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Among patients with Coronavirus disease (COVID-19), the ability to identify patients at risk for deterioration during their hospital stay is essential for effective patient allocation and management. To predict patient risk for critical COVID-19 based on status at admission using machine-learning models. Retrospective study based on a database of tertiary medical center with designated departments for patients with COVID-19. Patients with severe COVID-19 at admission, based on low oxygen saturation, low partial arterial oxygen pressure,

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In addition, patients with PCOS with pathogenic mutations had lower numbers of oocytes; however, the difference was not statistically significant. Of note, these observations should be interpreted with caution due to the relatively small sample size in the present study. Therefore, a larger number of samples should be collected to validate the results of the present study in future studies. In summary, the present study identified three potential pathogenic mutations in 258 Han Chinese patients with PCOS and these mutations may have