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109 results on '"Madlock‐Brown, Charisse"'

1. Associations of County-Level Social Determinants of Health with COVID-19 Related Hospitalization Among People with HIV: A Retrospective Analysis of the U.S. National COVID Cohort Collaborative (N3C)

Author

Islam, Jessica Y., Hurwitz, Eric, Li, Dongmei, Camacho-Rivera, Marlene, Sun, Jing, Safo, Sandra, Ross, Jennifer M., Wilkins, Kenneth, Hassan, Shukri, Hill, Elaine L., Nosyk, Bohdan, Varley, Cara, Fadul, Nada, Madlock-Brown, Charisse, and Patel, Rena C.

Published
2024
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2. Generalisable long COVID subtypes: Findings from the NIH N3C and RECOVER programmes

Author

Reese, Justin T, Blau, Hannah, Casiraghi, Elena, Bergquist, Timothy, Loomba, Johanna J, Callahan, Tiffany J, Laraway, Bryan, Antonescu, Corneliu, Coleman, Ben, Gargano, Michael, Wilkins, Kenneth J, Cappelletti, Luca, Fontana, Tommaso, Ammar, Nariman, Antony, Blessy, Murali, TM, Caufield, J Harry, Karlebach, Guy, McMurry, Julie A, Williams, Andrew, Moffitt, Richard, Banerjee, Jineta, Solomonides, Anthony E, Davis, Hannah, Kostka, Kristin, Valentini, Giorgio, Sahner, David, Chute, Christopher G, Madlock-Brown, Charisse, Haendel, Melissa A, Robinson, Peter N, Consortium, N3C, Spratt, Heidi, Visweswaran, Shyam, Flack, Joseph Eugene, Yoo, Yun Jae, Gabriel, Davera, Alexander, G Caleb, Mehta, Hemalkumar B, Liu, Feifan, Miller, Robert T, Wong, Rachel, Hill, Elaine L, Consortium, RECOVER, Thorpe, Lorna E, and Divers, Jasmin

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Coronaviruses, Emerging Infectious Diseases, Networking and Information Technology R&D (NITRD), Infectious Diseases, Precision Medicine, Machine Learning and Artificial Intelligence, Good Health and Well Being, Humans, COVID-19, Disease Progression, Post-Acute COVID-19 Syndrome, SARS-CoV-2, N3C Consortium, RECOVER Consortium, Human Phenotype Ontology, Long COVID, Machine learning, Precision medicine, Semantic similarity, Public Health and Health Services, Clinical sciences, Epidemiology
Abstract

BackgroundStratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, long COVID is incompletely understood and characterised by a wide range of manifestations that are difficult to analyse computationally. Additionally, the generalisability of machine learning classification of COVID-19 clinical outcomes has rarely been tested.MethodsWe present a method for computationally modelling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning.FindingsWe found six clusters of PASC patients, each with distinct profiles of phenotypic abnormalities, including clusters with distinct pulmonary, neuropsychiatric, and cardiovascular abnormalities, and a cluster associated with broad, severe manifestations and increased mortality. There was significant association of cluster membership with a range of pre-existing conditions and measures of severity during acute COVID-19. We assigned new patients from other healthcare centres to clusters by maximum semantic similarity to the original patients, and showed that the clusters were generalisable across different hospital systems. The increased mortality rate originally identified in one cluster was consistently observed in patients assigned to that cluster in other hospital systems.InterpretationSemantic phenotypic clustering provides a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC.FundingNIH (TR002306/OT2HL161847-01/OD011883/HG010860), U.S.D.O.E. (DE-AC02-05CH11231), Donald A. Roux Family Fund at Jackson Laboratory, Marsico Family at CU Anschutz.

Published
2023

3. From Alpha to Omicron and Beyond: Associations Between SARS-CoV-2 Variants and Surgical Outcomes

Author

Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred, Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O'Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O'Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Verhagen, Nathaniel B., Geissler, Thomas, SenthilKumar, Gopika, Gehl, Carson, Shaik, Tahseen, Flitcroft, Madelyn A., Yang, Xin, Taylor, Bradley W., Ghaferi, Amir A., Gould, Jon C., and Kothari, Anai N.

Published
2024
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4. The prevalence of postacute sequelae of coronavirus disease 2019 in solid organ transplant recipients: Evaluation of risk in the National COVID Cohort Collaborative

Author

Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred Jerrod, Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O'Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O'Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Vinson, Amanda J., Schissel, Makayla, Anzalone, Alfred J., Dai, Ran, French, Evan T., Olex, Amy L., Lee, Stephen B., Ison, Michael, and Mannon, Roslyn B.

Published
2024
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5. Risk factors associated with post-acute sequelae of SARS-CoV-2: an N3C and NIH RECOVER study

Author

Hill, Elaine L., Mehta, Hemalkumar B., Sharma, Suchetha, Mane, Klint, Singh, Sharad Kumar, Xie, Catherine, Cathey, Emily, Loomba, Johanna, Russell, Seth, Spratt, Heidi, DeWitt, Peter E., Ammar, Nariman, Madlock-Brown, Charisse, Brown, Donald, McMurry, Julie A., Chute, Christopher G., Haendel, Melissa A., Moffitt, Richard, Pfaff, Emily R., and Bennett, Tellen D.

Published
2023
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8. Decreasing Case Fatality Rates for Patients With Cirrhosis Infected With SARS-CoV-2: A National COVID Cohort Collaborative Study

Author

Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O'Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O'Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Far, Aryana T., Digitale, Jean C., Pletcher, Mark J., and Lai, Jennifer C.

Published
2024
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9. Nonelective coronary artery bypass graft outcomes are adversely impacted by Coronavirus disease 2019 infection, but not altered processes of care: A National COVID Cohort Collaborative and National Surgery Quality Improvement Program analysis

Author

Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O'Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O'Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Grimsley, Emily A., Torikashvili, Johnathan V., Janjua, Haroon M., Read, Meagan D., Kothari, Anai N., Verhagen, Nate B., Pietrobon, Ricardo, Kuo, Paul C., and Rogers, Michael P.

Published
2023
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10. Hormone replacement therapy and COVID-19 outcomes in solid organ transplant recipients compared with the general population

Author

Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O'Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O'Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Vinson, Amanda J., Anzalone, Alfred, Schissel, Makayla, Dai, Ran, French, Evan T., Olex, Amy L., and Mannon, Roslyn B.

Published
2023
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12. Thirty-Day Mortality and Complication Rates in Total Joint Arthroplasty After a Recent COVID-19 Diagnosis: A Retrospective Cohort in the National COVID Cohort Collaborative (N3C)

Author

Pincavitch, Jami D., Pisquiy, John J., Wen, Sijin, Bryan, Nicole, Ammons, Jeffrey, Makwana, Priyal, Dietz, Matthew J., Abel, Amber, Eicher, Jennifer, Danley, Suzanne, Gabriel, Davera, Kasicky, Kathryn, Levitt, Eli, Patrick, Sharon, Russell, Michael, Mozingo, Casey, Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O’Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O’Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, and Zhang, Xiaohan Tanner

Published
2023
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13. Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes

Author

Spratt, Heidi, Visweswaran, Shyam, Flack, Joseph Eugene, IV, Yoo, Yun Jae, Gabriel, Davera, Alexander, G. Caleb, Mehta, Hemalkumar B., Liu, Feifan, Miller, Robert T., Wong, Rachel, Hill, Elaine L., Thorpe, Lorna E., Divers, Jasmin, Reese, Justin T., Blau, Hannah, Casiraghi, Elena, Bergquist, Timothy, Loomba, Johanna J., Callahan, Tiffany J., Laraway, Bryan, Antonescu, Corneliu, Coleman, Ben, Gargano, Michael, Wilkins, Kenneth J., Cappelletti, Luca, Fontana, Tommaso, Ammar, Nariman, Antony, Blessy, Murali, T.M., Caufield, J. Harry, Karlebach, Guy, McMurry, Julie A., Williams, Andrew, Moffitt, Richard, Banerjee, Jineta, Solomonides, Anthony E., Davis, Hannah, Kostka, Kristin, Valentini, Giorgio, Sahner, David, Chute, Christopher G., Madlock-Brown, Charisse, Haendel, Melissa A., and Robinson, Peter N.

Published
2023
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14. COVID-19 outcomes in persons with hemophilia: results from a US-based national COVID-19 surveillance registry

Author

Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J. W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O’Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O’Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Sharathkumar, Anjali, Wendt, Linder, Ortman, Chris, Srinivasan, Ragha, Chute, Christopher G., Chrischilles, Elizabeth, and Takemoto, Clifford M.

Published
2023
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15. The Prevalence of Post-Acute Sequelae of COVID-19 in Solid Organ Transplant Recipients: Evaluation of Risk in the National COVID Cohort Collaborative (N3C)

Author

Vinson, Amanda J., primary, Schissel, Makayla, additional, Anzalone, Alfred J., additional, Dai, Ran, additional, French, Evan T., additional, Olex, Amy L., additional, Lee, Stephen B., additional, Ison, Michael, additional, Mannon, Roslyn B., additional, Wilcox, Adam B., additional, Lee, Adam M., additional, Graves, Alexis, additional, Anzalone, Alfred (Jerrod), additional, Manna, Amin, additional, Saha, Amit, additional, Olex, Amy, additional, Zhou, Andrea, additional, Williams, Andrew E., additional, Southerland, Andrew, additional, Girvin, Andrew T., additional, Walden, Anita, additional, Sharathkumar, Anjali A., additional, Amor, Benjamin, additional, Bates, Benjamin, additional, Hendricks, Brian, additional, Patel, Brijesh, additional, Alexander, Caleb, additional, Bramante, Carolyn, additional, Ward-Caviness, Cavin, additional, Madlock-Brown, Charisse, additional, Suver, Christine, additional, Chute, Christopher, additional, Dillon, Christopher, additional, Wu, Chunlei, additional, Schmitt, Clare, additional, Takemoto, Cliff, additional, Housman, Dan, additional, Gabriel, Davera, additional, Eichmann, David A., additional, Mazzotti, Diego, additional, Brown, Don, additional, Boudreau, Eilis, additional, Hill, Elaine, additional, Zampino, Elizabeth, additional, Marti, Emily Carlson, additional, Pfaff, Emily R., additional, French, Evan, additional, Koraishy, Farrukh M., additional, Mariona, Federico, additional, Prior, Fred, additional, Sokos, George, additional, Martin, Greg, additional, Lehmann, Harold, additional, Spratt, Heidi, additional, Mehta, Hemalkumar, additional, Liu, Hongfang, additional, Sidky, Hythem, additional, Hayanga, J.W. Awori, additional, Pincavitch, Jami, additional, Clark, Jaylyn, additional, Harper, Jeremy Richard, additional, Islam, Jessica, additional, Ge, Jin, additional, Gagnier, Joel, additional, Saltz, Joel H., additional, Saltz, Joel, additional, Loomba, Johanna, additional, Buse, John, additional, Mathew, Jomol, additional, Rutter, Joni L., additional, McMurry, Julie A., additional, Guinney, Justin, additional, Starren, Justin, additional, Crowley, Karen, additional, Bradwell, Katie Rebecca, additional, Walters, Kellie M., additional, Wilkins, Ken, additional, Gersing, Kenneth R., additional, Cato, Kenrick Dwain, additional, Murray, Kimberly, additional, Kostka, Kristin, additional, Northington, Lavance, additional, Pyles, Lee Allan, additional, Misquitta, Leonie, additional, Cottrell, Lesley, additional, Portilla, Lili, additional, Deacy, Mariam, additional, Bissell, Mark M., additional, Clark, Marshall, additional, Emmett, Mary, additional, Saltz, Mary Morrison, additional, Palchuk, Matvey B., additional, Haendel, Melissa A., additional, Adams, Meredith, additional, Temple-O'Connor, Meredith, additional, Kurilla, Michael G., additional, Morris, Michele, additional, Qureshi, Nabeel, additional, Safdar, Nasia, additional, Garbarini, Nicole, additional, Sharafeldin, Noha, additional, Sadan, Ofer, additional, Francis, Patricia A., additional, Burgoon, Penny Wung, additional, Robinson, Peter, additional, Payne, Philip R.O., additional, Fuentes, Rafael, additional, Jawa, Randeep, additional, Erwin-Cohen, Rebecca, additional, Patel, Rena, additional, Moffitt, Richard A., additional, Zhu, Richard L., additional, Kamaleswaran, Rishi, additional, Hurley, Robert, additional, Miller, Robert T., additional, Pyarajan, Saiju, additional, Michael, Sam G., additional, Bozzette, Samuel, additional, Mallipattu, Sandeep, additional, Vedula, Satyanarayana, additional, Chapman, Scott, additional, O'Neil, Shawn T., additional, Setoguchi, Soko, additional, Hong, Stephanie S., additional, Johnson, Steve, additional, Bennett, Tellen D., additional, Callahan, Tiffany, additional, Topaloglu, Umit, additional, Sheikh, Usman, additional, Gordon, Valery, additional, Subbian, Vignesh, additional, Kibbe, Warren A., additional, Hernandez, Wenndy, additional, Beasley, Will, additional, Cooper, Will, additional, Hillegass, William, additional, and Zhang, Xiaohan Tanner, additional

Published
2024
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16. Assessing associations between individual-level social determinants of health and COVID-19 hospitalizations: investigating racial/ethnic disparities among people living with HIV in the U.S. National COVID Cohort Collaborative (N3C)

Author

Vaidya, Dimple, primary, Wilkins, Kenneth J., additional, Hurwitz, Eric, additional, Islam, Jessica Y., additional, Li, Dongmei, additional, Sun, Jing, additional, Safo, Sandra E., additional, Ross, Jennifer M., additional, Hassan, Shukri, additional, Hill, Elaine, additional, Nosyk, Bohdan, additional, Varley, Cara D., additional, Fadul, Nada, additional, Camacho-Rivera, Marlene, additional, Madlock-Brown, Charisse, additional, and Patel, Rena C., additional

Published
2024
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20. The prevalence of postacute sequelae of coronavirus disease 2019 in solid organ transplant recipients: Evaluation of risk in the National COVID Cohort Collaborative

Author

Vinson, Amanda J., Schissel, Makayla, Anzalone, Alfred J., Dai, Ran, French, Evan T., Olex, Amy L., Lee, Stephen B., Ison, Michael, Mannon, Roslyn B., Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred Jerrod, Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O'Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O'Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, and Zhang, Xiaohan Tanner

Abstract

Postacute sequelae after the coronavirus disease (COVID) of 2019 (PASC) is increasingly recognized, although data on solid organ transplant (SOT) recipients (SOTRs) are limited. Using the National COVID Cohort Collaborative, we performed 1:1 propensity score matching (PSM) of all adult SOTR and nonimmunosuppressed/immunocompromised (ISC) patients with acute COVID infection (August 1, 2021 to January 13, 2023) for a subsequent PASC diagnosis using International Classification of Diseases, 10th Revision, Clinical Modification codes. Multivariable logistic regression was used to examine not only the association of SOT status with PASC, but also other patient factors after stratifying by SOT status. Prior to PSM, there were 8769 SOT and 1 576 769 non-ISC patients with acute COVID infection. After PSM, 8756 SOTR and 8756 non-ISC patients were included; 2.2% of SOTR (n = 192) and 1.4% (n = 122) of non-ISC patients developed PASC (Pvalue < .001). In the overall matched cohort, SOT was independently associated with PASC (adjusted odds ratio [aOR], 1.48; 95% confidence interval [CI], 1.09-2.01). Among SOTR, COVID infection severity (aOR, 11.6; 95% CI, 3.93-30.0 for severe vs mild disease), older age (aOR, 1.02; 95% CI, 1.01-1.03 per year), and mycophenolate mofetil use (aOR, 2.04; 95% CI, 1.38-3.05) were each independently associated with PASC. In non-ISC patients, only depression (aOR, 1.96; 95% CI, 1.24-3.07) and COVID infection severity were. In conclusion, PASC occurs more commonly in SOTR than in non-ISC patients, with differences in risk profiles based on SOT status.

Published
2024
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21. Risk for stillbirth among pregnant individuals with SARS-CoV-2 infection varied by gestational age

Author

Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O’Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O’Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Lyu, Tianchu, Liang, Chen, Liu, Jihong, Hung, Peiyin, Zhang, Jiajia, Campbell, Berry, Ghumman, Nadia, Olatosi, Bankole, Hikmet, Neset, Zhang, Manting, Yi, Honggang, and Li, Xiaoming

Published
2023
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23. Nonelective coronary artery bypass graft outcomes are adversely impacted by Coronavirus disease 2019 infection, but not altered processes of care: A National COVID Cohort Collaborative and National Surgery Quality Improvement Program analysis

Author

Grimsley, Emily A., primary, Torikashvili, Johnathan V., additional, Janjua, Haroon M., additional, Read, Meagan D., additional, Kothari, Anai N., additional, Verhagen, Nate B., additional, Pietrobon, Ricardo, additional, Kuo, Paul C., additional, Rogers, Michael P., additional, Wilcox, Adam B., additional, Lee, Adam M., additional, Graves, Alexis, additional, Anzalone, Alfred (Jerrod), additional, Manna, Amin, additional, Saha, Amit, additional, Olex, Amy, additional, Zhou, Andrea, additional, Williams, Andrew E., additional, Southerland, Andrew, additional, Girvin, Andrew T., additional, Walden, Anita, additional, Sharathkumar, Anjali A., additional, Amor, Benjamin, additional, Bates, Benjamin, additional, Hendricks, Brian, additional, Patel, Brijesh, additional, Alexander, Caleb, additional, Bramante, Carolyn, additional, Ward-Caviness, Cavin, additional, Madlock-Brown, Charisse, additional, Suver, Christine, additional, Chute, Christopher, additional, Dillon, Christopher, additional, Wu, Chunlei, additional, Schmitt, Clare, additional, Takemoto, Cliff, additional, Housman, Dan, additional, Gabriel, Davera, additional, Eichmann, David A., additional, Mazzotti, Diego, additional, Brown, Don, additional, Boudreau, Eilis, additional, Hill, Elaine, additional, Zampino, Elizabeth, additional, Marti, Emily Carlson, additional, Pfaff, Emily R., additional, French, Evan, additional, Koraishy, Farrukh M., additional, Mariona, Federico, additional, Prior, Fred, additional, Sokos, George, additional, Martin, Greg, additional, Lehmann, Harold, additional, Spratt, Heidi, additional, Mehta, Hemalkumar, additional, Liu, Hongfang, additional, Sidky, Hythem, additional, Hayanga, J.W. Awori, additional, Pincavitch, Jami, additional, Clark, Jaylyn, additional, Harper, Jeremy Richard, additional, Islam, Jessica, additional, Ge, Jin, additional, Gagnier, Joel, additional, Saltz, Joel H., additional, Saltz, Joel, additional, Loomba, Johanna, additional, Buse, John, additional, Mathew, Jomol, additional, Rutter, Joni L., additional, McMurry, Julie A., additional, Guinney, Justin, additional, Starren, Justin, additional, Crowley, Karen, additional, Bradwell, Katie Rebecca, additional, Walters, Kellie M., additional, Wilkins, Ken, additional, Gersing, Kenneth R., additional, Cato, Kenrick Dwain, additional, Murray, Kimberly, additional, Kostka, Kristin, additional, Northington, Lavance, additional, Pyles, Lee Allan, additional, Misquitta, Leonie, additional, Cottrell, Lesley, additional, Portilla, Lili, additional, Deacy, Mariam, additional, Bissell, Mark M., additional, Clark, Marshall, additional, Emmett, Mary, additional, Saltz, Mary Morrison, additional, Palchuk, Matvey B., additional, Haendel, Melissa A., additional, Adams, Meredith, additional, Temple-O'Connor, Meredith, additional, Kurilla, Michael G., additional, Morris, Michele, additional, Qureshi, Nabeel, additional, Safdar, Nasia, additional, Garbarini, Nicole, additional, Sharafeldin, Noha, additional, Sadan, Ofer, additional, Francis, Patricia A., additional, Burgoon, Penny Wung, additional, Robinson, Peter, additional, Payne, Philip R.O., additional, Fuentes, Rafael, additional, Jawa, Randeep, additional, Erwin-Cohen, Rebecca, additional, Patel, Rena, additional, Moffitt, Richard A., additional, Zhu, Richard L., additional, Kamaleswaran, Rishi, additional, Hurley, Robert, additional, Miller, Robert T., additional, Pyarajan, Saiju, additional, Michael, Sam G., additional, Bozzette, Samuel, additional, Mallipattu, Sandeep, additional, Vedula, Satyanarayana, additional, Chapman, Scott, additional, O'Neil, Shawn T., additional, Setoguchi, Soko, additional, Hong, Stephanie S., additional, Johnson, Steve, additional, Bennett, Tellen D., additional, Callahan, Tiffany, additional, Topaloglu, Umit, additional, Sheikh, Usman, additional, Gordon, Valery, additional, Subbian, Vignesh, additional, Kibbe, Warren A., additional, Hernandez, Wenndy, additional, Beasley, Will, additional, Cooper, Will, additional, Hillegass, William, additional, and Zhang, Xiaohan Tanner, additional

Published
2023
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25. Effect of Nirmatrelvir/Ritonavir (Paxlovid) on Hospitalization among Adults with COVID-19: an EHR-based Target Trial Emulation from N3C

Author

Bhatia, Abhishek, Preiss, Alexander J., Xiao, Xuya, Brannock, M. Daniel, Alexander, G. Caleb, Chew, Robert F., Fitzgerald, Megan, Hill, Elaine, Kelly, Elizabeth P., Mehta, Hemalkumar B., Madlock-Brown, Charisse, Wilkins, Kenneth J., Chute, Christopher G., Haendel, Melissa, Moffitt, Richard, and Pfaff, Emily R.

Subjects
Article
Abstract

This study leverages electronic health record data in the National COVID Cohort Collaborative’s (N3C) repository to investigate disparities in Paxlovid treatment and to emulate a target trial assessing its effectiveness in reducing COVID-19 hospitalization rates. From an eligible population of 632,822 COVID-19 patients seen at 33 clinical sites across the United States between December 23, 2021 and December 31, 2022, patients were matched across observed treatment groups, yielding an analytical sample of 410,642 patients. We estimate a 65% reduced odds of hospitalization among Paxlovid-treated patients within a 28-day follow-up period, and this effect did not vary by patient vaccination status. Notably, we observe disparities in Paxlovid treatment, with lower rates among Black and Hispanic or Latino patients, and within socially vulnerable communities. Ours is the largest study of Paxlovid’s real-world effectiveness to date, and our primary findings are consistent with previous randomized control trials and real-world studies.

Published
2023

26. Hormone Replacement Therapy and COVID-19 Outcomes in Solid Organ Transplant Recipients Compared with the General Population

Author

Vinson, Amanda J., primary, Anzalone, Alfred, additional, Schissel, Makayla, additional, Dai, Ran, additional, French, Evan T., additional, Olex, Amy L., additional, Mannon, Roslyn B., additional, Wilcox, Adam B., additional, Lee, Adam M., additional, Graves, Alexis, additional, Anzalone, Alfred Jerrod, additional, Manna, Amin, additional, Saha, Amit, additional, Olex, Amy, additional, Zhou, Andrea, additional, Williams, Andrew E., additional, Southerland, Andrew, additional, Girvin, Andrew T., additional, Walden, Anita, additional, Sharathkumar, Anjali A., additional, Amor, Benjamin, additional, Bates, Benjamin, additional, Hendricks, Brian, additional, Patel, Brijesh, additional, Alexander, Caleb, additional, Bramante, Carolyn, additional, Ward-Caviness, Cavin, additional, Madlock-Brown, Charisse, additional, Suver, Christine, additional, Chute, Christopher, additional, Dillon, Christopher, additional, Wu, Chunlei, additional, Schmitt, Clare, additional, Takemoto, Cliff, additional, Housman, Dan, additional, Gabriel, Davera, additional, Eichmann, David A., additional, Mazzotti, Diego, additional, Brown, Don, additional, Boudreau, Eilis, additional, Hill, Elaine, additional, Zampino, Elizabeth, additional, Marti, Emily Carlson, additional, Pfaff, Emily R., additional, French, Evan, additional, Koraishy, Farrukh M., additional, Mariona, Federico, additional, Prior, Fred, additional, Sokos, George, additional, Martin, Greg, additional, Lehmann, Harold, additional, Spratt, Heidi, additional, Mehta, Hemalkumar, additional, Liu, Hongfang, additional, Sidky, Hythem, additional, Hayanga, J.W. Awori, additional, Pincavitch, Jami, additional, Clark, Jaylyn, additional, Harper, Jeremy Richard, additional, Islam, Jessica, additional, Ge, Jin, additional, Gagnier, Joel, additional, Saltz, Joel H., additional, Saltz, Joel, additional, Loomba, Johanna, additional, Buse, John, additional, Mathew, Jomol, additional, Rutter, Joni L., additional, McMurry, Julie A., additional, Guinney, Justin, additional, Starren, Justin, additional, Crowley, Karen, additional, Bradwell, Katie Rebecca, additional, Walters, Kellie M., additional, Wilkins, Ken, additional, Gersing, Kenneth R., additional, Cato, Kenrick Dwain, additional, Murray, Kimberly, additional, Kostka, Kristin, additional, Northington, Lavance, additional, Pyles, Lee Allan, additional, Misquitta, Leonie, additional, Cottrell, Lesley, additional, Portilla, Lili, additional, Deacy, Mariam, additional, Bissell, Mark M., additional, Clark, Marshall, additional, Emmett, Mary, additional, Saltz, Mary Morrison, additional, Palchuk, Matvey B., additional, Haendel, Melissa A., additional, Adams, Meredith, additional, Temple-O'Connor, Meredith, additional, Kurilla, Michael G., additional, Morris, Michele, additional, Qureshi, Nabeel, additional, Safdar, Nasia, additional, Garbarini, Nicole, additional, Sharafeldin, Noha, additional, Sadan, Ofer, additional, Francis, Patricia A., additional, Burgoon, Penny Wung, additional, Robinson, Peter, additional, Payne, Philip R.O., additional, Fuentes, Rafael, additional, Jawa, Randeep, additional, Erwin-Cohen, Rebecca, additional, Patel, Rena, additional, Moffitt, Richard A., additional, Zhu, Richard L., additional, Kamaleswaran, Rishi, additional, Hurley, Robert, additional, Miller, Robert T., additional, Pyarajan, Saiju, additional, Michael, Sam G., additional, Bozzette, Samuel, additional, Mallipattu, Sandeep, additional, Vedula, Satyanarayana, additional, Chapman, Scott, additional, O'Neil, Shawn T., additional, Setoguchi, Soko, additional, Hong, Stephanie S., additional, Johnson, Steve, additional, Bennett, Tellen D., additional, Callahan, Tiffany, additional, Topaloglu, Umit, additional, Sheikh, Usman, additional, Gordon, Valery, additional, Subbian, Vignesh, additional, Kibbe, Warren A., additional, Hernandez, Wenndy, additional, Beasley, Will, additional, Cooper, Will, additional, Hillegass, William, additional, and Zhang, Xiaohan Tanner, additional

Published
2023
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27. Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes

Author

Reese, Justin T., primary, Blau, Hannah, additional, Casiraghi, Elena, additional, Bergquist, Timothy, additional, Loomba, Johanna J., additional, Callahan, Tiffany J., additional, Laraway, Bryan, additional, Antonescu, Corneliu, additional, Coleman, Ben, additional, Gargano, Michael, additional, Wilkins, Kenneth J., additional, Cappelletti, Luca, additional, Fontana, Tommaso, additional, Ammar, Nariman, additional, Antony, Blessy, additional, Murali, T.M., additional, Caufield, J. Harry, additional, Karlebach, Guy, additional, McMurry, Julie A., additional, Williams, Andrew, additional, Moffitt, Richard, additional, Banerjee, Jineta, additional, Solomonides, Anthony E., additional, Davis, Hannah, additional, Kostka, Kristin, additional, Valentini, Giorgio, additional, Sahner, David, additional, Chute, Christopher G., additional, Madlock-Brown, Charisse, additional, Haendel, Melissa A., additional, Robinson, Peter N., additional, Spratt, Heidi, additional, Visweswaran, Shyam, additional, Flack, Joseph Eugene, additional, Yoo, Yun Jae, additional, Gabriel, Davera, additional, Alexander, G. Caleb, additional, Mehta, Hemalkumar B., additional, Liu, Feifan, additional, Miller, Robert T., additional, Wong, Rachel, additional, Hill, Elaine L., additional, Thorpe, Lorna E., additional, and Divers, Jasmin, additional

Published
2023
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28. Additional file 1 of Coding long COVID: characterizing a new disease through an ICD-10 lens

Author

Pfaff, Emily R., Madlock-Brown, Charisse, Baratta, John M., Bhatia, Abhishek, Davis, Hannah, Girvin, Andrew, Hill, Elaine, Kelly, Elizabeth, Kostka, Kristin, Loomba, Johanna, McMurry, Julie A., Wong, Rachel, Bennett, Tellen D., Moffitt, Richard, Chute, Christopher G., and Haendel, Melissa

Abstract

Additional file 1: Supplemental methods, supplemental table 1, supplemental figures 1-3. Supplemental Methods – Description of additional methods used, including: Community detection in diagnosis analysis. network stability, age-stratified condition co-occurrence networks, and standard N3C data quality checks. Supplemental Table 1. – Demographic breakdown of all COVID-positive patients across 34 N3C sites. Supplemental Figure 1. – Uptake of U09.9 and B94.8 ICD-10_CM codes across 34 N3C sites. Supplemental Figure 2. – Common medications among patients with a U09.9 code. Supplemental Figure 3. – Common conditions among patients with a U09.9 code

Published
2023
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29. Advancing Interoperability of Patient-level Social Determinants of Health Data to Support COVID-19 Research

Author

Phuong, Jimmy, Hong, Stephanie, Palchuk, Matvey B., Espinoza, Juan, Meeker, Daniella, Dorr, David A., Lozinski, Galina, Madlock-Brown, Charisse, and Adams, William G.

Subjects
Cohort Studies, Social Determinants of Health, COVID-19, Humans, Mass Screening, Articles, Healthcare Disparities
Abstract

Including social determinants of health (SDoH) data in health outcomes research is essential for studying the sources of healthcare disparities and developing strategies to mitigate stressors. In this report, we describe a pragmatic design and approach to explore the encoding needs for transmitting SDoH screening tool responses from a large safety-net hospital into the National Covid Cohort Collaborative (N3C) OMOP dataset. We provide a stepwise account of designing data mapping and ingestion for patient-level SDoH and summarize the results of screening. Our approach demonstrates that sharing of these important data - typically stored as non-standard, EHR vendor specific codes - is feasible. As SDoH screening gains broader use nationally, the approach described in this paper could be used for other screening instruments and improve the interoperability of these important data.

Published
2022

30. The Launch of the iCoDE Standard Project

Author

Xu, Nicole Y., primary, Nguyen, Kevin T., additional, DuBord, Ashley Y., additional, Klonoff, David C., additional, Goldman, Julian M., additional, Shah, Shahid N., additional, Spanakis, Elias K., additional, Madlock-Brown, Charisse, additional, Sarlati, Siavash, additional, Rafiq, Azhar, additional, Wirth, Axel, additional, Kerr, David, additional, Khanna, Raman, additional, Weinstein, Scott, additional, and Espinoza, Juan, additional

Published
2022
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32. Social Determinants of Health Factors for Gene–Environment COVID‐19 Research: Challenges and Opportunities

Author

Phuong, Jimmy, primary, Riches, Naomi O., additional, Madlock‐Brown, Charisse, additional, Duran, Deborah, additional, Calzoni, Luca, additional, Espinoza, Juan C., additional, Datta, Gora, additional, Kavuluru, Ramakanth, additional, Weiskopf, Nicole G., additional, Ward‐Caviness, Cavin K., additional, and Lin, Asiyah Yu, additional

Published
2022
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33. Additional file 1 of Clinical, social, and policy factors in COVID-19 cases and deaths: methodological considerations for feature selection and modeling in county-level analyses

Author

Madlock-Brown, Charisse, Wilkens, Ken, Weiskopf, Nicole, Cesare, Nina, Bhattacharyya, Sharmodeep, Riches, Naomi O., Espinoza, Juan, Dorr, David, Goetz, Kerry, Phuong, Jimmy, Sule, Anupam, Kharrazi, Hadi, Liu, Feifan, Lemon, Cindy, and Adams, William G.

Abstract

Additional file 1: Table 1. Distribution of normalized independent and potential confounding variable values across counties before re-scaling. Table 2. Distribution of outcome variable values across counties per 100,000 residents. In some instances, the minimum case count is zero due to rounding. In some instances, the cumulative case count is 0 and a 14- maximum rolling average is 1. This discrepancy is due to issues related to incorrect new case counts as described in the methods section. Table 3. RUCC classification. Table 4. Univariate Analysis of health status variables for mortality outcomes. Statistically significant results are indicated with an asterisk. Figure 1. Correlation plot of independent variables. All correlations were significant with p-value < 0.05. Figure 2. Diagnostics for cumulative cases models. Figure 3. Diagnostics for cumulative deaths models. Figure 4. Diagnostics for 14-day maximum cases models. Figure 5. Diagnostics for 14-day maximum deaths models. Figure 6. Sensitivity analysis distribution of county-level pandemic start dates. Figure 7. Coefficient estimates for statistically significant variables for cumulative cases. Figure 8. Coefficient estimates for statistically significant variables for cumulative deaths. Figure 9. Coefficient estimates for statistically significant variables for maximum 14-day rolling average cases. Figure 10. Coefficient estimates for statistically significant variables for maximum 14-day rolling average deaths.

Published
2022
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34. Characterizing Long COVID: Deep Phenotype of a Complex Condition

Author

Deer, Rachel R, primary, Rock, Madeline A, additional, Vasilevsky, Nicole, additional, Carmody, Leigh, additional, Rando, Halie, additional, Anzalone, Alfred J, additional, Basson, Marc D, additional, Bennett, Tellen D, additional, Bergquist, Timothy, additional, Boudreau, Eilis A, additional, Bramante, Carolyn T, additional, Byrd, James Brian, additional, Callahan, Tiffany J, additional, Chan, Lauren E, additional, Chu, Haitao, additional, Chute, Christopher G, additional, Coleman, Ben D, additional, Davis, Hannah E, additional, Gagnier, Joel, additional, Greene, Casey S, additional, Hillegass, William B, additional, Kavuluru, Ramakanth, additional, Kimble, Wesley D, additional, Koraishy, Farrukh M, additional, Köhler, Sebastian, additional, Liang, Chen, additional, Liu, Feifan, additional, Liu, Hongfang, additional, Madhira, Vithal, additional, Madlock-Brown, Charisse R, additional, Matentzoglu, Nicolas, additional, Mazzotti, Diego R, additional, McMurry, Julie A, additional, McNair, Douglas S, additional, Moffitt, Richard A, additional, Monteith, Teshamae S, additional, Parker, Ann M, additional, Perry, Mallory A, additional, Pfaff, Emily, additional, Reese, Justin T, additional, Saltz, Joel, additional, Schuff, Robert A, additional, Solomonides, Anthony E, additional, Solway, Julian, additional, Spratt, Heidi, additional, Stein, Gary S, additional, Sule, Anupam A, additional, Topaloglu, Umit, additional, Vavougios, George D., additional, Wang, Liwei, additional, Haendel, Melissa A, additional, and Robinson, Peter N, additional

Published
2021
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37. Increases in multimorbidity with weight class in the United States.

Author

Madlock‐Brown, Charisse R., Reynolds, Rebecca B., and Bailey, James E.

Subjects
*COMORBIDITY, *DISEASE clusters, *CHRONIC kidney failure, *BODY weight, *DATA warehousing
Abstract

Summary: Little is known regarding how multimorbidity combinations associated with obesity change with increase in body weight. This study employed data from the national Cerner HealthFacts Data Warehouse to identify changes in multimorbidity patterns by weight class using network analysis. Networks were generated for 154 528 middle‐aged patients in the following categories: normal weight, overweight, and classes 1, 2, and 3 obesity. The results show significant differences (P‐value<0.05) in prevalence by weight class for all but three of 82 diseases considered. The percentage of patients with multimorbidity (excluding obesity) increases from in 55.1% in patients with normal weight, to 57.88% with overweight, 70.39% with Class 1 obesity, 73.99% with Class 2 obesity, and 71.68% in Class 3 obesity, increasing most substantially with the progression from overweight to class 1 obesity. Most prevalent disease clusters expand from only hypertension and dorsalgia in normal weight, to add joint disorders in overweight, lipidemias in class 1 obesity, diabetes in class 2 obesity, and sleep disorders and chronic kidney disease in class 3 obesity. Recognition of multimorbidity patterns associated with weight increase is essential for true precision care of obesity‐associated chronic conditions and can help clinicians identify and address preclinical disease before additional complications arise. [ABSTRACT FROM AUTHOR]

Published
2021
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39. ASSESSING THE PREVALENCE OF AHIMA-IDENTIFIED HEALTH INFORMATICS AND INFORMATION MANAGEMENT CAREERS AND RELATED SKILLS: A CROSS-SECTIONAL STUDY.

Author

Madlock-Brown, Charisse R., Sharp, Marcia Y., and Reynolds, Rebecca B.

Abstract

This study's objective was to identify the prevalence of the American Health Information Management Association (AHIMA) career map jobs and determine which job categories, degrees, and skills are associated with higher pay. We extracted data from SimplyHired, a major employment website, from December 2018 to December 2019. We retrieved 12,688 career posts. We found differences in average salary by career category (p-value 0.00). Most jobs were in coding and revenue cycle (CRC) and information governance (IG) categories. The highest average salaries were in data analytics (DA) and informatics (IN). Each career category had a unique set of skills associated with the highest paying jobs. Eighty-two percent of CRC, 67 percent of IG, 65 percent of IN, and 83 percent of DA jobs listed in the AHIMA career map were present in the extracted dataset. These results can help employees, academics, and industry leaders understand the health informatics and information management (HIM) workforce landscape. [ABSTRACT FROM AUTHOR]

Published
2021

40. A SURVEY-BASED STUDY OF PHARMACIST ACCEPTANCE AND RESISTANCE TO HEALTH INFORMATION TECHNOLOGY.

Author

Darby, Alaina B., Yin Su, Reynolds, Rebecca B., and Madlock-Brown, Charisse

Abstract

Purpose: Because user acceptance and resistance to the use of health information technology (HIT) affects system utilization and previous studies in this area have typically excluded pharmacists, this study specifically addresses the response of institutional pharmacists to HIT. Methods: A survey investigating pharmacists' responses to electronic medical record (EMR) system use was developed using questions modified from previously validated research. The survey was distributed electronically to the mailing list for pharmacy preceptors for the University of Tennessee College of Pharmacy. Descriptive statistics and univariate and multivariate analyses were used to analyze the collected data based on a previously validated dual-factor model. Results: Of the 96 responses from institutional pharmacists, 64 responses (66.7 percent) were complete and usable. Of the acceptance and resistance constructs evaluated, only attitude and perceived behavior control were found to be significantly associated with acceptance of use (p = .036 and p = .025, respectively), and only transition cost was found to be significantly associated with resistance to use (p = .018). System vendor and interface integration were also significantly associated with acceptance of use. These findings suggest that attitude, perceived behavior control, and transition costs may have the most impact on pharmacists' responses to the use of EMR systems. Conclusion: It is reasonable for hospitals to focus efforts on specific factors influencing acceptance of and resistance to EMR use and, before a system is selected, to consider the effects of vendor selection and level of interface integration on acceptance of use. [ABSTRACT FROM AUTHOR]

Published
2019

44. Firework visualization

Author

Chin, Si-Chi, primary, Madlock-Brown, Charisse, additional, Street, W. Nick, additional, and Eichmann, David, additional

Published
2012
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46. COVID-19 outcomes in persons with hemophilia: results from a US-based national COVID-19 surveillance registry

Author

Sharathkumar, Anjali, Wendt, Linder, Ortman, Chris, Srinivasan, Ragha, Chute, Christopher G., Chrischilles, Elizabeth, Takemoto, Clifford M., Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J. W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O’Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O’Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, and Zhang, Xiaohan Tanner

Abstract

Hypercoagulable state contributing to thrombotic complications worsens COVID-19 severity and outcomes, whereas anticoagulation improves outcomes by alleviating hypercoagulability.

Published
2023
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48. Finding Long-COVID: Temporal Topic Modeling of Electronic Health Records from the N3C and RECOVER Programs.

Author

O'Neil ST, Madlock-Brown C, Wilkins KJ, McGrath BM, Davis HE, Assaf GS, Wei H, Zareie P, French ET, Loomba J, McMurry JA, Zhou A, Chute CG, Moffitt RA, Pfaff ER, Yoo YJ, Leese P, Chew RF, Lieberman M, and Haendel MA

Abstract

Post-Acute Sequelae of SARS-CoV-2 infection (PASC), also known as Long-COVID, encompasses a variety of complex and varied outcomes following COVID-19 infection that are still poorly understood. We clustered over 600 million condition diagnoses from 14 million patients available through the National COVID Cohort Collaborative (N3C), generating hundreds of highly detailed clinical phenotypes. Assessing patient clinical trajectories using these clusters allowed us to identify individual conditions and phenotypes strongly increased after acute infection. We found many conditions increased in COVID-19 patients compared to controls, and using a novel method to associate patients with clusters over time, we additionally found phenotypes specific to patient sex, age, wave of infection, and PASC diagnosis status. While many of these results reflect known PASC symptoms, the resolution provided by this unprecedented data scale suggests avenues for improved diagnostics and mechanistic understanding of this multifaceted disease., Competing Interests: Competing Interests The authors declare no competing interests.

Published
2024
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49. Assessing associations between individual-level social determinants of health and COVID-19 hospitalizations: Investigating racial/ethnic disparities among people living with human immunodeficiency virus (HIV) in the U.S. National COVID Cohort Collaborative (N3C).

Author

Vaidya D, Wilkins KJ, Hurwitz E, Islam JY, Li D, Sun J, Safo SE, Ross JM, Hassan S, Hill E, Nosyk B, Varley CD, Fadul N, Camacho-Rivera M, Madlock-Brown C, and Patel RC

Abstract

Background: Leveraging the National COVID-19 Cohort Collaborative (N3C), a nationally sampled electronic health records repository, we explored associations between individual-level social determinants of health (SDoH) and COVID-19-related hospitalizations among racialized minority people with human immunodeficiency virus (HIV) (PWH), who have been historically adversely affected by SDoH., Methods: We retrospectively studied PWH and people without HIV (PWoH) using N3C data from January 2020 to November 2023. We evaluated SDoH variables across three domains in the Healthy People 2030 framework: (1) healthcare access, (2) economic stability, and (3) social cohesion with our primary outcome, COVID-19-related hospitalization. We conducted hierarchically nested additive and adjusted mixed-effects logistic regression models, stratifying by HIV status and race/ethnicity groups, accounting for age, sex, comorbidities, and data partners., Results: Our analytic sample included 280,441 individuals from 24 data partner sites, where 3,291 (1.17%) were PWH, with racialized minority PWH having higher proportions of adverse SDoH exposures than racialized minority PWoH. COVID-19-related hospitalizations occurred in 11.23% of all individuals (9.17% among PWH, 11.26% among PWoH). In our initial additive modeling, we observed that all three SDoH domains were significantly associated with hospitalizations, even with progressive adjustments (adjusted odds ratios [aOR] range 1.36-1.97). Subsequently, our HIV-stratified analyses indicated economic instability was associated with hospitalization in both PWH and PWoH (aOR range 1.35-1.48). Lastly, our fully adjusted, race/ethnicity-stratified analysis, indicated access to healthcare issues was associated with hospitalization across various racialized groups (aOR range 1.36-2.00)., Conclusion: Our study underscores the importance of assessing individual-level SDoH variables to unravel the complex interplay of these factors for racialized minority groups., Competing Interests: All authors declare no conflicts of interest., (© The Author(s) 2024.)

Published
2024
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50. Increased Incidence of Vestibular Disorders in Patients With SARS-CoV-2.

Author

Lee L, French E, Coelho DH, Manzoor NF, Wilcox AB, Lee AM, Graves A, Anzalone A, Manna A, Saha A, Olex A, Zhou A, Williams AE, Southerland A, Girvin AT, Walden A, Sharathkumar AA, Amor B, Bates B, Hendricks B, Patel B, Alexander C, Bramante C, Ward-Caviness C, Madlock-Brown C, Suver C, Chute C, Dillon C, Wu C, Schmitt C, Takemoto C, Housman D, Gabriel D, Eichmann DA, Mazzotti D, Brown D, Boudreau E, Hill E, Zampino E, Marti EC, Pfaff ER, French E, Koraishy FM, Mariona F, Prior F, Sokos G, Martin G, Lehmann H, Spratt H, Mehta H, Liu H, Sidky H, Awori Hayanga JW, Pincavitch J, Clark J, Harper JR, Islam J, Ge J, Gagnier J, Saltz JH, Saltz J, Loomba J, Buse J, Mathew J, Rutter JL, McMurry JA, Guinney J, Starren J, Crowley K, Bradwell KR, Walters KM, Wilkins K, Gersing KR, Cato KD, Murray K, Kostka K, Northington L, Pyles LA, Misquitta L, Cottrell L, Portilla L, Deacy M, Bissell MM, Clark M, Emmett M, Saltz MM, Palchuk MB, Haendel MA, Adams M, Temple-O'Connor M, Kurilla MG, Morris M, Qureshi N, Safdar N, Garbarini N, Sharafeldin N, Sadan O, Francis PA, Burgoon PW, Robinson P, Payne PRO, Fuentes R, Jawa R, Erwin-Cohen R, Patel R, Moffitt RA, Zhu RL, Kamaleswaran R, Hurley R, Miller RT, Pyarajan S, Michael SG, Bozzette S, Mallipattu S, Vedula S, Chapman S, O'Neil ST, Setoguchi S, Hong SS, Johnson S, Bennett TD, Callahan T, Topaloglu U, Sheikh U, Gordon V, Subbian V, Kibbe WA, Hernandez W, Beasley W, Cooper W, Hillegass W, and Zhang XT

Abstract

Objective: Determine the incidence of vestibular disorders in patients with SARS-CoV-2 compared to the control population., Study Design: Retrospective., Setting: Clinical data in the National COVID Cohort Collaborative database (N3C)., Methods: Deidentified patient data from the National COVID Cohort Collaborative database (N3C) were queried based on variant peak prevalence (untyped, alpha, delta, omicron 21K, and omicron 23A) from covariants.org to retrospectively analyze the incidence of vestibular disorders in patients with SARS-CoV-2 compared to control population, consisting of patients without documented evidence of COVID infection during the same period., Results: Patients testing positive for COVID-19 were significantly more likely to have a vestibular disorder compared to the control population. Compared to control patients, the odds ratio of vestibular disorders was significantly elevated in patients with untyped (odds ratio [OR], 2.39; confidence intervals [CI], 2.29-2.50; P < 0.001), alpha (OR, 3.63; CI, 3.48-3.78; P < 0.001), delta (OR, 3.03; CI, 2.94-3.12; P < 0.001), omicron 21K variant (OR, 2.97; CI, 2.90-3.04; P < 0.001), and omicron 23A variant (OR, 8.80; CI, 8.35-9.27; P < 0.001)., Conclusions: The incidence of vestibular disorders differed between COVID-19 variants and was significantly elevated in COVID-19-positive patients compared to the control population. These findings have implications for patient counseling and further research is needed to discern the long-term effects of these findings., Competing Interests: None declared., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of Otology & Neurotology, Inc.)

Published
2024
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