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1. Global Mpox spread due to increased air travel.

Author

Qiao H, Paansri P, and Escobar LE

Subjects
Humans, Mpox (monkeypox) epidemiology, Mpox (monkeypox) transmission, Global Health, Pandemics, Airports, Communicable Diseases, Emerging epidemiology, Travel, Disease Outbreaks, Air Travel, COVID-19 epidemiology, COVID-19 transmission, SARS-CoV-2
Abstract

Mpox is an emerging, infectious disease that has caused outbreaks in at least 91 countries from May to August 2022. We assessed the link between international air travel patterns and Mpox transmission risk, and the relationship between the translocation of Mpox and human mobility dynamics after travel restrictions due to the COVID-19 pandemic had been lifted. Our three novel observations were that: i) more people traveled internationally after the removal of travel restrictions in the summer of 2022 compared to pre-pandemic levels; ii) countries with a high concentration of global air travel have the most recorded Mpox cases; and iii) Mpox transmission includes a number of previously nonendemic regions. These results suggest that international airports should be a primary location for monitoring the risk of emerging communicable diseases. Findings highlight the need for global collaboration concerning proactive measures emphasizing realtime surveillance.

Published
2024
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2. Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.

Author

Batra R, Uni R, Akchurin OM, Alvarez-Mulett S, Gómez-Escobar LG, Patino E, Hoffman KL, Simmons W, Whalen W, Chetnik K, Buyukozkan M, Benedetti E, Suhre K, Schenck E, Cho SJ, Choi AMK, Schmidt F, Choi ME, and Krumsiek J

Subjects
Humans, Proteomics, Multiomics, Inflammation, COVID-19 complications, Respiratory Distress Syndrome etiology, Sepsis complications
Abstract

Background: Acute respiratory distress syndrome (ARDS), a life-threatening condition during critical illness, is a common complication of COVID-19. It can originate from various disease etiologies, including severe infections, major injury, or inhalation of irritants. ARDS poses substantial clinical challenges due to a lack of etiology-specific therapies, multisystem involvement, and heterogeneous, poor patient outcomes. A molecular comparison of ARDS groups holds the potential to reveal common and distinct mechanisms underlying ARDS pathogenesis., Methods: We performed a comparative analysis of urine-based metabolomics and proteomics profiles from COVID-19 ARDS patients (n = 42) and bacterial sepsis-induced ARDS patients (n = 17). To this end, we used two different approaches, first we compared the molecular omics profiles between ARDS groups, and second, we correlated clinical manifestations within each group with the omics profiles., Results: The comparison of the two ARDS etiologies identified 150 metabolites and 70 proteins that were differentially abundant between the two groups. Based on these findings, we interrogated the interplay of cell adhesion/extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis through a multi-omic network approach. Moreover, we identified a proteomic signature associated with mortality in COVID-19 ARDS patients, which contained several proteins that had previously been implicated in clinical manifestations frequently linked with ARDS pathogenesis., Conclusion: In summary, our results provide evidence for significant molecular differences in ARDS patients from different etiologies and a potential synergy of extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis. The proteomic mortality signature should be further investigated in future studies to develop prediction models for COVID-19 patient outcomes., (© 2023. The Author(s).)

Published
2023
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3. Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.

Author

Batra R, Whalen W, Alvarez-Mulett S, Gomez-Escobar LG, Hoffman KL, Simmons W, Harrington J, Chetnik K, Buyukozkan M, Benedetti E, Choi ME, Suhre K, Schenck E, Choi AMK, Schmidt F, Cho SJ, and Krumsiek J

Subjects
Arginine, Humans, Interleukin-17, Lipids, Sphingosine, Acute Kidney Injury, COVID-19 complications, Janus Kinase Inhibitors, Respiratory Distress Syndrome etiology, Sepsis complications, Thrombocytosis
Abstract

Background: Acute respiratory distress syndrome (ARDS), a life-threatening condition characterized by hypoxemia and poor lung compliance, is associated with high mortality. ARDS induced by COVID-19 has similar clinical presentations and pathological manifestations as non-COVID-19 ARDS. However, COVID-19 ARDS is associated with a more protracted inflammatory respiratory failure compared to traditional ARDS. Therefore, a comprehensive molecular comparison of ARDS of different etiologies groups may pave the way for more specific clinical interventions., Methods and Findings: In this study, we compared COVID-19 ARDS (n = 43) and bacterial sepsis-induced (non-COVID-19) ARDS (n = 24) using multi-omic plasma profiles covering 663 metabolites, 1,051 lipids, and 266 proteins. To address both between- and within- ARDS group variabilities we followed two approaches. First, we identified 706 molecules differently abundant between the two ARDS etiologies, revealing more than 40 biological processes differently regulated between the two groups. From these processes, we assembled a cascade of therapeutically relevant pathways downstream of sphingosine metabolism. The analysis suggests a possible overactivation of arginine metabolism involved in long-term sequelae of ARDS and highlights the potential of JAK inhibitors to improve outcomes in bacterial sepsis-induced ARDS. The second part of our study involved the comparison of the two ARDS groups with respect to clinical manifestations. Using a data-driven multi-omic network, we identified signatures of acute kidney injury (AKI) and thrombocytosis within each ARDS group. The AKI-associated network implicated mitochondrial dysregulation which might lead to post-ARDS renal-sequalae. The thrombocytosis-associated network hinted at a synergy between prothrombotic processes, namely IL-17, MAPK, TNF signaling pathways, and cell adhesion molecules. Thus, we speculate that combination therapy targeting two or more of these processes may ameliorate thrombocytosis-mediated hypercoagulation., Conclusion: We present a first comprehensive molecular characterization of differences between two ARDS etiologies-COVID-19 and bacterial sepsis. Further investigation into the identified pathways will lead to a better understanding of the pathophysiological processes, potentially enabling novel therapeutic interventions., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: A.M.K.C. is a cofounder and equity stockholder for Proterris, which develops therapeutic uses for carbon monoxide. A.M.K.C. has a use patent on CO. Additionally, A.M.K.C. has a patent in COPD. ES consults for Axle informatics regarding COVID vaccine clinical trials through NIAID. JK holds equity in Chymia LLC and IP in PsyProtix and is cofounder of iollo.

Published
2022
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4. A metagenomic DNA sequencing assay that is robust against environmental DNA contamination.

Author

Mzava O, Cheng AP, Chang A, Smalling S, Djomnang LK, Lenz JS, Longman R, Steadman A, Gómez-Escobar LG, Schenck EJ, Salvatore M, Satlin MJ, Suthanthiran M, Lee JR, Mason CE, Dadhania D, and De Vlaminck I

Subjects
DNA, DNA Contamination, DNA, Bacterial genetics, High-Throughput Nucleotide Sequencing, Humans, Metagenomics, Sequence Analysis, DNA, COVID-19, DNA, Environmental
Abstract

Metagenomic DNA sequencing is a powerful tool to characterize microbial communities but is sensitive to environmental DNA contamination, in particular when applied to samples with low microbial biomass. Here, we present Sample-Intrinsic microbial DNA Found by Tagging and sequencing (SIFT-seq) a metagenomic sequencing assay that is robust against environmental DNA contamination introduced during sample preparation. The core idea of SIFT-seq is to tag the DNA in the sample prior to DNA isolation and library preparation with a label that can be recorded by DNA sequencing. Any contaminating DNA that is introduced in the sample after tagging can then be bioinformatically identified and removed. We applied SIFT-seq to screen for infections from microorganisms with low burden in blood and urine, to identify COVID-19 co-infection, to characterize the urinary microbiome, and to identify microbial DNA signatures of sepsis and inflammatory bowel disease in blood., (© 2022. The Author(s).)

Published
2022
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5. Angiopoietin 2 Is Associated with Vascular Necroptosis Induction in Coronavirus Disease 2019 Acute Respiratory Distress Syndrome.

Author

Price DR, Benedetti E, Hoffman KL, Gomez-Escobar L, Alvarez-Mulett S, Capili A, Sarwath H, Parkhurst CN, Lafond E, Weidman K, Ravishankar A, Cheong JG, Batra R, Büyüközkan M, Chetnik K, Easthausen I, Schenck EJ, Racanelli AC, Outtz Reed H, Laurence J, Josefowicz SZ, Lief L, Choi ME, Schmidt F, Borczuk AC, Choi AMK, Krumsiek J, and Rafii S

Subjects
Humans, Proteomics, Angiopoietin-2 metabolism, COVID-19 complications, Necroptosis, Respiratory Distress Syndrome virology
Abstract

Vascular injury is a well-established, disease-modifying factor in acute respiratory distress syndrome (ARDS) pathogenesis. Recently, coronavirus disease 2019 (COVID-19)-induced injury to the vascular compartment has been linked to complement activation, microvascular thrombosis, and dysregulated immune responses. This study sought to assess whether aberrant vascular activation in this prothrombotic context was associated with the induction of necroptotic vascular cell death. To achieve this, proteomic analysis was performed on blood samples from COVID-19 subjects at distinct time points during ARDS pathogenesis (hospitalized at risk, N = 59; ARDS, N = 31; and recovery, N = 12). Assessment of circulating vascular markers in the at-risk cohort revealed a signature of low vascular protein abundance that tracked with low platelet levels and increased mortality. This signature was replicated in the ARDS cohort and correlated with increased plasma angiopoietin 2 levels. COVID-19 ARDS lung autopsy immunostaining confirmed a link between vascular injury (angiopoietin 2) and platelet-rich microthrombi (CD61) and induction of necrotic cell death [phosphorylated mixed lineage kinase domain-like (pMLKL)]. Among recovery subjects, the vascular signature identified patients with poor functional outcomes. Taken together, this vascular injury signature was associated with low platelet levels and increased mortality and can be used to identify ARDS patients most likely to benefit from vascular targeted therapies., (Copyright © 2022 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Published
2022
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6. COVID-19 Lockdown Effects on Acute Stroke Care in Latin America.

Author

Pujol-Lereis VA, Flores A, Barboza MA, Abanto-Argomedo C, Amaya P, Bayona H, Bonardo P, Diaz-Escobar L, Gomez-Schneider M, Góngora-Rivera F, Lavados PM, Leon C, Luraschi A, Marquez-Romero JM, Ouriques-Martins SC, Navia VH, Ruiz-Franco A, Vences MÁ, Zurrú MC, Arauz A, and Ameriso SF

Subjects
COVID-19 transmission, Cause of Death trends, Endovascular Procedures adverse effects, Endovascular Procedures mortality, Female, Health Care Surveys, Hospital Mortality trends, Humans, Latin America, Length of Stay trends, Male, Patient Admission trends, Patient Discharge trends, Stroke diagnosis, Stroke mortality, Time Factors, Treatment Outcome, COVID-19 prevention & control, Endovascular Procedures trends, Hospitalization trends, Practice Patterns, Physicians' trends, Stroke therapy, Time-to-Treatment trends
Abstract

Objectives: COVID-19 pandemic has forced important changes in health care worldwide. Stroke care networks have been affected, especially during peak periods. We assessed the impact of the pandemic and lockdowns in stroke admissions and care in Latin America., Materials and Methods: A multinational study (7 countries, 18 centers) of patients admitted during the pandemic outbreak (March-June 2020). Comparisons were made with the same period in 2019. Numbers of cases, stroke etiology and severity, acute care and hospitalization outcomes were assessed., Results: Most countries reported mild decreases in stroke admissions compared to the same period of 2019 (1187 vs. 1166, p = 0.03). Among stroke subtypes, there was a reduction in ischemic strokes (IS) admissions (78.3% vs. 73.9%, p = 0.01) compared with 2019, especially in IS with NIHSS 0-5 (50.1% vs. 44.9%, p = 0.03). A substantial increase in the proportion of stroke admissions beyond 48 h from symptoms onset was observed (13.8% vs. 20.5%, p < 0.001). Nevertheless, no differences in total reperfusion treatment rates were observed, with similar door-to-needle, door-to-CT, and door-to-groin times in both periods. Other stroke outcomes, as all-type mortality during hospitalization (4.9% vs. 9.7%, p < 0.001), length of stay (IQR 1-5 days vs. 0-9 days, p < 0.001), and likelihood to be discharged home (91.6% vs. 83.0%, p < 0.001), were compromised during COVID-19 lockdown period., Conclusions: In this Latin America survey, there was a mild decrease in admissions of IS during the COVID-19 lockdown period, with a significant delay in time to consultations and worse hospitalization outcomes., Competing Interests: Declarations of Competing Interest None., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Published
2021
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7. Identifying organ dysfunction trajectory-based subphenotypes in critically ill patients with COVID-19.

Author

Su C, Xu Z, Hoffman K, Goyal P, Safford MM, Lee J, Alvarez-Mulett S, Gomez-Escobar L, Price DR, Harrington JS, Torres LK, Martinez FJ, Campion TR Jr, Wang F, and Schenck EJ

Subjects
Aged, COVID-19 complications, COVID-19 physiopathology, Critical Illness, Female, Humans, Male, Middle Aged, Multiple Organ Failure etiology, Multiple Organ Failure physiopathology, Organ Dysfunction Scores, Prognosis, SARS-CoV-2 isolation & purification, Severity of Illness Index, COVID-19 diagnosis, Multiple Organ Failure diagnosis
Abstract

COVID-19-associated respiratory failure offers the unprecedented opportunity to evaluate the differential host response to a uniform pathogenic insult. Understanding whether there are distinct subphenotypes of severe COVID-19 may offer insight into its pathophysiology. Sequential Organ Failure Assessment (SOFA) score is an objective and comprehensive measurement that measures dysfunction severity of six organ systems, i.e., cardiovascular, central nervous system, coagulation, liver, renal, and respiration. Our aim was to identify and characterize distinct subphenotypes of COVID-19 critical illness defined by the post-intubation trajectory of SOFA score. Intubated COVID-19 patients at two hospitals in New York city were leveraged as development and validation cohorts. Patients were grouped into mild, intermediate, and severe strata by their baseline post-intubation SOFA. Hierarchical agglomerative clustering was performed within each stratum to detect subphenotypes based on similarities amongst SOFA score trajectories evaluated by Dynamic Time Warping. Distinct worsening and recovering subphenotypes were identified within each stratum, which had distinct 7-day post-intubation SOFA progression trends. Patients in the worsening suphenotypes had a higher mortality than those in the recovering subphenotypes within each stratum (mild stratum, 29.7% vs. 10.3%, p = 0.033; intermediate stratum, 29.3% vs. 8.0%, p = 0.002; severe stratum, 53.7% vs. 22.2%, p < 0.001). Pathophysiologic biomarkers associated with progression were distinct at each stratum, including findings suggestive of inflammation in low baseline severity of illness versus hemophagocytic lymphohistiocytosis in higher baseline severity of illness. The findings suggest that there are clear worsening and recovering subphenotypes of COVID-19 respiratory failure after intubation, which are more predictive of outcomes than baseline severity of illness. Distinct progression biomarkers at differential baseline severity of illness suggests a heterogeneous pathobiology in the progression of COVID-19 respiratory failure., (© 2021. The Author(s).)

Published
2021
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8. Cytokine signatures of end organ injury in COVID-19.

Author

Gómez-Escobar LG, Hoffman KL, Choi JJ, Borczuk A, Salvatore S, Alvarez-Mulett SL, Galvan MD, Zhao Z, Racine-Brzostek SE, Yang HS, Stout-Delgado HW, Choi ME, Choi AMK, Cho SJ, and Schenck EJ

Subjects
Acute Kidney Injury blood, Acute Kidney Injury pathology, Acute Kidney Injury virology, Aged, COVID-19 blood, COVID-19 therapy, Case-Control Studies, Cytokine Release Syndrome virology, Female, Hospitals, Humans, Lung pathology, Lung virology, Male, Middle Aged, New York City, Respiration, Artificial, Respiratory Distress Syndrome blood, Respiratory Distress Syndrome virology, Treatment Outcome, COVID-19 mortality, COVID-19 physiopathology, Cytokines blood
Abstract

Increasing evidence has shown that Coronavirus disease 19 (COVID-19) severity is driven by a dysregulated immunologic response. We aimed to assess the differences in inflammatory cytokines in COVID-19 patients compared to contemporaneously hospitalized controls and then analyze the relationship between these cytokines and the development of Acute Respiratory Distress Syndrome (ARDS), Acute Kidney Injury (AKI) and mortality. In this cohort study of hospitalized patients, done between March third, 2020 and April first, 2020 at a quaternary referral center in New York City we included adult hospitalized patients with COVID-19 and negative controls. Serum specimens were obtained on the first, second, and third hospital day and cytokines were measured by Luminex. Autopsies of nine cohort patients were examined. We identified 90 COVID-19 patients and 51 controls. Analysis of 48 inflammatory cytokines revealed upregulation of macrophage induced chemokines, T-cell related interleukines and stromal cell producing cytokines in COVID-19 patients compared to the controls. Moreover, distinctive cytokine signatures predicted the development of ARDS, AKI and mortality in COVID-19 patients. Specifically, macrophage-associated cytokines predicted ARDS, T cell immunity related cytokines predicted AKI and mortality was associated with cytokines of activated immune pathways, of which IL-13 was universally correlated with ARDS, AKI and mortality. Histopathological examination of the autopsies showed diffuse alveolar damage with significant mononuclear inflammatory cell infiltration. Additionally, the kidneys demonstrated glomerular sclerosis, tubulointerstitial lymphocyte infiltration and cortical and medullary atrophy. These patterns of cytokine expression offer insight into the pathogenesis of COVID-19 disease, its severity, and subsequent lung and kidney injury suggesting more targeted treatment strategies.

Published
2021
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9. The 2020 report of The Lancet Countdown on health and climate change: responding to converging crises.

Author

Watts N, Amann M, Arnell N, Ayeb-Karlsson S, Beagley J, Belesova K, Boykoff M, Byass P, Cai W, Campbell-Lendrum D, Capstick S, Chambers J, Coleman S, Dalin C, Daly M, Dasandi N, Dasgupta S, Davies M, Di Napoli C, Dominguez-Salas P, Drummond P, Dubrow R, Ebi KL, Eckelman M, Ekins P, Escobar LE, Georgeson L, Golder S, Grace D, Graham H, Haggar P, Hamilton I, Hartinger S, Hess J, Hsu SC, Hughes N, Jankin Mikhaylov S, Jimenez MP, Kelman I, Kennard H, Kiesewetter G, Kinney PL, Kjellstrom T, Kniveton D, Lampard P, Lemke B, Liu Y, Liu Z, Lott M, Lowe R, Martinez-Urtaza J, Maslin M, McAllister L, McGushin A, McMichael C, Milner J, Moradi-Lakeh M, Morrissey K, Munzert S, Murray KA, Neville T, Nilsson M, Sewe MO, Oreszczyn T, Otto M, Owfi F, Pearman O, Pencheon D, Quinn R, Rabbaniha M, Robinson E, Rocklöv J, Romanello M, Semenza JC, Sherman J, Shi L, Springmann M, Tabatabaei M, Taylor J, Triñanes J, Shumake-Guillemot J, Vu B, Wilkinson P, Winning M, Gong P, Montgomery H, and Costello A

Subjects
Conservation of Natural Resources trends, Health Policy, Humans, International Cooperation, Pandemics, SARS-CoV-2, COVID-19, Climate Change, Extreme Weather, Global Health
Abstract

Translations: For the Chinese, French, German, and Spanish translations of the abstract see Supplementary Materials section., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Published
2021
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10. 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

11. Global Impact of COVID-19 on Stroke Care and IV Thrombolysis

Author

Nogueira, Raul, Qureshi, Muhammad, Abdalkader, Mohamad, Martins, Sheila Ouriques, Yamagami, Hiroshi, Qiu, Zhongming, Mansour, Ossama Yassin, Sathya, Anvitha, Czlonkowska, Anna, Tsivgoulis, Georgios, Aguiar de Sousa, Diana, Demeestere, Jelle, Mikulik, Robert, Vanacker, Peter, Siegler, James, Kõrv, Janika, Biller, Jose, Liang, Conrad, Sangha, Navdeep, Zha, Alicia, Czap, Alexandra, Holmstedt, Christine Anne, Turan, Tanya, Ntaios, George, Malhotra, Konark, Tayal, Ashis, Loochtan, Aaron, Ranta, Annamarei, Mistry, Eva, Alexandrov, Anne, Huang, David, Yaghi, Shadi, Raz, Eytan, Sheth, Sunil, Mohammaden, Mahmoud, Frankel, Michael, Bila Lamou, Eric Guemekane, Aref, Hany, Elbassiouny, Ahmed, Hassan, Farouk, Menecie, Tarek, Mustafa, Wessam, Shokri, Hossam, Roushdy, Tamer, Sarfo, Fred, Alabi, Tolulope Oyetunde, Arabambi, Babawale, Nwazor, Ernest, Sunmonu, Taofiki Ajao, Wahab, Kolawole, Yaria, Joseph, Mohammed, Haytham Hussein, Adebayo, Philip, Riahi, Anis, Sassi, Samia Ben, Gwaunza, Lenon, Ngwende, Gift Wilson, Sahakyan, David, Rahman, Aminur, Ai, Zhibing, Bai, Fanghui, Duan, Zhenhui, Hao, Yonggang, Huang, Wenguo, Li, Guangwen, Li, Wei, Liu, Ganzhe, Luo, Jun, Shang, Xianjin, Sui, Yi, Tian, Ling, Wen, Hongbin, Wu, Bo, Yan, Yuying, Yuan, Zhengzhou, Zhang, Hao, Zhang, Jun, Zhao, Wenlong, Zi, Wenjie, Leung, Thomas, Chugh, Chandril, Huded, Vikram, Menon, Bindu, Pandian, Jeyaraj Durai, Sylaja, Pn, Usman, Fritz Sumantri, Farhoudi, Mehdi, Hokmabadi, Elyar Sadeghi, Horev, Anat, Reznik, Anna, Sivan Hoffmann, Rotem, Ohara, Nobuyuki, Sakai, Nobuyuki, Watanabe, Daisuke, Yamamoto, Ryoo, Doijiri, Ryosuke, Tokuda, Naoki, Yamada, Takehiro, Terasaki, Tadashi, Yazawa, Yukako, Uwatoko, Takeshi, Dembo, Tomohisa, Shimizu, Hisao, Sugiura, Yuri, Miyashita, Fumio, Fukuda, Hiroki, Miyake, Kosuke, Shimbo, Junsuke, Sugimura, Yusuke, Yagita, Yoshiki, Takenobu, Yohei, Matsumaru, Yuji, Yamada, Satoshi, Kono, Ryuhei, Kanamaru, Takuya, Yamazaki, Hidekazu, Sakaguchi, Manabu, Todo, Kenichi, Yamamoto, Nobuaki, Sonoda, Kazutaka, Yoshida, Tomoko, Hashimoto, Hiroyuki, Nakahara, Ichiro, Kondybayeva, Aida, Faizullina, Kamila, Kamenova, Saltanat, Zhanuzakov, Murat, Baek, Jang-Hyun, Hwang, Yangha, Lee, Jin Soo, Lee, Si Baek, Moon, Jusun, Park, Hyungjong, Seo, Jung Hwa, Seo, Kwon-Duk, Sohn, Sung Il, Young, Chang Jun, Ahdab, Rechdi, Wan Zaidi, Wan Asyraf, Aziz, Zariah Abdul, Basri, Hamidon Bin, Chung, Law Wan, Ibrahim, Aznita Binti, Ibrahim, Khairul Azmi, Looi, Irene, Tan, Wee Yong, Yahya, Nafisah Wan, Groppa, Stanislav, Leahu, Pavel, Al Hashmi, Amal, Imam, Yahia Zakaria, Akhtar, Naveed, Pineda-Franks, Maria Carissa, Co, Christian Oliver, Kandyba, Dmitriy, Alhazzani, Adel, Al-Jehani, Hosam, Tham, Carol Huilian, Mamauag, Marlie Jane, Venketasubramanian, Narayanaswamy, Chen, Chih-Hao, Tang, Sung-Chun, Churojana, Anchalee, Akil, Esref, Aykaç, Özlem, Ozdemir, Atilla Ozcan, Giray, Semih, Hussain, Syed Irteza, John, Seby, Le Vu, Huynh, Tran, Anh Duc, Nguyen, Huy Hoang, Nhu Pham, Thong, Nguyen, Thang Huy, Nguyen, Trung Quoc, Gattringer, Thomas, Enzinger, Christian, Killer-Oberpfalzer, Monika, Bellante, Flavio, de Blauwe, Sofie, Vanhooren, Geert, de Raedt, Sylvie, Dusart, Anne, Lemmens, Robin, Ligot, Noemie, Pierre Rutgers, Matthieu, Yperzeele, Laetitia, Alexiev, Filip, Sakelarova, Teodora, Bedeković, Marina Roje, Budincevic, Hrvoje, Cindric, Igor, Hucika, Zlatko, Ozretic, David, Saric, Majda Seferovic, Pfeifer, František, Karpowic, Igor, Cernik, David, Sramek, Martin, Skoda, Miroslav, Hlavacova, Helena, Klecka, Lukas, Koutny, Martin, Vaclavik, Daniel, Skoda, Ondrej, Fiksa, Jan, Hanelova, Katerina, Nevsimalova, Miroslava, Rezek, Robert, Prochazka, Petr, Krejstova, Gabriela, Neumann, Jiri, Vachova, Marta, Brzezanski, Henryk, Hlinovsky, David, Tenora, Dusan, Jura, Rene, Jurák, Lubomír, Novak, Jan, Novak, Ales, Topinka, Zdenek, Fibrich, Petr, Sobolova, Helena, Volny, Ondrej, Krarup Christensen, Hanne, Drenck, Nicolas, Klingenberg Iversen, Helle, Simonsen, Claus, Truelsen, Thomas Clement, Wienecke, Troels, Vibo, Riina, Gross-Paju, Katrin, Toomsoo, Toomas, Antsov, Katrin, Caparros, Francois, Cordonnier, Charlotte, Dan, Maria, Faucheux, Jean-Marc, Mechtouff, Laura, Eker, Omer, Lesaine, Emilie, Ondze, Basile, Peres, Roxane, Pico, Fernando, Piotin, Michel, Pop, Raoul, Rouanet, Francois, Gubeladze, Tatuli, Khinikadze, Mirza, Lobjanidze, Nino, Tsiskaridze, Alexander, Nagel, Simon, Ringleb, Peter Arthur, Rosenkranz, Michael, Schmidt, Holger, Sedghi, Annahita, Siepmann, Timo, Szabo, Kristina, Thomalla, Götz, Palaiodimou, Lina, Sagris, Dimitrios, Kargiotis, Odysseas, Klivenyi, Peter, Szapary, Laszlo, Tarkanyi, Gabor, Adami, Alessandro, Bandini, Fabio, Calabresi, Paolo, Frisullo, Giovanni, Renieri, Leonardo, Sangalli, Davide, Pirson, Anne, Uyttenboogaart, Maarten, van den Wijngaard, Ido, Kristoffersen, Espen Saxhaug, Brola, Waldemar, Fudala, Małgorzata, Horoch-Lyszczarek, Ewa, Karlinski, Michal, Kazmierski, Radoslaw, Kram, Pawel, Rogoziewicz, Marcin, Kaczorowski, Rafal, Luchowski, Piotr, Sienkiewicz-Jarosz, Halina, Sobolewski, Piotr, Fryze, Waldemar, Wisniewska, Anna, Wiszniewska, Malgorzata, Ferreira, Patricia, Ferreira, Paulo, Fonseca, Luisa, Marto, João Pedro, Pinho E Melo, Teresa, Nunes, Ana Paiva, Rodrigues, Miguel, Tedim Cruz, Vítor, Falup-Pecurariu, Cristian, Krastev, Georgi, Mako, Miroslav, de Leciñana, María Alonso, Arenillas, Juan, Ayo-Martin, Oscar, Cruz Culebras, Antonio, Tejedor, Exuperio Diez, Montaner, Joan, Pérez-Sánchez, Soledad, Tola Arribas, Miguel Angel, Rodriguez Vasquez, Alejandro, Mayza, Michael, Bernava, Gianmarco, Brehm, Alex, Machi, Paolo, Fischer, Urs, Gralla, Jan, Michel, Patrik, Psychogios, Marios-Nikos, Strambo, Davide, Banerjee, Soma, Krishnan, Kailash, Kwan, Joseph, Butt, Asif, Catanese, Luciana, Demchuk, Andrew, Field, Thalia, Haynes, Jennifer, Hill, Michael, Khosravani, Houman, Mackey, Ariane, Pikula, Aleksandra, Saposnik, Gustavo, Scott, Courtney Anne, Shoamanesh, Ashkan, Shuaib, Ashfaq, Yip, Samuel, Barboza, Miguel, Barrientos, Jose Domingo, Portillo Rivera, Ligia Ibeth, Gongora-Rivera, Fernando, Novarro-Escudero, Nelson, Blanco, Anmylene, Abraham, Michael, Alsbrook, Diana, Altschul, Dorothea, Alvarado-Ortiz, Anthony, Bach, Ivo, Badruddin, Aamir, Barazangi, Nobl, Brereton, Charmaine, Castonguay, Alicia, Chaturvedi, Seemant, Chaudry, Saqib, Choe, Hana, Choi, Jae, Dharmadhikari, Sushrut, Desai, Kinjal, Devlin, Thomas, Doss, Vinodh, Edgell, Randall, Etherton, Mark, Farooqui, Mudassir, Frei, Don, Gandhi, Dheeraj, Grigoryan, Mikayel, Gupta, Rishi, Hassan, Ameer, Helenius, Johanna, Kaliaev, Artem, Kaushal, Ritesh, Khandelwal, Priyank, Khawaja, Ayaz, Khoury, Naim, Kim, Benny, Kleindorfer, Dawn, Koyfman, Feliks, Lee, Vivien, Leung, Lester, Linares, Guillermo, Linfante, Italo, Lutsep, Helmi, Macdougall, Lisa, Male, Shailesh, Malik, Amer, Masoud, Hesham, Mcdermott, Molly, Mehta, Brijesh, Min, Jiangyong, Mittal, Manoj, Morris, Jane, Multani, Sumeet, Nahab, Fadi, Nalleballe, Krishna, Nguyen, Claude, Novakovic-White, Roberta, Ortega-Gutierrez, Santiago, Rahangdale, Rahul, Ramakrishnan, Pankajavalli, Romero, Jose Rafael, Rost, Natalia, Rothstein, Aaron, Ruland, Sean, Shah, Ruchir, Sharma, Malveeka, Silver, Brian, Simmons, Marc, Singh, Abhishek, Starosciak, Amy, Strasser, Sheryl, Szeder, Viktor, Teleb, Mohamed, Tsai, Jenny, Voetsch, Barbara, Balaguera, Oscar, Pujol Lereis, Virginia, Luraschi, Adriana, Almeida, Marcele Schettini, Cardoso, Fabricio Buchdid, Conforto, Adriana, de Deus Silva, Leonardo, Varrone Giacomini, Luidia, Oliveira Lima, Fabricio, Longo, Alexandre, Magalhães, Pedro, Martins, Rodrigo Targa, Mont'Alverne, Francisco, Mora Cuervo, Daissy Liliana, Costa Rebello, Leticia, Valler, Lenise, Zetola, Viviane Flumignan, Lavados, Pablo, Navia, Victor, Olavarría, Verónica, Almeida Toro, Juan Manuel, Amaya, Pablo Felipe Ricardo, Bayona, Hernan, Corredor, Angel, Rivera Ordonez, Carlos Eduardo, Mantilla Barbosa, Diana Katherine, Lara, Osvaldo, Patiño, Mauricio, Diaz Escobar, Luis Fernando, Dejesus Melgarejo Fariña, Donoband Edson, Cardozo Villamayor, Analia, Zelaya Zarza, Adolfo Javier, Barrientos Iman, Danny Moises, Rodriguez Kadota, Liliana, Campbell, Bruce, Hankey, Graeme, Hair, Casey, Kleinig, Timothy, Ma, Alice, Tomazini Martins, Rodrigo, Sahathevan, Ramesh, Thijs, Vincent, Salazar, Daniel, Yuan-Hao Wu, Teddy, Haussen, Diogo, Liebeskind, David, Yavagal, Dileep, Jovin, Tudor, Zaidat, Osama, Nguyen, Thanh, Magalhães, Pedro S.C., Emory University School of Medicine, Emory University [Atlanta, GA], Boston University School of Medicine (BUSM), Boston University [Boston] (BU), Lille Neurosciences & Cognition - U 1172 (LilNCog), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Max Super Speciality Hospital -Saket [New Delhi, Inde] (Max Saket), Dupuis, Christine, Lille Neurosciences & Cognition - U 1172 (LilNCog (ex-JPARC)), and Repositório da Universidade de Lisboa

Subjects
medicine.medical_specialty, MESH: Pandemics, HSJ NEU, Cross-sectional study, medicine.medical_treatment, [SDV]Life Sciences [q-bio], SVIN COVID-19 Global Stroke Registry, MESH: Hospitalization, 030204 cardiovascular system & hematology, Article, MESH: Stroke, COVID-19, cross-sectional studies, hospitalization, humans, pandemics, retrospective studies, SARS-CoV-2, stroke, 03 medical and health sciences, 0302 clinical medicine, MESH: Cross-Sectional Studies, Pandemic, Medicine, Humans, MESH: COVID-19, Thrombolytic Therapy, MESH: SARS-CoV-2, Stroke, Pandemics, Retrospective Studies, MESH: Thrombolytic Therapy, Rehabilitation, MESH: Humans, business.industry, Retrospective cohort study, MESH: Retrospective Studies, medicine.disease, Thrombolysis, Confidence interval, 3. Good health, Hospitalization, [SDV] Life Sciences [q-bio], Clinical research, Cross-Sectional Studies, Emergency medicine, Observational study, Neurology (clinical), business, 030217 neurology & neurosurgery
Abstract

© 2021 American Academy of Neurology, Objective: To measure the global impact of COVID-19 pandemic on volumes of IV thrombolysis (IVT), IVT transfers, and stroke hospitalizations over 4 months at the height of the pandemic (March 1 to June 30, 2020) compared with 2 control 4-month periods. Methods: We conducted a cross-sectional, observational, retrospective study across 6 continents, 70 countries, and 457 stroke centers. Diagnoses were identified by their ICD-10 codes or classifications in stroke databases. Results: There were 91,373 stroke admissions in the 4 months immediately before compared to 80,894 admissions during the pandemic months, representing an 11.5% (95% confidence interval [CI] -11.7 to -11.3, p < 0.0001) decline. There were 13,334 IVT therapies in the 4 months preceding compared to 11,570 procedures during the pandemic, representing a 13.2% (95% CI -13.8 to -12.7, p < 0.0001) drop. Interfacility IVT transfers decreased from 1,337 to 1,178, or an 11.9% decrease (95% CI -13.7 to -10.3, p = 0.001). Recovery of stroke hospitalization volume (9.5%, 95% CI 9.2-9.8, p < 0.0001) was noted over the 2 later (May, June) vs the 2 earlier (March, April) pandemic months. There was a 1.48% stroke rate across 119,967 COVID-19 hospitalizations. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection was noted in 3.3% (1,722/52,026) of all stroke admissions. Conclusions: The COVID-19 pandemic was associated with a global decline in the volume of stroke hospitalizations, IVT, and interfacility IVT transfers. Primary stroke centers and centers with higher COVID-19 inpatient volumes experienced steeper declines. Recovery of stroke hospitalization was noted in the later pandemic months.

Published
2021

12. In-hospital cardiac arrest in critically ill patients with covid-19: multicenter cohort study

Author

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

Subjects
Adult, Male, medicine.medical_specialty, medicine.medical_treatment, Pneumonia, Viral, 030204 cardiovascular system & hematology, law.invention, Cohort Studies, Betacoronavirus, 03 medical and health sciences, 0302 clinical medicine, law, Intensive care, Humans, Medicine, Hospital Mortality, Cardiopulmonary resuscitation, Asystole, Pandemics, Aged, Aged, 80 and over, SARS-CoV-2, business.industry, Research, Incidence (epidemiology), COVID-19, 030208 emergency & critical care medicine, General Medicine, Middle Aged, medicine.disease, Intensive care unit, United States, Heart Arrest, Intensive Care Units, Pneumonia, Pulseless electrical activity, Emergency medicine, Female, Coronavirus Infections, business, Cohort study
Abstract

Objectives To estimate the incidence, risk factors, and outcomes associated with in-hospital cardiac arrest and cardiopulmonary resuscitation in critically ill adults with coronavirus disease 2019 (covid-19). Design Multicenter cohort study. Setting Intensive care units at 68 geographically diverse hospitals across the United States. Participants Critically ill adults (age ≥18 years) with laboratory confirmed covid-19. Main outcome measures In-hospital cardiac arrest within 14 days of admission to an intensive care unit and in-hospital mortality. Results Among 5019 critically ill patients with covid-19, 14.0% (701/5019) had in-hospital cardiac arrest, 57.1% (400/701) of whom received cardiopulmonary resuscitation. Patients who had in-hospital cardiac arrest were older (mean age 63 (standard deviation 14) v 60 (15) years), had more comorbidities, and were more likely to be admitted to a hospital with a smaller number of intensive care unit beds compared with those who did not have in-hospital cardiac arrest. Patients who received cardiopulmonary resuscitation were younger than those who did not (mean age 61 (standard deviation 14) v 67 (14) years). The most common rhythms at the time of cardiopulmonary resuscitation were pulseless electrical activity (49.8%, 199/400) and asystole (23.8%, 95/400). 48 of the 400 patients (12.0%) who received cardiopulmonary resuscitation survived to hospital discharge, and only 7.0% (28/400) survived to hospital discharge with normal or mildly impaired neurological status. Survival to hospital discharge differed by age, with 21.2% (11/52) of patients younger than 45 years surviving compared with 2.9% (1/34) of those aged 80 or older. Conclusions Cardiac arrest is common in critically ill patients with covid-19 and is associated with poor survival, particularly among older patients.

Published
2020

13. BCG vaccine protection from severe coronavirus disease 2019 (COVID-19).

Author

Escobar, Luis E., Molina-Cruz, Alvaro, and Barillas-Mury, Carolina

Subjects
*COVID-19, *BCG vaccines, *PANDEMICS, *NULL hypothesis
Abstract

A series of epidemiological explorations has suggested a negative association between national bacillus Calmette-Guérin (BCG) vaccination policy and the prevalence and mortality of coronavirus disease 2019 (COVID-19). However, these comparisons are difficult to validate due to broad differences between countries such as socioeconomic status, demographic structure, rural vs. urban settings, time of arrival of the pandemic, number of diagnostic tests and criteria for testing, and national control strategies to limit the spread of COVID-19. We review evidence for a potential biological basis of BCG cross-protection from severe COVID-19, and refine the epidemiological analysis to mitigate effects of potentially confounding factors (e.g., stage of the COVID-19 epidemic, development, rurality, population density, and age structure). A strong correlation between the BCG index, an estimation of the degree of universal BCG vaccination deployment in a country, and COVID- 19 mortality in different socially similar European countries was observed (r² = 0.88; P = 8 × 10-7), indicating that every 10% increase in the BCG index was associated with a 10.4% reduction in COVID-19 mortality. Results fail to confirm the null hypothesis of no association between BCG vaccination and COVID-19 mortality, and suggest that BCG could have a protective effect. Nevertheless, the analyses are restricted to coarse-scale signals and should be considered with caution. BCG vaccination clinical trials are required to corroborate the patterns detected here, and to establish causality between BCG vaccination and protection from severe COVID- 19. Public health implications of a plausible BCG cross-protection from severe COVID-19 are discussed. [ABSTRACT FROM AUTHOR]

Published
2020
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14. A Cross Sectional Sampling Reveals Novel Coronaviruses in Bat Populations of Georgia.

Author

Urushadze, Lela, Babuadze, George, Shi, Mang, Escobar, Luis E., Mauldin, Matthew R., Natradeze, Ioseb, Machablishvili, Ann, Kutateladze, Tamar, Imnadze, Paata, Nakazawa, Yoshinori, and Velasco-Villa, Andres

Subjects
COVID-19, BATS, CORONAVIRUSES, BETACORONAVIRUS, GENETIC distance, PANDEMICS, DEMOGRAPHIC surveys, AMINO acids
Abstract

Mammal-associated coronaviruses have a long evolutionary history across global bat populations, which makes them prone to be the most likely ancestral origins of coronavirus-associated epidemics and pandemics globally. Limited coronavirus research has occurred at the junction of Europe and Asia, thereby investigations in Georgia are critical to complete the coronavirus diversity map in the region. We conducted a cross-sectional coronavirus survey in bat populations at eight locations of Georgia, from July to October of 2014. We tested 188 anal swab samples, remains of previous pathogen discovery studies, for the presence of coronaviruses using end-point pan-coronavirus RT-PCR assays. Samples positive for a 440 bp amplicon were Sanger sequenced to infer coronavirus subgenus or species through phylogenetic reconstructions. Overall, we found a 24.5% positive rate, with 10.1% for Alphacoronavirus and 14.4% for Betacoronavirus. Albeit R. euryale, R. ferrumequinum, M. blythii and M. emarginatus were found infected with both CoV genera, we could not rule out CoV co-infection due to limitation of the sequencing method used and sample availability. Based on phylogenetic inferences and genetic distances at nucleotide and amino acid levels, we found one putative new subgenus and three new species of Alphacoronavirus, and two new species of Betacoronavirus. [ABSTRACT FROM AUTHOR]

Published
2022
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16. Hyperglycemia in acute COVID-19 is characterized by insulin resistance and adipose tissue infectivity by SARS-CoV-2.

Author

Reiterer, Moritz, Rajan, Mangala, Gómez-Banoy, Nicolás, Lau, Jennifer D., Gomez-Escobar, Luis G., Ma, Lunkun, Gilani, Ankit, Alvarez-Mulett, Sergio, Sholle, Evan T., Chandar, Vasuretha, Bram, Yaron, Hoffman, Katherine, Bhardwaj, Priya, Piloco, Phoebe, Rubio-Navarro, Alfonso, Uhl, Skyler, Carrau, Lucia, Houhgton, Sean, Redmond, David, and Shukla, Alpana P.

Abstract

Individuals infected with SARS-CoV-2 who also display hyperglycemia suffer from longer hospital stays, higher risk of developing acute respiratory distress syndrome (ARDS), and increased mortality. Nevertheless, the pathophysiological mechanism of hyperglycemia in COVID-19 remains poorly characterized. Here, we show that hyperglycemia is similarly prevalent among patients with ARDS independent of COVID-19 status. Yet among patients with ARDS and COVID-19, insulin resistance is the prevalent cause of hyperglycemia, independent of glucocorticoid treatment, which is unlike patients with ARDS but without COVID-19, where pancreatic beta cell failure predominates. A screen of glucoregulatory hormones revealed lower levels of adiponectin in patients with COVID-19. Hamsters infected with SARS-CoV-2 demonstrated a strong antiviral gene expression program in the adipose tissue and diminished expression of adiponectin. Moreover, we show that SARS-CoV-2 can infect adipocytes. Together these data suggest that SARS-CoV-2 may trigger adipose tissue dysfunction to drive insulin resistance and adverse outcomes in acute COVID-19. [Display omitted] • Hyperglycemia is highly prevalent in acute respiratory distress syndrome ± COVID-19 • Insulin resistance is the main cause for hyperglycemia in patients with severe COVID-19 • Patients with COVID-19 and hamsters infected with SARS-CoV-2 have decreased adiponectin • SARS-CoV-2 can directly infect human and mouse adipocytes Here, Reiterer et al. report that hyperglycemia in critically ill patients with COVID-19 is caused mainly by insulin resistance and is associated with decreased circulating adiponectin. SARS-CoV-2 is shown to directly infect human adipocytes, trigger an inflammatory antiviral response in the adipose tissue, and cause its dysfunction. [ABSTRACT FROM AUTHOR]

Published
2021
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