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151. Waning effectiveness of BNT162b2 and ChAdOx1 covid-19 vaccines over six months since second dose: OpenSAFELY cohort study using linked electronic health records

Author

Horne, Elsie M F, primary, Hulme, William J, additional, Keogh, Ruth H, additional, Palmer, Tom M, additional, Williamson, Elizabeth J, additional, Parker, Edward P K, additional, Green, Amelia, additional, Walker, Venexia, additional, Walker, Alex J, additional, Curtis, Helen, additional, Fisher, Louis, additional, MacKenna, Brian, additional, Croker, Richard, additional, Hopcroft, Lisa, additional, Park, Robin Y, additional, Massey, Jon, additional, Morley, Jessica, additional, Mehrkar, Amir, additional, Bacon, Sebastian, additional, Evans, David, additional, Inglesby, Peter, additional, Morton, Caroline E, additional, Hickman, George, additional, Davy, Simon, additional, Ward, Tom, additional, Dillingham, Iain, additional, Goldacre, Ben, additional, Hernán, Miguel A, additional, and Sterne, Jonathan A C, additional

Published
2022
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152. Comparative effectiveness of ChAdOx1 versus BNT162b2 covid-19 vaccines in health and social care workers in England: cohort study using OpenSAFELY

Author

Hulme, William J, primary, Williamson, Elizabeth J, additional, Green, Amelia C A, additional, Bhaskaran, Krishnan, additional, McDonald, Helen I, additional, Rentsch, Christopher T, additional, Schultze, Anna, additional, Tazare, John, additional, Curtis, Helen J, additional, Walker, Alex J, additional, Tomlinson, Laurie A, additional, Palmer, Tom, additional, Horne, Elsie M F, additional, MacKenna, Brian, additional, Morton, Caroline E, additional, Mehrkar, Amir, additional, Morley, Jessica, additional, Fisher, Louis, additional, Bacon, Sebastian C J, additional, Evans, David, additional, Inglesby, Peter, additional, Hickman, George, additional, Davy, Simon, additional, Ward, Tom, additional, Croker, Richard, additional, Eggo, Rosalind M, additional, Wong, Angel Y S, additional, Mathur, Rohini, additional, Wing, Kevin, additional, Forbes, Harriet, additional, Grint, Daniel J, additional, Douglas, Ian J, additional, Evans, Stephen J W, additional, Smeeth, Liam, additional, Bates, Chris, additional, Cockburn, Jonathan, additional, Parry, John, additional, Hester, Frank, additional, Harper, Sam, additional, Sterne, Jonathan A C, additional, Hernán, Miguel A, additional, and Goldacre, Ben, additional

Published
2022
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153. Comparative Safety of BNT162b2 and mRNA-1273 Vaccines in a Nationwide Cohort of US Veterans

Author

Dickerman, Barbra A., primary, Madenci, Arin L., additional, Gerlovin, Hanna, additional, Kurgansky, Katherine E., additional, Wise, Jessica K., additional, Figueroa Muñiz, Michael J., additional, Ferolito, Brian R., additional, Gagnon, David R., additional, Gaziano, J. Michael, additional, Cho, Kelly, additional, Casas, Juan P., additional, and Hernán, Miguel A., additional

Published
2022
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154. Effect of immediate initiation of antiretroviral treatment on the risk of acquired HIV drug resistance

Author

Lodi, Sara, Günthard, Huldrych F., Dunn, David, Garcia, Federico, Logan, Roger, Jose, Sophie, Bucher, Heiner C., Scherrer, Alexandra U., Schneider, Marie-Paule, Egger, Matthias, Glass, Tracy R., Reiss, Peter, van Sighem, Ard, Boender, T. Sonia, Phillips, Andrew N., Porter, Kholoud, Hawkins, David, Moreno, Santiago, Monge, Susana, Paraskevis, Dimitrios, Simeon, Metallidis, Vourli, Georgia, Sabin, Caroline, and Hernán, Miguel A.

Published
2018
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156. Commonly Prescribed Antiretroviral Therapy Regimens and Incidence of AIDS-Defining Neurological Conditions

Author

Caniglia, Ellen C., Phillips, Andrew, Porter, Kholoud, Sabin, Caroline A., Winston, Alan, Logan, Roger, Gill, John, Vandenhende, Marie-Anne, Barger, Diana, Lodi, Sara, Moreno, Santiago, Arribas, José Ramón, Pacheco, Antonio, Cardoso, Sandra W., Chrysos, George, Gogos, Charalabos, Abgrall, Sophie, Costagliola, Dominique, Meyer, Laurence, Seng, Remonie, van Sighem, Ard, Reiss, Peter, Muga, Roberto, Hoyos, Santiago Pérez, Braun, Dominique, Hauser, Christoph, Barrufet, Pilar, Leyes, Maria, Tate, Janet, Justice, Amy, and Hernán, Miguel A.

Published
2018
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162. A population-based controlled experiment assessing the epidemiological impact of digital contact tracing

Author

Rodríguez-García, Jorge Pablo, Graña, Santiago, Álvarez-León, Eva Elisa, Battaglini, Manuela, Darias, Francisco Javier, Hernán, Miguel A., López, Raquel, Llaneza, Paloma, Martín, María Cristina, Radar Covid Pilot Group, Ramirez-Rubio, Oriana, Romaní, Adriana, Suárez-Rodríguez, Berta, Sánchez-Monedero, Javier, Arenas, Alex, Lacasa, Lucas, Ministerio de Asuntos Económicos y Transformación Digital (España), Gobierno de Canarias, Indra, Fundación ONCE, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Generalitat de Catalunya, James S. McDonnell Foundation, Engineering and Physical Sciences Research Council (UK), European Research Council, European Commission, Hernán, Miguel A. [0000-0003-1619-8456], Arenas, Alex [0000-0003-0937-0334], Lacasa, Lucas [0000-0003-3057-0357], Hernán, Miguel A., Arenas, Alex, and Lacasa, Lucas

Subjects
0301 basic medicine, Male, General Physics and Astronomy, Tracing, Turnaround time, law.invention, 0302 clinical medicine, law, Surveys and Questionnaires, Epidemiology, 030212 general & internal medicine, Longitudinal Studies, Controlled experiment, education.field_of_study, Multidisciplinary, Middle Aged, Mobile Applications, 3. Good health, Transmission (mechanics), Geography, Privacy, Female, Smartphone, Adult, medicine.medical_specialty, Adolescent, Science, Population, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Young Adult, Age Distribution, medicine, Humans, education, Pandemics, SARS-CoV-2, COVID-19, General Chemistry, Computer science, body regions, 030104 developmental biology, Spain, Viral infection, Patient Compliance, Observational study, Contact Tracing, Contact tracing, Demography
Abstract

While Digital contact tracing (DCT) has been argued to be a valuable complement to manual tracing in the containment of COVID-19, no empirical evidence of its effectiveness is available to date. Here, we report the results of a 4-week population-based controlled experiment that took place in La Gomera (Canary Islands, Spain) between June and July 2020, where we assessed the epidemiological impact of the Spanish DCT app Radar Covid. After a substantial communication campaign, we estimate that at least 33% of the population adopted the technology and further showed relatively high adherence and compliance as well as a quick turnaround time. The app detects about 6.3 close-contacts per primary simulated infection, a significant percentage being contacts with strangers, although the spontaneous follow-up rate of these notified cases is low. Overall, these results provide experimental evidence of the potential usefulness of DCT during an epidemic outbreak in a real population., This work was funded by the Secretary of State of Digitalisation and Artificial Intelligence, Ministry of Economic Affairs and Digital Transformation, Government of Spain. We thank Government of Spain, Gobierno de Canarias, INDRA, CCN, Fundación ONCE and the EU e-health Network for continuous support. We also thank Elisa Molino, Isabel Zanforlin, Alberto Ricci (Apple) and María Álvarez, Julián Toledo, Marcel Pinto (Google), Jorge García Vidal, Fernando Cucchietti, Josep Martorell and Mateo Valero (BSC). This work was made possible thanks to the incredible collaboration and engagement of the citizens of San Sebastián de la Gomera, Canary Islands (Spain). We also thank the DP3T community for helpful discussions. AA acknowledges financial support from Spanish MINECO (grant PGC2018-094754-B-C21), Generalitat de Catalunya (grant No. 2017SGR-896), and the James S. McDonnell Foundation (grant #220020325). LL acknowledges funding by EPSRC EC Fellowship EP/P01660X/1 and a QMUL COVID-19 Rapid Response Grant. JSM acknowledges funding by a Starting Grant from the European Research Council (grant #759903).

Published
2021

163. Effect of Immediate Initiation of Antiretroviral Treatment in HIV-Positive Individuals Aged 50 Years or Older

Author

Lodi, Sara, Costagliola, Dominique, Sabin, Caroline, del Amo, Julia, Logan, Roger, Abgrall, Sophie, Reiss, Peter, van Sighem, Ard, Jose, Sophie, Blanco, Jose-Ramon, Hernando, Victoria, Bucher, Heiner C., Kovari, Helen, Segura, Ferran, Ambrosioni, Juan, Gogos, Charalambos A., Pantazis, Nikos, Dabis, Francois, Vandenhende, Marie-Anne, Meyer, Laurence, Seng, Rémonie, Gill, M. John, Krentz, Hartmut, Phillips, Andrew N., Porter, Kholoud, Grinsztejn, Beatriz, Pacheco, Antonio G., Muga, Roberto, Tate, Janet, Justice, Amy, and Hernán, Miguel A.

Published
2017
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166. A formal causal interpretation of the case‐crossover design.

Author

Shahn, Zach, Hernán, Miguel A., and Robins, James M.

Subjects
*FIX-point estimation, *TREATMENT effectiveness, *NULL hypothesis, *COUNTERFACTUALS (Logic), *CAUSAL inference
Abstract

The case‐crossover design of Maclure is widely used in epidemiology and other fields to study causal effects of transient treatments on acute outcomes. However, its validity and causal interpretation have only been justified under informal conditions. Here, we place the design in a formal counterfactual framework for the first time. Doing so helps to clarify its assumptions and interpretation. In particular, when the treatment effect is nonnull, we identify a previously unnoticed bias arising from strong common causes of the outcome at different person‐times. We analyze this bias and demonstrate its potential importance with simulations. We also use our derivation of the limit of the case‐crossover estimator to analyze its sensitivity to treatment effect heterogeneity, a violation of one of the informal criteria for validity. The upshot of this work for practitioners is that, while the case‐crossover design can be useful for testing the causal null hypothesis in the presence of baseline confounders, extra caution is warranted when using the case‐crossover design for point estimation of causal effects. [ABSTRACT FROM AUTHOR]

Published
2023
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167. Rejoinder: A formal causal interpretation of the case‐crossover design.

Author

Shahn, Zach, Hernán, Miguel A., and Robins, James M.

Subjects
*COMPUTER simulation
Abstract

We thank the discussants for their insightful commentary and questions. In our rejoinder, we extend our analysis to additional settings, control strategies, and sources of bias relevant to how case‐crossover is often used in practice, as suggested by multiple discussants. In particular, we consider: control exposures that follow occurrence of events, settings with shared exposure trajectories (which are common in case‐crossover studies of effects of air pollution), bias due to non‐transient treatment effects, removing bias due to time trends in treatment using control subjects, and extending our results to the continuous time setting. We also take the opportunity to clarify an easily misinterpreted comment we made about collapsibility, which we thank Andersen and Martinussen for highlighting. Throughout, in the spirit of the discussants. contributions, we iterate between general bias formulas and simulations and numerical studies from illustrative simplified scenarios to build insight. [ABSTRACT FROM AUTHOR]

Published
2023
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169. Benchmarking Observational Analyses Before Using Them to Address Questions Trials Do Not Answer : An Application to Coronary Thrombus Aspiration.

Author

Matthews, Anthony A, Dahabreh, Issa J, Fröbert, Ole, Lindahl, Bertil, James, Stefan, Feychting, Maria, Jernberg, Tomas, Berglund, Anita, Hernán, Miguel A, Matthews, Anthony A, Dahabreh, Issa J, Fröbert, Ole, Lindahl, Bertil, James, Stefan, Feychting, Maria, Jernberg, Tomas, Berglund, Anita, and Hernán, Miguel A

Abstract

To increase confidence in the use of observational analyses when addressing effectiveness questions beyond those addressed by randomized trials, one can first benchmark the observational analyses against existing trial results. We used Swedish registry data to emulate a target trial similar to the Thrombus Aspiration in ST-Elevation Myocardial Infarction in Scandinavia (TASTE) randomized trial, which found no difference in the risk of death or myocardial infarction by 1 year with or without thrombus aspiration among individuals with ST-elevation myocardial infarction. We benchmarked the emulation against the trial at 1 year and then extended the emulation's follow-up to 3 years and estimated effects in subpopulations underrepresented in the trial. As in the TASTE trial, the observational analysis found no differences in risk of outcomes by 1 year between groups (risk difference = 0.7 (confidence interval, -0.7, 2.0) and -0.2 (confidence interval, -1.3, 1.0) for death and myocardial infarction, respectively), so benchmarking was considered successful. We additionally showed no difference in risk of death or myocardial infarction by 3 years, or within subpopulations by 1 year. Benchmarking against an index trial before using observational analyses to answer questions beyond those the trial could address allowed us to explore whether the observational data can be trusted to deliver valid estimates of treatment effects.

Published
2022
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170. Extending treatment effects from a randomized trial using observational data

Author

Matthews, Anthony, Dahabreh, Issa J., Fröbert, Ole, Lindahl, Bertil, James, Stefan, Feychting, Maria, Jernberg, Tomas, Berglund, Anita, Hernán, Miguel A., Matthews, Anthony, Dahabreh, Issa J., Fröbert, Ole, Lindahl, Bertil, James, Stefan, Feychting, Maria, Jernberg, Tomas, Berglund, Anita, and Hernán, Miguel A.

Abstract

Background: To increase confidence in the use of observational data for extending inferences from randomized trials, one can first benchmark. That is, demonstrate the observational analysis can replicate an index trial's findings, before using the observational data to estimate what the trial could not. Objectives: To benchmark an observational study designed to ask the questions to the TASTE trial against results from the TASTE trial itself. Then, if benchmarking is successful, use the observational data to extend the inferences made in the trial. Methods: We use Swedish registry data to emulate a target trial similar to the TASTE randomized trial, which found no difference in the risk of death or myocardial infarction by 1 year with or without thrombus aspiration among individuals with ST-elevation myocardial infarction. We benchmark the emulation against the trial at 1 year, then extend the emulation's follow-up to 3 years and estimate effects in subpopulations underrepresented in the trial. Results: Like TASTE, the observational analysis found no differences in risk of outcomes by 1 year between groups (risk difference 0.7 (0.7, 2.0) and0.2 (1.3, 1.0) for death and myocardial infarction respectively), so benchmarking was considered successful. We additionally show no difference in risk of death or myocardial infarction by 3 years, or within subpopulations by 1 year. Conclusions: Benchmarking before using observational data to extend treatment effects from a randomized trial allows us to understand if the observational data can be trusted to deliver valid estimates of treatment effects.

Published
2022

171. Effectiveness of BNT162b2 booster doses in England: an observational study in OpenSAFELY-TPP

Author

Hulme, William J, primary, Williamson, Elizabeth J, additional, Horne, Elsie, additional, Green, Amelia, additional, Nab, Linda, additional, Keogh, Ruth, additional, Parker, Edward PK, additional, Walker, Venexia, additional, Palmer, Tom, additional, Curtis, Helen, additional, Wiedemann, Milan, additional, Cunningham, Christine, additional, Walker, Alex J, additional, Fisher, Louis, additional, MacKenna, Brian, additional, Rentsch, Christopher T, additional, Schultze, Anna, additional, Bhaskaran, Krishnan, additional, Tazare, John, additional, Tomlinson, Laurie, additional, McDonald, Helen I, additional, Morton, Caroline E, additional, Croker, Richard, additional, Andrews, Colm, additional, Parks, Robin, additional, Hopcroft, Lisa, additional, Massey, Jon, additional, Morley, Jessica, additional, Mehrkar, Amir, additional, Bacon, Seb, additional, Evans, Dave, additional, Inglesby, Peter, additional, Hickman, George, additional, Davy, Simon, additional, Dillingham, Iain, additional, Ward, Tom, additional, Mahalingasivam, Viyasaan, additional, Zheng, Bang, additional, Douglas, Ian J, additional, Evans, Stephen JW, additional, Bates, Chris, additional, Sterne, Jonathan AC, additional, Hernán, Miguel A, additional, and Goldacre, Ben, additional

Published
2022
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178. Outcomes of critically ill solid organ transplant patients with COVID-19 in the United States

Author

Molnar, Miklos Z., Bhalla, Anshul, Azhar, Ambreen, Tsujita, Makoto, Talwar, Manish, Balaraman, Vasanthi, Sodhi, Amik, Kadaria, Dipen, Eason, James D., Hayek, Salim S., Coca, Steven G., Shaefi, Shahzad, Neyra, Javier A., Gupta, Shruti, Leaf, David E., Kovesdy, Csaba P., Walther, Carl P., Anumudu, Samaya J., Arunthamakun, Justin, Kopecky, Kathleen F., Milligan, Gregory P., McCullough, Peter A., Nguyen, Thuy‐Duyen, Krajewski, Megan L., Shankar, Sidharth, Pannu, Ameeka, Valencia, Juan D., Waikar, Sushrut S., Kibbelaar, Zoe A., Athavale, Ambarish M., Hart, Peter, Upadhyay, Shristi, Vohra, Ishaan, Oyintayo, Ajiboye, Green, Adam, Rachoin, Jean‐Sebastien, Schorr, Christa A., Shea, Lisa, Edmonston, Daniel L., Mosher, Christopher L., Shehata, Alexandre M, Cohen, Zaza, Allusson, Valerie, Bambrick‐Santoyo, Gabriela, Bhatti, Noor ul aain, Mehta, Bijal, Williams, Aquino, Brenner, Samantha K., Walters, Patricia, Go, Ronaldo C., Rose, Keith M., Hernán, Miguel A., Lisk, Rebecca, Zhou, Amy M., Kim, Ethan C., Chan, Lili, Mathews, Kusum S., Altman, Deena R., Saha, Aparna, Soh, Howard, Wen, Huei Hsun, Bose, Sonali, Leven, Emily A., Wang, Jing G., Mosoyan, Gohar, Nadkarni, Girish N., Pattharanitima, Pattharawin, Gallagher, Emily J., Friedman, Allon N., Guirguis, John, Kapoor, Rajat, Meshberger, Christopher, Kelly, Katherine J., Parikh, Chirag R., Garibaldi, Brian T., Corona‐Villalobos, Celia P., Wen, Yumeng, Menez, Steven, Malik, Rubab F., Cervantes, Carmen Elena, Gautam, Samir C., Mallappallil, Mary C., Ouyang, Jie, John, Sabu, Yap, Ernie, Melaku, Yohannes, Mohamed, Ibrahim, Bajracharya, Siddhartha, Puri, Isha, Thaxton, Mariah, Bhattacharya, Jyotsna, Wagner, John, Boudourakis, Leon, Nguyen, H. Bryant, Ahoubim, Afshin, Kashani, Kianoush, Tehranian, Shahrzad, Thomas, Leslie F., Sirganagari, Dheeraj Reddy, Guru, Pramod K., Zhou, Yan, Bergl, Paul A., Rodriguez, Jesus, Shah, Jatan A., Gupta, Mrigank S., Kumar, Princy N., Lazarous, Deepa G., Kassaye, Seble G., Melamed, Michal L., Johns, Tanya S., Mocerino, Ryan, Prudhvi, Kalyan, Zhu, Denzel, Levy, Rebecca V., Azzi, Yorg, Fisher, Molly, Yunes, Milagros, Sedaliu, Kaltrina, Golestaneh, Ladan, Brogan, Maureen, Kumar, Neelja, Chang, Michael, Thakkar, Jyotsana, Raichoudhury, Ritesh, Athreya, Akshay, Farag, Mohamed, Schenck, Edward J., Cho, Soo Jung, Plataki, Maria, Alvarez‐Mulett, Sergio L., Gomez‐Escobar, Luis G., Pan, Di, Lee, Stefi, Krishnan, Jamuna, Whalen, William, Charytan, David, Macina, Ashley, Chaudhry, Sobaata, Wu, Benjamin, Modersitzki, Frank, Srivastava, Anand, Leidner, Alexander, Martinez, Carlos, Kruser, Jacqueline M., Wunderink, Richard G., Hodakowski, Alexander J., Velez, Juan Carlos Q., Price‐Haywood, Eboni G., Matute‐Trochez, Luis A., Hasty, Anna E., Mohamed, Muner MB, Avasare, Rupali S., Zonies, David, Leaf, David E, Sise, Meghan E., Newman, Erik T., Omar, Samah Abu, Pokharel, Kapil K., Sharma, Shreyak, Singh, Harkarandeep, Correa, Simon, Shaukat, Tanveer, Kamal, Omer, Wang, Wei, Yang, Heather, Boateng, Jeffery O., Lee, Meghan, Strohbehn, Ian A., Li, Jiahua, Mueller, Ariel L., Redfern, Roberta E., Cairl, Nicholas S., Naimy, Gabriel, Abu‐Saif, Abeer, Hall, Danyell, Bickley, Laura, Rowan, Chris, Madhani‐Lovely, Farah, Peev, Vasil, Reiser, Jochen, Byun, John J., Vissing, Andrew, Kapania, Esha M., Post, Zoe, Patel, Nilam P., Hermes, Joy‐Marie, Sutherland, Anne K., Patrawalla, Amee, Finkel, Diana G., Danek, Barbara A., Arikapudi, Sowminya, Paer, Jeffrey M., Cangialosi, Peter, Liotta, Mark, Radbel, Jared, Puri, Sonika, Sunderram, Jag, Scharf, Matthew T., Ahmed, Ayesha, Berim, Ilya, Vatson, Jayanth S., Anand, Shuchi, Levitt, Joseph E., Garcia, Pablo, Boyle, Suzanne M., Song, Rui, Arif, Ali, Zhang, Jingjing, Woo, Sang Hoon, Deng, Xiaoying, Katz‐Greenberg, Goni, Senter, Katharine, Sharshir, Moh’d A., Rusnak, Vadym V, Ali, Muhammad Imran, Peters, Terri, Hughes, Kathy, Bansal, Anip, Podoll, Amber S., Chonchol, Michel, Sharma, Sunita, Burnham, Ellen L., Douin, David J., Rashidi, Arash, Hejal, Rana, Judd, Eric, Latta, Laura, Tolwani, Ashita, Albertson, Timothy E., Adams, Jason Y., Chang, Steven Y., Beutler, Rebecca M., Schulze, Carl E., Macedo, Etienne, Rhee, Harin, Liu, Kathleen D., Jotwani, Vasantha K., Koyner, Jay L., Shah, Chintan V., Jaikaransingh, Vishal, Toth‐Manikowski, Stephanie M., Joo, Min J., Lash, James P., Chaaban, Nourhan, Elias, Madona, Ahmad, Yahya, Iardino, Alfredo, Au, Elizabeth H., Sharma, Jill H., Sosa, Marie Anne, Taldone, Sabrina, Contreras, Gabriel, Zerda, David De La, Fornoni, Alessia, Gershengorn, Hayley B., Blakely, Pennelope, Berlin, Hanna, Azam, Tariq U., Shadid, Husam, Pan, Michael, Hayer, Patrick O’, Meloche, Chelsea, Feroze, Rafey, Kishan J. Padalia, Bitar, Abbas, Leya, Jeff, Donnelly, John P., Admon, Andrew J., Flythe, Jennifer E., Tugman, Matthew J., Chang, Emily H., Brown, Brent R., Leonberg‐Yoo, Amanda K., Spiardi, Ryan C., Miano, Todd A., Roche, Meaghan S., Vasquez, Charles R., Bansal, Amar D., Ernecoff, Natalie C., Kapoor, Sanjana, Verma, Siddharth, Chen, Huiwen, Hedayati, S. Susan, Nadamuni, Mridula V., Shastri, Shani, Willett, Duwayne L., Short, Samuel A.P., Renaghan, Amanda D., Enfield, Kyle B., Bhatraju, Pavan K., Malik, A. Bilal, Semler, Matthew W., Vijayan, Anitha, Joy, Christina Mariyam, Li, Tingting, Goldberg, Seth, Kao, Patricia F., Schumaker, Greg L., Goyal, Nitender, Faugno, Anthony J., Hsu, Caroline M., Tariq, Asma, Meyer, Leah, Kshirsagar, Ravi K., Jose, Aju, Weiner, Daniel E., Christov, Marta, Griffiths, Jennifer, Gupta, Sanjeev, Kapoor, Aromma, Wilson, Perry, Arora, Tanima, and Ugwuowo, Ugochukwu

Subjects
Male, medicine.medical_specialty, Critical Illness, medicine.medical_treatment, Comorbidity, 030230 surgery, Organ transplantation, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Internal medicine, Intensive care, medicine, Humans, Immunology and Allergy, Pharmacology (medical), Hospital Mortality, Renal replacement therapy, Pandemics, Survival rate, Aged, Transplantation, SARS-CoV-2, business.industry, Acute kidney injury, COVID-19, Original Articles, Organ Transplantation, Middle Aged, medicine.disease, United States, Hospitalization, Survival Rate, Intensive Care Units, Relative risk, Propensity score matching, Original Article, Female, business, Follow-Up Studies, Cohort study
Abstract

National data on patient characteristics, treatment, and outcomes of critically ill coronavirus disease 2019 (COVID-19) solid organ transplant (SOT) patients are limited. We analyzed data from a multicenter cohort study of adults with laboratory-confirmed COVID-19 admitted to intensive care units (ICUs) at 68 hospitals across the United States from March 4 to May 8, 2020. From 4153 patients, we created a propensity score matched cohort of 386 patients, including 98 SOT patients and 288 non-SOT patients. We used a binomial generalized linear model (log-binomial model) to examine the association of SOT status with death and other clinical outcomes. Among the 386 patients, the median age was 60 years, 72% were male, and 41% were black. Death within 28 days of ICU admission was similar in SOT and non-SOT patients (40% and 43%, respectively; relative risk [RR] 0.92; 95% confidence interval [CI]: 0.70-1.22). Other outcomes and requirement for organ support including receipt of mechanical ventilation, development of acute respiratory distress syndrome, and receipt of vasopressors were also similar between groups. There was a trend toward higher risk of acute kidney injury requiring renal replacement therapy in SOT vs. non-SOT patients (37% vs. 27%; RR [95% CI]: 1.34 [0.97-1.85]). Death and organ support requirement were similar between SOT and non-SOT critically ill patients with COVID-19.

Published
2020

183. Emulating a Target Trial of Interventions Initiated During Pregnancy with Healthcare Databases: The Example of COVID-19 Vaccination.

Author

Hernández-Díaz, Sonia, Huybrechts, Krista F., Chiu, Yu-Han, Yland, Jennifer J., Bateman, Brian T., and Hernán, Miguel A.

Abstract

Background: Observational studies are often the only option to estimate effects of interventions during pregnancy. Causal inference from observational data can be conceptualized as an attempt to emulate a hypothetical pragmatic randomized trial: the target trial. Objective: To provide a step-by-step description of how to use healthcare databases to estimate the effects of interventions initiated during pregnancy. As an example, we describe how to specify and emulate a target trial of COVID-19 vaccination during pregnancy, but the framework can be generally applied to point and sustained strategies involving both pharmacologic and non-pharmacologic interventions. Methods: First, we specify the protocol of a target trial to evaluate the safety and effectiveness of vaccination during pregnancy. Second, we describe how to use observational data to emulate each component of the protocol of the target trial. We propose different target trials for different gestational periods because the outcomes of interest vary by gestational age at exposure. We identify challenges that affect (i) the target trial and thus its observational emulation (censoring and competing events), and (ii) mostly the observational emulation (confounding, immortal time, and measurement biases). Conclusion: Some biases may be unavoidable in observational emulations, but others are avoidable. For instance, immortal time bias can be avoided by aligning the start of follow-up with the gestational age at the time of the intervention, as we would do in the target trial. Explicitly emulating target trials at different gestational ages can help reduce bias and improve the interpretability of effect estimates for interventions during pregnancy. [ABSTRACT FROM AUTHOR]

Published
2023
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184. Effectiveness of a Second Dose of an mRNA Vaccine Against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Omicron Infection in Individuals Previously Infected by Other Variants.

Author

Monge, Susana, Rojas-Benedicto, Ayelén, Olmedo, Carmen, Martín-Merino, Elisa, Mazagatos, Clara, Limia, Aurora, Sierra, María José, Larrauri, Amparo, Hernán, Miguel A, and IBERCovid

Subjects
DRUG efficacy, COVID-19, IMMUNIZATION, CONFIDENCE intervals, COVID-19 vaccines, REINFECTION, TREATMENT effectiveness, MESSENGER RNA, INDEPENDENT living, KAPLAN-Meier estimator, EVALUATION
Abstract

Background Single-dose vaccination was widely recommended in the pre-Omicron era for persons with previous SARS-CoV-2 infection. The effectiveness of a second vaccine dose in this group in the Omicron era is unknown. Methods We linked nationwide population registries in Spain to identify community-dwelling individuals aged 18–64, with a positive SARS-CoV-2 test before single-dose mRNA vaccination (mRNA-1273 or BNT162b2). Every day between 3 January and 6 February 2022 we matched 1:1 individuals receiving a second mRNA vaccine dose and controls on sex, age, province, first dose type and time, month of primary infection, and number of previous tests. We then estimated Kaplan–Meier risks of confirmed SARS-CoV-2 reinfection. We performed a similar analysis in a Delta-dominant period, between 19 July and 30 November 2021. Results In the Omicron period, estimated effectiveness (95% CI) of a second dose was 62.2% (58.2–66.4%) 7–34 days after administration, similar across groups defined by age, sex, type of first vaccine, and time since the first dose. Estimated effectiveness was 65.4% (61.1–69.9%) for mRNA-1273 and 52.0% (41.8–63.1%) for BNT162b2. Estimated effectiveness was 78.5% (67.4–89.9%), 66.1% (54.9–77.5%), and 60.2% (55.5–64.8%) when primary infection had occurred in the Delta, Alpha, and pre-Alpha periods, respectively. In the Delta period, the estimated effectiveness of a second dose was 8.8% (−55.3% to 81.1%). Conclusions Our results suggest that, over 1 month after administration, a second dose of mRNA vaccine increases protection against SARS-CoV-2 reinfection with the Omicron variant among individuals with single-dose vaccination and previously infected with another variant. [ABSTRACT FROM AUTHOR]

Published
2023
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188. Near real-time surveillance of the SARS-CoV-2 epidemic with incomplete data

Author

De Salazar, Pablo M., primary, Lu, Fred, additional, Hay, James A, additional, Gómez-Barroso, Diana, additional, Fernández-Navarro, Pablo, additional, Martínez, Elena V, additional, Astray-Mochales, Jenaro, additional, Amillategui, Rocío, additional, García-Fulgueiras, Ana, additional, Chirlaque, Maria D, additional, Sánchez-Migallón, Alonso, additional, Larrauri, Amparo, additional, Sierra, María J, additional, Lipsitch, Marc, additional, Simón, Fernando, additional, Santillana, Mauricio, additional, and Hernán, Miguel A, additional

Published
2022
Full Text
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191. Comparative Effectiveness of BNT162b2 and mRNA-1273 Vaccines in U.S. Veterans

Author

Dickerman, Barbra A., primary, Gerlovin, Hanna, additional, Madenci, Arin L., additional, Kurgansky, Katherine E., additional, Ferolito, Brian R., additional, Figueroa Muñiz, Michael J., additional, Gagnon, David R., additional, Gaziano, J. Michael, additional, Cho, Kelly, additional, Casas, Juan P., additional, and Hernán, Miguel A., additional

Published
2022
Full Text
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