Potential biochemical markers to identify severe cases among COVID-19 patients
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Abstract
There is a high mortality and long hospitalization period for severe cases with 2019 novel coronavirus disease (COVID-19) pneumonia. Therefore, it makes sense to search for a potential biomarker that could rapidly and effectively identify severe cases early. Clinical samples from 28 cases of COVID-19 (8 severe cases, 20 mild cases) in Zunyi District from January 29, 2020 to February 21, 2020 were collected and otherwise statistically analysed for biochemical markers. Serum urea, creatinine (CREA) and cystatin C (CysC) concentrations in severe COVID-19 patients were significantly higher than those in mild COVID-19 patients (P<0.001), and there were also significant differences in serum direct bilirubin (DBIL), cholinesterase (CHE) and lactate dehydrogenase (LDH) concentrations between severe and mild COVID-19 patients (P<0.05). Serum urea, CREA, CysC, DBIL, CHE and LDH could be used to distinguish severe COVID-19 cases from mild COVID-19 cases. In particular, serum biomarkers, including urea, CREA, CysC, which reflect glomerular filtration function, may have some significance as potential indicators for the early diagnosis of severe COVID-19 and to distinguish it from mild COVID-19. Glomerular filtration function injury in severe COVID-19 patients should also be considered by clinicians.
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SciScore for 10.1101/2020.03.19.20034447: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources The statistical analysis was performed using IBM SPSS Statistics 22.0 SPSSsuggested: (SPSS, RRID:SCR_002865)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Two limitations are inherent in our study. First, the survey area is relatively limited. Additionally, …
SciScore for 10.1101/2020.03.19.20034447: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources The statistical analysis was performed using IBM SPSS Statistics 22.0 SPSSsuggested: (SPSS, RRID:SCR_002865)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Two limitations are inherent in our study. First, the survey area is relatively limited. Additionally, the relatively small number of participants in the survey may not fully reflect the overall situation. Thus, further studies are necessary to execute a large number of data surveys in multiple regions by multi-centre cooperation. Herein, we found that some serum indicators of glomerular function, including urea, CREA, and CysC, were observably higher in severe COVID-19 patients than in mild COVID-19 patients. This result indicates that serum urea, CREA, and CysC could be used as potential biochemical biomarkers to identify a severe COVID-19 patient. Moreover, clinicians should constantly monitor the glomerular filtration function while treating patients with a severe SARS-CoV-2 infection.
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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SciScore for 10.1101/2020.03.19.20034447: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement Ethical Statement This study was approved by the Ethics Commissions of the Affiliated Hospital of Zunyi Medical University (No. KLL-2020-008). Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable Severe cases Mild cases N 8 20 Gender ( male/female ) 4/4 11/9 Age ( years ) 66 Table 2: Resources
Software and Algorithms Sentences Resources ± 22 41 ± 19 Diabetes mellitus ( N , % ) 2 , 25.0 % 2 , 10.0 % Hypertension ( N , % ) 4 , 50.0 % 1 , 5.0 % Cardiovascular disease ( N , % ) 1 , 12.5 % 3 , 15.0 % Nephropathy ( N , % ) 0 , 0 % 1 , 5.0 % The statistical analysis was performed using IBM SPSS Statistics 22.0 …SciScore for 10.1101/2020.03.19.20034447: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement Ethical Statement This study was approved by the Ethics Commissions of the Affiliated Hospital of Zunyi Medical University (No. KLL-2020-008). Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable Severe cases Mild cases N 8 20 Gender ( male/female ) 4/4 11/9 Age ( years ) 66 Table 2: Resources
Software and Algorithms Sentences Resources ± 22 41 ± 19 Diabetes mellitus ( N , % ) 2 , 25.0 % 2 , 10.0 % Hypertension ( N , % ) 4 , 50.0 % 1 , 5.0 % Cardiovascular disease ( N , % ) 1 , 12.5 % 3 , 15.0 % Nephropathy ( N , % ) 0 , 0 % 1 , 5.0 % The statistical analysis was performed using IBM SPSS Statistics 22.0 SPSSsuggested: (SPSS, SCR_002865)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
About SciScore
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