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Background and objective: Neonatal jaundice is a common clinical disease in neonates. Pathologic jaundice is more harmful to neonates. There are a few studies on the biomarkers of pathologic jaundice and the correlation between gut microbiota and clinical indices. Therefore, we aimed to reveal the characteristics of gut microbiota in pathologic jaundice, provide potential biomarkers for the diagnosis of pathologic jaundice, and find the correlation between gut microbiota and clinical indices. Methods: Fourteen neonates with physiologic jaundice were recruited into a control group (Group A). Additionally, 14 neonates with pathologic jaundice were recruited into a case group (Group B). The microbial communities were analyzed using 16S rDNA sequencing. LEfSe and the differences in the relative abundance of gut microbiota were used to identify different bacteria among the two groups. The ROC curve was used to assess effective biomarkers for pathologic jaundice. Spearman's rank-sum correlation coefficient was used to evaluate the correlation between gut microbiota and clinical indices. Results: There were no differences in the total richness or diversity of gut microbiota between the two groups. At the phylum and genus levels, compared with the control group, Bacteroidetes (p = 0.002) and Braydrhizobium (p = 0.01) were significantly higher, while Actinobacteria (p = 0.003) and Bidfldobacterium (p = 0.016) were significantly lower in the case group. Bacteroidetes were valuable in differentiating pathologic jaundice from physiologic jaundice by the ROC curve, and the area under the ROC curve (AUC) value was 0.839 [95%CI (0.648-0.995)]. In the case group, Bacteroidetes were negatively associated with total bilirubin (TBIL) (p < 0.05). In the control group, Bacteroidetes were positively associated with TBIL (p < 0.05). Conclusion: Bacteroidetes could be used as biomarkers to identify pathologic jaundice and Bacteroidetes are positively associated with bilirubin levels.
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PURPOSE: The COVID-19 pandemic may increase the development of psychiatric disorders, such as posttraumatic stress disorder (PTSD) among medical staff. A brief validated screening tool is essential for the early diagnosis of PTSD. The purpose of the present study was to evaluate the validation of a Chinese version of the Primary Care-PTSD-5 (C-PC-PTSD-5) and determine an appropriate cutoff score with optimal sensitivity and specificity for medical staff in China during the COVID-19 pandemic. PARTICIPANTS AND METHODS: An online cross-sectional survey was conducted on medical staff (n = 1104) from 17 medical institutions in Shanghai. Questionnaires comprising general information, medical-related traumatic event experiences, the PTSD Checklist (PCL-5), and C-PC-PTSD-5 were distributed to participants using the online Questionnaire Star electronic system. Internal consistency, convergent validity, and test-retest reliability were calculated. Receiver operating characteristic (ROC) analysis was performed to determine diagnostic accuracy and the optimal cutoff score of the C-PC-PTSD-5 for medical staff. RESULTS: We included 1062 valid questionnaires for the analysis. Data of 838 traumatic experiences were analyzed. Internal consistency of the C-PC-PTSD-5 was satisfied (Cronbach's α = 0.756). The total score of the C-PC-PTSD-5 showed good test-retest reliability (r = 0.746). We found a strong correlation between the C-PC-PTSD-5 score and PCL-5 total score (r = 0.669, p < 0.001), which indicated good convergent validity. The ROC analysis showed an area under the curve of 0.81 ± 0.016. A cutoff score of 2 provided optimal sensitivity and specificity for the C-PC-PTSD-5 (sensitivity = 0.632, specificity = 0.871, Youden index = 0.503, and overall efficiency = 0.768). CONCLUSION: Our results indicated that the C-PC-PTSD-5 can be employed as a brief and efficient screening instrument for medical staff exposed to the COVID-19 pandemic. A score of 2 was identified as the optimal threshold for probable clinical PTSD symptoms.
