PubMed COVID-19 Clinical Care

CONCLUSION: Teacher training and sensitization of parents and children can help overcome the perceived challenges.

CONCLUSION: Based on our current study, it was concluded that the educational program effectively improves breastfeeding women's knowledge and practices. There was a highly statistically significant positive linear correlation between the

CONCLUSION: From a biorisk management point of view, EHS was able to confine aerosols at their potential source using simple designs and equipment and adhering to the hierarchy of controls. This article demonstrates how a straightforward design

CONCLUSION: During the second wave of COVID-19 pandemic, we observed a significant rise in acute invasive mucormycosis infection primarily involving the paranasal sinuses and spread to orbito-facial, cerebral parenchyma causing related complications

Reduced carbon monoxide diffusing capacity (DL(CO) ) is common after recovery from severe COVID-19 pneumonitis. The extent to which this relates to alveolar membrane dysfunction as opposed to vascular injury is uncertain. Simultaneous measurement of

CONCLUSION: The AI algorithm demonstrated high sensitivity, specificity, and accuracy for PE on contrast-enhanced CT scans in patients with COVID-19 regardless of parenchymal disease. Accuracy was significantly affected by the mean attenuation of the

CONCLUSION: The AI algorithm demonstrated high sensitivity, specificity, and accuracy for PE on contrast-enhanced CT scans in patients with COVID-19 regardless of parenchymal disease. Accuracy was significantly affected by the mean attenuation of the

CONCLUSIONS: The factors associated with adverse job outcomes among nurses-intent to leave, reduced clinical hours, travel nursing, or recent departure-consistently align with issues that predated the pandemic. Few nurses cite COVID as the primary

Working mothers face challenges in pursuing their career aspirations due to work-family conflict. The recent COVID-19 pandemic has posed added challenges for working mothers by increasing care demands while also causing numerous health, economic and

Current remote monitoring of COVID-19 patients relies on manual symptom reporting, which is highly dependent on patient compliance. In this research, we present a machine learning (ML)-based remote monitoring method to estimate patient recovery from