Hospitalization and mortality associated with SARS-CoV-2 viral clades in COVID-19
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Abstract
The COVID-19 epidemic of 2019–20 is due to the novel coronavirus SARS-CoV-2. Following first case description in December, 2019 this virus has infected over 10 million individuals and resulted in at least 500,000 deaths world-wide. The virus is undergoing rapid mutation, with two major clades of sequence variants emerging. This study sought to determine whether SARS-CoV-2 sequence variants are associated with differing outcomes among COVID-19 patients in a single medical system. Whole genome SARS-CoV-2 RNA sequence was obtained from isolates collected from patients registered in the University of Washington Medicine health system between March 1 and April 15, 2020. Demographic and baseline clinical characteristics of patients and their outcome data including their hospitalization and death were collected. Statistical and machine learning models were applied to determine if viral genetic variants were associated with specific outcomes of hospitalization or death. Full length SARS-CoV-2 sequence was obtained 190 subjects with clinical outcome data. 35 (18.4%) were hospitalized and 14 (7.4%) died from complications of infection. A total of 289 single nucleotide variants were identified. Clustering methods demonstrated two major viral clades, which could be readily distinguished by 12 polymorphisms in 5 genes. A trend toward higher rates of hospitalization of patients with Clade 2 infections was observed ( p = 0.06, Fisher’s exact). Machine learning models utilizing patient demographics and co-morbidities achieved area-under-the-curve (AUC) values of 0.93 for predicting hospitalization. Addition of viral clade or sequence information did not significantly improve models for outcome prediction. In summary, SARS-CoV-2 shows substantial sequence diversity in a community-based sample. Two dominant clades of virus are in circulation. Among patients sufficiently ill to warrant testing for virus, no significant difference in outcomes of hospitalization or death could be discerned between clades in this sample. Major risk factors for hospitalization and death for either major clade of virus include patient age and comorbid conditions.
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SciScore for 10.1101/2020.09.24.20201228: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: Subjects, samples, and sequencing: Institutional Review Board (IRB) approval for this study was obtained from the University of Washington, and all research was conducted in compliance with the Declaration of Helsinki.
Consent: This study was exempted by the IRB from informed consent requirement as a retrospective chart review study.Randomization Model tuning was accomplished using 10000 random sets of hyperparameters for each of 4 model architectures (AdaBoost, Extra Trees, Gradient Boosting, Random Forest). Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Libr… SciScore for 10.1101/2020.09.24.20201228: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: Subjects, samples, and sequencing: Institutional Review Board (IRB) approval for this study was obtained from the University of Washington, and all research was conducted in compliance with the Declaration of Helsinki.
Consent: This study was exempted by the IRB from informed consent requirement as a retrospective chart review study.Randomization Model tuning was accomplished using 10000 random sets of hyperparameters for each of 4 model architectures (AdaBoost, Extra Trees, Gradient Boosting, Random Forest). Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Libraries were sequenced on MiSeq, NextSeq or NovaSeq instruments (Illumina) using 1×185, 1×75, or 1×100 runs respectively. MiSeqsuggested: (A5-miseq, RRID:SCR_012148)Raw reads and consensus sequences were deposited to NCBI SRA and Genbank respectively under BioProject PRJNA610428. BioProjectsuggested: (NCBI BioProject, RRID:SCR_004801)Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This study has some unique strengths and weaknesses. Our data were derived from a single health-care system encompassing three hospitals in a major metropolitan area. By using a single medical system, we had access to substantial medical history on these subjects as well as reduced concern regarding the influence of hospital system on outcomes (i.e. we assume that decisions for hospitalization and quality of care of hospitalized patients will be more consistent in patients treated within a single system). Our system served as the primary site for COVID-19 testing particularly in March and April, 2020, which gave us access to a substantial number of patients with linked outcome data. However, our outcomes at present are limited to hospitalization and death. Use of hospitalization as outcome represents a useful dichotomous outcome that is a proxy for disease severity. However, the decision to admit may be influenced by factors other than the patient’s immediate status, and may be biased toward admission of patients with significant comorbidities, advanced age, or socio-economic considerations. It is conceivable that viral sequence variants might be associated with differential outcomes looking at more granular and direct disease features such as pulmonary radiologic outcomes or specific complications. The use of machine learning produced predictive models with excellent overall performance, particularly for predicting those patients who would not require hospitalization. Althou...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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