Introduction: The outbreak of the coronavirus disease 2019 (COVID-19) poses an unprecedented challenge to healthcare workers (HCWs) globally. This study investigated potential factors related to depression, anxiety, and stress in a sample of Chinese HCWs during the peak of the COVID-19 epidemic. Methods: An online survey was distributed to Chinese HCWs using respondent-driven sampling. Data were collected between February 13th and February 20th, 2020, immediately following the COVID-19 contagion peak in Hubei. A total of 1208 respondents were eligible for analysis. Mental health problems and social support were measured by the Depression Anxiety Stress Scales-21 (DASS-21) and the Perceived Social Support Scale (PSS). Results: The prevalence rates of depression, (DASS-depression > 9) anxiety (DASS-anxiety > 7) and stress (DASS-stress > 14) were 37.8%, 43.0% and 38.5%, respectively. Multivariate logistic regressions revealed that stress, anxiety, and depression were positively related to lower levels of social support, longer working hours, discrimination experience and workplace violence. The scarcity of medical equipment was correlated with increased stress and depression. Chinese HCWs working at COVID 19 designated hospitals were more likely to report anxiety. Additionally, volunteering to work in the frontline health facilities was inversely associated with depression. Conclusion: Mental health problems among Chinese HCWs were alarming during the peak of the COVID-19 epidemic. Health facilities require appropriate and standing services that address the mental health of healthcare workers, particularly during epidemic outbreaks.

Background: The objective of this study was to investigate the use of ensemble methods to improve the prediction of fetal macrosomia and large for gestational age from prenatal ultrasound imaging measurements. Methods: We evaluated and compared the prediction accuracies of nonlinear and quadratic mixed-effects models coupled with 26 different empirical formulas for estimating fetal weights in predicting large fetuses at birth. The data for the investigation were taken from the Successive Small-for-Gestational-Age-Births study. Ensemble methods, a class of machine learning techniques, were used to improve the prediction accuracies by combining the individual models and empirical formulas. Results: The prediction accuracy of individual statistical models and empirical formulas varied considerably in predicting macrosomia but varied less in predicting large for gestational age. Two ensemble methods, voting and stacking, with model selection, can combine the strengths of individual models and formulas and can improve the prediction accuracy. Conclusions: Ensemble learning can improve the prediction of fetal macrosomia and large for gestational age and have the potential to assist obstetricians in clinical decisions.

Background: This study proposes the use of machine learning algorithms to improve the accuracy of type 2 diabetes predictions using non-invasive risk score systems. Methods: We evaluated and compared the prediction accuracies of existing non-invasive risk score systems using the data from the REACTION study (Risk Evaluation of Cancers in Chinese Diabetic Individuals: A Longitudinal Study). Two simple risk scores were established on the bases of logistic regression. Machine learning techniques (ensemble methods) were used to improve prediction accuracies by combining the individual score systems. Results: Existing score systems from Western populations performed worse than the scores from Eastern populations in general. The two newly established score systems performed better than most existing scores systems but a little worse than the Chinese score system. Using ensemble methods with model selection algorithms yielded better prediction accuracy than all the simple score systems. Conclusion: Our proposed machine learning methods can be used to improve the accuracy of screening the undiagnosed type 2 diabetes and identifying the high-risk patients.

Objective: To study the association between glucose metabolism disorders and hepatotropic virus infection. Methods: A cross-sectional analysis was performed using data from the REACTION study (Risk Evaluation of Cancers in Chinese Diabetic Individuals: A Longitudinal Study). Outcomes of the analysis were test results of kidney function, liver function, lipid metabolism, and the prevalence of hepatitis B virus (HBV) infection and potential hepatitis C virus (HCV) infection (positive hepatitis C virus antibody) among individuals with and without diabetes mellitus (DM) or pre-diabetes mellitus (pre-DM). Results: Of the 10,080 patients who participated in the study, 7665 eligible subjects were included in the analysis. There was no significant difference in the prevalence of HBV infection between DM and normal subjects, pre-DM and normal subjects, and DM or pre-DM and normal subjects (p-values of 0.9180, 0.8154, and 0.6448, respectively). There was also no significant difference in the prevalence of potential HCV infection between DM and normal subjects, pre-DM and normal subjects, and DM or pre-DM and normal subjects (p-values of 0.1190, 0.0591, and 0.5591, respectively). Lipid metabolism showed a significant difference between DM or pre-DM subjects and normal subjects (p-values were less than 0.0221 in all cases). Multiple logistic regression analysis revealed hypertension as the leading significant variable associated with DM, pre-DM, and both. Other significant factors included gender, body mass index, age, and alanine aminotransferase. Conclusion: No significant association was detected between DM or pre-DM and HBV or potential HCV infection. Significant association was detected between lipid metabolism disorders and DM, but this association was absent in pre-DM patients when adjusting for other factors.

Objective: This study evaluated change in caesarean section rate with reform of birth planning policy in China from one-child to two-child policy. Methods: Study data were collected from patient-level hospital records of 59,668 pregnant women who visited three major urban hospitals in Jiangsu Province and Inner Mongolia Autonomous Region of China between January 2012 and December 2016. A segmented logistic regression approach was developed to evaluate the changes in caesarean section rate in these regions with the launch of China’s new partial and universal two-child policies in January 2014 and January 2016, respectively. Results: Jiangsu Province had a significantly lower non-emergency caesarean rate (Jiangsu 8.15% vs Inner Mongolia 34.03%, p < 0.001) and a much lower percentage of minority population (Jiangsu 6.99% vs Inner Mongolia 21.76%, p < 0.001) than Inner Mongolia Autonomous Region. In Jiangsu Province, no change in caesarean section rate was detected with the two-child policies (all p-values > 0.05), although the unadjusted trend change (0.038, 95% confidence interval or CI: [0.016, 0.060], p < 0.001) in log odds after the implementation of the partial two-child policy was statistically significant. In Inner Mongolia Autonomous Region, an immediate jump in caesarean section rate was discovered by the segmented logistic regression with the implementation of both the partial (unadjusted level change 0.297, CI: [0.105, 0.489], p = 0.002) and universal two-child policies (unadjusted level change 1.945, CI: [1.277, 2.614], p < 0.001); but the rate reverted to the previous level thereafter. Ethnicity, maternal age, maternal reproduction history, insurance coverage type, infant weight, and infant gender were the significant factors associated with caesarean section rate (for odds ratios, all p-values < 0.05). However, the significance of infant gender may stem from the large sample size of the study and is not clinically meaningful. Conclusion: Change in caesarean section rate was not observed with the launch of two-child policy in China.

Hospital-acquired Aspergillus rates among coronavirus disease 2019 (COVID-19) patients were initially higher at a hospital with high negative-pressure room utilization compared to a similar hospital with low utilization but with otherwise identical infection control policies. After the index hospital decreased negative-pressure utilization, hospital-acquired Aspergillus case rates at the 2 hospitals converged.