Objective To investigate the methodological characteristics of observational studies on the correlation between drug exposure during pregnancy and birth defects. Methods The PubMed database was searched from January 1, 2020 to December 31, 2020 to identify observational studies investigating the correlation between drug use during pregnancy and birth defects. Literature screening and data extraction were conducted by two researchers and statistical analysis was performed using R 3.6.1 software. Results A total of 40 relevant articles were identified, of which 8 (20.0%) were published in the four major medical journals and their sub-journals, 21 (42.5%) were conducted in Europe and the United States, and 4 were conducted (10.0%) in China. Cohort studies (30, 75.0%) and case-control studies (10, 25%) were the most commonly used study designs. Sixteen studies (40.0%) did not specify how the databases were linked. Sixteen studies (40.0%) did not report a clear definition of exposure, while 17 studies (42.5%) defined exposure as prescribing a drug that could not be guaranteed to have been taken by the pregnant women, possibly resulting in misclassification bias. Six studies (15.0%) did not report the diagnostic criteria for birth defects and 18 studies (45.0%) did not report the types of birth defects. In addition, 33 studies (82.5%) did not control for confounding factors in the study design, while only 19 studies (47.5%) considered live birth bias. Conclusion Improvements are imperative in reporting and conducting observational studies on the correlation between drug use during pregnancy and birth defects. This includes the methods for linking data sources, definition of exposure and outcomes, and control of confounding factors. Methodological criteria are needed to improve the quality of these studies to provide higher quality evidence for policymakers and researchers.
The monitoring of pregnant women is very important. It plays an important role in reducing fetal mortality, ensuring the safety of perinatal mother and fetus, preventing premature delivery and pregnancy accidents. At present, regular examination is the mainstream method for pregnant women's monitoring, but the means of examination out of hospital is scarce, and the equipment of hospital monitoring is expensive and the operation is complex. Using intelligent information technology (such as machine learning algorithm) can analyze the physiological signals of pregnant women, so as to realize the early detection and accident warning for mother and fetus, and achieve the purpose of high-quality monitoring out of hospital. However, at present, there are not enough public research reports related to the intelligent processing methods of out-of-hospital monitoring for pregnant women, so this paper takes the out-of-hospital monitoring for pregnant women as the research background, summarizes the public research reports of intelligent processing methods, analyzes the advantages and disadvantages of the existing research methods, points out the possible problems, and expounds the future development trend, which could provide reference for future related researches.
Objective To assess and report on the current situation of the families of students, who were involved in the Wenchuan earthquake, to provide data for the government to make decisions that should help with recovery from the earthquake. Methods We selected 2 towns and 4 villages using stratified sampling to take account of different levels of destruction. We performed on-site surveys and secondary research. Results The psychological problems of the parents of the students were serious. These families’ economic situations were not good. Conclusion We should build ‘Mutual Aid’ organization and take the advantage of rural hospitals to promote the long-acting mechanism of the psychological intervention.
ObjectiveTo evaluate liver perfusion in pregnant women with hepatitis between 13 and 41 weeks of gestation by three-dimensional color power Doppler angiography (3D-CPA) vascular indexes. MethodsThis study involved 73 pregnant women with hepatitis and 44 healthy pregnant women who had the pregnancy examination between February 2012 and June 2013. We sampled in the area which was near the right lobe of the pregnant women liver's portal vein branch, and obtained the vascularization index (VI), flow index (FI) and vascularization flow index (VFI) via the virtual organ computer-aided analysis (VOCAL) method. Then, we compared the liver perfusion differences between the pregnant women with hepatitis and healthy pregnant women. ResultsThe hepatic flow indexes obtained by 3D-CPA were significantly different between the HBV-DNA viral load and the control groups. The cutoff values of the three vascular indexes of patients with hepatitis with HBV-DNA viral load and the healthy pregnant women were respectively VI=8.760 (P<3×10-4); FI=22.180 (P<6×10-7); and VFI=1.575 (P<3×10-5). ConclusionApplication of the 3D-CPA on liver perfusion may differentiate pregnant women with hepatitis B from normal ones, thus offer a support for clinical prevention and treatment for pregnant women with hepatitis B.
ObjectiveTo determine teratogenicity of beta-blockers in early pregnancy. MethodsWe searched PubMed, EMbase, Cochrane Clinical Trials, clinicaltrials.gov, CBM, Wanfang database, and CNKI from establishment of each database to December 2014. We evaluated the quality of included literature. Statistical analysis was conducted in RevMan5.3 software. ResultsFifteen population-based case-control or cohort studies were identified. The score of included studies changed from 5-7 points. Based on meta-analysis, first trimester oral beta-blocker use showed no increased odds of all or major congenital anomalies. While in analysis examining organ-specific malformations, statistically increased odds of cardiovascular (CV) defects with OR 2.21 and 95% CI 1.63 to 3.01, cleft lip/palate (CL/P) with OR 3.11 and 95% CI 1.78 to 9.89, and neural tube (NT) defects with OR 3.56 and 95% CI 1.19 to 10.67 were observed. ConclusionCausality is difficult to interpret given small number of heterogeneous studies and possibility of biases. Given the frequency of this exposure in pregnancy, further research is needed.
Objective To compare the central foveal thickness (CFT) and subfoveal choroidal thickness (SFCT) in healthy pregnant women and patients with pre-eclampsia. Methods A prospective control study. Twenty normal subjects, 20 healthy pregnant women and 20 patients with pre-eclampsia were included. The difference of gestational weeks between healthy pregnant women and patients with pre-eclampsia was not significant (χ2=0.012, P=0.913). The differences of age and spherical equivalent among normal subjects, healthy pregnant women and patients with pre-eclampsia were not significant (χ2=1.760, 0.087; P=0.413, 0.957). All eyes underwent optical coherence tomography examination to measure the CFT and SFCT. Results The mean CFT of normal subjects, healthy pregnant women and patients with pre-eclampsia were (194.40±16.17), (201.2±17.33), (199.00±15.46) μm, there was no significant difference among the three groups (χ2=0.888, P=0.641). The mean SFCT of normal subjects, healthy pregnant women and patients with pre-eclampsia were (263.45±69.66), (330.00±49.20), (373.40±52.00) μm, there was significant difference among the three groups (χ2=22.818, P=0.000). The mean SFCT of healthy pregnant women was increased than that of normal subjects (Z=−2.991, P=0.002). The mean SFCT of patients with pre-eclampsia was increased than that of healthy pregnant women (Z=−2.638, P=0.007). Conclusion The mean SFCT of patients with pre-eclampsia is increased than healthy pregnant women.
ObjectiveTo construct and verify the nomogram prediction model of pregnant women's fear of childbirth. MethodsA convenient sampling method was used to select 675 pregnant women in tertiary hospital in Tangshan City, Hebei Province from July to September 2022 as the modeling group, and 290 pregnant women in secondary hospital in Tangshan City from October to December 2022 as the verification group. The risk factors were determined by logistic regression analysis, and the nomogram was drawn by R 4.1.2 software. ResultsSix predictors were entered into the model: prenatal education, education level, depression, pregnancy complications, anxiety and preference for delivery mode. The areas under the ROC curves of the modeling group and the verification group were 0.834 and 0.806, respectively. The optimal critical values were 0.113 and 0.200, respectively, with sensitivities of 67.2% and 77.1%, the specificities were 87.3% and 74.0%, and the Jordan indices were 0.545 and 0.511, respectively. The calibration charts of the modeling group and the verification group showed that the coincidence degree between the actual curve and the ideal curve was good. The results of Hosmer-Lemeshow goodness of fit test were χ2=6.541 (P=0.685) and χ2=5.797 (P=0.760), and Brier scores were 0.096 and 0.117, respectively. DCA in modeling group and verification group showed that when the threshold probability of fear of childbirth were 0.00 to 0.70 and 0.00 to 0.70, it had clinical practical value. ConclusionThe nomogram model has good discrimination, calibration and clinical applicability, which can effectively predict the risk of pregnant women's fear of childbirth and provide references for early clinical identification of high-risk pregnant women and targeted intervention.