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Detecting early physiologic changes through cardiac implantable electronic device data among patients with COVID-19.
Reading Turchioe, Meghan; Ahmed, Rezwan; Masterson Creber, Ruth; Axsom, Kelly; Horn, Evelyn; Sayer, Gabriel; Uriel, Nir; Stein, Kenneth; Slotwiner, David.
Afiliación
  • Reading Turchioe M; Columbia University Irving Medical Center, New York, New York.
  • Ahmed R; Boston Scientific, Marlborough, Massachusetts.
  • Masterson Creber R; Weill Cornell Medicine, New York, New York.
  • Axsom K; Columbia University Irving Medical Center, New York, New York.
  • Horn E; Weill Cornell Medicine, New York, New York.
  • Sayer G; Columbia University Irving Medical Center, New York, New York.
  • Uriel N; Columbia University Irving Medical Center, New York, New York.
  • Stein K; Boston Scientific, Marlborough, Massachusetts.
  • Slotwiner D; Weill Cornell Medicine, New York, New York.
Cardiovasc Digit Health J ; 3(5): 247-255, 2022 Oct.
Article en En | MEDLINE | ID: mdl-35942055
Background: Cardiac implantable electronic devices (CIEDs) may enable early identification of COVID-19 to facilitate timelier intervention. Objective: To characterize early physiologic changes associated with the onset of acute COVID-19 infection, as well as during and after acute infection, among patients with CIEDs. Methods: CIED sensor data from March 2020 to February 2021 from 286 patients with a CIED were linked to clinical data from electronic health records. Three cohorts were created: known COVID-positive (n = 20), known COVID-negative (n = 166), and a COVID-untested control group (n = 100) included to account for testing bias. Associations between changes in CIED sensors from baseline (including HeartLogic index, a composite index predicting worsening heart failure) and COVID-19 status were evaluated using logistic regression models, Wilcoxon signed rank tests, and Mann-Whitney U tests. Results: Significant differences existed between the cohorts by race, ethnicity, CIED device type, and medical admissions. Several sensors changed earlier for COVID-positive vs COVID-negative patients: HeartLogic index (mean 16.4 vs 9.2 days [P = .08]), respiratory rate (mean 8.5 vs 3.9 days [P = .01], and activity (mean 8.2 vs 3.5 days [P = .008]). Respiratory rate during the 7 days before testing significantly predicted a positive vs negative COVID-19 test, adjusting for age, sex, race, and device type (odds ratio 2.31 [95% confidence interval 1.33-5.13]). Conclusion: Physiologic data from CIEDs could signal early signs of infection that precede clinical symptoms, which may be used to support early detection of infection to prevent decompensation in this at-risk population.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Screening_studies Idioma: En Revista: Cardiovasc Digit Health J Año: 2022 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
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XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Screening_studies Idioma: En Revista: Cardiovasc Digit Health J Año: 2022 Tipo del documento: Article Pais de publicación: Estados Unidos