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Accuracy of the Veterans Health Administration COVID-19 (VACO) Index for predicting short-term mortality among 1307 US academic medical centre inpatients and 427 224 US Medicare patients.
King, Joseph T; Yoon, James S; Bredl, Zachary M; Habboushe, Joseph P; Walker, Graham A; Rentsch, Christopher T; Tate, Janet P; Kashyap, Nitu M; Hintz, Richard C; Chopra, Aneesh P; Justice, Amy C.
  • King JT; VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA joseph.king@yale.edu.
  • Yoon JS; Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut, USA.
  • Bredl ZM; Yale School of Medicine, New Haven, Connecticut, USA.
  • Habboushe JP; CareJourney, Arlington, Virginia, USA.
  • Walker GA; Emergency Medicine, Weill Cornell Medicine, New York, New York, USA.
  • Rentsch CT; MDCalc.com, New York, New York, USA.
  • Tate JP; MDCalc.com, New York, New York, USA.
  • Kashyap NM; Emergency Medicine, Kaiser Permanente, Oakland, California, USA.
  • Hintz RC; VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA.
  • Chopra AP; Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
  • Justice AC; VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA.
J Epidemiol Community Health ; 76(3): 254-260, 2022 03.
Article in English | MEDLINE | ID: covidwho-1443618
ABSTRACT

BACKGROUND:

The Veterans Health Administration COVID-19 (VACO) Index predicts 30-day all-cause mortality in patients with COVID-19 using age, sex and pre-existing comorbidity diagnoses. The VACO Index was initially developed and validated in a nationwide cohort of US veterans-we now assess its accuracy in an academic medical centre and a nationwide US Medicare cohort.

METHODS:

With measures and weights previously derived and validated in US national Veterans Health Administration (VA) inpatients and outpatients (n=13 323), we evaluated the accuracy of the VACO Index for estimating 30-day all-cause mortality using area under the receiver operating characteristic curve (AUC) and calibration plots of predicted versus observed mortality in inpatients at a single US academic medical centre (n=1307) and in Medicare inpatients and outpatients aged 65+ (n=427 224).

RESULTS:

30-day mortality varied by data source VA 8.5%, academic medical centre 17.5%, Medicare 16.0%. The VACO Index demonstrated similar discrimination in VA (AUC=0.82) and academic medical centre inpatient population (AUC=0.80), and when restricted to patients aged 65+ in VA (AUC=0.69) and Medicare inpatient and outpatient data (AUC=0.67). The Index modestly overestimated risk in VA and Medicare data and underestimated risk in Yale New Haven Hospital data.

CONCLUSIONS:

The VACO Index estimates risk of short-term mortality across a wide variety of patients with COVID-19 using data available prior to or at the time of diagnosis. The VACO Index could help inform primary and booster vaccination prioritisation, and indicate who among outpatients testing positive for SARS-CoV-2 should receive greater clinical attention or scarce treatments.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Veterans / COVID-19 Type of study: Observational study / Prognostic study / Risk factors Limits: Aged / Humans Country/Region as subject: North America Language: English Journal: J Epidemiol Community Health Year: 2022 Document Type: Article Affiliation country: Jech-2021-216697

Full text: Available Collection: International databases Database: MEDLINE Main subject: Veterans / COVID-19 Type of study: Observational study / Prognostic study / Risk factors Limits: Aged / Humans Country/Region as subject: North America Language: English Journal: J Epidemiol Community Health Year: 2022 Document Type: Article Affiliation country: Jech-2021-216697