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2. Choice of Specialty Careers among Final Year MBBS Students

Author

Madiha Sajjad , Rehan Ahmed Khan , Shazia Qayyum

Subjects
career choice, career preferences, influential factors, medical specialties., Medicine
Abstract

Objective: To explore the different specialty career choices of undergraduate medical students and to identify the factors influencing their career choices. Study Design: A descriptive cross-sectional survey. Place and Duration of Study: This study was conducted in Islamic International Medical College in April 2013. Materials and Methods: Final year students were selected through convenience sampling for this study.A 20 items questionnaire with one open ended and 19 Likert scale based close- ended questions was handed to 100 final year MBBS students, in order to explore their preferred career choices and reasons behind them. Non parametric data analysis was done through SPSS 20. Results: Response rate of students was 82% of which 49 (60%) were female and 33 (40%) were male. Medicine, surgery and gynecology were the top career choices among students. Family practice was the least chosen specialty. The top 3 reasons to choose a specialty were natural aptitude, better subject comprehension and work enjoyment. Parents in the same field, easy career progression and specialty related illness in the family were the least chosen reasons. Conclusion: Choice of specialty career in health professions has an impact on the healthcare needs of the country. 'Family practice' is a forgotten domain and its importance needs to be stressed. Medical curricula should emphasize on the importance of family practice as a career choice.

Published
2016

3. Morphological Spectrum of Diseases in Patients Presenting with Enlarged Cervical lymph Nodes, Diagnosed on FNAC

Author

Madiha Sajjad, Rehan Ahmed Khan, Samina Iltaf

Subjects
cervical lymphadenopathy, tuberculosis, fnac., Medicine
Abstract

Objective: Purpose of the study was to know the relative frequencies of different morphological disease patterns in patients of cervical lymphadenopathy by FNAC. Study Design: A descriptive cross sectional study. Place and Duration of Study: Surgery and Pathology department of Pakistan Railway teaching Hospital Rawalpindi from January 2005 to October 2011. Materials and Methods: Results of fine needle aspiration cytology of patients with enlarged cervical lymphnodes was recorded. Results: Total number of patients was 150. The male to female ratio was 1.3:1 (86 males and 64 females). The maximum patients were in 11-20 years (40%), followed by 21-30 years (20%). The youngest patient was 4 Years and the oldest was 67 years. The FNAC showed chronic granulomatous inflammation suggestive of tuberculosis (43%) as the commonest pathology, followed by reactive hyperplasia (39%), nonspecific lymphadenitis (9%), lymphoma, (5%), and metastatic carcinoma (4%). Conclusion: All patients with enlarged cervical lymph nodes should be thoroughly investigated. FNAC is a reliable diagnostic tool in evaluation of lymphadenopathy. Chronic granulomatous inflammation suggesting tuberculosisis one of the major causes of enlarged cervical lymphnodes in our country.

Published
2014

5. Frequency and Prognostic Significance of Clinical Fluctuations Before Hospital Arrival in Stroke

Author

Romano, Jose G., primary, Gardener, Hannah, additional, Smith, Eric E., additional, Campo-Bustillo, Iszet, additional, Khan, Yosef, additional, Tai, Sofie, additional, Riley, Nikesha, additional, Sacco, Ralph L., additional, Khatri, Pooja, additional, Alger, Heather M., additional, Mac Grory, Brian, additional, Gulati, Deepak, additional, Sangha, Navdeep S., additional, Olds, Karin E., additional, Benesch, Curtis G., additional, Kelly, Adam G., additional, Brehaut, Scott S., additional, Kansara, Amit C., additional, Schwamm, Lee H., additional, Moody, Scott, additional, Ye, Weiping, additional, Sobhawongse, Vena, additional, Craig, Jeffrey M., additional, Pearson, Heloisa, additional, Summers, Deborah, additional, Boerman, Christine, additional, Rice, Christy, additional, Kintner, Robin, additional, Oka, Mayumi, additional, Baran, Sarah, additional, Roels, Christina, additional, Dosunmu, Maureen, additional, Chang, Cherylee W. J., additional, Moran, Jennifer, additional, Ditrich, Denise, additional, Lanciano, Nicholas, additional, Mann, Aimee, additional, Romero, Charles E., additional, Thiele, Becky, additional, Salvatore, David, additional, Taylor, Annette, additional, Shah, Neel, additional, Leacock, Rodney, additional, Rochester, Angel, additional, Guillerminet, Fanny, additional, Martin, Jerry C., additional, Jones, Johnny, additional, Brandon, Nicol, additional, Grover, Vikas, additional, Gibson, Maryika, additional, Malik, Maheen, additional, Mechem, Carol, additional, Logan, William R., additional, Cook, Camilla, additional, Khan, Muhib A, additional, Rood, Christa, additional, Babu, Arun, additional, Steinig, Leah, additional, Carlson, Jestin, additional, Henderson, Melanie, additional, Vidal, Gabriel, additional, Jennings, Bethany, additional, Lynch, Jennifer, additional, Ratcliff, Jessica, additional, Kirchoff, Kathryn, additional, Moncrieffe, Khadean, additional, Rasmussen-Winkler, Jennifer, additional, Allen, Leigh, additional, Thompson, Gary, additional, Firek, Christopher, additional, Martino, Stephen, additional, Georgy, Baher, additional, Gordon-Perue, Gillian L., additional, Vekima, Nina, additional, Gildersleeve, Kasey, additional, Skewes, Marian, additional, Valdovinos, Christina, additional, Parsons, Timothy C., additional, Marques, Cynthia, additional, Chen, John W., additional, Lombardi, David, additional, Perez, Brenda, additional, Malik, Amer, additional, Hesse, Kathy, additional, Guzik, Amy, additional, Norona, Sandra E., additional, Hoesch, Robert, additional, Anderson, Jacki, additional, Altschul, Dorothea, additional, Fermin, Farah, additional, Salgado, Miran, additional, Muller, Jonathan, additional, Acosta, Indrani, additional, Hartwell, Brooke, additional, Neill, Terry A., additional, Hundley, Carrie, additional, Chowdhary, Abhineet, additional, Fortney, Tina, additional, Romero, Jose Rafael, additional, Finn, Brandon, additional, Assad, Refat, additional, Ellithorpe, Maggie, additional, Sugg, Rebecca, additional, Hetzel, Susan, additional, Alvi, Muhammad M., additional, Sherman, Jay, additional, Hartman, Jonathan, additional, Orr, Tashia, additional, Garg, Ankur, additional, Turner, Melissa, additional, Given, Curtis, additional, Renfrow, Sara, additional, Hilburn, Jeffrey, additional, Looney, Ellen, additional, Commichau, Christopher, additional, Jarvis, Paul, additional, Hahm, Changsoo, additional, Mccaulley, Melissa, additional, Pulido, Angel, additional, Michel, Sergio, additional, Ramezan-Arab, Nima, additional, Toussaint- Jones, Françoise, additional, Khanna, Anna, additional, Olasoji, Esther, additional, Williams, Armistead, additional, Purrington, Elizabeth, additional, Reddy, Ratna, additional, Potter, Renee, additional, Desai, Bhupat, additional, Tse-Chang, Karen, additional, Ufford, Laurence, additional, Drager, Leslie, additional, Jones, Keith O., additional, Ellebusch, Teresa, additional, Dobrzynski, Michelle, additional, Wise, Elizabeth H., additional, Jerde, Ann, additional, Chaudhary, Gauhar, additional, McLean, Robyn, additional, Hanna, Joseph, additional, Cook, Dana, additional, Marden, Franklin, additional, Orde, Jennifer, additional, Arora, Ajay, additional, Miller, Shawna, additional, Reichwein, Raymond, additional, Hoffman, Deborah, additional, Matmati, Kelly, additional, Matmati, Nabil, additional, Owada, Kumiko, additional, Murphy, Laura, additional, Masih, Ashish, additional, Fife, Bethany, additional, Shepherd, Larry, additional, Holzmann, Matthew, additional, Gancher, Stephen, additional, Enoch, Sabrina, additional, Smith, Matthew, additional, Goings, Denise, additional, Mazzola, Joseph, additional, Plyler, Edward, additional, Landers, Lisa, additional, Napier, James, additional, Thoreson, Laura, additional, Alshekhlee, Amer, additional, Raymond, Michelle, additional, Ramachandran, Tarakad, additional, Jorolemon, Michael, additional, Padalino, David, additional, Maloney, Collin, additional, Mott, Jenny Rae, additional, Dhakal, Laxmi P., additional, Murphy, Cindy, additional, Milling, Truman J., additional, Lawrence, Patrick, additional, Shownkeen, Harish, additional, Hansen, Kathy, additional, Cullis, Paul A., additional, Froehlich, Lynne, additional, Mueed, Sajjad, additional, Pavolka, Ryan, additional, Levine, Steven R., additional, Gilles, Nadege, additional, LaChance, Laura, additional, Nayyar, Kanwal, additional, Klein, Karen, additional, Dotson, Rose, additional, Rowe, Kristopher, additional, Coleman, Elisheva, additional, Sayles, Emily, additional, Gadhia, Rajan, additional, Lee, Jason, additional, Lewis, Paul W., additional, Nunley, Jenny, additional, Sajjad, Rehan, additional, Halliday, Carol, additional, Katramados, Angelos, additional, Holmes, Theresa, additional, Kothari, Rashmikant, additional, Mader, Linda, additional, Chang, Fen Lei, additional, Western, Kelly, additional, Desai, Kinjal, additional, Kehr, Colleen, additional, Reese, Gary, additional, Jadhav, Ashu, additional, Steinbach, Mackenzie, additional, Saver, Jeffrey, additional, Avila, Gilda, additional, Miller, Janice A., additional, Gneiting, Alicia, additional, Tenser, Matthew S., additional, and Burke, Sarah, additional

Published
2021
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6. Predictors of Outcomes in Patients With Mild Ischemic Stroke Symptoms: MaRISS

Author

Romano, Jose G., primary, Gardener, Hannah, additional, Campo-Bustillo, Iszet, additional, Khan, Yosef, additional, Tai, Sofie, additional, Riley, Nikesha, additional, Smith, Eric E., additional, Sacco, Ralph L., additional, Khatri, Pooja, additional, Alger, Heather M., additional, Mac Grory, Brian, additional, Gulati, Deepak, additional, Sangha, Navdeep S., additional, Craig, Jeffrey M., additional, Olds, Karin E., additional, Benesch, Curtis G., additional, Kelly, Adam G., additional, Brehaut, Scott S., additional, Kansara, Amit C., additional, Schwamm, Lee H., additional, Grory, Brian Mac, additional, Oka, Mayumi, additional, Roels, Christina, additional, Chang, Cherylee W. J., additional, Moran, Jennifer, additional, Lanciano, Nicholas, additional, Romero, Charles E., additional, Salvatore, David, additional, Shah, Neel, additional, Leacock, Rodney, additional, Rochester, Angel, additional, Martin, Jerry C., additional, Grover, Vikas, additional, Malik, Maheen, additional, Logan, William R., additional, Khan, Muhib A, additional, Babu, Arun, additional, Carlson, Jestin, additional, Vidal, Gabriel, additional, Lynch, Jennifer, additional, Kirchoff, Kathryn, additional, Rasmussen-Winkler, Jennifer, additional, Thompson, Gary, additional, Martino, Stephen, additional, Gordon-Perue, Gillian L., additional, Gildersleeve, Kasey, additional, Parsons, Timothy C., additional, Chen, John W., additional, Lombardi, David, additional, Malik, Amer, additional, Guzik, Amy, additional, Hoesch, Robert, additional, Altschul, Dorothea, additional, Salgado, Miran, additional, Acosta, Indrani, additional, Neill, Terry A., additional, Chowdhary, Abhineet, additional, Romero, Jose Rafael, additional, Assad, Refat, additional, Sugg, Rebecca, additional, Alvi, Muhammad M., additional, Hartman, Jonathan, additional, Garg, Ankur, additional, Given, Curtis, additional, Hilburn, Jeffrey, additional, Commichau, Christopher, additional, Hahm, Changsoo, additional, Pulido, Angel, additional, Ramezan-Arab, Nima, additional, Khanna, Anna, additional, Williams, Armistead, additional, Reddy, Ratna, additional, Desai, Bhupat, additional, Ufford, Laurence, additional, Jones, Keith O., additional, Wise, Elizabeth H., additional, Chaudhary, Gauhar, additional, Hanna, Joseph, additional, Marden, Franklin, additional, Arora, Ajay, additional, Reichwein, Raymond, additional, Matmati, Kelly, additional, Owada, Kumiko, additional, Masih, Ashish, additional, Shepherd, Larry, additional, Gancher, Stephen, additional, Smith, Matthew, additional, Mazzola, Joseph, additional, Plyler, Edward, additional, Napier, James, additional, Alshekhlee, Amer, additional, Ramachandran, Tarakad, additional, Jorolemon, David, Michael, additional, Collin Maloney, Padalino, additional, Dhakal, Laxmi P., additional, Milling, Truman J., additional, Shownkeen, Harish, additional, Cullis, Paul A., additional, Mueed, Sajjad, additional, Levine, Steven R., additional, Nayyar, Kanwal, additional, Dotson, Rose, additional, Coleman, Elisheva, additional, Gadhia, Rajan, additional, Lewis, Paul W., additional, Sajjad, Rehan, additional, Katramados, Angelos, additional, Kothari, Rashmikant, additional, Chang, Fen Lei, additional, Desai, Kinjal, additional, Reese, Gary, additional, Jadhav, Ashu, additional, Saver, Jeffrey, additional, Miller, Janice A., additional, and Tenser, Matthew S., additional

Published
2021
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8. Validation of Stroke Network of Wisconsin Scale at Aurora Health Care System

Author

Panichpisal, Kessarin, Singh, Maharaj, Chohan, Adil, Vilar, Paul, Babygirija, Reji, Hook, Mary, Matyas, Sharon, Kojis, Nathaniel, Sajjad, Rehan, Wolfe, Thomas, Kassam, Amin, and Rovin, Richard Adam

Subjects
Article
Abstract

The Stroke Network of Wisconsin (SNOW) scale, previously called the Pomona scale, was developed to predict large-vessel occlusions (LVOs) in patients with acute ischemic stroke (AIS). The original study showed a high accuracy of this scale. We sought to externally validate the SNOW scale in an independent cohort.We retrospectively reviewed and calculated the SNOW scale, the Vision Aphasia and Neglect Scale (VAN), the Cincinnati Prehospital Stroke Severity (CPSS), the Los Angeles Motor Scale (LAMS), and the Prehospital Acute Stroke Severity Scale (PASS) for all patients who were presented within 24 hours after onset at AHCS (14 hospitals) between January 2015 and December 2016. The predictive performance of all scales and several National Institute of Health Stroke Scale cutoffs (≥6) were determined and compared. LVO was defined by total occlusions involving the intracranial internal carotid artery, middle cerebral artery (MCA; M1), or basilar arteries.Among 2183 AIS patients, 1381 had vascular imaging and were included in the analysis. LVO was detected in 169 (12%). A positive SNOW scale had comparable accuracy to predict LVO and showed a sensitivity of 0.80, specificity of 0.76, the positive predictive value (PPV) of 0.31, and negative predictive value of 0.96 for the detection of LVO versus CPSS ≥ 2 of 0.64, 0.87, 0.41, and 0.95. A positive SNOW scale had higher accuracy than VAN, LAMS, and PASS.In our large stroke network cohort, the SNOW scale has promising sensitivity, specificity and accuracy to predict LVO. Future prospective studies in both prehospital and emergency room settings are warranted.

Published
2018

9. Abstract WP293: A Prospective Validation of Stroke Network of Wisconsin (snow) Scale to Predict Large Vessel Occlusion (lvo) and Comparison With Other Stroke Scales

Author

Panichpisal, Kessarin, primary, Hess, Maureen, additional, Singh, Maharaj, additional, Dellemann, Elizabeth, additional, Vilar, Paul, additional, Babygirija, Reji P, additional, Erpenbeck, Sarah, additional, Chohan, Adil, additional, Wolfe, Thomas, additional, Sajjad, Rehan, additional, and Rovin, Richard A, additional

Published
2019
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16. Abstract W P256.

Author

Ortega Gutierrez, Santiago, Aranda Calleja, Maria Angeles, Shah, Pankhil, Amaro Delgado, Sergio, Agarwal, Sachin, Cunningham, Alyson, Sajjad, Rehan, Szeder, Viktor, and Torbey, Michel T

Published
2014

17. Validation of Stroke Network of Wisconsin Scale at Aurora Health Care System.

Author

Panichpisal K, Singh M, Chohan A, Vilar P, Babygirija R, Hook M, Matyas S, Kojis N, Sajjad R, Wolfe T, Kassam A, and Rovin RA

Abstract

Background: The Stroke Network of Wisconsin (SNOW) scale, previously called the Pomona scale, was developed to predict large-vessel occlusions (LVOs) in patients with acute ischemic stroke (AIS). The original study showed a high accuracy of this scale. We sought to externally validate the SNOW scale in an independent cohort., Methods: We retrospectively reviewed and calculated the SNOW scale, the Vision Aphasia and Neglect Scale (VAN), the Cincinnati Prehospital Stroke Severity (CPSS), the Los Angeles Motor Scale (LAMS), and the Prehospital Acute Stroke Severity Scale (PASS) for all patients who were presented within 24 hours after onset at AHCS (14 hospitals) between January 2015 and December 2016. The predictive performance of all scales and several National Institute of Health Stroke Scale cutoffs (≥6) were determined and compared. LVO was defined by total occlusions involving the intracranial internal carotid artery, middle cerebral artery (MCA; M1), or basilar arteries., Results: Among 2183 AIS patients, 1381 had vascular imaging and were included in the analysis. LVO was detected in 169 (12%). A positive SNOW scale had comparable accuracy to predict LVO and showed a sensitivity of 0.80, specificity of 0.76, the positive predictive value (PPV) of 0.31, and negative predictive value of 0.96 for the detection of LVO versus CPSS ≥ 2 of 0.64, 0.87, 0.41, and 0.95. A positive SNOW scale had higher accuracy than VAN, LAMS, and PASS., Conclusion: In our large stroke network cohort, the SNOW scale has promising sensitivity, specificity and accuracy to predict LVO. Future prospective studies in both prehospital and emergency room settings are warranted.

Published
2018

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