Browsing by Author "Vijayan, Anitha"

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    AKI Treated with Renal Replacement Therapy in Critically Ill Patients with COVID-19
    (Wolters Kluwer, 2021) Gupta, Shruti; Coca, Steven G.; Chan, Lili; Melamed, Michal L.; Brenner, Samantha K.; Hayek, Salim S.; Sutherland, Anne; Puri, Sonika; Srivastava, Anand; Leonberg-Yoo, Amanda; Shehata, Alexandre M.; Flythe, Jennifer E.; Rashidi, Arash; Schenck, Edward J.; Goyal, Nitender; Hedayati, S. Susan; Dy, Rajany; Bansal, Anip; Athavale, Ambarish; Nguyen, H. Bryant; Vijayan, Anitha; Charytan, David M.; Schulze, Carl E.; Joo, Min J.; Friedman, Allon N.; Zhang, Jingjing; Sosa, Marie Anne; Judd, Eric; Velez, Juan Carlos Q.; Mallappallil, Mary; Redfern, Roberta E.; Bansal, Amar D.; Neyra, Javier A.; Liu, Kathleen D.; Renaghan, Amanda D.; Christov, Marta; Molnar, Miklos Z.; Sharma, Shreyak; Kamal, Omer; Boateng, Jeffery Owusu; Short, Samuel A.P.; Admon, Andrew J.; Sise, Meghan E.; Wang, Wei; Parikh, Chirag R.; Leaf, David E.; STOP-COVID Investigators; Medicine, School of Medicine
    Background: AKI is a common sequela of coronavirus disease 2019 (COVID-19). However, few studies have focused on AKI treated with RRT (AKI-RRT). Methods: We conducted a multicenter cohort study of 3099 critically ill adults with COVID-19 admitted to intensive care units (ICUs) at 67 hospitals across the United States. We used multivariable logistic regression to identify patient-and hospital-level risk factors for AKI-RRT and to examine risk factors for 28-day mortality among such patients. Results: A total of 637 of 3099 patients (20.6%) developed AKI-RRT within 14 days of ICU admission, 350 of whom (54.9%) died within 28 days of ICU admission. Patient-level risk factors for AKI-RRT included CKD, men, non-White race, hypertension, diabetes mellitus, higher body mass index, higher d-dimer, and greater severity of hypoxemia on ICU admission. Predictors of 28-day mortality in patients with AKI-RRT were older age, severe oliguria, and admission to a hospital with fewer ICU beds or one with greater regional density of COVID-19. At the end of a median follow-up of 17 days (range, 1-123 days), 403 of the 637 patients (63.3%) with AKI-RRT had died, 216 (33.9%) were discharged, and 18 (2.8%) remained hospitalized. Of the 216 patients discharged, 73 (33.8%) remained RRT dependent at discharge, and 39 (18.1%) remained RRT dependent 60 days after ICU admission. Conclusions: AKI-RRT is common among critically ill patients with COVID-19 and is associated with a hospital mortality rate of >60%. Among those who survive to discharge, one in three still depends on RRT at discharge, and one in six remains RRT dependent 60 days after ICU admission.
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    An atlas of healthy and injured cell states and niches in the human kidney
    (Springer Nature, 2023) Lake, Blue B.; Menon, Rajasree; Winfree, Seth; Hu, Qiwen; Ferreira, Ricardo Melo; Kalhor, Kian; Barwinska, Daria; Otto, Edgar A.; Ferkowicz, Michael; Diep, Dinh; Plongthongkum, Nongluk; Knoten, Amanda; Urata, Sarah; Mariani, Laura H.; Naik, Abhijit S.; Eddy, Sean; Zhang, Bo; Wu, Yan; Salamon, Diane; Williams, James C.; Wang, Xin; Balderrama, Karol S.; Hoover, Paul J.; Murray, Evan; Marshall, Jamie L.; Noel, Teia; Vijayan, Anitha; Hartman, Austin; Chen, Fei; Waikar, Sushrut S.; Rosas, Sylvia E.; Wilson, Francis P.; Palevsky, Paul M.; Kiryluk, Krzysztof; Sedor, John R.; Toto, Robert D.; Parikh, Chirag R.; Kim, Eric H.; Satija, Rahul; Greka, Anna; Macosko, Evan Z.; Kharchenko, Peter V.; Gaut, Joseph P.; Hodgin, Jeffrey B.; KPMP Consortium; Eadon, Michael T.; Dagher, Pierre C.; El-Achkar, Tarek M.; Zhang, Kun; Kretzler, Matthias; Jain, Sanjay; Medicine, School of Medicine
    Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.
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    Factors Associated With Death in Critically Ill Patients With Coronavirus Disease 2019 in the US
    (American Medical Association, 2020-07-15) Gupta, Shruti; Hayek, Salim S.; Wang, Wei; Chan, Lili; Mathews, Kusum S.; Melamed, Michal L.; Brenner, Samantha K.; Leonberg-Yoo, Amanda; Schenck, Edward J.; Radbel, Jared; Reiser, Jochen; Bansal, Anip; Srivastava, Anand; Zhou, Yan; Sutherland, Anne; Green, Adam; Shehata, Alexandre M.; Goyal, Nitender; Vijayan, Anitha; Velez, Juan Carlos Q.; Shaefi, Shahzad; Parikh, Chirag R.; Arunthamakun, Justin; Athavale, Ambarish M.; Friedman, Allon N.; Short, Samuel A. P.; Kibbelaar, Zoe A.; Omar, Samah Abu; Admon, Andrew J.; Donnelly, John P.; Gershengorn, Hayley B.; Hernán, Miguel A.; Semler, Matthew W.; Leaf, David E.; Medicine, School of Medicine
    Importance: The US is currently an epicenter of the coronavirus disease 2019 (COVID-19) pandemic, yet few national data are available on patient characteristics, treatment, and outcomes of critical illness from COVID-19. Objectives: To assess factors associated with death and to examine interhospital variation in treatment and outcomes for patients with COVID-19. Design, Setting, and Participants: This multicenter cohort study assessed 2215 adults with laboratory-confirmed COVID-19 who were admitted to intensive care units (ICUs) at 65 hospitals across the US from March 4 to April 4, 2020. Exposures: Patient-level data, including demographics, comorbidities, and organ dysfunction, and hospital characteristics, including number of ICU beds. Main Outcomes and Measures: The primary outcome was 28-day in-hospital mortality. Multilevel logistic regression was used to evaluate factors associated with death and to examine interhospital variation in treatment and outcomes. Results: A total of 2215 patients (mean [SD] age, 60.5 [14.5] years; 1436 [64.8%] male; 1738 [78.5%] with at least 1 chronic comorbidity) were included in the study. At 28 days after ICU admission, 784 patients (35.4%) had died, 824 (37.2%) were discharged, and 607 (27.4%) remained hospitalized. At the end of study follow-up (median, 16 days; interquartile range, 8-28 days), 875 patients (39.5%) had died, 1203 (54.3%) were discharged, and 137 (6.2%) remained hospitalized. Factors independently associated with death included older age (≥80 vs <40 years of age: odds ratio [OR], 11.15; 95% CI, 6.19-20.06), male sex (OR, 1.50; 95% CI, 1.19-1.90), higher body mass index (≥40 vs <25: OR, 1.51; 95% CI, 1.01-2.25), coronary artery disease (OR, 1.47; 95% CI, 1.07-2.02), active cancer (OR, 2.15; 95% CI, 1.35-3.43), and the presence of hypoxemia (Pao2:Fio2<100 vs ≥300 mm Hg: OR, 2.94; 95% CI, 2.11-4.08), liver dysfunction (liver Sequential Organ Failure Assessment score of 2 vs 0: OR, 2.61; 95% CI, 1.30–5.25), and kidney dysfunction (renal Sequential Organ Failure Assessment score of 4 vs 0: OR, 2.43; 95% CI, 1.46–4.05) at ICU admission. Patients admitted to hospitals with fewer ICU beds had a higher risk of death (<50 vs ≥100 ICU beds: OR, 3.28; 95% CI, 2.16-4.99). Hospitals varied considerably in the risk-adjusted proportion of patients who died (range, 6.6%-80.8%) and in the percentage of patients who received hydroxychloroquine, tocilizumab, and other treatments and supportive therapies. Conclusions and Relevance: This study identified demographic, clinical, and hospital-level risk factors that may be associated with death in critically ill patients with COVID-19 and can facilitate the identification of medications and supportive therapies to improve outcomes.
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    Factors Associated With Death in Critically Ill Patients With Coronavirus Disease 2019 in the US
    (American Medical Association, 2020-11) Gupta, Shruti; Hayek, Salim S.; Wang, Wei; Chan, Lili; Mathews, Kusum S.; Melamed, Michal L.; Brenner, Samantha K.; Leonberg-Yoo, Amanda; Schenck, Edward J.; Radbel, Jared; Reiser, Jochen; Bansal, Anip; Srivastava, Anand; Zhou, Yan; Sutherland, Anne; Green, Adam; Shehata, Alexandre M.; Goyal, Nitender; Vijayan, Anitha; Velez, Juan Carlos Q.; Shaefi, Shahzad; Parikh, Chirag R.; Arunthamakun, Justin; Athavale, Ambarish M.; Friedman, Allon N.; Short, Samuel A.P.; Kibbelaar, Zoe A.; Omar, Samah Abu; Admon, Andrew J.; Donnelly, John P.; Gershengorn, Hayley B.; Hernán, Miguel A.; Semler, Matthew W.; Leaf, David E.; Medicine, School of Medicine
    Importance: The US is currently an epicenter of the coronavirus disease 2019 (COVID-19) pandemic, yet few national data are available on patient characteristics, treatment, and outcomes of critical illness from COVID-19. Objectives: To assess factors associated with death and to examine interhospital variation in treatment and outcomes for patients with COVID-19. Design, setting, and participants: This multicenter cohort study assessed 2215 adults with laboratory-confirmed COVID-19 who were admitted to intensive care units (ICUs) at 65 hospitals across the US from March 4 to April 4, 2020. Exposures: Patient-level data, including demographics, comorbidities, and organ dysfunction, and hospital characteristics, including number of ICU beds. Main outcomes and measures: The primary outcome was 28-day in-hospital mortality. Multilevel logistic regression was used to evaluate factors associated with death and to examine interhospital variation in treatment and outcomes. Results: A total of 2215 patients (mean [SD] age, 60.5 [14.5] years; 1436 [64.8%] male; 1738 [78.5%] with at least 1 chronic comorbidity) were included in the study. At 28 days after ICU admission, 784 patients (35.4%) had died, 824 (37.2%) were discharged, and 607 (27.4%) remained hospitalized. At the end of study follow-up (median, 16 days; interquartile range, 8-28 days), 875 patients (39.5%) had died, 1203 (54.3%) were discharged, and 137 (6.2%) remained hospitalized. Factors independently associated with death included older age (≥80 vs <40 years of age: odds ratio [OR], 11.15; 95% CI, 6.19-20.06), male sex (OR, 1.50; 95% CI, 1.19-1.90), higher body mass index (≥40 vs <25: OR, 1.51; 95% CI, 1.01-2.25), coronary artery disease (OR, 1.47; 95% CI, 1.07-2.02), active cancer (OR, 2.15; 95% CI, 1.35-3.43), and the presence of hypoxemia (Pao2:Fio2<100 vs ≥300 mm Hg: OR, 2.94; 95% CI, 2.11-4.08), liver dysfunction (liver Sequential Organ Failure Assessment score of 2-4 vs 0: OR, 2.61; 95% CI, 1.30-5.25), and kidney dysfunction (renal Sequential Organ Failure Assessment score of 4 vs 0: OR, 2.43; 95% CI, 1.46-4.05) at ICU admission. Patients admitted to hospitals with fewer ICU beds had a higher risk of death (<50 vs ≥100 ICU beds: OR, 3.28; 95% CI, 2.16-4.99). Hospitals varied considerably in the risk-adjusted proportion of patients who died (range, 6.6%-80.8%) and in the percentage of patients who received hydroxychloroquine, tocilizumab, and other treatments and supportive therapies. Conclusions and relevance: This study identified demographic, clinical, and hospital-level risk factors that may be associated with death in critically ill patients with COVID-19 and can facilitate the identification of medications and supportive therapies to improve outcomes.