Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)

Detalhes bibliográficos
Autor(a) principal: Vizcaychipi,Marcela P.
Data de Publicação: 2020
Outros Autores: Shovlin,Claire L., McCarthy,Alex, Godfrey,Andrew, Patel,Sheena, Shah,Pallav L., Hayes,Michelle, Keays,Richard T., Beveridge,Iain, Davies,Gary
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Infectious Diseases
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-86702020000500412
Resumo: Abstract Introduction Our goal was to evaluate if traffic-light driven personalized care for COVID-19 was associated with improved survival in acute hospital settings. Methods Discharge outcomes were evaluated before and after prospective implementation of a real-time dashboard with feedback to ward-based clinicians. Thromboembolism categories were “medium-risk” (D-dimer >1000 ng/mL or CRP >200 mg/L); “high-risk” (D-dimer >3000 ng/mL or CRP >250 mg/L) or “suspected” (D-dimer >5000 ng/mL). Cytokine storm risk was categorized by ferritin. Results 939/1039 COVID-19 positive patients (median age 67 years, 563/939 (60%) male) completed hospital encounters to death or discharge by 21st May 2020. Thromboembolism flag criteria were reached by 568/939 (60.5%), including 238/275 (86.6%) of the patients who died, and 330/664 (49.7%) of the patients who survived to discharge, p < 0.0001. Cytokine storm flag criteria were reached by 212 (22.6%) of admissions, including 80/275 (29.1%) of the patients who died, and 132/664 (19.9%) of the patients who survived, p < 0.0001. The maximum thromboembolism flag discriminated completed encounter mortality (no flag: 37/371 [9.97%] died; medium-risk: 68/239 [28.5%]; high-risk: 105/205 [51.2%]; and suspected thromboembolism: 65/124 [52.4%], p < 0.0001). Flag criteria were reached by 535 consecutive COVID-19 positive patients whose hospital encounter completed before traffic-light introduction: 173/535 (32.3% [95% confidence intervals 28.0, 36.0]) died. For the 200 consecutive admissions after implementation of real-time traffic light flags, 46/200 (23.0% [95% confidence intervals 17.1, 28.9]) died, p = 0.013. Adjusted for age and sex, the probability of death was 0.33 (95% confidence intervals 0.30, 0.37) before traffic light implementation, 0.22 (0.17, 0.27) after implementation, p < 0.001. In subgroup analyses, older patients, males, and patients with hypertension (p ≤ 0.01), and/or diabetes (p = 0.05) derived the greatest benefit from admission under the traffic light system. Conclusion Personalized early interventions were associated with a 33% reduction in early mortality. We suggest benefit predominantly resulted from early triggers to review/enhance anticoagulation management, without exposing lower-risk patients to potential risks of full anticoagulation therapy.
id BSID-1_1181c584a021fe7f7503fbc6125b3f97
oai_identifier_str oai:scielo:S1413-86702020000500412
network_acronym_str BSID-1
network_name_str Brazilian Journal of Infectious Diseases
repository_id_str
spelling Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)AnticoagulationC-reactive proteinD-dimerDischargeFerritinMortalitySARS-CoV2Abstract Introduction Our goal was to evaluate if traffic-light driven personalized care for COVID-19 was associated with improved survival in acute hospital settings. Methods Discharge outcomes were evaluated before and after prospective implementation of a real-time dashboard with feedback to ward-based clinicians. Thromboembolism categories were “medium-risk” (D-dimer >1000 ng/mL or CRP >200 mg/L); “high-risk” (D-dimer >3000 ng/mL or CRP >250 mg/L) or “suspected” (D-dimer >5000 ng/mL). Cytokine storm risk was categorized by ferritin. Results 939/1039 COVID-19 positive patients (median age 67 years, 563/939 (60%) male) completed hospital encounters to death or discharge by 21st May 2020. Thromboembolism flag criteria were reached by 568/939 (60.5%), including 238/275 (86.6%) of the patients who died, and 330/664 (49.7%) of the patients who survived to discharge, p < 0.0001. Cytokine storm flag criteria were reached by 212 (22.6%) of admissions, including 80/275 (29.1%) of the patients who died, and 132/664 (19.9%) of the patients who survived, p < 0.0001. The maximum thromboembolism flag discriminated completed encounter mortality (no flag: 37/371 [9.97%] died; medium-risk: 68/239 [28.5%]; high-risk: 105/205 [51.2%]; and suspected thromboembolism: 65/124 [52.4%], p < 0.0001). Flag criteria were reached by 535 consecutive COVID-19 positive patients whose hospital encounter completed before traffic-light introduction: 173/535 (32.3% [95% confidence intervals 28.0, 36.0]) died. For the 200 consecutive admissions after implementation of real-time traffic light flags, 46/200 (23.0% [95% confidence intervals 17.1, 28.9]) died, p = 0.013. Adjusted for age and sex, the probability of death was 0.33 (95% confidence intervals 0.30, 0.37) before traffic light implementation, 0.22 (0.17, 0.27) after implementation, p < 0.001. In subgroup analyses, older patients, males, and patients with hypertension (p ≤ 0.01), and/or diabetes (p = 0.05) derived the greatest benefit from admission under the traffic light system. Conclusion Personalized early interventions were associated with a 33% reduction in early mortality. We suggest benefit predominantly resulted from early triggers to review/enhance anticoagulation management, without exposing lower-risk patients to potential risks of full anticoagulation therapy.Brazilian Society of Infectious Diseases2020-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-86702020000500412Brazilian Journal of Infectious Diseases v.24 n.5 2020reponame:Brazilian Journal of Infectious Diseasesinstname:Brazilian Society of Infectious Diseases (BSID)instacron:BSID10.1016/j.bjid.2020.07.010info:eu-repo/semantics/openAccessVizcaychipi,Marcela P.Shovlin,Claire L.McCarthy,AlexGodfrey,AndrewPatel,SheenaShah,Pallav L.Hayes,MichelleKeays,Richard T.Beveridge,IainDavies,Garyeng2020-11-26T00:00:00Zoai:scielo:S1413-86702020000500412Revistahttps://www.bjid.org.br/https://old.scielo.br/oai/scielo-oai.phpbjid@bjid.org.br||lgoldani@ufrgs.br1678-43911413-8670opendoar:2020-11-26T00:00Brazilian Journal of Infectious Diseases - Brazilian Society of Infectious Diseases (BSID)false
dc.title.none.fl_str_mv Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)
title Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)
spellingShingle Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)
Vizcaychipi,Marcela P.
Anticoagulation
C-reactive protein
D-dimer
Discharge
Ferritin
Mortality
SARS-CoV2
title_short Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)
title_full Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)
title_fullStr Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)
title_full_unstemmed Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)
title_sort Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)
author Vizcaychipi,Marcela P.
author_facet Vizcaychipi,Marcela P.
Shovlin,Claire L.
McCarthy,Alex
Godfrey,Andrew
Patel,Sheena
Shah,Pallav L.
Hayes,Michelle
Keays,Richard T.
Beveridge,Iain
Davies,Gary
author_role author
author2 Shovlin,Claire L.
McCarthy,Alex
Godfrey,Andrew
Patel,Sheena
Shah,Pallav L.
Hayes,Michelle
Keays,Richard T.
Beveridge,Iain
Davies,Gary
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Vizcaychipi,Marcela P.
Shovlin,Claire L.
McCarthy,Alex
Godfrey,Andrew
Patel,Sheena
Shah,Pallav L.
Hayes,Michelle
Keays,Richard T.
Beveridge,Iain
Davies,Gary
dc.subject.por.fl_str_mv Anticoagulation
C-reactive protein
D-dimer
Discharge
Ferritin
Mortality
SARS-CoV2
topic Anticoagulation
C-reactive protein
D-dimer
Discharge
Ferritin
Mortality
SARS-CoV2
description Abstract Introduction Our goal was to evaluate if traffic-light driven personalized care for COVID-19 was associated with improved survival in acute hospital settings. Methods Discharge outcomes were evaluated before and after prospective implementation of a real-time dashboard with feedback to ward-based clinicians. Thromboembolism categories were “medium-risk” (D-dimer >1000 ng/mL or CRP >200 mg/L); “high-risk” (D-dimer >3000 ng/mL or CRP >250 mg/L) or “suspected” (D-dimer >5000 ng/mL). Cytokine storm risk was categorized by ferritin. Results 939/1039 COVID-19 positive patients (median age 67 years, 563/939 (60%) male) completed hospital encounters to death or discharge by 21st May 2020. Thromboembolism flag criteria were reached by 568/939 (60.5%), including 238/275 (86.6%) of the patients who died, and 330/664 (49.7%) of the patients who survived to discharge, p < 0.0001. Cytokine storm flag criteria were reached by 212 (22.6%) of admissions, including 80/275 (29.1%) of the patients who died, and 132/664 (19.9%) of the patients who survived, p < 0.0001. The maximum thromboembolism flag discriminated completed encounter mortality (no flag: 37/371 [9.97%] died; medium-risk: 68/239 [28.5%]; high-risk: 105/205 [51.2%]; and suspected thromboembolism: 65/124 [52.4%], p < 0.0001). Flag criteria were reached by 535 consecutive COVID-19 positive patients whose hospital encounter completed before traffic-light introduction: 173/535 (32.3% [95% confidence intervals 28.0, 36.0]) died. For the 200 consecutive admissions after implementation of real-time traffic light flags, 46/200 (23.0% [95% confidence intervals 17.1, 28.9]) died, p = 0.013. Adjusted for age and sex, the probability of death was 0.33 (95% confidence intervals 0.30, 0.37) before traffic light implementation, 0.22 (0.17, 0.27) after implementation, p < 0.001. In subgroup analyses, older patients, males, and patients with hypertension (p ≤ 0.01), and/or diabetes (p = 0.05) derived the greatest benefit from admission under the traffic light system. Conclusion Personalized early interventions were associated with a 33% reduction in early mortality. We suggest benefit predominantly resulted from early triggers to review/enhance anticoagulation management, without exposing lower-risk patients to potential risks of full anticoagulation therapy.
publishDate 2020
dc.date.none.fl_str_mv 2020-10-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-86702020000500412
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-86702020000500412
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1016/j.bjid.2020.07.010
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Brazilian Society of Infectious Diseases
publisher.none.fl_str_mv Brazilian Society of Infectious Diseases
dc.source.none.fl_str_mv Brazilian Journal of Infectious Diseases v.24 n.5 2020
reponame:Brazilian Journal of Infectious Diseases
instname:Brazilian Society of Infectious Diseases (BSID)
instacron:BSID
instname_str Brazilian Society of Infectious Diseases (BSID)
instacron_str BSID
institution BSID
reponame_str Brazilian Journal of Infectious Diseases
collection Brazilian Journal of Infectious Diseases
repository.name.fl_str_mv Brazilian Journal of Infectious Diseases - Brazilian Society of Infectious Diseases (BSID)
repository.mail.fl_str_mv bjid@bjid.org.br||lgoldani@ufrgs.br
_version_ 1754209245103915008