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10.1016/j.jaip.2020.10.043 http://scihub22266oqcxt.onion/10.1016/j.jaip.2020.10.043 33160092!7640885!33160092     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Allergy+Clin+Immunol+Pract 2021 ; 9 (1): 177-184.e3 Nephropedia Template TP {{tp|p=33160092|t=2021. Predictive Nomogram for Severe COVID-19 and Identification of Mortality-Related Immune Features |pdf=|usr=}}{{33160092}} gab.com Text Predictive Nomogram for Severe COVID-19 and Identification of Mortality-Related Immune Features JO: J Allergy Clin Immunol Pract http://www.kidney.de/pget.php?&tw=1&pmid=33160092 #FOAvip BACKGROUND: Patients with severe 2019 novel coronavirus disease (COVID-19) have a high mortality rate. The early identification of severe COVID-19 is of critical concern. In addition, the correlation between the immunological features and clinical outcomes in severe cases needs to be explored. OBJECTIVE: To build a nomogram for identifying patients with severe COVID-19 and explore the immunological features correlating with fatal outcomes. METHODS: We retrospectively enrolled 85 and 41 patients with COVID-19 in primary and validation cohorts, respectively. A predictive nomogram based on risk factors for severe COVID-19 was constructed using the primary cohort and evaluated internally and externally. In addition, in the validation cohort, immunological features in patients with severe COVID-19 were analyzed and correlated with disease outcomes. RESULTS: The risk prediction nomogram incorporating age, C-reactive protein, and D-dimer for early identification of patients with severe COVID-19 showed favorable discrimination in both the primary (area under the curve [AUC] 0.807) and validation cohorts (AUC 0.902) and was well calibrated. Patients who died from COVID-19 showed lower abundance of peripheral CD45RO(+)CD3(+) T cells and natural killer cells, but higher neutrophil counts than that in the patients who recovered (P = .001, P = .009, and P = .009, respectively). Moreover, the abundance of CD45RO(+)CD3(+) T cells, neutrophil-to-lymphocyte ratio, and neutrophil-to-natural killer cell ratio were strong indicators of death in patients with severe COVID-19 (AUC 0.933 for all 3). CONCLUSION: The novel nomogram aided the early identification of severe COVID-19 cases. In addition, the abundance of CD45RO(+)CD3(+) T cells and neutrophil-to-lymphocyte and neutrophil-to-natural killer cell ratios may serve as useful prognostic predictors in severe patients. Twit Text FOAVip Predictive Nomogram for Severe COVID-19 and Identification of Mortality-Related Immune Features ????J Allergy Clin Immunol Pract http://www.kidney.de/pget.php?&tw=1&pmid=33160092 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33160092 #FOAvip English Wikipedia <ref>{{Cite pmid|33160092}}</ref> Predictive Nomogram for Severe COVID-19 and Identification of Mortality-Related Immune Features #MMPMID33160092 Cai L; Zhou X; Wang M; Mei H; Ai L; Mu S; Zhao X; Chen W; Hu Y; Wang H J Allergy Clin Immunol Pract 2021[Jan]; 9 (1): 177-184.e3 PMID33160092show ga BACKGROUND: Patients with severe 2019 novel coronavirus disease (COVID-19) have a high mortality rate. The early identification of severe COVID-19 is of critical concern. In addition, the correlation between the immunological features and clinical outcomes in severe cases needs to be explored. OBJECTIVE: To build a nomogram for identifying patients with severe COVID-19 and explore the immunological features correlating with fatal outcomes. METHODS: We retrospectively enrolled 85 and 41 patients with COVID-19 in primary and validation cohorts, respectively. A predictive nomogram based on risk factors for severe COVID-19 was constructed using the primary cohort and evaluated internally and externally. In addition, in the validation cohort, immunological features in patients with severe COVID-19 were analyzed and correlated with disease outcomes. RESULTS: The risk prediction nomogram incorporating age, C-reactive protein, and D-dimer for early identification of patients with severe COVID-19 showed favorable discrimination in both the primary (area under the curve [AUC] 0.807) and validation cohorts (AUC 0.902) and was well calibrated. Patients who died from COVID-19 showed lower abundance of peripheral CD45RO(+)CD3(+) T cells and natural killer cells, but higher neutrophil counts than that in the patients who recovered (P = .001, P = .009, and P = .009, respectively). Moreover, the abundance of CD45RO(+)CD3(+) T cells, neutrophil-to-lymphocyte ratio, and neutrophil-to-natural killer cell ratio were strong indicators of death in patients with severe COVID-19 (AUC 0.933 for all 3). CONCLUSION: The novel nomogram aided the early identification of severe COVID-19 cases. In addition, the abundance of CD45RO(+)CD3(+) T cells and neutrophil-to-lymphocyte and neutrophil-to-natural killer cell ratios may serve as useful prognostic predictors in severe patients. |*Nomograms[MESH] |Age Factors[MESH] |Aged[MESH] |C-Reactive Protein/immunology[MESH] |COVID-19/*epidemiology/*immunology/mortality[MESH] |Female[MESH] |Flow Cytometry[MESH] |Humans[MESH] |Lymphocytes/immunology[MESH] |Male[MESH] |Middle Aged[MESH] |Neutrophils/immunology[MESH] |Retrospective Studies[MESH] |Risk Assessment[MESH] |Risk Factors[MESH]Predictive Nomogram for Severe COVID-19 and Identification of Mortalit(epmc).pdf DeepDyve Pubget Overpricing