Development of a nomogram for the prediction of complicated appendicitis during pregnancy.

BACKGROUND: Complicated appendicitis during pregnancy directly affects the clinical prognosis of both mother and fetus. However, accurate identification of complicated appendicitis in pregnancy is fraught with various challenges. The purpose of this study was to identify the risk factors and to develop a useful nomogram to predict complicated appendicitis during pregnancy. METHODS: This retrospective study involved pregnant women who underwent appendectomy at the Maternal and Child Health Hospital of Hubei Provincial from May 2016 to May 2022 and who ultimately had histopathological confirmed acute appendicitis. Univariate and multivariate logistic regression were applied to analyze clinical parameters and imaging features as a way to identify risk factors. Then, nomogram and scoring systems predicting complicated appendicitis in pregnancy were constructed and evaluated. Finally, the potential non-linear association between risk factors and complicated appendicitis was analyzed using restricted cubic splines. RESULTS: Three indicators were finally identified for the construction of the nomogram: gestational weeks, C-reactive protein (CRP), and neutrophil percentage (NEUT%). To improve the clinical utility, the gestational weeks were divided into three periods (first trimesters, second trimesters, and third trimesters), while the optimal cut-offs for CRP level and NEUT% were found to be 34.82 mg/L and 85.35%, respectively. Multivariate regression analysis showed that third trimesters (P = 0.013, OR = 16.81), CRP level ≥ 34.82 mg/L (P = 0.007, OR = 6.24) and NEUT% ≥85.35% (P = 0.011, OR = 18.05) were independent risk factors for complicated appendicitis. The area under the ROC curve (AUC) of the nomogram predicting complicated appendicitis in pregnancy was 0.872 (95% CI: 0.803-0.942). In addition, the model was shown to have excellent predictive performance by plotting calibration plots, Decision Curve Analysis (DCA), and clinical impact curves. When the optimal cut-off point of the scoring system was set at 12, the corresponding AUC, sensitivity, specificity, Positive Likelihood Ratio (PLR), Negative Likelihood Ratio (NLR), Positive Predictive Value (PPV), and Negative Predictive Value (NPV) values were AUC: 0.869(95% CI: 0.799-0.939),100%, 58.60%, 2.41, 0, 42%, and 100%, respectively. The restricted cubic splines revealed a linear relationship between these predictors and complicated appendicitis during pregnancy. CONCLUSIONS: The nomogram utilizes a minimum number of variables to develop an optimal predictive model. Using this model, the risk of developing complicated appendicitis in individual patients can be determined so that reasonable treatment choices can be made.

Analysis of risk factors for complicated appendicitis during pregnancy and evaluation of clinical prediction model: A prospective cohort study.

OBJECTIVE: To investigate the risk factors and the value of clinical prediction model for complicated appendicitis (CA) during pregnancy. METHODS: Prospective analysis of pregnant patients who underwent appendectomy at a single tertiary care center between February 2020 and February 2023 and who ultimately had pathologically confirmed acute appendicitis (AA). According to intraoperative conditions and postoperative pathology, they were divided into the CA group and the uncomplicated appendicitis (UA) group. The two groups of patients were then compared in terms of demographic characteristics, disease features, ancillary tests and predictive models of acute appendicitis. RESULTS: A total of 90 patients with AA in pregnancy were included, 21 of whom had CA in pregnancy and 69 had UA in pregnancy. Multivariate regression analysis showed that gestational week, neutrophil ratio and C-reactive protein (CRP) were independent risk factors for CA during pregnancy. Relative to the first trimester, the third trimesters had an increased risk of complicated appendicitis (OR = 12.48, 95% CI: 1.56-99.57, P = 0.017). Neutrophil ratio ≥85.30% (OR = 24.54, 95% CI: 2.59-232.72, P = 0.005) and CRP ≥34.26 mg/L (OR = 7.86, 95% CI: 2.18-28.38, P = 0.002) had a significantly increased risk of CA. The AIR and AAS score models were statistically different between the two groups, but with a lower sensitivity of 52.38% and 42.86%, respectively. CONCLUSION: The third trimesters, neutrophil ratio ≥85.30% and CRP ≥34.26 mg/L may be key predictors of CA in pregnancy. The current scoring model is inadequate to identify complex appendicitis in pregnancy and further research is needed.

Comparision of Ligasure hemorrhoidectomy and conservative treatment for thrombosed external hemorrhoids (TEH) in pregnancy.

BACKGROUND: Ligasure hemorrhoidectomy for thrombosed external hemorrhoids in pregnancy has been rarely studied. OBJECTIVE: The purpose of this article is to study the efficacy and safety of Ligasure hemorrhoidectomy comparing with conservative treatment for thrombosed external hemorrhoids in pregnancy. DESIGN: This was a retrospective cohort study. SETTING: The patients were treated at a tertiary referral center in China. PATIENTS: 94 pregnant patients hospitalized for thrombosed external hemorrhoids from September 2020 to December 2021. INTERVENTIONS: Ligasure hemorrhoidectomy treatment or conservative treatment according to the patient's wishes. MAIN OUTCOME MEASURES: Symptom relief, recurrence and satisfaction of thrombosed external hemorrhoids in pregnancy with different interventions. RESULTS: There were no differences between groups in maternal age, gestational age, body mass index, parity, constipation and a prior history of thrombosed external hemorrhoids. The pain scores were less in surgical group than in conservative group in post-treatment days 1 and 7. Time to return to normal activities was shorter in surgical group than in conservative group (6.51 vs. 13.52 days, P < 0.001). Post-treatment complications were mild in surgical group and there were no significant differences concerning the rate of abortion, preterm birth, cesarean delivery and weight of fetus. Recurrence rate was significantly lower in surgical group (8.57% vs. 30.43%, P = 0.017). The patient satisfaction scores were significantly higher in surgical group than in conservative group (Z = - 2.979, P = 0.003). LIMITATIONS: This was a retrospective study with a limited number of patients, the data was obtained from only one center. CONCLUSIONS: Comparing with conservative treatment, Ligasure hemorrhoidectomy for TEH in pregnancy results in more rapid pain relief, shorter time to return to normal activities, lower incidence of recurrence, and better patient satisfaction. This type of surgery has low and mild postoperative complications, is not attended by any risk to the mother or her fetus.

Optimizing the Synthetic Conditions of "Green" Colloidal AgBiS2 Nanocrystals Using a Low-Cost Sulfur Source.

Colloidal AgBiS2 nanocrystals (NCs) have attracted increasing attention as a near-infrared absorbent materials with non-toxic elements and a high absorption coefficient. In recent years, colloidal AgBiS2 NCs have typically been synthesized via the hot injection method using hexamethyldisilathiane (TMS) as the sulfur source. However, the cost of TMS is one of the biggest obstacles to large-scale synthesis of colloidal AgBiS2 NCs. Herein, we synthesized colloidal AgBiS2 NCs using oleylamine@sulfur (OLA-S) solution as the sulfur source instead of TMS and optimized the synthesis conditions of colloidal AgBiS2 NCs. By controlling the reaction injection temperature and the dosage of OLA-S, colloidal AgBiS2 NCs with adjustable size can be synthesized. Compared with TMS-based colloidal AgBiS2 NCs, the colloidal AgBiS2 NCs based on OLA-S has good crystallinity and fewer defects.

The Material Basis and Mechanism of Xuefu Zhuyu Decoction in Treating Stable Angina Pectoris and Unstable Angina Pectoris.

METHODS: Firstly, we used a network proximity approach to calculate and compare the effectiveness of the formula with that of Western drugs for each type of angina, including all targets and intersecting targets, from a topological perspective. Secondly, we compared the mechanisms of action of the two angina pectoris at three levels and five aspects, including conventional and modular analysis approaches. Thirdly, based on the unique functions of each angina in the complex heterogeneous network, we designed a reverse process for finding the material basis using dynamic, static, and enriched items as well as a total item. Finally, the designed inverse process, material basis, and mechanism of action were validated. RESULTS: The target network of Xuefu Zhuyu decoction is closer to the target network of each type of angina than that of Western drugs, and the intersection targets have a closer proximity. Comparison of the mechanisms of action showed that stable angina and unstable angina had 158 common targets, while the unique targets were 34 and 1, respectively. Modularity analysis showed that the GO similarity of target modules was highly correlated with KEGG similarity. We ended up with 67 compounds upregulated for stable angina and 47 compounds upregulated for unstable angina. Our results were validated by literature mining, high-volume molecular docking, and miRNA enrichment analysis. CONCLUSIONS: For both types of angina pectoris, Xuefu Zhuyu decoction is superior to Western drugs. A comparison of various aspects led to the unique mechanisms of action, from which the material basis of each type of angina was deduced.

A Complex Heterogeneous Network Model of Disease Regulated by Noncoding RNAs: A Case Study of Unstable Angina Pectoris.

MicroRNAs (miRNAs) are important types of noncoding RNAs, and there is a lack of holistic and systematic understanding of the functions they play in disease. We proposed a research strategy, including two parts network analysis and network modelling, to analyze, model, and predict the regulatory network of miRNAs from a network perspective, using unstable angina pectoris as an example. In the network analysis section, we proposed the WGCNA & SimCluster method using both correlation and similarity to find hub miRNAs, and validation on two datasets showed better results than the methods using correlation or similarity alone. In the network modelling section, we used six knowledge graph or graph neural network models for link prediction of three types of edges and multilabel classification of two types of nodes. Comparative experiments showed that the RotatE model was a good model for link prediction, while the RGCN model was the best model for multilabel classification. Potential target genes were predicted for hub miRNAs and validation of hub miRNA-target gene interactions, target genes as biomarkers and target gene functions were performed using a three-step validation approach. In conclusion, our study provides a new strategy to analyze and model miRNA regulatory networks.