Screening of COVID-19 cases through a Bayesian network symptoms model and psychophysical olfactory test
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SciScore for 10.1101/2021.01.18.21249821: (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: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This anosmia score overcomes the known limitations of olfactory dysfunction self-report, i.e., usually underestimation of olfactory dysfunction severity (Fig. 2B), and furthermore, it substantially increases the predictive power of the model (Fig. 3B-C). We found that the full model incorporating this index yielded COVID-19 status predictions with high fidelity (AUC 0.785), which worsened when this index was left out (AUC 0.733). In the case of …
SciScore for 10.1101/2021.01.18.21249821: (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: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This anosmia score overcomes the known limitations of olfactory dysfunction self-report, i.e., usually underestimation of olfactory dysfunction severity (Fig. 2B), and furthermore, it substantially increases the predictive power of the model (Fig. 3B-C). We found that the full model incorporating this index yielded COVID-19 status predictions with high fidelity (AUC 0.785), which worsened when this index was left out (AUC 0.733). In the case of asymptomatic individuals (miners data), where the only measurement is obtained from the KOR test, the model was able to identify 100% of the individuals with olfactory impairment. Among the 15 individuals that were RT-PCR positive, six of them recognized less than four odors, the remaining 9 recognized at least five out of the six different odors. We obtained a similar performance on the asymptomatic participants from the UC-Christus sample. The model recognized all individuals with RT-PCR positive who identified less than four odors and one individual who identified four odors. For the model to recognize an individual infected that identified four odors, mint has to be among the not recognized odors. Mint has two features that are especially attractive in a smell test, such as KOR. First, mint has a very distinctive smell and is rarely confused with other odors. Second, mint is a familiar smell to most people. In the KOR test, mint was correctly recognized by a majority of participants with a negative RT-PCR (93%). Hence, mint has a l...
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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