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Risk Factors for Intensive Care Unit Admission and In-hospital Mortality Among Hospitalized Adults Identified through the US Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET).
Kim, Lindsay; Garg, Shikha; O'Halloran, Alissa; Whitaker, Michael; Pham, Huong; Anderson, Evan J; Armistead, Isaac; Bennett, Nancy M; Billing, Laurie; Como-Sabetti, Kathryn; Hill, Mary; Kim, Sue; Monroe, Maya L; Muse, Alison; Reingold, Arthur L; Schaffner, William; Sutton, Melissa; Talbot, H Keipp; Torres, Salina M; Yousey-Hindes, Kimberly; Holstein, Rachel; Cummings, Charisse; Brammer, Lynnette; Hall, Aron J; Fry, Alicia M; Langley, Gayle E.
  • Kim L; Coronavirus Disease 2019 (COVID-19) Associated Hospitalization Surveillance Network (COVID-NET) Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
  • Garg S; US Public Health Service, Rockville, Maryland, USA.
  • O'Halloran A; Coronavirus Disease 2019 (COVID-19) Associated Hospitalization Surveillance Network (COVID-NET) Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
  • Whitaker M; US Public Health Service, Rockville, Maryland, USA.
  • Pham H; Coronavirus Disease 2019 (COVID-19) Associated Hospitalization Surveillance Network (COVID-NET) Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
  • Anderson EJ; Coronavirus Disease 2019 (COVID-19) Associated Hospitalization Surveillance Network (COVID-NET) Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
  • Armistead I; Eagle Global Scientific, Atlanta, Georgia, USA.
  • Bennett NM; Coronavirus Disease 2019 (COVID-19) Associated Hospitalization Surveillance Network (COVID-NET) Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
  • Billing L; Department of Medicine and Pediatrics, Emory University School of Medicine, Atlanta, Georgia, USA.
  • Como-Sabetti K; Emerging Infections Program, Georgia Department of Health, Atlanta, Georgia, USA.
  • Hill M; Veterans Affairs Medical Center, Atlanta, Georgia, USA.
  • Kim S; University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
  • Monroe ML; University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
  • Muse A; Ohio Department of Health, Columbus, Ohio, USA.
  • Reingold AL; Minnesota Department of Health, St. Paul, Minnesota, USA.
  • Schaffner W; Salt Lake County Health Department, Salt Lake City, Utah, USA.
  • Sutton M; Michigan Department of Health and Human Services, Lansing, Michigan, USA.
  • Talbot HK; Maryland Department of Health, Baltimore, Maryland, USA.
  • Torres SM; New York State Department of Health, Albany, New York, USA.
  • Yousey-Hindes K; University of California, Berkeley, Berkeley, California, USA.
  • Holstein R; Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
  • Cummings C; Oregon Health Authority, Portland, Oregon, USA.
  • Brammer L; Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
  • Hall AJ; New Mexico Department of Health, Santa Fe, New Mexico, USA.
  • Fry AM; Connecticut Emerging Infections Program, Yale School of Public Health, New Haven, Connecticut, USA.
  • Langley GE; Coronavirus Disease 2019 (COVID-19) Associated Hospitalization Surveillance Network (COVID-NET) Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Clin Infect Dis ; 72(9): e206-e214, 2021 05 04.
Article in English | MEDLINE | ID: covidwho-649371
ABSTRACT

BACKGROUND:

Currently, the United States has the largest number of reported coronavirus disease 2019 (COVID-19) cases and deaths globally. Using a geographically diverse surveillance network, we describe risk factors for severe outcomes among adults hospitalized with COVID-19.

METHODS:

We analyzed data from 2491 adults hospitalized with laboratory-confirmed COVID-19 between 1 March-2 May 2020, as identified through the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network, which comprises 154 acute-care hospitals in 74 counties in 13 states. We used multivariable analyses to assess associations between age, sex, race and ethnicity, and underlying conditions with intensive care unit (ICU) admission and in-hospital mortality.

RESULTS:

The data show that 92% of patients had ≥1 underlying condition; 32% required ICU admission; 19% required invasive mechanical ventilation; and 17% died. Independent factors associated with ICU admission included ages 50-64, 65-74, 75-84, and ≥85 years versus 18-39 years (adjusted risk ratios [aRRs], 1.53, 1.65, 1.84, and 1.43, respectively); male sex (aRR, 1.34); obesity (aRR, 1.31); immunosuppression (aRR, 1.29); and diabetes (aRR, 1.13). Independent factors associated with in-hospital mortality included ages 50-64, 65-74, 75-84, and ≥ 85 years versus 18-39 years (aRRs, 3.11, 5.77, 7.67, and 10.98, respectively); male sex (aRR, 1.30); immunosuppression (aRR, 1.39); renal disease (aRR, 1.33); chronic lung disease (aRR 1.31); cardiovascular disease (aRR, 1.28); neurologic disorders (aRR, 1.25); and diabetes (aRR, 1.19).

CONCLUSIONS:

In-hospital mortality increased markedly with increasing age. Aggressive implementation of prevention strategies, including social distancing and rigorous hand hygiene, may benefit the population as a whole, as well as those at highest risk for COVID-19-related complications.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Limits: Adult / Humans / Male / Middle aged Country/Region as subject: North America Language: English Journal: Clin Infect Dis Journal subject: Communicable Diseases Year: 2021 Document Type: Article Affiliation country: Cid

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study / Prognostic study Limits: Adult / Humans / Male / Middle aged Country/Region as subject: North America Language: English Journal: Clin Infect Dis Journal subject: Communicable Diseases Year: 2021 Document Type: Article Affiliation country: Cid