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Can we clinically identify pre-symptomatic and asymptomatic COVID-19?
OBJECTIVES: COVID-19 has had a severe impact on morbidity and mortality among nursing home (NH) residents. Earlier detection of SARS-CoV-2 may position us to better mitigate risk of spread. Both asymptomatic or pre-symptomatic transmission are common in outbreaks, and threshold temperatures, such as...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328068/ https://www.ncbi.nlm.nih.gov/pubmed/34341800 http://dx.doi.org/10.1101/2021.07.23.21260676 |
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author | Elhamamsy, Salaheldin DeVone, Frank Bayer, Tom Halladay, Chris Cadieux, Marilyne McConeghy, Kevin Rajan, Ashna Sachar, Moniyka Mujahid, Nadia Nanda, Aman McNicoll, Lynn Rudolph, James L Gravenstein, Stefan |
author_facet | Elhamamsy, Salaheldin DeVone, Frank Bayer, Tom Halladay, Chris Cadieux, Marilyne McConeghy, Kevin Rajan, Ashna Sachar, Moniyka Mujahid, Nadia Nanda, Aman McNicoll, Lynn Rudolph, James L Gravenstein, Stefan |
author_sort | Elhamamsy, Salaheldin |
collection | PubMed |
description | OBJECTIVES: COVID-19 has had a severe impact on morbidity and mortality among nursing home (NH) residents. Earlier detection of SARS-CoV-2 may position us to better mitigate risk of spread. Both asymptomatic or pre-symptomatic transmission are common in outbreaks, and threshold temperatures, such as 38C, for screening for infection could miss timely detection in the majority. DESIGN: Retrospective cohort study using electronic health records METHODS: We hypothesized that in long-term care residents, temperature trends with SARS-CoV-2 infection could identify infection in pre-symptomatic and asymptomatic individuals earlier. We collected information about age and other demographics, baseline temperature, and specific comorbidities. We created standardized definitions, and an alternative hypothetical model to test measures of temperature variation and compare outcomes to the VA reality. SETTINGS AND PARTICIPANTS: Our subjects were 6,176 residents of the VA NHs who underwent SARS-CoV-2 trigger testing. RESULTS: We showed that a change from baseline of >0.4C identifies 47% of the SARS-CoV-2 positive NH residents early, and achieves earlier detection by 42.2 hours. Range improves early detection to 55% when paired with a 37.2C cutoff, and achieves earlier detection by 44.4 hours. Temperature elevation >0.4C from baseline, when combined with a 0.7C range, would detect 52% early, leading to earlier detection by more than 3 days in 22% of the residents. This earlier detection comes at the expense of triggering 57,793 tests, as compared to the number of trigger tests ordered in the VA system of 40,691. CONCLUSION AND IMPLICATIONS: Our model suggests that current clinical screening for SARS-CoV-2 in NHs can be substantially improved upon by triggering testing using a patient-derived baseline temperature with a 0.4C degree relative elevation or temperature variability of 0.7C trigger threshold for SARS-CoV2 testing. Such triggers could be automated in facilities that track temperatures in their electronic records. |
format | Online Article Text |
id | pubmed-8328068 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-83280682021-08-03 Can we clinically identify pre-symptomatic and asymptomatic COVID-19? Elhamamsy, Salaheldin DeVone, Frank Bayer, Tom Halladay, Chris Cadieux, Marilyne McConeghy, Kevin Rajan, Ashna Sachar, Moniyka Mujahid, Nadia Nanda, Aman McNicoll, Lynn Rudolph, James L Gravenstein, Stefan medRxiv Article OBJECTIVES: COVID-19 has had a severe impact on morbidity and mortality among nursing home (NH) residents. Earlier detection of SARS-CoV-2 may position us to better mitigate risk of spread. Both asymptomatic or pre-symptomatic transmission are common in outbreaks, and threshold temperatures, such as 38C, for screening for infection could miss timely detection in the majority. DESIGN: Retrospective cohort study using electronic health records METHODS: We hypothesized that in long-term care residents, temperature trends with SARS-CoV-2 infection could identify infection in pre-symptomatic and asymptomatic individuals earlier. We collected information about age and other demographics, baseline temperature, and specific comorbidities. We created standardized definitions, and an alternative hypothetical model to test measures of temperature variation and compare outcomes to the VA reality. SETTINGS AND PARTICIPANTS: Our subjects were 6,176 residents of the VA NHs who underwent SARS-CoV-2 trigger testing. RESULTS: We showed that a change from baseline of >0.4C identifies 47% of the SARS-CoV-2 positive NH residents early, and achieves earlier detection by 42.2 hours. Range improves early detection to 55% when paired with a 37.2C cutoff, and achieves earlier detection by 44.4 hours. Temperature elevation >0.4C from baseline, when combined with a 0.7C range, would detect 52% early, leading to earlier detection by more than 3 days in 22% of the residents. This earlier detection comes at the expense of triggering 57,793 tests, as compared to the number of trigger tests ordered in the VA system of 40,691. CONCLUSION AND IMPLICATIONS: Our model suggests that current clinical screening for SARS-CoV-2 in NHs can be substantially improved upon by triggering testing using a patient-derived baseline temperature with a 0.4C degree relative elevation or temperature variability of 0.7C trigger threshold for SARS-CoV2 testing. Such triggers could be automated in facilities that track temperatures in their electronic records. Cold Spring Harbor Laboratory 2021-07-26 /pmc/articles/PMC8328068/ /pubmed/34341800 http://dx.doi.org/10.1101/2021.07.23.21260676 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Elhamamsy, Salaheldin DeVone, Frank Bayer, Tom Halladay, Chris Cadieux, Marilyne McConeghy, Kevin Rajan, Ashna Sachar, Moniyka Mujahid, Nadia Nanda, Aman McNicoll, Lynn Rudolph, James L Gravenstein, Stefan Can we clinically identify pre-symptomatic and asymptomatic COVID-19? |
title | Can we clinically identify pre-symptomatic and asymptomatic COVID-19? |
title_full | Can we clinically identify pre-symptomatic and asymptomatic COVID-19? |
title_fullStr | Can we clinically identify pre-symptomatic and asymptomatic COVID-19? |
title_full_unstemmed | Can we clinically identify pre-symptomatic and asymptomatic COVID-19? |
title_short | Can we clinically identify pre-symptomatic and asymptomatic COVID-19? |
title_sort | can we clinically identify pre-symptomatic and asymptomatic covid-19? |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328068/ https://www.ncbi.nlm.nih.gov/pubmed/34341800 http://dx.doi.org/10.1101/2021.07.23.21260676 |
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