Disseminated Intravascular Coagulation Score and Sepsis-induced Coagulopathy Score in Prediction of COVID-19 Severity: A Retrospective Analysis
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
No abstract available
Article activity feed
-
-
SciScore for 10.1101/2021.06.26.21259369: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: IEC approval: The Institutional Ethical committee of All India Institute of Medical Sciences Rishikesh approved the study prior to data collection. Sex as a biological variable DIC scores and SIC scores were calculated according to the respective guidelines.(1),(3) Patients having active thromboembolic disease before symptom onset or before testing for COVID-19 and pregnant females were excluded from the analysis. Randomization not detected. Blinding not detected. Power Analysis Sample size: Logistic regression of a binary response variable (Y) on a binary independent variable (X) with a sample size of 127 observations achieved 80% power. Cell Line Authentication Authentication: The D-dimer … SciScore for 10.1101/2021.06.26.21259369: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: IEC approval: The Institutional Ethical committee of All India Institute of Medical Sciences Rishikesh approved the study prior to data collection. Sex as a biological variable DIC scores and SIC scores were calculated according to the respective guidelines.(1),(3) Patients having active thromboembolic disease before symptom onset or before testing for COVID-19 and pregnant females were excluded from the analysis. Randomization not detected. Blinding not detected. Power Analysis Sample size: Logistic regression of a binary response variable (Y) on a binary independent variable (X) with a sample size of 127 observations achieved 80% power. Cell Line Authentication Authentication: The D-dimer levels (calculated by immune-turbidometric assay) and routine blood investigations within three days of hospital admission were collected. Table 2: Resources
Software and Algorithms Sentences Resources Statistical analyses were performed with the SPSS software version 25. 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:Our study has limitations. First, owing to our study design we could analyze only the hospitalized patients which allowed us to include fewer mild severity disease cases in comparison to high prevalence of mild COVID 19 cases in the population. So, the results of mild cases cannot be extrapolated to the population as a whole. Hence, larger population studies are needed to confirm our finding. Second, the decision to perform CTPA was purely at the discretion of the treating physician. Hence, CTPA could not be done for all the 168 subjects. As a result, we could have missed some sub-clinical PE cases.
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.
Results from scite Reference Check: We found no unreliable references.
-
