Dataset Information

Predictors of Nonseroconversion after SARS-CoV-2 Infection.

ABSTRACT: Not all persons recovering from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection develop SARS-CoV-2-specific antibodies. We show that nonseroconversion is associated with younger age and higher reverse transcription PCR cycle threshold values and identify SARS-CoV-2 viral loads in the nasopharynx as a major correlate of the systemic antibody response.

SUBMITTER: Liu W

PROVIDER: S-EPMC8386781 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Predictors of Nonseroconversion after SARS-CoV-2 Infection.

Liu Weimin W Russell Ronnie M RM Bibollet-Ruche Frederic F Skelly Ashwin N AN Sherrill-Mix Scott S Freeman Drew A DA Stoltz Regina R Lindemuth Emily E Lee Fang-Hua FH Sterrett Sarah S Bar Katharine J KJ Erdmann Nathaniel N Gouma Sigrid S Hensley Scott E SE Ketas Thomas T Cupo Albert A Cruz Portillo Victor M VM Moore John P JP Bieniasz Paul D PD Hatziioannou Theodora T Massey Greer G Minyard Mary-Beth MB Saag Michael S MS Davis Randall S RS Shaw George M GM Britt William J WJ Leal Sixto M SM Goepfert Paul P Hahn Beatrice H BH

Emerging infectious diseases 20210630 9

Not all persons recovering from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection develop SARS-CoV-2-specific antibodies. We show that nonseroconversion is associated with younger age and higher reverse transcription PCR cycle threshold values and identify SARS-CoV-2 viral loads in the nasopharynx as a major correlate of the systemic antibody response. ...[more]

PMID: 34193339

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Project description:Background and Objectives: The severe forms of SARS-CoV-2 pneumonia are associated with acute hypoxic respiratory failure and high mortality rates, raising significant challenges for the medical community. The objective of this paper is to present the importance of early quantitative evaluation of radiological changes in SARS-CoV-2 pneumonia, including an alternative way to evaluate lung involvement using normal density clusters. Based on these elements we have developed a more accurate new predictive score which includes quantitative radiological parameters. The current evolution models used in the evaluation of severe cases of COVID-19 only include qualitative or semi-quantitative evaluations of pulmonary lesions which lead to a less accurate prognosis and assessment of pulmonary involvement. Materials and Methods: We performed a retrospective observational cohort study that included 100 adult patients admitted with confirmed severe COVID-19. The patients were divided into two groups: group A (76 survivors) and group B (24 non-survivors). All patients were evaluated by CT scan upon admission in to the hospital. Results: We found a low percentage of normal lung densities, PaO2/FiO2 ratio, lymphocytes, platelets, hemoglobin and serum albumin associated with higher mortality; a high percentage of interstitial lesions, oxygen flow, FiO2, Neutrophils/lymphocytes ratio, lactate dehydrogenase, creatine kinase MB, myoglobin, and serum creatinine were also associated with higher mortality. The most accurate regression model included the predictors of age, lymphocytes, PaO2/FiO2 ratio, percent of lung involvement, lactate dehydrogenase, serum albumin, D-dimers, oxygen flow, and myoglobin. Based on these parameters we developed a new score (COV-Score). Conclusions: Quantitative assessment of lung lesions improves the prediction algorithms compared to the semi-quantitative parameters. The cluster evaluation algorithm increases the non-survivor and overall prediction accuracy.COV-Score represents a viable alternative to current prediction scores, demonstrating improved sensitivity and specificity in predicting mortality at the time of admission.

Dataset Information

Predictors of Nonseroconversion after SARS-CoV-2 Infection.

Publications

Predictors of Nonseroconversion after SARS-CoV-2 Infection.

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