An external validation of the QCovid risk prediction algorithm for risk of mortality from COVID-19 in adults: a national validation cohort study in England
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SciScore for 10.1101/2021.01.22.21249968: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
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:This study also has several limitations. First, because of data limitations, we could not derive all predictors in the same way as in the derivation cohort. Despite these inconsistencies, the model had excellent discrimination and calibration. Second, we only focused on COVID-19 related deaths, but not hospital admissions, because of the …
SciScore for 10.1101/2021.01.22.21249968: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
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:This study also has several limitations. First, because of data limitations, we could not derive all predictors in the same way as in the derivation cohort. Despite these inconsistencies, the model had excellent discrimination and calibration. Second, we only focused on COVID-19 related deaths, but not hospital admissions, because of the lack of data. Finally, because the Public Health Data Asset is based on the 2011 Census, our sample was restricted to patients who were enumerated in 2011, that is about 94% of the population living in England in 2011. Recent migrants were excluded from this study, but they tend to be younger than the native population and therefore at lower risk of COVID-19 death. QCovid represents a new approach for population risk-stratification for adverse outcomes from COVID-19, and our validation indicates that the risk algorithm performs well on external data not used for its derivation. Whilst it has been specifically designed to inform UK health policy and interventions to manage COVID-19 related risks, it also has international potential, subject to local validation. It could also be deployed in a number of health and care applications, either during the current phase of the pandemic, or in subsequent ‘waves’ of infection. These could include supporting targeted recruitment for clinical trials, vaccine prioritisation, and discussions between patients and clinicians in relation to work and health risks, for example through weight reduction since obes...
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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