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14 results on '"Pfaff, Emily"'

1. Effect of Paxlovid Treatment on Long COVID Onset: An EHR-Based Target Trial Emulation from N3C

Author

Preiss, Alexander, primary, Bhatia, Abhishek, additional, Zang, Chengxi, additional, Aragon, Leyna V., additional, Baratta, John M., additional, Baskaran, Monika, additional, Blancero, Frank, additional, Brannock, M. Daniel, additional, Chew, Robert F., additional, Díaz, Iván, additional, Fitzgerald, Megan, additional, Kelly, Elizabeth P., additional, Zhou, Andrea, additional, Weiner, Mark G., additional, Carton, Thomas W., additional, Wang, Fei, additional, Kaushal, Rainu, additional, Chute, Christopher G., additional, Haendel, Melissa, additional, Moffitt, Richard, additional, and Pfaff, Emily, additional

Published
2024
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2. Reengineering a machine learning phenotype to adapt to the changing COVID-19 landscape: A study from the N3C and RECOVER consortia

Author

Crosskey, Miles, primary, McIntee, Tomas, additional, Preiss, Alexander J, additional, Brannock, M Daniel, additional, Yoo, Yun Jae, additional, Hadley, Emily C, additional, Blanceró, Frank, additional, Chew, Rob, additional, Loomba, Johanna, additional, Bhatia, Abhishek, additional, Chute, Christopher G, additional, Haendel, Melissa, additional, Moffitt, Richard, additional, and Pfaff, Emily, additional

Published
2023
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3. 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

5. SARS-CoV-2 Reinfection is Preceded by Unique Biomarkers and Related to Initial Infection Timing and Severity: an N3C RECOVER EHR-Based Cohort Study

Author

Hadley, Emily, Yoo, Yun Jae, Patel, Saaya, Zhou, Andrea, Laraway, Bryan, Wong, Rachel, Preiss, Alexander, Chew, Rob, Davis, Hannah, Chute, Christopher G, Pfaff, Emily R, Loomba, Johanna, Haendel, Melissa, Hill, Elaine, and Moffitt, Richard

Subjects
Article
Abstract

Although the COVID-19 pandemic has persisted for over 2 years, reinfections with SARS-CoV-2 are not well understood. We use the electronic health record (EHR)-based study cohort from the National COVID Cohort Collaborative (N3C) as part of the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection. We validate previous findings of reinfection incidence (5.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present novel findings that Long COVID diagnoses occur closer to the index date for infection or reinfection in the Omicron BA epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between first infection and reinfection (chi-squared value: 9446.2, p-value: 0) with a medium effect size (Cramer’s V: 0.18, DoF = 4).

Published
2023
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8. Who has long-COVID? A big data approach

Author

Pfaff, Emily R., primary, Girvin, Andrew T, additional, Bennett, Tellen D., additional, Bhatia, Abhishek, additional, Brooks, Ian M., additional, Deer, Rachel R, additional, Dekermanjian, Jonathan P, additional, Jolley, Sarah Elizabeth, additional, Kahn, Michael G., additional, Kostka, Kristin, additional, McMurry, Julie A, additional, Moffitt, Richard, additional, Walden, Anita, additional, Chute, Christopher G, additional, and Haendel, Melissa A, additional

Published
2021
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9. Children with SARS-CoV-2 in the National COVID Cohort Collaborative (N3C)

Author

Martin, Blake, primary, DeWitt, Peter E., additional, Russell, Seth, additional, Anand, Adit, additional, Bradwell, Katie R., additional, Bremer, Carolyn, additional, Gabriel, Davera, additional, Girvin, Andrew T., additional, Hajagos, Janos G., additional, McMurry, Julie A., additional, Neumann, Andrew J., additional, Pfaff, Emily R., additional, Walden, Anita, additional, Wooldridge, Jacob T., additional, Yoo, Yun Jae, additional, Saltz, Joel, additional, Gersing, Ken R., additional, Chute, Christopher G., additional, Haendel, Melissa A., additional, Moffitt, Richard, additional, and Bennett, Tellen D., additional

Published
2021
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10. 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, Callahan, Tiffany J, additional, Bramante, Carolyn T, additional, Chute, Christopher G, additional, Greene, Casey S, additional, Gagnier, Joel, additional, Chu, Haitao, additional, Koraishy, Farrukh M, additional, Liang, Chen, additional, Liu, Feifan, additional, Madlock-Brown, Charisse R, additional, Mazzotti, Diego R, additional, McNair, Douglas S, additional, Parker, Ann M, additional, Coleman, Ben D, additional, Davis, Hannah E, additional, Perry, Mallory A, additional, Reese, Justin T, additional, Saltz, Joel, additional, Solomonides, Anthony E, additional, Sule, Anupam A, additional, Stein, Gary S, additional, Köhler, Sebastian, additional, Monteith, Teshamae S, additional, Madhira, Vithal, additional, Kimble, Wesley D, additional, Kavuluru, Ramakanth, additional, Hillegass, William B, additional, Chan, Lauren E, additional, Byrd, James Brian, additional, Boudreau, Eilis A, additional, Liu, Hongfang, additional, McMurry, Julie A, additional, Pfaff, Emily, additional, Matentzoglu, Nicolas, additional, Relevo, Rose, additional, Moffitt, Richard A, additional, Schuff, Robert A, additional, Solway, Julian, additional, Spratt, Heidi, additional, Bergquist, Timothy, additional, Bennett, Tellen D, additional, Basson, Marc D, additional, Topaloglu, Umit, additional, Wang, Liwei, additional, Haendel, Melissa A, additional, and Robinson, Peter N, additional

Published
2021
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11. NSAID use and clinical outcomes in COVID-19 patients: A 38-center retrospective cohort study

Author

Reese, Justin T., primary, Coleman, Ben, additional, Chan, Lauren, additional, Blau, Hannah, additional, Callahan, Tiffany J., additional, Cappelletti, Luca, additional, Fontana, Tommaso, additional, Bradwell, Katie Rebecca, additional, Harris, Nomi L., additional, Casiraghi, Elena, additional, Valentini, Giorgio, additional, Karlebach, Guy, additional, Deer, Rachel, additional, McMurry, Julie A., additional, Haendel, Melissa A., additional, Chute, Christopher G., additional, Pfaff, Emily, additional, Moffitt, Richard, additional, Spratt, Heidi, additional, Singh, Jasvinder, additional, Mungall, Christopher J., additional, Williams, Andrew E., additional, and Robinson, Peter N., additional

Published
2021
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12. Challenges in defining Long COVID: Striking differences across literature, Electronic Health Records, and patient-reported information

Author

Rando, Halie M., primary, Bennett, Tellen D., additional, Byrd, James Brian, additional, Bramante, Carolyn, additional, Callahan, Tiffany J., additional, Chute, Christopher G., additional, Davis, Hannah E., additional, Deer, Rachel, additional, Gagnier, Joel, additional, Koraishy, Farrukh M, additional, Liu, Feifan, additional, McMurry, Julie A., additional, Moffitt, Richard A., additional, Pfaff, Emily R., additional, Reese, Justin T., additional, Relevo, Rose, additional, Robinson, Peter N., additional, Saltz, Joel H., additional, Solomonides, Anthony, additional, Sule, Anupam, additional, Topaloglu, Umit, additional, and Haendel, Melissa A., additional

Published
2021
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13. Semantic Integration of Clinical Laboratory Tests from Electronic Health Records for Deep Phenotyping and Biomarker Discovery: Supplementary materials

Author

Zhang, Xingmin Aaron, Yates, Amy, Vasilevsky, Nicole, Gourdine, JP, Carmody, Leigh C, Danis, Daniel, Joachimiak, Marcin P, Ravanmehr, Vida, Pfaff, Emily R, Champion, James, Robasky, Kimberly, Xu, Hao, Fecho, Karamarie, Walton, Nephi A, Zhu, Richard, Ramsdill, Justin, Mungall, Chris, Kohler, Sebastian, Haendel, Melissa A, McDonald, Clem, Vreeman, Daniel J, Peden, David B, Chute, Christopher G, and Robinson, Peter N

Subjects
fungi
Abstract

Electronic Health Record (EHR) systems typically define laboratory test results using the Laboratory Observation Identifier Names and Codes (LOINC) and can transmit them using Fast Healthcare Interoperability Resource (FHIR) standards. LOINC has not yet been semantically integrated with computational resources for phenotype analysis. Here, we provide a method for mapping LOINC-encoded laboratory test results transmitted in FHIR standards to the Human Phenotype Ontology (HPO) terms. We annotated the medical implications of 2421 commonly used laboratory tests with HPO terms. Using these annotations, a software assesses laboratory test results and converts each into an HPO term. We validated our approach with EHR data from 15,681 patients with respiratory complaints and identified known biomarkers for asthma. Finally, we provide a freely available SMART on FHIR application that can be used within EHR systems. Our approach allows reusing readily available laboratory tests in EHR for deep phenotyping and using the hierarchical structure of HPO for association studies with medical outcomes and genomics.

Published
2019
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14. Semantic Integration of Clinical Laboratory Tests from Electronic Health Records for Deep Phenotyping and Biomarker Discovery

Author

Zhang, Xingmin Aaron, primary, Yates, Amy, additional, Vasilevsky, Nicole, additional, Gourdine, JP, additional, Carmody, Leigh C., additional, Danis, Daniel, additional, Joachimiak, Marcin P., additional, Ravanmehr, Vida, additional, Pfaff, Emily R., additional, Champion, James, additional, Robasky, Kimberly, additional, Xu, Hao, additional, Fecho, Karamarie, additional, Walton, Nephi A., additional, Zhu, Richard, additional, Ramsdill, Justin, additional, Mungall, Chris, additional, Köhler, Sebastian, additional, Haendel, Melissa A., additional, McDonald, Clem, additional, Vreeman, Daniel J., additional, Peden, David B., additional, Chute, Christopher G., additional, and Robinson, Peter N., additional

Published
2019
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