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10.1111/ijlh.13312 http://scihub22266oqcxt.onion/10.1111/ijlh.13312 32812365!7461522!32812365     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Lab+Hematol 2021 ; 43 (1): 116-122 Nephropedia Template TP {{tp|p=32812365|t=2021. Interest of the cellular population data analysis as an aid in the early diagnosis of SARS-CoV-2 infection |pdf=|usr=}}{{32812365}} gab.com Text Interest of the cellular population data analysis as an aid in the early diagnosis of SARS-CoV-2 infection JO: Int J Lab Hematol http://www.kidney.de/pget.php?&tw=1&pmid=32812365 #FOAvip 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. Twit Text FOAVip Interest of the cellular population data analysis as an aid in the early diagnosis of SARS-CoV-2 infection ????Int J Lab Hematol http://www.kidney.de/pget.php?&tw=1&pmid=32812365 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32812365 #FOAvip English Wikipedia <ref>{{Cite pmid|32812365}}</ref> Interest of the cellular population data analysis as an aid in the early diagnosis of SARS-CoV-2 infection #MMPMID32812365 Vasse M; Ballester MC; Ayaka D; Sukhachev D; Delcominette F; Habarou F; Jolly E; Sukhacheva E; Pascreau T; Farfour E Int J Lab Hematol 2021[Feb]; 43 (1): 116-122 PMID32812365show ga 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. |*COVID-19 Testing[MESH] |*Early Diagnosis[MESH] |*Leukocyte Count[MESH] |*Pandemics[MESH] |*SARS-CoV-2[MESH] |Adolescent[MESH] |Adult[MESH] |Aged[MESH] |Aged, 80 and over[MESH] |COVID-19 Nucleic Acid Testing[MESH] |COVID-19/blood/*diagnosis/diagnostic imaging/epidemiology[MESH] |Decision Trees[MESH] |False Negative Reactions[MESH] |False Positive Reactions[MESH] |Female[MESH] |Humans[MESH] |Leukocytes/classification[MESH] |Male[MESH] |Middle Aged[MESH] |Predictive Value of Tests[MESH] |Prospective Studies[MESH] |ROC Curve[MESH] |Reverse Transcriptase Polymerase Chain Reaction[MESH] |Supervised Machine Learning[MESH] |Tomography, X-Ray Computed[MESH]Interest of the cellular population data analysis as an aid in the ear(epmc).pdf DeepDyve Pubget Overpricing