Nursing Care of 26 Infants Born to Mothers With COVID-19.

BACKGROUND: Novel coronavirus disease (COVID-19) has spread throughout the world; yet, there are few reports of neonatal cases. Thus, information about related clinical care experience is scarce. CLINICAL FINDINGS: This case report includes 26 infants admitted to the neonatal intensive care unit (NICU) of Tongji Hospital in Wuhan City who were born to mothers with suspected/confirmed COVID-19. The nursing and medical staff implemented care of these infants in strict accordance with infection control measures. INTERVENTION: Emergency measures for the prevention and control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the NICU were developed, and neonatal isolation, observation, and treatment were performed. OUTCOMES: Vital signs of the 26 infants remained stable during isolation and treatment, and no complications occurred. During the study period, neither the infants nor the nursing and medical staff were infected with SARS-CoV-2. PRACTICE RECOMMENDATIONS: Based on our strict practices, infants born to mothers with suspected/confirmed COVID-19 should receive care in a single-patient room to support infection control and provide enhanced observation. During initial contact and nursing care, increased attention should be given to the protection of infants born to mothers with suspected/confirmed COVID-19.

Development and Validation of a Carbohydrate Metabolism-Related Model for Predicting Prognosis and Immune Landscape in Hepatocellular Carcinoma Patients.

OBJECTIVE: The activities and products of carbohydrate metabolism are involved in key processes of cancer. However, its relationship with hepatocellular carcinoma (HCC) is unclear. METHODS: The cancer genome atlas (TCGA)-HCC and ICGC-LIRI-JP datasets were acquired via public databases. Differentially expressed genes (DEGs) between HCC and control samples in the TCGA-HCC dataset were identified and overlapped with 355 carbohydrate metabolism-related genes (CRGs) to obtain differentially expressed CRGs (DE-CRGs). Then, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were applied to identify risk model genes, and HCC samples were divided into high/low-risk groups according to the median risk score. Next, gene set enrichment analysis (GSEA) was performed on the risk model genes. The sensitivity of the risk model to immunotherapy and chemotherapy was also explored. RESULTS: A total of 8 risk model genes, namely, G6PD, PFKFB4, ACAT1, ALDH2, ACYP1, OGDHL, ACADS, and TKTL1, were identified. Moreover, the risk score, cancer status, age, and pathologic T stage were strongly associated with the prognosis of HCC patients. Both the stromal score and immune score had significant negative/positive correlations with the risk score, reflecting the important role of the risk model in immunotherapy sensitivity. Furthermore, the stromal and immune scores had significant negative/positive correlations with risk scores, reflecting the important role of the risk model in immunotherapy sensitivity. Eventually, we found that high-/low-risk patients were more sensitive to 102 drugs, suggesting that the risk model exhibited sensitivity to chemotherapy drugs. The results of the experiments in HCC tissue samples validated the expression of the risk model genes. CONCLUSION: Through bioinformatic analysis, we constructed a carbohydrate metabolism-related risk model for HCC, contributing to the prognosis prediction and treatment of HCC patients.