The low‐harm score for predicting mortality in patients diagnosed with COVID‐19: A multicentric validation study
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SciScore for 10.1101/2020.05.26.20111120: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: Ethical approval: This study was assessed and approved by the Ethics Committee of the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán on April 29th, 2020 (Reg. No. DMC-3369-20-20-1). 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 All calculations were performed using Microsoft Excel® and STATA® v12 software. STATA®suggested: (Stata, RRID:SCR_012763)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).
Result…SciScore for 10.1101/2020.05.26.20111120: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: Ethical approval: This study was assessed and approved by the Ethics Committee of the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán on April 29th, 2020 (Reg. No. DMC-3369-20-20-1). 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 All calculations were performed using Microsoft Excel® and STATA® v12 software. STATA®suggested: (Stata, RRID:SCR_012763)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:Finally, scores usually have practical and logistical limitations that preclude their applicability and adoption in real-world settings. As a part of this study, we have created a free digital tool where the calculation of the LOW-HARM score can be automatized, allowing quick, frequent (even daily), and reproducible predictions as the patient’s status evolves20. Choosing a cut-off: A numerical score is useful for making comparisons or tracking clinical evolution on their own, however, having a cut-off value could be useful for decision making. The largest AUROC was observed using a cut-off score of 25 (0.90, 95% CI 0.87-0.93). However, when predicting mortality, and particularly when resources might be allocated based on this prediction, it is preferable to avoid false positive errors (predicting a patient will die when they will survive). Therefore, we propose 65 points as a more clinically useful cut-off, since it has a more than five times lower rate of false positive results if compared against the 25-point cut-off (2% vs 11 %). It should be emphasized that, regardless of its diagnostic accuracy, proposing a score cut-off is as useful as the proportion of times this cut-off is met. In this case, 137/400 (36%) patients had a score above 65 which means it is possible to predict mortality with a specificity of 98% and a positive predictive value of 96% in more than a third of the patients at the time of admission. It is also worth mentioning that, compared with other countri...
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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