tetano
Editor, Senior Moderator
Int J Lab Hematol
. 2020 Aug 19.
doi: 10.1111/ijlh.13312. Online ahead of print.
Interest of the cellular population data analysis as an aid in the early diagnosis of SARS-CoV-2 infection
Marc Vasse[SUP] 1 [/SUP], Marie-Christine Ballester[SUP] 2 [/SUP], Degnile Ayaka[SUP] 3 [/SUP], Dmitry Sukhachev[SUP] 4 [/SUP], Fr?d?rique Delcominette[SUP] 3 [/SUP], Florence Habarou[SUP] 3 [/SUP], Emilie Jolly[SUP] 3 [/SUP], Elena Sukhacheva[SUP] 5 [/SUP], Tiffany Pascreau[SUP] 1 [/SUP], ?ric Farfour[SUP] 3 [/SUP]
Affiliations
Abstract
Introduction: Coronavirus disease 2019 (COVID-19) is characterized by a high contagiousness requiring isolation measures. At this time, diagnosis is based on the positivity of specific RT-PCR and/or chest computed tomography scan, which are time-consuming and may delay diagnosis. Complete blood count (CBC) can potentially contribute to the diagnosis of COVID-19. We studied whether the analysis of cellular population data (CPD), provided as part of CBC-Diff analysis by the DxH 800 analyzers (Beckman Coulter), can help to identify SARS-CoV-2 infection.
Methods: Cellular population data of the different leukocyte subpopulations were analyzed in 137 controls, 322 patients with proven COVID-19 (COVID+), and 285 patients for whom investigations were negative for SARS-CoV-2 infection (COVID-). When CPD of COVID+ were different from controls and COVID- patients, we used receiver operating characteristic analysis to test the discriminating capacity of the individual parameters. Using a random forest classifier, we developed the algorithm based on the combination of 4 monocyte CPD to discriminate COVID+ from COVID- patients. This algorithm was tested prospectively in a series of 222 patients referred to the emergency unit.
Results: Among the 222 patients, 86 were diagnosed as COVID-19 and 60.5% were correctly identified using the discriminating protocol. Among the 136 COVID- patients, 10.3% were misclassified (specificity 89.7%, sensitivity 60.5%). False negatives were observed mainly in patients with a low inflammatory state whereas false positives were mainly seen in patients with sepsis.
Conclusion: Consideration of CPD could constitute a first step and potentially aid in the early diagnosis of COVID-19.
Keywords: DxH800 analyzer; SARS-CoV-2 diagnosis; cellular population data.
. 2020 Aug 19.
doi: 10.1111/ijlh.13312. Online ahead of print.
Interest of the cellular population data analysis as an aid in the early diagnosis of SARS-CoV-2 infection
Marc Vasse[SUP] 1 [/SUP], Marie-Christine Ballester[SUP] 2 [/SUP], Degnile Ayaka[SUP] 3 [/SUP], Dmitry Sukhachev[SUP] 4 [/SUP], Fr?d?rique Delcominette[SUP] 3 [/SUP], Florence Habarou[SUP] 3 [/SUP], Emilie Jolly[SUP] 3 [/SUP], Elena Sukhacheva[SUP] 5 [/SUP], Tiffany Pascreau[SUP] 1 [/SUP], ?ric Farfour[SUP] 3 [/SUP]
Affiliations
- PMID: 32812365
- DOI: 10.1111/ijlh.13312
Abstract
Introduction: Coronavirus disease 2019 (COVID-19) is characterized by a high contagiousness requiring isolation measures. At this time, diagnosis is based on the positivity of specific RT-PCR and/or chest computed tomography scan, which are time-consuming and may delay diagnosis. Complete blood count (CBC) can potentially contribute to the diagnosis of COVID-19. We studied whether the analysis of cellular population data (CPD), provided as part of CBC-Diff analysis by the DxH 800 analyzers (Beckman Coulter), can help to identify SARS-CoV-2 infection.
Methods: Cellular population data of the different leukocyte subpopulations were analyzed in 137 controls, 322 patients with proven COVID-19 (COVID+), and 285 patients for whom investigations were negative for SARS-CoV-2 infection (COVID-). When CPD of COVID+ were different from controls and COVID- patients, we used receiver operating characteristic analysis to test the discriminating capacity of the individual parameters. Using a random forest classifier, we developed the algorithm based on the combination of 4 monocyte CPD to discriminate COVID+ from COVID- patients. This algorithm was tested prospectively in a series of 222 patients referred to the emergency unit.
Results: Among the 222 patients, 86 were diagnosed as COVID-19 and 60.5% were correctly identified using the discriminating protocol. Among the 136 COVID- patients, 10.3% were misclassified (specificity 89.7%, sensitivity 60.5%). False negatives were observed mainly in patients with a low inflammatory state whereas false positives were mainly seen in patients with sepsis.
Conclusion: Consideration of CPD could constitute a first step and potentially aid in the early diagnosis of COVID-19.
Keywords: DxH800 analyzer; SARS-CoV-2 diagnosis; cellular population data.