patients. The influence of RA disease characteristics on the predictive ability of these prediction models remains inconclusive.

Published
2020

9. Smoking cessation is associated with lower disease activity and predicts cardiovascular risk reduction in rheumatoid arthritis patients

Author

Roelsgaard, Ida K, Ikdahl, Eirik, Rollefstad, Silvia, Wibetoe, Grunde, Esbensen, Bente A, Kitas, George D, van Riel, Piet, Gabriel, Sherine, Kvien, Tore K, Douglas, Karen, Wållberg-Jonsson, Solveig, Dahlqvist, Solbritt Rantapää, Karpouzas, George, Dessein, Patrick H, Tsang, Linda, El-Gabalawy, Hani, Hitchon, Carol A, Pascual-Ramos, Virginia, Contreras-Yáñez, Irazú, Sfikakis, Petros P, González-Gay, Miguel A, Crowson, Cynthia S, and Semb, Anne Grete

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Tobacco Smoke and Health, Arthritis, Prevention, Cardiovascular, Heart Disease, Tobacco, Clinical Research, Good Health and Well Being, Adult, Aged, Arthritis, Rheumatoid, Blood Pressure, Cardiovascular Diseases, Female, Humans, Lipoproteins, Male, Middle Aged, Risk Factors, Risk Reduction Behavior, Severity of Illness Index, Smoking, Smoking Cessation, rheumatoid arthritis, epidemiology, behaviour, quality of life, outcome measures, Immunology, Public Health and Health Services, Arthritis & Rheumatology, Clinical sciences
Abstract

ObjectivesSmoking is a major risk factor for the development of both cardiovascular disease (CVD) and RA and may cause attenuated responses to anti-rheumatic treatments. Our aim was to compare disease activity, CVD risk factors and CVD event rates across smoking status in RA patients.MethodsDisease characteristics, CVD risk factors and relevant medications were recorded in RA patients without prior CVD from 10 countries (Norway, UK, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico). Information on CVD events was collected. Adjusted analysis of variance, logistic regression and Cox models were applied to compare RA disease activity (DAS28), CVD risk factors and event rates across categories of smoking status.ResultsOf the 3311 RA patients (1012 former, 887 current and 1412 never smokers), 235 experienced CVD events during a median follow-up of 3.5 years (interquartile range 2.5-6.1). At enrolment, current smokers were more likely to have moderate or high disease activity compared with former and never smokers (P

Published
2020

13. Characterization of COVID-19 severity in infected lungs via artificial intelligence transfer learning

Author

Skandha, Sanagala S, primary, Saba, Luca, additional, Gupta, Suneet K, additional, Kumar, Vijaya K, additional, Johri, Amer M, additional, Khanna, Narendra N, additional, Mavrogeni, Sophie, additional, Laird, John R, additional, Pareek, Gyan, additional, Sfikakis, Petros P, additional, Protogerou, Athanasios, additional, Turk, Monica, additional, Sharma, Aditya M, additional, Nicolaides, Andrew, additional, Kitas, George D, additional, Viskovic, Klaudija, additional, Omerzu, Tomaz, additional, and Suri, Jasjit S, additional

Published
2022
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14. Artificial intelligence based carotid plaque tissue characterisation and classification from ultrasound images using a deep learning paradigm

Author

Saba, Luca, primary, Skandha, Sanagala S, additional, Gupta, Suneet K, additional, Puvvula, Anudeep, additional, Koppula, Vijaya K, additional, Johri, Amer M, additional, Khanna, Narendra N, additional, Mavrogeni, Sophie, additional, Laird, John R, additional, Pareek, Gyan, additional, Miner, Martin, additional, Sfikakis, Petros P, additional, Protogerou, Athanasios, additional, Misra, Durga P, additional, Agarwal, Vikas, additional, Sharma, Aditya M, additional, Viswanathan, Vijay, additional, Rathore, Vijay S, additional, Turk, Monika, additional, Kolluri, Raghu, additional, Viskovic, Klaudija, additional, Cuadrado-Godia, Elisa, additional, Kitas, George D, additional, Nambi, Vijay, additional, Bhatt, Deepak L, additional, Nicolaides, Andrew, additional, and Suri, Jasjit S, additional

Published
2022
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15. Magnetic resonance based Wilson’s disease tissue characterization in an artificial intelligence framework using transfer learning

Author

Skandha, Siva, primary, Saba, Luca, additional, Gupta, Suneet K, additional, Kumar, Vijaya K, additional, Johri, Amer M, additional, Khanna, Narendra N, additional, Mavrogeni, Sophie, additional, Laird, John R, additional, Pareek, Gyan, additional, Sfikakis, Petros P, additional, Protogerou, Athanasios, additional, Turk, Monica, additional, Sharma, Aditya M, additional, Nicolaides, Andrew, additional, Kitas, George D, additional, Viskovic, Klaudija, additional, Omerzu, Tomaz, additional, and Suri, Jasjit S, additional

Published
2022
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17. Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0

Author

Agarwal, Mohit, Agarwal, Sushant, Saba, Luca, Chabert, Gian Luca, Gupta, Suneet, Carriero, Alessandro, Pasche, Alessio, Danna, Pietro, Mehmedovic, Armin, Faa, Gavino, Shrivastava, Saurabh, Jain, Kanishka, Jain, Harsh, Jujaray, Tanay, Singh, Inder M., Turk, Monika, Chadha, Paramjit S., Johri, Amer M., Khanna, Narendra N., Mavrogeni, Sophie, Laird, John R., Sobel, David W., Miner, Martin, Balestrieri, Antonella, Sfikakis, Petros P., Tsoulfas, George, Misra, Durga Prasanna, Agarwal, Vikas, Kitas, George D., Teji, Jagjit S., Al-Maini, Mustafa, Dhanjil, Surinder K., Nicolaides, Andrew, Sharma, Aditya, Rathore, Vijay, Fatemi, Mostafa, Alizad, Azra, Krishnan, Pudukode R., Yadav, Rajanikant R., Nagy, Frence, Kincses, Zsigmond Tamás, Ruzsa, Zoltan, Naidu, Subbaram, Viskovic, Klaudija, Kalra, Manudeep K., and Suri, Jasjit S.

Published
2022
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22. Impact of risk factors associated with cardiovascular outcomes in patients with rheumatoid arthritis

Author

Crowson, Cynthia S, Rollefstad, Silvia, Ikdahl, Eirik, Kitas, George D, van Riel, Piet LCM, Gabriel, Sherine E, Matteson, Eric L, Kvien, Tore K, Douglas, Karen, Sandoo, Aamer, Arts, Elke, Wållberg-Jonsson, Solveig, Innala, Lena, Karpouzas, George, Dessein, Patrick H, Tsang, Linda, El-Gabalawy, Hani, Hitchon, Carol, Ramos, Virginia Pascual, Yáñez, Irazú Contreras, Sfikakis, Petros P, Zampeli, Evangelia, Gonzalez-Gay, Miguel A, Corrales, Alfonso, Laar, Mart van de, Vonkeman, Harald E, Meek, Inger, and Semb, Anne Grete

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Immunology, Cardiovascular, Aging, Prevention, Rheumatoid Arthritis, Clinical Research, Heart Disease, Arthritis, Autoimmune Disease, 2.4 Surveillance and distribution, 2.3 Psychological, social and economic factors, Aetiology, Inflammatory and immune system, Good Health and Well Being, Adult, Aged, Arthritis, Rheumatoid, Cardiovascular Diseases, Cholesterol, Cohort Studies, Female, Follow-Up Studies, Humans, Hypertension, Incidence, Male, Middle Aged, Risk Factors, Severity of Illness Index, Sex Factors, Smoking, A Trans-Atlantic Cardiovascular Consortium for Rheumatoid Arthritis, Cardiovascular disease, population attributable risk, rheumatoid arthritis, risk factor, Public Health and Health Services, Arthritis & Rheumatology, Clinical sciences
Abstract

ObjectivesPatients with rheumatoid arthritis (RA) have an excess risk of cardiovascular disease (CVD). We aimed to assess the impact of CVD risk factors, including potential sex differences, and RA-specific variables on CVD outcome in a large, international cohort of patients with RA.MethodsIn 13 rheumatology centres, data on CVD risk factors and RA characteristics were collected at baseline. CVD outcomes (myocardial infarction, angina, revascularisation, stroke, peripheral vascular disease and CVD death) were collected using standardised definitions.Results5638 patients with RA and no prior CVD were included (mean age: 55.3 (SD: 14.0) years, 76% women). During mean follow-up of 5.8 (SD: 4.4) years, 148 men and 241 women developed a CVD event (10-year cumulative incidence 20.9% and 11.1%, respectively). Men had a higher burden of CVD risk factors, including increased blood pressure, higher total cholesterol and smoking prevalence than women (all p

Published
2018

25. A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence

Author

Suri, Jasjit S., Agarwal, Sushant, Gupta, Suneet K., Puvvula, Anudeep, Biswas, Mainak, Saba, Luca, Bit, Arindam, Tandel, Gopal S., Agarwal, Mohit, Patrick, Anubhav, Faa, Gavino, Singh, Inder M., Oberleitner, Ronald, Turk, Monika, Chadha, Paramjit S., Johri, Amer M., Miguel Sanches, J., Khanna, Narendra N., Viskovic, Klaudija, Mavrogeni, Sophie, Laird, John R., Pareek, Gyan, Miner, Martin, Sobel, David W., Balestrieri, Antonella, Sfikakis, Petros P., Tsoulfas, George, Protogerou, Athanasios, Misra, Durga Prasanna, Agarwal, Vikas, Kitas, George D., Ahluwalia, Puneet, Teji, Jagjit, Al-Maini, Mustafa, Dhanjil, Surinder K., Sockalingam, Meyypan, Saxena, Ajit, Nicolaides, Andrew, Sharma, Aditya, Rathore, Vijay, Ajuluchukwu, Janet N.A., Fatemi, Mostafa, Alizad, Azra, Viswanathan, Vijay, Krishnan, P.K., and Naidu, Subbaram

Published
2021
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26. Rheumatoid arthritis-specific cardiovascular risk scores are not superior to general risk scores: a validation analysis of patients from seven countries.

Author

Crowson, Cynthia S, Gabriel, Sherine E, Semb, Anne Grete, van Riel, Piet LCM, Karpouzas, George, Dessein, Patrick H, Hitchon, Carol, Pascual-Ramos, Virginia, Kitas, George D, Douglas, Karen, Sandoo, Aamer, Rollefstad, Silvia, Ikdahl, Eirik, Kvien, Tore K, Arts, Elke, Fransen, Jaap, Tsang, Linda, El-Gabalawy, Hani, Yáñez, Irazú Contreras, Matteson, Eric L, Rantapää-Dahlqvist, Solbritt, Wållberg-Jonsson, Solveig, Innala, Lena, Sfikakis, Petros P, Zampeli, Evi, Gonzalez-Gay, Miguel A, Corrales, Alfonso, van de Laar, Mart, Vonkeman, Harald, Meek, Inger, Husni, Elaine, Overman, Robert, Colunga, Iris, and Galarza, Dionicio

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Immunology, Cardiovascular, Heart Disease, Prevention, Arthritis, Clinical Research, Adult, Age Distribution, Aged, Algorithms, Arthritis, Rheumatoid, Canada, Cardiovascular Diseases, Cohort Studies, Comorbidity, Female, Humans, Incidence, Internationality, Male, Mexico, Middle Aged, Netherlands, Norway, Predictive Value of Tests, Prognosis, Risk Assessment, Severity of Illness Index, Sex Distribution, South Africa, United Kingdom, United States, rheumatoid arthritis, cardiovascular disease, risk prediction, risk assessment, Trans-Atlantic Cardiovascular Consortium for Rheumatoid Arthritis, Public Health and Health Services, Arthritis & Rheumatology, Clinical sciences
Abstract

ObjectivesCardiovascular disease (CVD) risk calculators developed for the general population do not accurately predict CVD events in patients with RA. We sought to externally validate risk calculators recommended for use in patients with RA including the EULAR 1.5 multiplier, the Expanded Cardiovascular Risk Prediction Score for RA (ERS-RA) and QRISK2.MethodsSeven RA cohorts from UK, Norway, Netherlands, USA, South Africa, Canada and Mexico were combined. Data on baseline CVD risk factors, RA characteristics and CVD outcomes (including myocardial infarction, ischaemic stroke and cardiovascular death) were collected using standardized definitions. Performance of QRISK2, EULAR multiplier and ERS-RA was compared with other risk calculators [American College of Cardiology/American Heart Association (ACC/AHA), Framingham Adult Treatment Panel III Framingham risk score-Adult Treatment Panel (FRS-ATP) and Reynolds Risk Score] using c-statistics and net reclassification index.ResultsAmong 1796 RA patients without prior CVD [mean ( s . d .) age: 54.0 (14.0) years, 74% female], 100 developed CVD events during a mean follow-up of 6.9 years (12430 person-years). Estimated CVD risk by ERS-RA [mean ( s . d .) 8.8% (9.8%)] was comparable to FRS-ATP [mean ( s . d .) 9.1% (8.3%)] and Reynolds [mean ( s . d .) 9.2% (12.2%)], but lower than ACC/AHA [mean ( s . d .) 9.8% (12.1%)]. QRISK2 substantially overestimated risk [mean ( s . d .) 15.5% (13.9%)]. Discrimination was not improved for ERS-RA (c-statistic = 0.69), QRISK2 or EULAR multiplier applied to ACC/AHA compared with ACC/AHA (c-statistic = 0.72 for all) or for FRS-ATP (c-statistic = 0.75). The net reclassification index for ERS-RA was low (-0.8% vs ACC/AHA and 2.3% vs FRS-ATP).ConclusionThe QRISK2, EULAR multiplier and ERS-RA algorithms did not predict CVD risk more accurately in patients with RA than CVD risk calculators developed for the general population.

Published
2017

27. A Review on Joint Carotid Intima-Media Thickness and Plaque Area Measurement in Ultrasound for Cardiovascular/Stroke Risk Monitoring: Artificial Intelligence Framework

Author

Biswas, Mainak, Saba, Luca, Omerzu, Tomaž, Johri, Amer M., Khanna, Narendra N., Viskovic, Klaudija, Mavrogeni, Sophie, Laird, John R., Pareek, Gyan, Miner, Martin, Balestrieri, Antonella, Sfikakis, Petros P, Protogerou, Athanasios, Misra, Durga Prasanna, Agarwal, Vikas, Kitas, George D, Kolluri, Raghu, Sharma, Aditya, Viswanathan, Vijay, Ruzsa, Zoltan, Nicolaides, Andrew, and Suri, Jasjit S.

Published
2021
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28. Sedentary Time

Author

O’Brien, Ciara M., Duda, Joan L., Kitas, George D., Fenton, Sally A. M., Phillips, Anna C., Section editor, and Gellman, Marc D., editor

Published
2020
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29. Artificial intelligence framework for predictive cardiovascular and stroke risk assessment models: A narrative review of integrated approaches using carotid ultrasound

Author

Jamthikar, Ankush D., Gupta, Deep, Saba, Luca, Khanna, Narendra N., Viskovic, Klaudija, Mavrogeni, Sophie, Laird, John R., Sattar, Naveed, Johri, Amer M., Pareek, Gyan, Miner, Martin, Sfikakis, Petros P., Protogerou, Athanasios, Viswanathan, Vijay, Sharma, Aditya, Kitas, George D., Nicolaides, Andrew, Kolluri, Raghu, and Suri, Jasjit S.

Published
2020
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30. Six artificial intelligence paradigms for tissue characterisation and classification of non-COVID-19 pneumonia against COVID-19 pneumonia in computed tomography lungs

Author

Saba, Luca, Agarwal, Mohit, Patrick, Anubhav, Puvvula, Anudeep, Gupta, Suneet K., Carriero, Alessandro, Laird, John R., Kitas, George D., Johri, Amer M., Balestrieri, Antonella, Falaschi, Zeno, Paschè, Alessio, Viswanathan, Vijay, El-Baz, Ayman, Alam, Iqbal, Jain, Abhinav, Naidu, Subbaram, Oberleitner, Ronald, Khanna, Narendra N., Bit, Arindam, Fatemi, Mostafa, Alizad, Azra, and Suri, Jasjit S.

Published
2021
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31. Wilson disease tissue classification and characterization using seven artificial intelligence models embedded with 3D optimization paradigm on a weak training brain magnetic resonance imaging datasets: a supercomputer application

Author

Agarwal, Mohit, Saba, Luca, Gupta, Suneet K., Johri, Amer M., Khanna, Narendra N., Mavrogeni, Sophie, Laird, John R., Pareek, Gyan, Miner, Martin, Sfikakis, Petros P., Protogerou, Athanasios, Sharma, Aditya M., Viswanathan, Vijay, Kitas, George D., Nicolaides, Andrew, and Suri, Jasjit S.

Published
2021
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33. 3-D optimized classification and characterization artificial intelligence paradigm for cardiovascular/stroke risk stratification using carotid ultrasound-based delineated plaque: Atheromatic™ 2.0

Author

Skandha, Sanagala S., Gupta, Suneet K., Saba, Luca, Koppula, Vijaya K., Johri, Amer M., Khanna, Narendra N., Mavrogeni, Sophie, Laird, John R., Pareek, Gyan, Miner, Martin, Sfikakis, Petros P., Protogerou, Athanasios, Misra, Durga P., Agarwal, Vikas, Sharma, Aditya M., Viswanathan, Vijay, Rathore, Vijay S., Turk, Monika, Kolluri, Raghu, Viskovic, Klaudija, Cuadrado-Godia, Elisa, Kitas, George D., Nicolaides, Andrew, and Suri, Jasjit S.

Published
2020
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34. COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review

Author

Suri, Jasjit S., Puvvula, Anudeep, Biswas, Mainak, Majhail, Misha, Saba, Luca, Faa, Gavino, Singh, Inder M., Oberleitner, Ronald, Turk, Monika, Chadha, Paramjit S., Johri, Amer M., Sanches, J. Miguel, Khanna, Narendra N., Viskovic, Klaudija, Mavrogeni, Sophie, Laird, John R., Pareek, Gyan, Miner, Martin, Sobel, David W., Balestrieri, Antonella, Sfikakis, Petros P., Tsoulfas, George, Protogerou, Athanasios, Misra, Durga Prasanna, Agarwal, Vikas, Kitas, George D., Ahluwalia, Puneet, Kolluri, Raghu, Teji, Jagjit, Maini, Mustafa Al, Agbakoba, Ann, Dhanjil, Surinder K., Sockalingam, Meyypan, Saxena, Ajit, Nicolaides, Andrew, Sharma, Aditya, Rathore, Vijay, Ajuluchukwu, Janet N.A., Fatemi, Mostafa, Alizad, Azra, Viswanathan, Vijay, Krishnan, Pudukode R., and Naidu, Subbaram

Published
2020
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41. Ranking of stroke and cardiovascular risk factors for an optimal risk calculator design: Logistic regression approach

Author

Cuadrado-Godia, Elisa, Jamthikar, Ankush D., Gupta, Deep, Khanna, Narendra N., Araki, Tadashi, Maniruzzaman, Md, Saba, Luca, Nicolaides, Andrew, Sharma, Aditya, Omerzu, Tomaz, Suri, Harman S., Gupta, Ajay, Mavrogeni, Sophie, Turk, Monika, Laird, John R., Protogerou, Athanasios, Sfikakis, Petros, Kitas, George D., Viswanathan, Vijay, and Suri, Jasjit S.

Published
2019
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42. Performance evaluation of 10-year ultrasound image-based stroke/cardiovascular (CV) risk calculator by comparing against ten conventional CV risk calculators: A diabetic study

Author

Khanna, Narendra N., Jamthikar, Ankush D., Gupta, Deep, Nicolaides, Andrew, Araki, Tadashi, Saba, Luca, Cuadrado-Godia, Elisa, Sharma, Aditya, Omerzu, Tomaz, Suri, Harman S., Gupta, Ajay, Mavrogeni, Sophie, Turk, Monika, Laird, John R., Protogerou, Athanasios, Sfikakis, Petros P., Kitas, George D., Viswanathan, Vijay, and Suri, Jasjit S.

Published
2019
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43. Non-Invasive Assessment of Micro- and Macrovascular Function after Initiation of JAK Inhibitors in Patients with Rheumatoid Arthritis.

Author

Anyfanti, Panagiota, Angeloudi, Elena, Dara, Athanasia, Pagkopoulou, Eleni, Moysidou, Georgia-Savina, Deuteraiou, Kleopatra, Boutel, Maria, Bekiari, Eleni, Doumas, Michael, Kitas, George D., and Dimitroulas, Theodoros

Subjects
CAROTID intima-media thickness, RHEUMATOID arthritis, AMBULATORY blood pressure monitoring, PULSE wave analysis, ARTERIAL diseases, ANTIRHEUMATIC agents, ABATACEPT
Abstract

Background: Janus kinase (JAK) inhibitors constitute a novel class of oral biologic disease-modifying antirheumatic drugs for patients with rheumatoid arthritis (RA). However, their use has been associated with increased risk of major cardiovascular events. We investigated whether treatment with JAK inhibitors exerts significant alterations in the micro- and microvasculature in RA patients. Methods: Thirteen patients with RA initiating treatment with JAK inhibitors were prospectively studied. Eventually, data from 11 patients who completed the study were analyzed. Procedures were performed at baseline and 3 months after treatment. Nailfold videocapillaroscopy was applied to detect alterations of the dermal capillary network. Participants underwent 24 h ambulatory blood pressure monitoring (Mobil-O-Graph device) for the assessment of blood pressure (both brachial and aortic) and markers of large artery stiffening [pulse wave velocity (PWV), augmentation index] throughout the whole 24 h and the respective day- and nighttime periods. Carotid intima–media thickness was assessed with ultrasound. Results: Three-month treatment with JAK inhibitors was not associated with any differences in brachial and aortic blood pressure, arterial stiffness, and carotid atherosclerosis, with the only exception of nighttime PWV, which was significantly elevated at follow-up. However, three-month treatment with JAK inhibitors induced significant microvascular alterations and increased the total number of capillaroscopic abnormalities. Conclusions: Three-month treatment with JAK inhibitors may exert significant effects on microcirculation as assessed with nailfold videocapillaroscopy, whereas macrovascular structure and function appears largely unaffected. Further research toward this direction may add substantial information to the available literature regarding cardiovascular aspects of JAK inhibitors in RA. [ABSTRACT FROM AUTHOR]

Published
2024
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45. The interrater and test–retest reliability of 3 modalities of quantitative sensory testing in healthy adults and people with chronic low back pain or rheumatoid arthritis

Author

Brady, Sophia M., primary, Georgopoulos, Vasileios, additional, Veldhuijzen van Zanten, Jet J.C.S., additional, Duda, Joan L., additional, Metsios, George S., additional, Kitas, George D., additional, Fenton, Sally A.M., additional, Walsh, David A., additional, and McWilliams, Daniel F., additional

Published
2023
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46. A special report on changing trends in preventive stroke/cardiovascular risk assessment via B-mode ultrasonography

Author

Jamthikar, Ankush, primary, Gupta, Deep, additional, Khanna, Narendra N., additional, Araki, Tadashi, additional, Saba, Luca, additional, Nicolaides, Andrew, additional, Sharma, Aditya, additional, Omerzu, Tomaz, additional, Suri, Harman S., additional, Gupta, Ajay, additional, Mavrogeni, Sophie, additional, Turk, Monika, additional, Laird, John R., additional, Protogerou, Athanasios, additional, Sfikakis, Petros P., additional, Kitas, George D., additional, Viswanathan, Vijay, additional, Pareek, Gyan, additional, Miner, Martin, additional, and Suri, Jasjit S., additional

Published
2020
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47. List of contributors

Author

Araki, Tadashi, primary, Bagga, Jaspal, additional, Barde, Snehlata, additional, Bharne, Ashish, additional, Borkar, Chandrashekhar, additional, Chakraborty, Pavan, additional, Choubey, Abha, additional, Choubey, Abhishek, additional, Choubey, Shruti Bhargava, additional, Choubey, Siddhartha, additional, CSN, Koushik, additional, Desai, Santosh R., additional, Dilliwar, Vikas, additional, Goyal, Shruti, additional, Guggari, Shankru, additional, Gupta, Ajay, additional, Gupta, Deep, additional, Indrajeet, Indrajeet, additional, Jamthikar, Ankush, additional, Kaimal, Veena, additional, Khanna, Narendra N., additional, Kitas, George D., additional, Koushik, C.S.N., additional, Laird, John R., additional, Mahato, Seema, additional, Mavrogeni, Sophie, additional, Miner, Martin, additional, Mishra, Jaya, additional, Miyapuram, Krishna P., additional, Momin, Abdul, additional, Nagendra, H., additional, Nakhate, Kartik, additional, Nicolaides, Andrew, additional, Omerzu, Tomaz, additional, Pareek, Gyan, additional, Protogerou, Athanasios, additional, Rahaman, Valiur, additional, Ray, Supriya, additional, Saba, Luca, additional, Sahu, Mridu, additional, Sahula, Vineet, additional, Saini, Sandeep, additional, Sanyal, Sudip, additional, Sfikakis, Petros P., additional, Shahu, Ambika, additional, Sharaff, Aakanksha, additional, Sharma, Aditya, additional, Sharma, Sanjiv, additional, Singh, Sandeep Kumar, additional, Soni, Asma, additional, Srivastava, Saurabh Kumar, additional, Suri, Harman S., additional, Suri, Jasjit S., additional, Thomas, Ani, additional, Turk, Monika, additional, Umadevi, V, additional, Viswanathan, Vijay, additional, and Yamazaki, Tatsuya, additional

Published
2020
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48. Geometric total plaque area is an equally powerful phenotype compared with carotid intima–media thickness for stroke risk assessment: A deep learning approach

Author

Cuadrado-Godia, Elisa, primary, Srivastava, Saurabh K., additional, Saba, Luca, additional, Araki, Tadashi, additional, Suri, Harman S., additional, Giannopolulos, Argiris, additional, Omerzu, Tomaz, additional, Laird, John, additional, Khanna, Narendra N., additional, Mavrogeni, Sophie, additional, Kitas, George D., additional, Nicolaides, Andrew, additional, and Suri, Jasjit S., additional

Published
2020
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50. Morphologic TPA (mTPA) and composite risk score for moderate carotid atherosclerotic plaque is strongly associated with HbA1c in diabetes cohort

Author

Cuadrado-Godia, Elisa, Maniruzzaman, Md, Araki, Tadashi, Puvvula, Anudeep, Jahanur Rahman, Md, Saba, Luca, Suri, Harman S., Gupta, Ajay, Banchhor, Sumit K., Teji, Jagjit S., Omerzu, Tomaž, Khanna, Narendra N., Laird, John R., Nicolaides, Andrew, Mavrogeni, Sophie, Kitas, George D., and Suri, Jasjit S.

Published
2018
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