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139 results on '"Khazen, Olga"'

8. Contributors

Author

Alterman, Ron, primary, Arle, Jeffrey E., additional, Bradley, Kerry, additional, Canavero, Sergio, additional, Falowski, Steven M., additional, Farley, Chad W., additional, Gologorsky, Yakov, additional, Gu, Jianwen Wendy, additional, Journée, H. Louis, additional, Kast, John, additional, Khazen, Olga, additional, Krauss, Joachim K., additional, Kumar, Vignessh, additional, Lent, Mark, additional, Levy, Robert M., additional, Lozano, Andres M., additional, Mackel, Charles, additional, Mandybur, George T., additional, McLaughlin, Bryan L., additional, Merrill, Daniel R., additional, Mogilner, Alon Y., additional, Molnar, Gabi, additional, Monsalve, Guillermo A., additional, North, Richard B., additional, Park, Yunseo Linda, additional, Parker, John, additional, Patel, Shrey, additional, Pilitsis, Julie G., additional, Ponce, Francisco A., additional, Pope, Jason E., additional, Ramirez-Zamora, Adolfo, additional, Raso, Louis J., additional, Rosenow, Joshua M., additional, Shils, Jay L., additional, Single, Peter, additional, Slavin, Konstantin V., additional, Staudt, Michael D., additional, Stecker, Mark M., additional, and Truong, Huy Q., additional

Published
2022
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23. Preoperative evaluation of coagulation status in neuromodulation patients

Author

Hadanny, Amir, primary, Olmsted, Zachary T., additional, Marchese, Anthony M., additional, Kroll, Kyle, additional, Figueroa, Christopher, additional, Tagney, Thomas, additional, Tram, Jennifer, additional, DiMarzio, Marisa, additional, Khazen, Olga, additional, Mitchell, Dorothy, additional, Cangero, Theodore, additional, Sukul, Vishad, additional, and Pilitsis, Julie G., additional

Published
2022
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25. In Reply: Development of Machine Learning-Based Models to Predict Treatment Response to Spinal Cord Stimulation

Author

Hadanny, Amir, Harland, Tessa A., Khazen, Olga, DiMarzio, Marisa, Telkes, Ilknur, and Pilitsis, Julie G.

Subjects
Cohort Studies, Machine Learning, Spinal Cord Stimulation, Logistic Models, Treatment Outcome, Spinal Cord, Pain, Humans, Surgery, Neurology (clinical), Chronic Pain
Abstract

Despite spinal cord stimulation's (SCS) proven efficacy, failure rates are high with no clear understanding of which patients benefit long term. Currently, patient selection for SCS is based on the subjective experience of the implanting physician.To develop machine learning (ML)-based predictive models of long-term SCS response.A combined unsupervised (clustering) and supervised (classification) ML technique was applied on a prospectively collected cohort of 151 patients, which included 31 features. Clusters identified using unsupervised K-means clustering were fitted with individualized predictive models of logistic regression, random forest, and XGBoost.Two distinct clusters were found, and patients in the cohorts significantly differed in age, duration of chronic pain, preoperative numeric rating scale, and preoperative pain catastrophizing scale scores. Using the 10 most influential features, logistic regression predictive models with a nested cross-validation demonstrated the highest overall performance with the area under the curve of 0.757 and 0.708 for each respective cluster.This combined unsupervised-supervised learning approach yielded high predictive performance, suggesting that advanced ML-derived approaches have potential to be used as a functional clinical tool to improve long-term SCS outcomes. Further studies are needed for optimization and external validation of these models.

Published
2022

27. 124 Feasibility of Spinal Motor Mapping Using High-resolution Spinal Cord Stimulation Paddles in Patients with Chronic Pain

Author

Telkes, Ilknur, primary, Hadanny, Amir, additional, DiMarzio, Marisa D., additional, Chitnis, Girish, additional, Staudt, Michael D., additional, Paniccioli, Steven, additional, O'Connor; Rachael Grey, Katherine, additional, Gillogly, Michael, additional, Khazen, Olga, additional, McLaughlin, Bryan, additional, and Pilitsis, Julie G., additional

Published
2022
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35. Sex-specific effects of subthalamic nucleus stimulation on pain in Parkinson’s disease

Author

Khazen, Olga, primary, DiMarzio, Marisa, additional, Platanitis, Kelsey, additional, Grimaudo, Heather C., additional, Hancu, Maria, additional, Shao, Miriam M., additional, Staudt, Michael D., additional, Maguire, Lucy, additional, Sukul, Vishad V., additional, Durphy, Jennifer, additional, Hanspal, Era K., additional, Adam, Octavian, additional, Molho, Eric, additional, and Pilitsis, Julie G., additional

Published
2021
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44. Treatment Strategies for Generator Pocket Pain

Author

Bao, Jonathan, primary, Khazen, Olga, additional, Olmsted, Zachary T, additional, Gechtman, Guy, additional, Shao, Miriam M, additional, DiMarzio, Marisa, additional, Topp, Gregory, additional, Sukul, Vishad V, additional, Staudt, Michael D, additional, and Pilitsis, Julie G, additional

Published
2021
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46. Contributors

Author

Acampora, Gregory A., Adams, Meredith C.B., Agarwal, Deepti, Alonso, Aurelio, Anderson, Thomas Anthony, Anitescu, Magdalena, Argoff, Charles E., Ares, Javier De Andrés, Baron, Ralf, Barry, Declan, Quevedo, Himayapsill Batista, Beitel, Mark, Benedetti, Fabrizio, Benson, John C., Benzon, Honorio T., Benzon, Hubert A., Bhatia, Anuj, Bhullar, Ravneet, Bielefeldt, Klaus, Blanchfield, Anna, Dratver, Milana Bochkur, Booker, Staja Q., Burchiel, Kim J., Burjek, Nicholas E., Cai, Yi, Candido, Kenneth D., Chadwick, Andrea L., Chandra, Ronil V., Chandwani, Kailash, Chang, Andrew K., Chen, Yun-Yun K., Cheng, Jianguo, Chiaramonte, Delia, Chou, Roger, Clauw, Daniel J., Cohen, Steven P., Columbano, Heather A., Cooper, Silvie, Copenhaver, David, Cortazzo, Megan H., Curran, Samantha, D’Adamo, Chris, Dailey, Dana, Dampier, Carlton D., De, Elise J.B., Deering, James, Delay, Lauriane, Derrico, David J., Dickenson, Anthony H., Diehn, Felix E., DiGiosia, Massimiliano, D’Souza, Ryan S., Duarte, Robert, Dubin, Andrew, Dunn, Lauren K., Edwards, Robert R., Edwards, Lori-Ann, Elhady, Dalya, Essner, Bonnie S., Fishman, Scott M., Fitzgibbon, Dermot, Forde, Grace, Frisaldi, Elisa, Fudin, Jeffrey, Furnish, Timothy, Galluzzi, Katherine E., Gaeta Gazzola, Marina, Gentry, Katherine, Gilmore, Christopher, Gonçalves dos Santos, Gilson, Gordon, Debra B., Guerrero, Carlos E., Gulati, Amit, Hadanny, Amir, Hadjistavropoulos, Thomas, Hamsher, Carlyle Peters, Hanes, Michael C., Hermes, Gretchen, Herr, Keela A., Hillen, Louise, Hirsch, Joshua A., Holland, Marshall T., Hoss, Rebecca, Hsu, Margaret, Huh, Yul, Hunt, Christine L., Huntoon, Marc A., Hurley, Robert W., Huygen, Frank J.P.M., Inturrisi, Charles, Issa, Mohammed A., Jamison, Robert N., Ji, Ru-Rong, Johnson, Rebecca L., Joshi, Jatin, Kapural, Leonardo, Kerns, Robert D., Khan, Dost, Khazen, Olga, Kruse, Jessica, Knezevic, Nebojsa Nick, Kooner, Preetma Kaur, Koutalianos, Evangeline P., Lam, Christopher M., Larach, Daniel B., Littlejohn, James, Leemputte, Mary, Maingard, Julian, Makris, Una E., Malik, Khalid, Maus, Timothy P., McCormick, Zachary L., McKenzie-Brown, Anne Marie, Meints, Samantha M., Meroney, Matthew, Moon, Jee Youn, Mora, Juan C., Morrison, Brian, Moryl, Natalie, Mossey, Jana M., Murphy, Tasha B., Nader, Antoun, Nagpal, Geeta, Nakad, Lynn, Nambiar, Mithun, Nelson, Ariana M., Novy, Diane, Nugent, Shannon, Okifuji, Akiko, Osaji, Dikachi, Mogica, Jan Alberto Paredes, Parikh, Sagar S., Patel, Ryan, Peralta, Feyce M., Pilitsis, Julie G., Piracha, Mohammad, Pisansky, AndrewJ.B., Ploner, Markus, Powelson, Elisabeth B., Provenzano, David A., Przkora, Rene, Ranavaya, Jamila I., Ranavaya, Mohammed I., Ranavaya II, Mohammed I., Raslan, Ahmed M., Rathmell, James P., Roy, Mathieu, Rubin, John E., Sachau, Juliane, Schober, Patrick, Schreiber, Kristin L., Seng, Elizabeth K., Shah, Ravi, Shaibani, Aziz, Shen, Liang, Silberstein, Stephen D., Singla, Priyanka, Slater, Lee-Anne, Sluka, Kathleen A., Stacey, Brett R., P. Stanos, Steven, Starr, Jordan, Steinhilber, Kylie, Strand, Natalie H., Sullivan, Mark D., Suresh, Santhanam, Tauben, David J., Terman, Gregory W., Tolba, Reda, Turk, Dennis C., Tyburski, Mark D., Vachon-Presseau, Etienne, van Boxem, Koen, van Eerd, Maarten, van Zundert, Jan, Vance, Carol G.T., Vanneste, Thibaut, Vargas, Angelica A., Verbunt, Jeanine A., Vetter, Thomas R., Dias, Elayne Viera, Vivaldi, Daniela, Vuong, Iris, Wagner, Graham, Wahezi, Sayed E., Walco, Gary A., Wallace, Mark S., Walsh, David Andrew, Wang, Ning Nan, Wasan, Ajay, Wegrzyn, Erica L., Westlund, Karin N., Williams, David A., Wittink, Harriet, Wu, Christopher L., Yaksh, Tony L., Zinboonyahgoon, Nantthasorn, and Zuidema, Xander

Published
2023
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47. Age as an Independent Predictor of Adult Spinal Cord Stimulation Pain Outcomes.

Author

Bondoc, Melanie, Hancu, Maria, DiMarzio, Marisa, Sheldon, Breanna L., Shao, Miriam M., Khazen, Olga, and Pilitsis, Julie G.

Abstract

Introduction: Spinal cord stimulation (SCS) is an efficacious chronic pain treatment most commonly used in middle-aged patients. Results from previous studies that investigated SCS′ effects in older patient populations have been equivocal. We examine whether SCS outcomes correlate with age. Methods: We retrospectively examined prospectively collected outcomes from 189 patients who underwent SCS at Albany Medical Center between 2012 and 2020. The patients completed the Numerical Rating Scale (NRS), McGill Pain Questionnaire (MPQ), Oswestry Disability Index (ODI), Beck Depression Inventory (BDI), and Pain Catastrophizing Scale (PCS) preoperatively and 1 year postoperatively. The mean percent change in each outcome was determined and compared via a regression analysis to determine relationships between patient age and each respective outcome metrics. Demographics were compared between patients aged under 65 versus those aged 65 and older via χ2 tests. Results: All subjects demonstrated the expected improvement on NRS, BDI, PCS, and MPQ from baseline to 1-year follow-up, with several demonstrating statistically significant changes: NRS-worst pain (18.66%, p < 0.001), NRS-least pain (26.9%, p < 0.001), NRS-average pain (26.9%, p < 0.01), NRS-current pain (26.4%, p < 0.001), ODI (19.6%, p < 0.001), PCS (29.8%, p < 0.001), and MPQ (29.4%, p < 0.001). There was no significant difference between patients aged under 65 versus those aged 65 and older based on lead type (p = 0.454). Six patients (3.1%) had lead migration, one of whom was 65 or older. Regression analysis revealed improvements in MPQ-sensory and MPQ-affective scores as age increased (p < 0.001, R2 = 0.09; p = 0.046, R2 = 0.05, respectively). Age did not correlate with NRS, ODI, BDI, or PCS. Diagnosis, spinal level of SCS, and lead type were not found to influence any respective outcome measure based on covariate analysis. Conclusion: This study represents the largest study where age was correlated to specific pain, depression, and disability outcomes following SCS. We provide evidence that SCS outcomes are equivalent, or better, in older patients following SCS. Based on these findings, SCS is a viable option for treatment of chronic pain in elderly patient populations. [ABSTRACT FROM AUTHOR]

Published
2022
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48. Diversity in Neuromodulators: Where We Are and Where We Need to Go

Author

Sabourin, Shelby, primary, Omoruan, Moje, additional, Khazen, Olga, additional, DiMarzio, Marisa, additional, Sofatzis, Tia, additional, Staples, Sarah, additional, Feustel, Paul J., additional, Petersen, Erika, additional, Casini, Gianna, additional, Spinoza, Zulma T., additional, and Pilitsis, Julie G., additional

Published
2020
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49. Incidence of mechanical thrombectomy among stroke patients brought directly to a comprehensive stroke center versus transfer from a primary stroke center in upstate New York

Author

Khazen, Olga, Bao, Jonathan, Gajjar, Avi A, Entezami, Pouya, Dalfino, John C, Feustel, Paul J, and Paul, Alexandra R

Abstract

Background Faster time to treatment for stroke is associated with improved outcomes. In cases of large vessel occlusion (LVO), standard of care treatment with thrombectomy can only be provided at a comprehensive stroke center (CSC). We examine the outcomes of patients who are directly brought to our center, a CSC, compared to those seen at a primary stroke center (PSC) and then transferred.Methods Patients with LVO presenting to our center from 1/1/2019 to 12/31/2019 were included. Cohorts of patients presenting first to a PSC and presenting first to a CSC were compared. Demographics and outcome metrics (Discharge Modified Rankin Scale (mRS) and National Institute of Health Stroke Severity Scale (NIHSS) scores) were obtained for all LVO patients. Imaging was also assessed.Results Of 864 stroke admissions, 346 had LVO (40%) with 183 (53%) transferring from a PSC and 163 (47%) presenting directly. Similar percentages of each cohort were taken for thrombectomy (25.1% transfer and 31.3% direct). However, as distance between PSC and CSC increased, likelihood of thrombectomy decreased. Transfer patients were more likely to be excluded from thrombectomy secondary to a large volume of complete stroke (p  =  0.0001). Direct presenters had lower discharge mRS scores than transfer patients (p < 0.01), however, severity of stroke upon admission was similar in the two groups.Conclusion Patients transferred from a PSC were more likely to have a worse outcome at time of discharge than those presenting directly to our center. Large volume of completed stroke was a frequent reason for exclusion from thrombectomy. Optimizing stroke protocols to CSC in cases of LVOs may result in better outcomes.

Published
2024
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50. Preoperative evaluation of coagulation status in neuromodulation patients.

Author

Hadanny A, Olmsted ZT, Marchese AM, Kroll K, Figueroa C, Tagney T, Tram J, DiMarzio M, Khazen O, Mitchell D, Cangero T, Sukul V, and Pilitsis JG

Abstract

Objective: The incidence of hemorrhage in patients who undergo deep brain stimulation (DBS) and spinal cord stimulation (SCS) is between 0.5% and 2.5%. Coagulation status is one of the factors that can predispose patients to the development of these complications. As a routine part of preoperative assessment, the authors obtain prothrombin time (PT), partial thromboplastin time (PTT), and platelet count. However, insurers often cover only PT/PTT laboratory tests if the patient is receiving warfarin/heparin. The authors aimed to examine their experience with abnormal coagulation parameters in patients who underwent neuromodulation., Methods: Patients who underwent neuromodulation (SCS, DBS, or intrathecal pump implantation) over a 9-year period and had preoperative laboratory values available were included. The authors determined abnormal values on the basis of a clinical protocol utilized at their practice, which combined the normal ranges of the laboratory tests and clinical relevance. This protocol had cutoff values of 12 seconds and 39 seconds for PT and PTT, respectively, and < 120,000 platelets/μl. The authors identified risk factors for these abnormalities and described interventions., Results: Of the 1767 patients who met the inclusion criteria, 136 had abnormal preoperative laboratory values. Five of these 136 patients had values that were misclassified as abnormal because they were within the normal ranges at the outside facility where they were tested. Fifty-one patients had laboratory values outside the ranges of our protocol, but the surgeons reviewed and approved these patients without further intervention. Of the remaining 80 patients, 8 had known coagulopathies and 24 were receiving warfarin/heparin. The remaining 48 patients were receiving other anticoagulant/antiplatelet medications. These included apixaban/rivaroxaban/dabigatran anticoagulants (n = 22; mean ± SD PT 13.7 ± 2.5 seconds) and aspirin/clopidogrel/other antiplatelet medications (n = 26; mean ± SD PT 14.4 ± 5.8 seconds). Eight new coagulopathies were identified and further investigated with hematological analysis., Conclusions: New anticoagulants and antiplatelet medications are not monitored with PT/PTT, but they affect coagulation status and laboratory values. Although platelet function tests aid in a subset of medications, it is more difficult to assess the coagulation status of patients receiving novel anticoagulants. PT/PTT may provide value preoperatively.

Published
2021
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