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. 2022 Feb 17;13:946. doi: 10.1038/s41467-022-28639-4

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 7 — a The clinical parameters available in the cohort were evaluated for their association with the 12-protein molecular severity score to identify significantly associated parameters and allow scoring (weighting) for the different groups in each clinical measurement. The box plots (median as center line, box marks the 25th and 75th percentiles, and whiskers define minimum and maximum) show the molecular severity score across the groups in the most associated clinical parameters; the number of patients (total of 100, 50 severe, and 50 non-severe) with data available for each parameter is stated in each panel. One-way ANOVA with Dunnett’s multiple testing correction was used for clinical parameters with more than two groups, and unpaired two-tailed t-test was used for parameters with two groups. Refer to Supplementary Data 6 for more details of the statistical comparisons and exact p-value. The groups in each of the seven selected clinical parameter (markers) were given a numeric, integer value from 0 to 3 (shown in red bold font) according to the 12-protein severity score. These values were then used to calculate the Clinical Risk Score by adding the values across the 7 markers for each patient. Refer to Supplementary Fig. 6 for details of variable selection. b ROC curve analysis confirmed the significant predictive value of the Clinical Risk Score, which combined the 7 clinical markers. c, d Of the 7 markers in (a), 4 (CRP and creatinine levels and lymphocyte and neutrophil cell counts) were available in the MGH cohort, thus, were used for independent validation (Supplementary Data 5). c, d Show the ROC curve of the Clinical Risk Score based on the 4 markers in our cohort from Qatar and the MGH cohort (from day 0 and day 3 data) from the US, respectively. D Also shows the risk of COVID-19 severity (% risk with 95% confidence interval) in the MGH cohort according to the 4-marker Clinical Risk Score. For b–d the Clinical Risk Scores outperformed each of the single clinical parameters in pairwise comparisons (p < 0.0001, DeLong et al. method⁷⁰).