OBJECTIVE: To develop a risk assessment model for predicting red blood cell (RBC) transfusion in neonatal patients to assist hospital blood supply departments in providing small portions of RBCs to those requiring RBC transfusion on time. METHODS: Clinical information was collected from 1201 children admitted to the neonatal unit. Clinical factors associated with predicting RBC transfusion were screened, and prediction models were developed using stepwise and multifactorial logistic regression analyses, followed by the evaluation of prediction models using receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). RESULTS: Overall, 81 neonatal patients were transfused with RBCs, and the variables of gestational age at birth, age <1 month, receipt of mechanical ventilation, and infant anaemia were included in the final prediction model. The area under the curve of the prediction model was 0.936 (0.921–0.949), which was significantly higher than that of the individual indicators of gestational age at birth, age at admission <1 month, receipt of mechanical ventilation, and infant anaemia (P<0.001). DCA showed a standardised net benefit for the possible risk of infant RBC transfusion at 0.1–1.0. CONCLUSION: We developed a risk assessment model to predict the risk of RBC transfusion in neonatal patients that can effectively assess the risk of RBC transfusion in children.

Objective This study aimed to investigate the factors associated with pregnancy outcomes and identify potential predictive parameters in women undergoing in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) treatments.Methods A total of 213 women of reproductive age who underwent their first cycle of IVF or ICSI were included in the study. Demographic, hormonal, metabolic, and endocrine data were collected. Logistic regression analysis was performed to evaluate the associations between various factors and pregnancy outcomes. Receiver operating characteristic (ROC) curve analysis was conducted to assess the predictive performance of the significant factors.Results The multivariate analysis revealed that body mass index (BMI), follicle-stimulating hormone (FSH), hemoglobin A1c (HbA1c), and 25-hydroxyvitamin D (Vitamin_D) were significantly associated with pregnancy outcomes. ROC curve analysis demonstrated that BMI, FSH, HbA1c, and Vitamin_D levels showed moderate predictive performance for pregnancy outcomes, with area under the curve (AUC) values ranging from 0.574 to 0.648.Conclusions This study suggests that BMI, FSH, HbA1c, and Vitamin_D levels may play crucial roles in predicting pregnancy outcomes in women undergoing IVF and ICSI treatments. Clinicians should consider these factors when counseling and managing patients undergoing assisted reproductive treatments.

Background This observational study aimed to compare the potential application of thromboelastography (TEG) in diagnosing women with normal pregnancy (NP) and women with threatened abortion (TA), missed abortion (MA), embryo arrest (EA), fetal death (FD), history of abnormal pregnancy (HAP), and antiphospholipid antibody syndrome (AA). Methods According to the relevant clinical criteria, patients were divided into groups, and their blood samples were subjected to TEG. Next, the parameters R, K, α‐angle, MA, LY‐30, G, and coagulation index (CI) were analyzed. Partial correlation analysis was used to analyze correlation between groups of data. LSD‐t test and Dunnett's T3 test were used to analyze continuous variables. Ordinal categorical variables were compared using ordinal logistic regression analysis and estimate odds ratio of risk factors. A receiver operating characteristic (ROC) curve was constructed to detect the ability of TEG to recognize various parameters, and areas under the curve were compared using Delong's test for diagnosing pregnancy‐related diseases. Results MA had a negative effect on the MA parameter in TEG; EA had a negative effect on the MA and G parameters; HAP had a negative effect on the CI parameter and a positive effect on the R parameter; AA had a negative effect on the CI parameter. Compared with that of the NP group, the G of the EA ( p = 0.014) group and the CI of the TA ( p = 0.036) MA ( p = 0.08) EA ( p = 0.026) HAP ( p = 0.000004) and AA ( p = 0.002) groups were reduced. In the ordinal logistic regression analysis, compared with that of the NP group, the high R value of the HAP group accounted for more than that of the NP group (OR = 48.76, p = 0.001); the high K value of the AA group accounted for more than that of the NP group (OR = 17.00, p = 0.023); the angle value distributions of the TA and AA groups were different from that of the NP group (OR = 3.30, p = 0.039; OR = 0.14, p = 0.029); the low MA value of the MA, EA, and HAP groups accounted for more than that of the NP group (OR = 0.16, p = 0.03; OR = 0.26, p = 0.005; OR = 0.11, p = 0.008); and the low CI value of the HAP group accounted for more than that of the NP group (OR = 0.09, p = 0.005). In the ROC analysis, there were no significant differences in the TEG parameters of pregnant women belonging to the NP and TA, NP and MA, NP and EA, NP and FD, NP and HAP, and NP and AA groups ( p > 0.05).