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Covid-19 in Critically Ill Patients in the Seattle Region — Case Series
Open accessAbstract
BACKGROUND: Community transmission of coronavirus 2019 (Covid-19) was detected in the state of Washington in February 2020. METHODS: We identified patients from nine Seattle-area hospitals who were admitted to the intensive care unit (ICU) with confirmed infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Clinical data were obtained through review of medical records. The data reported here are those available through March 23, 2020. Each patient had at least 14 days of follow-up. RESULTS: We identified 24 patients with confirmed Covid-19. The mean (±SD) age of the patients was 64±18 years, 63% were men, and symptoms began 7±4 days before admission. The most common symptoms were cough and shortness of breath; 50% of patients had fever on admission, and 58% had diabetes mellitus. All the patients were admitted for hypoxemic respiratory failure; 75% (18 patients) needed mechanical ventilation. Most of the patients (17) also had hypotension and needed vasopressors. No patient tested positive for influenza A, influenza B, or other respiratory viruses. Half the patients (12) died between ICU day 1 and day 18, including 4 patients who had a do-not-resuscitate order on admission. Of the 12 surviving patients, 5 were discharged home, 4 were discharged from the ICU but remained in the hospital, and 3 continued to receive mechanical ventilation in the ICU. CONCLUSIONS: During the first 3 weeks of the Covid-19 outbreak in the Seattle area, the most common reasons for admission to the ICU were hypoxemic respiratory failure leading to mechanical ventilation, hypotension requiring vasopressor treatment, or both. Mortality among these critically ill patients was high. (Funded by the National Institutes of Health.).
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Cites
Clinical characteristics of coronavirus disease 2019 in China
Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., Liu, L., Shan, H., Lei, C.-L., Hui, D. S. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2002032 · Cited by 30,246
First case of 2019 novel coronavirus in the United States
Holshue, M. L., DeBolt, C., Lindquist, S., Lofy, K. H., Wiesman, J., Bruce, H., Spitters, C., Ericson, K., Wilkerson, S., Tural, A., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001191 · Cited by 6,030
Prone positioning in severe acute respiratory distress syndrome.
Guérin, C., Reignier, J., Richard, J.-C., Beuret, P., Gacouin, A., Boulain, T., Mercier, E., Badet, M., Mercat, A., Baudin, O., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1214103 · Cited by 4,040
Characteristics and outcomes of 21 critically ill patients with COVID-19 in Washington State
Arentz, M., Yim, E., Klaff, L., Lokhandwala, S., Riedo, F. X., Chong, M., & Lee, M. (2020) · JAMA · doi:10.1001/jama.2020.4326 · Cited by 2,259
Early Neuromuscular Blockade in the Acute Respiratory Distress Syndrome
The National Heart, L. (2019) · New England Journal of Medicine · doi:10.1056/nejmoa1901686 · Cited by 886
Lansbury, L. E., Rodrigo, C., Leonardi-Bee, J., Nguyen-Van-Tam, J., & Shen Lim, W. (2020) · Critical Care Medicine · doi:10.1097/ccm.0000000000004093 · Cited by 207
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Extrapulmonary manifestations of COVID-19
Gupta, A., Madhavan, M. V., Sehgal, K., Nair, N., Mahajan, S., Sehrawat, T. S., Bikdeli, B., Ahluwalia, N., Ausiello, J. C., Wan, E. Y., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0968-3 · Cited by 3,185
Hospitalization and mortality among Black patients and White patients with Covid-19.
Price-Haywood, E. G., Burton, J., Fort, D., & Seoane, L. (2020) · New England Journal of Medicine · doi:10.1056/nejmsa2011686 · Cited by 1,660
Rawson, T. M., Moore, L. S. P., Zhu, N., Ranganathan, N., Skolimowska, K., Gilchrist, M., Satta, G., Cooke, G., & Holmes, A. (2020) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa530 · Cited by 1,662
Co-infections in people with COVID-19: a systematic review and meta-analysis.
Lansbury, L., Lim, B., Baskaran, V., & Lim, W. S. (2020) · Journal of Infection · doi:10.1016/j.jinf.2020.05.046 · Cited by 1,619
Acute kidney injury in patients hospitalized with COVID-19
Hirsch, J. S., Ng, J. H., Ross, D. W., Sharma, P., Shah, H. H., Barnett, R. L., Hazzan, A. D., Fishbane, S., Jhaveri, K. D., Abate, M., et al. (2020) · Kidney International · doi:10.1016/j.kint.2020.05.006 · Cited by 1,523
Popkin, B. M., Du, S., Green, W. D., Beck, M. A., Algaith, T., Herbst, C. H., Alsukait, R. F., Alluhidan, M., Alazemi, N., & Shekar, M. (2020) · Obesity Reviews · doi:10.1111/obr.13128 · Cited by 1,150
Why does COVID-19 disproportionately affect older people?
Mueller, A. L., McNamara, M. S., & Sinclair, D. A. (2020) · Aging · doi:10.18632/aging.103344 · Cited by 1,128
Factors associated with death in critically ill patients with coronavirus disease 2019 in the US
Gupta, S., Hayek, S. S., Wang, W., Chan, L., Mathews, K. S., Melamed, M. L., Brenner, S. K., Leonberg-Yoo, A., Schenck, E. J., Radbel, J., et al. (2020) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2020.3596 · Cited by 957
Self-citationCOVID-19 antibody seroprevalence in santa clara county, california
Bendavid, E., Mulaney, B., Sood, N., Shah, S., Bromley-Dulfano, R., Lai, C., Weissberg, Z., Saavedra-Walker, R., Tedrow, J., Bogan, A., et al. (2021) · International Journal of Epidemiology · doi:10.1093/ije/dyab010 · Cited by 669
Kim, L., Garg, S., O’Halloran, A., Whitaker, M., Pham, H., Anderson, E. J., Armistead, I., Bennett, N. M., Billing, L., Como-Sabetti, K., et al. (2021) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa1012 · Cited by 649
Obesity and impaired metabolic health in patients with COVID-19
Stefan, N., Birkenfeld, A. L., Schulze, M. B., & Ludwig, D. S. (2020) · Nature Reviews Endocrinology · doi:10.1038/s41574-020-0364-6 · Cited by 626
Description and Proposed Management of the Acute COVID-19 Cardiovascular Syndrome
Hendren, N. S., Drazner, M. H., Bozkurt, B., & Cooper, L. T. (2020) · Circulation · doi:10.1161/circulationaha.120.047349 · Cited by 576
Gupta, S., Wang, W., Hayek, S. S., Chan, L., Mathews, K. S., Melamed, M. L., Brenner, S. K., Leonberg-Yoo, A., Schenck, E. J., Radbel, J., et al. (2021) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2020.6252 · Cited by 535
Self-citationMultiplexed Nanomaterial-Based Sensor Array for Detection of COVID-19 in Exhaled Breath
Shan, B., Broza, Y. Y., Li, W., Wang, Y., Wu, S., Liu, Z., Wang, J., Gui, S., Wang, L., Zhang, Z., et al. (2020) · ACS Nano · doi:10.1021/acsnano.0c05657 · Cited by 384
Managing ICU surge during the COVID-19 crisis: Rapid guidelines.
Aziz, S., Arabi, Y. M., Alhazzani, W., Evans, L., Citerio, G., Fischkoff, K., Salluh, J., Meyfroidt, G., Alshamsi, F., Oczkowski, S., et al. (2020) · Intensive Care Medicine · doi:10.1007/s00134-020-06092-5 · Cited by 380
Self-citationDistinct Early Serological Signatures Track with SARS-CoV-2 Survival
Atyeo, C., Fischinger, S., Zohar, T., Slein, M. D., Burke, J., Loos, C., McCulloch, D. J., Newman, K. L., Wolf, C., Yu, J., et al. (2020) · Immunity · doi:10.1016/j.immuni.2020.07.020 · Cited by 349
COVID-19 deaths in Africa: prospective systematic postmortem surveillance study
Mwananyanda, L., Gill, C. J., MacLeod, W., Kwenda, G., Pieciak, R., Mupila, Z., Lapidot, R., Mupeta, F., Forman, L., Ziko, L., et al. (2021) · BMJ · doi:10.1136/bmj.n334 · Cited by 211
Singh, R., Rathore, S. S., Khan, H., Karale, S., Chawla, Y., Iqbal, K., Bhurwal, A., Tekin, A., Jain, N., Mehra, I., et al. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.780872 · Cited by 193
Zhou, Y., Hou, Y., Shen, J., Mehra, R., Kallianpur, A., Culver, D. A., Gack, M. U., Farha, S., Zein, J., Comhair, S., et al. (2020) · PLoS Biology · doi:10.1371/journal.pbio.3000970 · Cited by 180
Anesi, G. L., Jablonski, J., Harhay, M. O., Atkins, J. H., Bajaj, J., Baston, C., Brennan, P. J., Candeloro, C. L., Catalano, L. M., Cereda, M. F., et al. (2021) · Annals of Internal Medicine · doi:10.7326/m20-5327 · Cited by 115
Fraser, D. D., Slessarev, M., Martin, C. M., Daley, M., Patel, M. A., Miller, M. R., Patterson, E. K., O’Gorman, D. B., Gill, S. E., Wishart, D. S., et al. (2020) · Critical Care Explorations · doi:10.1097/cce.0000000000000272 · Cited by 114
Equitably Allocating Resources during Crises: Racial Differences in Mortality Prediction Models
Ashana, D. C., Anesi, G. L., Liu, V. X., Escobar, G. J., Chesley, C., Eneanya, N. D., Weissman, G. E., Miller, W. D., Harhay, M. O., & Halpern, S. D. (2021) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.202012-4383oc · Cited by 98
Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort
Magunia, H., Lederer, S., Verbuecheln, R., Gilot, B. J., Koeppen, M., Haeberle, H. A., Mirakaj, V., Hofmann, P., Marx, G., Bickenbach, J., et al. (2021) · Critical Care · doi:10.1186/s13054-021-03720-4 · Cited by 65
Amass, T., Van Scoy, L. J., Hua, M., Ambler, M., Armstrong, P., Baldwin, M. R., Bernacki, R., Burhani, M. D., Chiurco, J., Cooper, Z., et al. (2022) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2022.1118 · Cited by 61
Correlation analysis of the severity and clinical prognosis of 32 cases of patients with COVID-19
Ding, M., Zhang, Q., Li, Q., Wu, T., & Huang, Y.-Z. (2020) · Respiratory Medicine · doi:10.1016/j.rmed.2020.105981 · Cited by 60
Zhong, M., Sun, A., Xiao, T., Yao, G., Sang, L., Zheng, X., Zhang, J., Jin, X., Xu, L., Yang, W., et al. (2020) · doi:10.1101/2020.04.15.20066266 · Cited by 53
COVID-19 and Avoiding Ibuprofen. How Good Is the Evidence?
Kutti Sridharan, G., Kotagiri, R., Chandiramani, V. H., Mohan, B. P., Vegunta, R., Vegunta, R., & Rokkam, V. R. P. (2020) · American Journal of Therapeutics · doi:10.1097/mjt.0000000000001196 · Cited by 34
Sands, K. E., Wenzel, R. P., McLean, L. E., Korwek, K. M., Roach, J. D., Miller, K. M., Poland, R. E., Burgess, L. H., Jackson, E. S., & Perlin, J. B. (2021) · Infection Control & Hospital Epidemiology · doi:10.1017/ice.2020.461 · Cited by 29
Quattrocchi, A., Mamais, I., Tsioutis, C., Christaki, E., Constantinou, C., Koliou, M., Pana, Z.-D., Silvestros, V., Theophanous, F., Haralambous, C., et al. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9113598 · Cited by 28
Jain, A., Bruno, K. A., Matsumori, A., Cooper, L. T., Yamani, M., & Fairweather, D. (2022) · Comprehensive Pharmacology · doi:10.1016/b978-0-12-820472-6.00091-8 · Cited by 1
Metadata
- Authors
- Bhatraju, P. K., Ghassemieh, B. J., Nichols, M., Kim, R., Jerome, K. R., Nalla, A. K., Greninger, A. L., Pipavath, S., Wurfel, M. M., Evans, L., Kritek, P. A., West, T. E., Luks, A., Gerbino, A., Dale, C. R., Goldman, J. D., O’Mahony, S., & Mikacenic, C.
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2020-05-21
- Volume
- 382
- Issue
- 21
- Pages
- 2012-2022
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W3013816672
- Cited by
- 2,583
- References
- 6
- FWCI
- 72.85
- Type
- journal article
- Language
- en
- Open access
- green
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