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2. Impact of SARS-CoV-2 Infection on Long-Term Depression Symptoms among Veterans

Author

Chen, Jason I., Bui, David, Iwashyna, Theodore J., Shahoumian, Troy A., Hickok, Alex, Shepherd-Banigan, Megan, Hawkins, Eric J., Naylor, Jennifer, Govier, Diana J., Osborne, Thomas F., Smith, Valerie A., Bowling, C. Barrett, Boyko, Edward J., Ioannou, George N., Maciejewski, Matthew L., O’Hare, Ann M., Viglianti, Elizabeth M., Bohnert, Amy S.-B., and Hynes, Denise M.

Published
2024
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3. Risk of Suicide-Related Outcomes After SARS-COV-2 Infection: Results from a Nationwide Observational Matched Cohort of US Veterans

Author

Hynes, Denise M., Niederhausen, Meike, Chen, Jason I., Shahoumian, Troy A., Rowneki, Mazhgan, Hickok, Alex, Shepherd-Banigan, Megan, Hawkins, Eric J., Naylor, Jennifer, Teo, Alan, Govier, Diana J., Berry, Kristin, McCready, Holly, Osborne, Thomas F., Wong, Edwin, Hebert, Paul L., Smith, Valerie A., Bowling, C. Barrett, Boyko, Edward J., Ioannou, George N., Iwashyna, Theodore J., Maciejewski, Matthew L., O’Hare, Ann M., Viglianti, Elizabeth M., and Bohnert, Amy S.-B.

Published
2024
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5. In-person peer support for critical care survivors: The ICU REcovery Solutions cO-Led through surVivor Engagement (ICURESOLVE) pilot randomised controlled trial

Author

Haines, Kimberley J., Hibbert, Elizabeth, Skinner, Elizabeth H., Leggett, Nina, Holdsworth, Clare, Ali Abdelhamid, Yasmine, Bates, Samantha, Bicknell, Erin, Booth, Sarah, Carmody, Jacki, Deane, Adam M., Emery, Kate, Farley, K.J., French, Craig, Krol, Lauren, MacLeod-Smith, Belinda, Maher, Lynne, Paykel, Melanie, and Iwashyna, Theodore J.

Published
2024
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11. Design and analysis of outcomes following SARS-CoV-2 infection in veterans

Author

Smith, Valerie A., Berkowitz, Theodore S. Z., Hebert, Paul, Wong, Edwin S., Niederhausen, Meike, Pura, John A., Berry, Kristin, Green, Pamela, Korpak, Anna, Fox, Alexandra, Baraff, Aaron, Hickok, Alex, Shahoumian, Troy A, Bohnert, Amy S.B., Hynes, Denise M., Boyko, Edward J., Ioannou, George N., Iwashyna, Theodore J., Bowling, C. Barrett, O’Hare, Ann M., and Maciejewski, Matthew L.

Published
2023
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16. The impact of distance on post-ICU disability

Author

D'Arcy, Jack, Haines, Kimberley, Paul, Eldho, Doherty, Zakary, Goodwin, Andrew, Bailey, Michael, Barrett, Jonathan, Bellomo, Rinaldo, Bucknall, Tracey, Gabbe, Belinda J., Higgins, Alisa M., Iwashyna, Theodore J., Murray, Lynne J., Myles, Paul S., Ponsford, Jennie, Pilcher, David, Udy, Andrew A., Walker, Craig, Young, Meredith, Cooper, D.J. (Jamie), and Hodgson, Carol L.

Published
2022
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25. Effect of Early High-Dose Vitamin D3 Repletion on Cognitive Outcomes in Critically Ill Adults

Author

Han, Jin H., Ginde, Adit A., Brown, Samuel M., Baughman, Adrienne, Collar, Erin M., Ely, E. Wesley, Gong, Michelle N., Hope, Aluko A., Hou, Peter C., Hough, Catherine L., Iwashyna, Theodore J., Jackson, James C., Khan, Akram, Orun, Onur M., Patel, Mayur B., Raman, Rameela, Rice, Todd W., Ringwood, Nancy, Semler, Matthew W., Shapiro, Nathan I., Talmor, Daniel S., and Self, Wesley H.

Published
2021
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26. Recall of clinical trial participation and attrition rates in survivors of acute respiratory distress syndrome

Author

Carlton, Erin F., Ice, Erin, Barbaro, Ryan P., Kampuis, Lee, Moss, Marc, Angus, Derek C., Banner-Goodspeed, Valerie M., Ginde, Adit A., Gong, Michelle N., Grissom, Colin K., Hou, Peter C., Huang, David T., Hough, Catherine Terri Lee, Talmor, Daniel S., Thompson, B. Taylor, Yealy, Donald M., Couper, Mick P., and Iwashyna, Theodore J.

Published
2021
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28. Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation

Author

Sjoding, Michael W, Taylor, Daniel, Motyka, Jonathan, Lee, Elizabeth, Co, Ivan, Claar, Dru, McSparron, Jakob I, Ansari, Sardar, Kerlin, Meeta Prasad, Reilly, John P, Shashaty, Michael G S, Anderson, Brian J, Jones, Tiffanie K, Drebin, Harrison M, Ittner, Caroline A G, Meyer, Nuala J, Iwashyna, Theodore J, Ward, Kevin R, and Gillies, Christopher E

Published
2021
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30. Extended versus Standard Proning Duration for COVID-19–associated Acute Respiratory Distress Syndrome: A Target Trial Emulation Study.

Author

Hochberg, Chad H., Colantuoni, Elizabeth, Sahetya, Sarina K., Eakin, Michelle N., Fan, Eddy, Psoter, Kevin J., Iwashyna, Theodore J., Needham, Dale M., and Hager, David N.

Subjects
ADULT respiratory distress syndrome, PATIENT positioning, INTENSIVE care units, ELECTRONIC health records, MEDICAL registries
Abstract

Rationale: Prone positioning for ⩾16 hours in moderate-to-severe acute respiratory distress syndrome (ARDS) improves survival. However, the optimal duration of proning is unknown. Objectives: To estimate the effect of extended versus standard proning duration on patients with moderate-to-severe coronavirus disease (COVID-19) ARDS. Methods: Data were extracted from a five-hospital electronic medical record registry. Patients who were proned within 72 hours of mechanical ventilation were categorized as receiving extended (⩾24 h) versus standard (16–24 h) proning based on the first proning session length. We used a target trial emulation design to estimate the effect of extended versus standard proning on the primary outcome of 90-day mortality and secondary outcomes of ventilator liberation and intensive care unit (ICU) discharge. Analytically, we used inverse probability of treatment weighted (IPTW) Cox or Fine-Gray regression models. Results: A total of 314 patients were included; 234 received extended proning, and 80 received standard-duration proning. Patients who received extended proning were older, had greater comorbidity, were more often at an academic hospital, and had shorter time from admission to mechanical ventilation. After IPTW, characteristics were well balanced. Unadjusted 90-day mortality in the extended versus standard proning groups was 39% versus 58%. In doubly robust IPTW analyses, we found no significant effects of extended versus standard proning duration on mortality (hazard ratio [95% confidence interval], 0.95 [0.51–1.77]), ventilator liberation (subdistribution hazard, 1.60 [0.97–2.64], or ICU discharge (subdistribution hazard, 1.31 [0.82–2.10]). Conclusions: Using target trial emulation, we found no significant effect of extended versus standard proning duration on mortality, ventilator liberation, or ICU discharge. However, given the imprecision of estimates, further study is justified. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Impact of High-Dose Early Mobilization on Outcomes for Patients with Diabetes: A Secondary Analysis of the TEAM Trial.

Author

Serpa Neto, Ary, Bailey, Michael, Seller, Daniel, Agli, Alicia, Bellomo, Rinaldo, Brickell, Kathy, Broadley, Tessa, Buhr, Heidi, Gabbe, Belinda J., Gould, Doug W., Harrold, Meg, Higgins, Alisa M., Hurford, Sally, Iwashyna, Theodore J., Nichol, Alistair D., Presneill, Jeffrey J., Schaller, Stefan J., Sivasuthan, Janani, Tipping, Claire J., and Poole, Alex

Subjects
PEOPLE with diabetes, ODDS ratio, ARTIFICIAL respiration, LOGISTIC regression analysis, SECONDARY analysis
Abstract

Rationale: Patients with diabetes represent almost 20% of all ICU admissions and might respond differently to high-dose early active mobilization. Objectives: To assess whether diabetes modified the relationship between the dose of early mobilization on clinical outcomes in the TEAM trial. Methods: All TEAM trial patients were included. The primary outcome was days alive and out of the hospital at Day 180. Secondary outcomes included 180-day mortality and long-term functional outcomes at Day 180. Logistic and median regression models were used to explore the effect of high-dose early mobilization on outcomes by diabetes status. Measurements and Main Results: All 741 patients from the original trial were included. Of these, 159 patients (21.4%) had diabetes. Patients with diabetes had fewer days alive and out of the hospital at Day 180 (124 [0–153] vs. 147 [82–164]; P = 0.013) and higher 180-day mortality (30% vs. 18%; P = 0.044). In patients receiving high-dose early mobilization, the number of days alive and out of the hospital at Day 180 was 73.0 (0.0–144.5) in patients with diabetes and 146.5 (95.8–163.0) in patients without diabetes (P value for interaction = 0.108). However, in patients with diabetes, high-dose early mobilization increased the odds of mortality at 180 days (adjusted odds ratio, 3.47; 95% confidence interval, 1.67–7.61; P value for interaction = 0.001). Conclusions: In this secondary analysis of the TEAM trial, in patients with diabetes, a high-dose early mobilization strategy did not significantly decrease the number of days alive and out of the hospital at Day 180, but it increased 180-day mortality. [ABSTRACT FROM AUTHOR]

Published
2024
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35. Extracorporeal membrane oxygenation support in COVID-19: an international cohort study of the Extracorporeal Life Support Organization registry

Author

Alexander, Peta, Barrett, Nicholas, Bělohlávek, Jan, Fisher, Dale, Fraser, John, Hssain, Ali Ait, Jung, Jae Sung, McMullan, Michael, Mehta, Yatin, Ogino, Mark T., Paden, Matthew L., Shekar, Kiran, Stead, Christine, Abu-Omar, Yasir, Agnoletti, Vanni, Akbar, Anzila, Alfoudri, Huda, Alviar, Carlos, Aronsky, Vladimir, August, Erin, Auzinger, Georg, Aveja, Hilda, Bakken, Rhonda, Balcells, Joan, Bangalore, Sripal, Barnes, Bernard W., Bautista, Alaiza, Bellows, Lorraine L., Beltran, Felipe, Benharash, Peyman, Benni, Marco, Berg, Jennifer, Bertini, Pietro, Blanco-Schweizer, Pablo, Brunsvold, Melissa, Budd, Jenny, Camp, Debra, Caridi-Scheible, Mark, Carton, Edmund, Casanova-Ghosh, Elena, Castleberry, Anthony, Chipongian, Christopher T., Choi, Chang Woo, Circelli, Alessandro, Cohen, Elliott, Collins, Michael, Copus, Scott, Coy, Jill, Crist, Brandon, Cruz, Leonora, Czuczwar, Mirosław, Daneshmand, Mani, Davis II, Daniel, De la Cruz, Kim, Devers, Cyndie, Duculan, Toni, Durham, Lucian, Elapavaluru, Subbarao, Elzo Kraemer, Carlos V., Filho, EDMÍLSON CARDOSO, Fitzgerald, Jillian, Foti, Giuseppe, Fox, Matthew, Fritschen, David, Fullerton, David, Gelandt, Elton, Gerle, Stacy, Giani, Marco, Goh, Si Guim, Govener, Sara, Grone, Julie, Guber, Miles, Gudzenko, Vadim, Gutteridge, Daniel, Guy, Jennifer, Haft, Jonathan, Hall, Cameron, Hassan, Ibrahim Fawzy, Herrán, Rubén, Hirose, Hitoshi, Ibrahim, Abdulsalam Saif, Igielski, Don, Ivascu, Felicia A., Izquierdo Blasco, Jaume, Jackson, Julie, Jain, Harsh, Jaiswal, Bhavini, Johnson, Andrea C., Jurynec, Jenniver A., Kellter, Norma M, Kohl, Adam, Kon, Zachary, Kredel, Markus, Kriska, Karen, Kunavarapu, Chandra, Lansink-Hartgring, Oude, LaRocque, Jeliene, Larson, Sharon Beth, Layne, Tracie, Ledot, Stephane, Lena, Napolitan, Lillie, Jonathan, Lotz, Gösta, Lucas, Mark, Ludwigson, Lee, Maas, Jacinta J., Maertens, Joanna, Mast, David, McCardle, Scott, McDonald, Bernard, McLarty, Allison, McMahon, Chelsea, Meybohm, Patrick, Meyns, Bart, Miller, Casey, Moraes Neto, Fernando, Morris, Kelly, Muellenbach, Ralf, Nicholson, Meghan, O'Brien, Serena, O'Keefe, Kathryn, Ogston, Tawnya, Oldenburg, Gary, Oliveira, Fabiana M., Oppel, Emily, Pardo, Diego, Parker, Sara J., Pedersen, Finn M., Pellecchia, Crescens, Pelligrini, Jose A.S., Pham, Thao T.N., Phillips, Ann R., Pirani, Tasneem, Piwowarczyk, Paweł, Plambeck, Robert, Pruett, William, Quandt, Brittany, Ramanathan, Kollengode, Rey, Alejandro, Reyher, Christian, Riera del Brio, Jordi, Roberts, Rachel, Roe, David, Roeleveld, Peter P., Rudy, Janet, Rueda, Luis F., Russo, Emanuele, Sánchez Ballesteros, Jesús, Satou, Nancy, Saueressig, Mauricio Guidi, Saunders, Paul C., Schlotterbeck, Margaret, Schwarz, Patricia, Scriven, Nicole, Serra, Alexis, Shamsah, Mohammad, Sim, Lucy, Smart, Alexandra, Smith, Adam, Smith, Deane, Smith, Maggie, Sodha, Neel, Sonntagbauer, Michael, Sorenson, Marc, Stallkamp, Eric B, Stewart, Allison, Swartz, Kathy, Takeda, Koji, Thompson, Shaun, Toy, Bridget, Tuazon, Divina, Uchiyama, Makoto, Udeozo, Obiora I., van Poppel, Scott, Ventetuolo, Corey, Vercaemst, Leen, Vinh Chau, Nguyen V., Wang, I-Wen, Williamson, Carrie, Wilson, Brock, Winkels, Helen, Barbaro, Ryan P, MacLaren, Graeme, Boonstra, Philip S, Iwashyna, Theodore J, Slutsky, Arthur S, Fan, Eddy, Bartlett, Robert H, Tonna, Joseph E, Hyslop, Robert, Fanning, Jeffrey J, Rycus, Peter T, Hyer, Steve J, Anders, Marc M, Agerstrand, Cara L, Hryniewicz, Katarzyna, Diaz, Rodrigo, Lorusso, Roberto, Combes, Alain, and Brodie, Daniel

Published
2020
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42. Hospital-level variation in the development of persistent critical illness

Author

Viglianti, Elizabeth M., Bagshaw, Sean M., Bellomo, Rinaldo, McPeake, Joanne, Wang, Xiao Qing, Seelye, Sarah, and Iwashyna, Theodore J.

Subjects
United States. Department of Veterans Affairs -- Analysis, Medical research -- Analysis -- Health aspects, Medicine, Experimental -- Analysis -- Health aspects, Hospitals -- United Kingdom -- Australia, Mortality -- United Kingdom -- Australia, Health care industry
Abstract

Purpose Patients with persistent critical illness may account for up to half of all intensive care unit (ICU) bed-days. It is unknown if there is hospital variation in the development of persistent critical illness and if hospital performance affects the incidence of persistent critical illness. Methods This is a retrospective analysis of Veterans admitted to the Veterans Administration (VA) ICUs from 2015 to 2017. Hospital performance was defined by the risk- and reliability-adjusted 30-day mortality. Persistent critical illness was defined as an ICU length of stay of at least 11 days. We used 2-level multilevel logistic regression models to assess variation in risk- and reliability-adjusted probabilities in the development of persistent critical illness. Results In the analysis of 100 hospitals which encompassed 153,512 hospitalizations, 4.9% (N = 7640/153,512) developed persistent critical illness. There was variation in the development of persistent critical illness despite controlling for patient characteristics (intraclass correlation: 0.067, 95% CI 0.049-0.091). Hospitals with higher risk- and reliability-adjusted 30-day mortality had higher probabilities of developing persistent critical illness (predicted probability: 0.057, 95% CI 0.051-0.063, p < 0.01) compared to those with lower risk- and reliability-adjusted 30-day mortality (predicted probability: 0.046, 95% CI 0.041-0.051, p < 0.01). The median odds ratio was 1.4 (95% CI 1.33-1.49) implying that, for two patients with the same physiology on admission at two different VA hospitals, the patient admitted to the hospital with higher adjusted mortality would have 40% greater odds of developing persistent critical illness. Conclusion Hospitals with higher risk- and reliability-adjusted 30-day mortality have a higher probability of developing persistent critical illness. Understanding the drivers of this variation may identify modifiable factors contributing to the development of persistent critical illness., Author(s): Elizabeth M. Viglianti [sup.1], Sean M. Bagshaw [sup.2], Rinaldo Bellomo [sup.3] [sup.4], Joanne McPeake [sup.5] [sup.6], Xiao Qing Wang [sup.1], Sarah Seelye [sup.7], Theodore J. Iwashyna [sup.1] [sup.7] [sup.8] [...]

Published
2020
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49. Tackling Brain and Muscle Dysfunction in Acute Respiratory Distress Syndrome Survivors: NHLBI Workshop Report.

Author

Palakshappa, Jessica A., Batt, Jane A. E., Bodine, Sue C., Connolly, Bronwen A., Doles, Jason, Falvey, Jason R., Ferrante, Lauren E., Files, D. Clark, Harhay, Michael O., Harrell, Kirsten, Hippensteel, Joseph A., Iwashyna, Theodore J., Jackson, James C., Lane-Fall, Meghan B., Monje, Michelle, Moss, Marc, Needham, Dale M., Semler, Matthew W., Lahiri, Shouri, and Larsson, Lars

Subjects
ADULT respiratory distress syndrome, RESPIRATORY distress syndrome
Abstract

Acute respiratory distress syndrome (ARDS) is associated with long-term impairments in brain and muscle function that significantly impact the quality of life of those who survive the acute illness. The mechanisms underlying these impairments are not yet well understood, and evidence-based interventions to minimize the burden on patients remain unproved. The NHLBI of the NIH assembled a workshop in April 2023 to review the state of the science regarding ARDS-associated brain and muscle dysfunction, to identify gaps in current knowledge, and to determine priorities for future investigation. The workshop included presentations by scientific leaders across the translational science spectrum and was open to the public as well as the scientific community. This report describes the themes discussed at the workshop as well as recommendations to advance the field toward the goal of improving the health and well-being of ARDS survivors. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Rural–Urban Differences in Mortality among Mechanically Ventilated Patients in Intensive and Intermediate Care.

Author

Harlan, Emily A., Venkatesh, Shrathinth, Morrison, Jean, Cooke, Colin R., Iwashyna, Theodore J., Ford, Dee W., Moscovice, Ira S., Sjoding, Michael W., and Valley, Thomas S.

Subjects
INTENSIVE care patients, RURAL-urban differences, INTERMEDIATE care, INTENSIVE care units, URBAN hospitals
Abstract

Rationale: Intermediate care (also termed "step-down" or "moderate care") has been proposed as a lower cost alternative to care for patients who may not clearly benefit from intensive care unit admission. Intermediate care units may be appealing to hospitals in financial crisis, including those in rural areas. Outcomes of patients receiving intermediate care are not widely described. Objectives: To examine relationships among rurality, location of care, and mortality for mechanically ventilated patients. Methods: Medicare beneficiaries aged 65 years and older who received invasive mechanical ventilation between 2010 and 2019 were included. Multivariable logistic regression was used to estimate the association between admission to a rural or an urban hospital and 30-day mortality, with separate analyses for patients in general, intermediate, and intensive care. Models were adjusted for age, sex, area deprivation index, primary diagnosis, severity of illness, year, comorbidities, and hospital volume. Results: There were 2,752,492 hospitalizations for patients receiving mechanical ventilation from 2010 to 2019, and 193,745 patients (7.0%) were in rural hospitals. The proportion of patients in rural intermediate care increased from 4.1% in 2010 to 6.3% in 2019. Patient admissions to urban hospitals remained relatively stable. Patients in rural and urban intensive care units had similar adjusted 30-day mortality, at 46.7% (adjusted absolute risk difference −0.1% [95% confidence interval, −0.7% to 0.6%]; P = 0.88). However, adjusted 30-day mortality for patients in rural intermediate care was significantly higher (36.9%) than for patients in urban intermediate care (31.3%) (adjusted absolute risk difference 5.6% [95% confidence interval, 3.7% to 7.6%]; P < 0.001). Conclusions: Hospitalization in rural intermediate care was associated with increased mortality. There is a need to better understand how intermediate care is used across hospitals and to carefully evaluate the types of patients admitted to intermediate care units. [ABSTRACT FROM AUTHOR]

Published
2024
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