Background::Pulmonary embolism (PE) is a severe and acute cardiovascular syndrome with high mortality among patients with autoimmune inflammatory rheumatic diseases (AIIRDs). Accurate prediction and timely intervention play a pivotal role in enhancing survival rates. However, there is a notable scarcity of practical early prediction and risk assessment systems of PE in patients with AIIRD.Methods::In the training cohort, 60 AIIRD with PE cases and 180 age-, gender-, and disease-matched AIIRD non-PE cases were identified from 7254 AIIRD cases in Tongji Hospital from 2014 to 2022. Univariable logistic regression (LR) and least absolute shrinkage and selection operator (LASSO) were used to select the clinical features for further training with machine learning (ML) methods, including random forest (RF), support vector machines (SVM), neural network (NN), logistic regression (LR), gradient boosted decision tree (GBDT), classification and regression trees (CART), and C5.0 models. The performances of these models were subsequently validated using a multicenter validation cohort.Results::In the training cohort, 24 and 13 clinical features were selected by univariable LR and LASSO strategies, respectively. The five ML models (RF, SVM, NN, LR, and GBDT) showed promising performances, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.962-1.000 in the training cohort and 0.969-0.999 in the validation cohort. CART and C5.0 models achieved AUCs of 0.850 and 0.932, respectively, in the training cohort. Using D-dimer as a pre-screening index, the refined C5.0 model achieved an AUC exceeding 0.948 in the training cohort and an AUC above 0.925 in the validation cohort. These results markedly outperformed the use of D-dimer levels alone.Conclusion::ML-based models are proven to be precise for predicting the onset of PE in patients with AIIRD exhibiting clinical suspicion of PE.Trial Registration::Chictr.org.cn: ChiCTR2200059599.

Objective:To explore the influencing factors of left ventricular thrombus (LVT) in patients with non-ischemic heart failure (NIHF) and to construct a nomogram prediction model for NIHF patients with LVT.Methods:This study was a case-control study. A total of 2 592 patients with NIHF hospitalized in Beijing Anzhen Hospital affiliated to Capital Medical University from January 2018 to July 2022 were selected. Fifty-one patients with LVT identified by echocardiography and cardiac magnetic resonance were classified into LVT group. One hundred and sixty patients were selected as the non-LVT group using a 1∶3 propensity score matching based on age and gender. Multivariate logistic regression analysis was used to explore the influencing factors of LVT in patients with NIHF. A nomogram prediction model was constructed, and the area under (AUC) the receiver operating characteristic (ROC) curve was calculated to evaluate the predictive effect of the model.Results:A total of 211 patients were enrolled, with a median age of 40 years old and 160 males (76%). Compared with non-LVT group, LVT group had lower systolic blood pressure ((112±20) mmHg vs. (120±19) mmHg; 1 mmHg=0.133 kPa), lower left ventricular ejection fraction (LVEF; (27±12)% vs. (39±14)% ), lower proportion of patients with history of hypertension (28% (14/51) vs. 44% (70/160)) and atrial fibrillation (8% (4/51)vs.39% (62/160)), higher proportion of patients with New York Heart Association functional class Ⅲ to Ⅳ (class Ⅲ: 59% (30/51) vs. 41% (66/160); class Ⅳ: 28% (14/51) vs. 19% (31/160)), and larger left ventricular end-systolic diameter (LVESD; (56±14) mm vs. (50±15) mm). The levels of hemoglobin ((152±23) g/L vs. (142±30) g/L), D-dimer (508 (300, 1 105) μg/L vs. 158 (68, 379) μg/L), and N-terminal pro-brain natriuretic peptide (3 429 (2 462, 4 734) ng/L vs. 1 288 (422, 2 544) ng/L) were higher in LVT group than in non-LVT group ( P all<0.05). LVT group had a higher proportion of patients using beta-blockers (92% (47/51) vs. 78% (124/160)), angiotensin-converting enzyme inhibitors or angiotensin receptor blockers or angiotensin receptor neprilysin inhibitors (88% (45/51) vs. 72% (115/160)), and anticoagulant drugs (98% (50/51) vs. 32% (51/160)) than non-LVT group (all P <0.05). Multivariate logistic regression showed that reduced LVEF ( OR=1.08, 95% CI 1.02-1.15, P=0.008), decreased LVESD ( OR=1.07, 95% CI 1.01-1.12, P=0.013), and increased D-dimer levels ( OR=5.40, 95% CI 1.98-14.74, P=0.001) were independent influencing factors for LVT in patients with NIHF. The ROC curve showed that the AUC of the nomogram for predicting LVT in patients with NIHF was 0.793 (95% CI 0.710-0.876, P<0.001). Conclusion:Reduced LVEF, decreased LVESD, and elevated D-dimer are associated with LVT in NIHF patients. The predictive model developed based on the above indicators has certain value in predicting LVT in NIHF patients.

Objective To explore the effect of deep learning image reconstruction(DLIR)algorithm combined with"double low"[low voltage(kV)and low contrast agent dosage]technique on the image quality of coronary computed tomography angiography(CCTA)in overweight patients compared with adaptive statistical iterative reconstruction(ASIR-V)and filtered back projection(FBP).Methods Fifty-two patients with body mass index(BMI)between 25.1 kg/m2and 28 kg/m2 who underwent CCTA scanning were prospectively selected,all of whom scanned on a GE Revolution APEX-CT with a tube voltage of 80 kV,a smart mA(500-1 300 mA),a noise index of 30,and a contrast dosage of 0.5 mL/kg;four groups of images were reconstructed for each patient,FBP,50％ASIR-V,DLIR-M,and DLIR-H.The CT and SD values of the aorta(AO)root,the proximal segment of the right coronary artery(RCA),the left circumflex(LCX),the left anterior descending branch(LAD)and the pericardial fat were measured,and the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were calculated.Two doctors experienced in the diagnosis of cardiovascular disease were selected to subjectively score the reconstructed images using a double-blind method.The SD value,SNR value,CNR value and subjective scores of images in the four groups were compared.Results In the objective image quality evaluation,there were statistically significant differences in SD value,SNR value and CNR value of reconstructed images in the four groups(P＜0.05).As the four groups of reconstruction algorithms FBP,50％ASIR-V,DLIR-M,and DLIR-H were changed sequentially,the image SD value gradually decreased,the SNR value and CNR value gradually increased,and the DLIR-H group had the lowest SD value and the highest SNR and CNR values.In the subjective image quality evaluation,the subjective scores of the two doctors had good consistency(Kappa value=0.900),and the difference between them was statistically significant(P＜0.001).The subjective scores of DLIR-M and DLIR-H groups were higher.Conclusion DLIR algorithm combined with"double-low"technique can significantly improve the CCTA image quality of overweight patients,which is better than 50％ASIR-V and FBP.

Malnutrition, as an independent predictor of incidence and mortality in patients with chronic heart failure (CHF), has a serious impact on the treatment effect of patients. Conducting nutritional risk assessment and providing nutritional interventions for CHF patients can effectively improve their quality of life. On the basis of elaborating on the risk factors for malnutrition in CHF patients, this paper reviews the assessment tools for malnutrition in CHF patients, aiming to promote the localization of malnutrition assessment tools and the research and clinical application of malnutrition specific assessment tools, making nutrition assessment a routine part of overall health assessment for CHF patients.

Objective:To explore the risk factors of oral-mucosal pressure injury (OMPI) in patients with tracheal intubation in ICU and to establish a nomogram model.Methods:Using the convenient sampling method, a total of 640 patients with oral tracheal intubation admitted to ICU of the First Affiliated Hospital of Xinjiang Medical University from January to May 2023 were selected as the research objects. They were divided into the occurrence group ( n=286) and the non-occurrence group ( n=354) according to whether OMPI occurred or not. Binomial Logistic regression analysis was used to explore the risk factors for OMPI in patients with tracheal intubation in ICU. A risk nomogram model was created based on independent risk factors, and internal verification was conducted by Bootstrap repeated sampling method. Results:OMPI occurred in 286 of 640 ICU patients with tracheal intubation. Binomial Logistic regression analysis showed that high APACHEⅡ score, modified Beck oral score greater than or equal to 11 points, use of sedative drugs, prone ventilation, long retention time of tracheal catheter, low oxygenation index less than 200 mmHg (1 mmHg=0.133 kPa) and tracheal catheter fixation frequency of 1 time /24 h were the risk factors for OMPI in patients with tracheal intubation in ICU ( P<0.05). A risk nomogram model for OMPI in patients with tracheal intubation in ICU was established based on independent risk factors. The results showed that the predictive performance (area under the receiver operating characteristic curve of subjects was 0.918, 95% confidence interval was 0.897 to 0.938) and calibration (χ 2 value of 4.647, P=0.795) of the risk nomogram model for OMPI in patients with tracheal intubation in ICU were good. When the threshold probability was 0 to 1, the decision curve showed that the model had good clinical effectiveness. Conclusions:The OMPI risk nomogram model of tracheal intubation patients in ICU established in this study has good calibration and differentiation, which can be used as an effective tool for screening high-risk patients.

This article reported a case of neurodevelopmental disorder accompanied by spastic diplegia and visual impairment with the manifestation of small fetal head circumference. Prenatal ultrasonography performed at 33 +5 weeks of pregnancy revealed small fetal head circumference (-2.61SD) and oligohydramnios. Whole-exome sequencing identified a heterozygous frameshift variation of c.1623_1624insA (p.R542Tfs*30) in the CTNNB1 gene (NM_001904.4) of the fetus. No phenotypic abnormalities or corresponding gene variations were detected in the parents, suggesting it was a de novo variation. Based on the clinical manifestations, the fetus was diagnosed with a neurodevelopmental disorder accompanied by spastic diplegia and visual defects. Following genetic counseling, the pregnant woman chose to terminate the pregnancy.

Objective:To investigate the effects of miRNA-30a-5p (miR-30a-5p) and metadherin (MTDH) on the proliferation, invasion and migration abilities of human breast cancer cells in vitro.Methods:The expression of MTDH in cancer and paracancerous tissues of 112 breast cancer patients in the database and miR-30a-5p in cancer and paracancerous tissues of 103 breast cancer patients in the database were analyzed using data from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was used to analyze the correlation between miR-30a-5p and MTDH in 1 222 breast cancer patients in the database; the data were updated to August 2022. Breast cancer MDA-MB-231 cells were divided into negative control group (transfected with negative control sequence), miR-30a-5p overexpression group (transfected with miR-30a-5p mimics), siMTDH group [transfected with small interfering RNA against MTDH (siMTDH)], siMTDH+miR-30a-5p overexpression group (transfected with both siMTDH and miR-30a-5p mimics); cell proliferation ability was detected by methyl thiazol tetrazolium (MTT) assay, cell migration ability was detected by cell scratch assay, cell invasion ability was detected by Transwell assay. The relative expressions of miR-30a-5p, MTDH, matrix metalloproteinase (MMP)-2, MMP-9, vimentin and β-catenin mRNA in cells were detected by quantitative real-time fluorescence polymerase chain reaction (qRT-PCR), and the expressions of MTDH, N-cadherin (N-cad), β-catenin, Snail and MMP-9 proteins were detected by Western blotting.Results:In the TCGA database, MTDH expression level was higher and miR-30a-5p expression level was lower in breast cancer tissues compared with paracancerous tissues, and the differences were statistically significant (both P < 0.001). There was a negative correlation between MTDH and miR-30a-5p expressions in 1 222 patients with breast cancer ( r=-0.134, P < 0.001). Compared with the negative control group, the cell proliferation ability was reduced in both siMTDH group and miR-30a-5p overexpression group at 24, 48 and 72 h (all P < 0.001). The cell scratch healing rate in miR-30a-5p overexpression group and siMTDH group was lower than that in negative control group [(61.6±1.6)%, (54.7±5.9)% vs. (80.3±3.0)%] (both P < 0.05). Compared with the negative control group, The number of migrated cells in miR-30a-5p overexpression group and siMTDH group was less than that in negative control group (881±50, 725±63 vs. 1 172±66) (both P < 0.05). Compared with the negative control group, the relative expressions of MMP-2, MMP-9, vimentin and β-catenin mRNA were all down-regulated in MDA-MB-231 cells of miR-30a-5p overexpression group and siMTDH group (all P < 0.05). Compared with the negative control group, the relative expressions of N-cad, β-catenin, Snail and MMP-9 proteins were down-regulated in MDA-MB-231 cells of miR-30a-5p overexpression group and siMTDH group (all P < 0.05). There was no statistical difference in the number of migrated MDA-MB-231 cells between siMTDH+miR-30a-5p overexpression group and siMTDH group (476±5 vs. 389±46, t = 3.37, P = 0.078). There was no statistical difference in the number of migrated cells between siMTDH+miR-30a-5p overexpression group and miR-30a-5p overexpression group (476±5 vs. 477±22, t = 0.02, P = 0.983). Conclusions:The expression of miR-30a-5p is negatively correlated with the expression of MTDH in breast cancer tissues, and either overexpression of miR-30a-5p or silence of MTDH in breast cancer MDA-MB-231 cells in vitro can inhibit cell proliferation, invasion and migration, but MTDH may not be a target gene of miR-30a-5p.

Objective: Metabolic syndrome (MetS) is closely related to the increased risk and poor prognosis of endometrial cancer (EC). The purpose of this study was to analyze the relationship between metabolic risk score (MRS) and EC, and establish a predictive model to predict the prognosis of EC. Methods: A retrospective study was designed of 834 patients admitted between January 2004 to December 2019. Univariate and multivariate Cox analysis were performed to screen independent prognostic factors for overall survival (OS). A predictive nomogram is built based on independent risk factors for OS. Consistency index (C-index), calibration plots and receiver operating characteristic curve were used to evaluate the predictive accuracy of the nomogram. Results: The patients were randomly divided into training cohort (n=556) and validation cohort (n=278). The MRS of EC patients, ranging from −8 to 15, was calculated. Univariate and multivariate Cox analysis indicated that age, MRS, FIGO stage, and tumor grade were independent risk factors for OS (p<0.05). The Kaplan–Meier analysis demonstrated that EC patients with low score showed a better prognosis in OS. Then, a nomogram was established and validated based on the above four variables. The C-index of nomogram were 0.819 and 0.829 in the training and validation cohorts, respectively. Patients with high-risk score had a worse OS according to the nomogram. Conclusion We constructed and validated a prognostic model based on MRS and clinical prognostic factors to predict the OS of EC patients accurately, which may help clinicians personalize prognostic assessments and effective clinical decisions.

Objective: To explore the relationship between the muscle mass index (MMI) and the aggregation of cardiovascular risk factors (CVRFs) in children and adolescents, and to provide a scientific basis for the prevention and treatment of cardiovascular diseases in children and adolescents. Methods: The current situation study design was adopted, and 1 622 children and adolescents aged 12-17 years old in Yinchuan City were selected by a cluster random sampling method. All subjects were subjected to questionnaire survey, physical examination, body composition determination and laboratory index testing. Results: When other variables were not adjusted, MMI was a risk factor for the aggregation of cardiovascular risk factors ( P <0.01). After adjusting for age, gender and BMI, MMI became a protective factor for CVRFs≥1 ( OR =0.74, 95% CI =0.62-0.89), compared with insufficient MMI, the risk of developing CVRFs≥1 with good MMI and sufficient MMI was 0.60(95% CI =0.46-0.79), 0.56(95% CI =0.37- 0.85 ) times. The risk of CVRFs≥2 was 0.54(95% CI =0.37-0.79), 0.51(95% CI =0.30-0.87) times, and similar results were found in boys ( P <0.05). Conclusion Under the same BMI level, muscle mass index is a protective factor for cardiovascular risk factor aggregation in children and adolescents. Physical exercise of children and adolescents should be emphasized to maintain the best muscle mass and weight.

Objective:To investigate the relationship between common functional gastrointestinal diseases symptoms with psychological factors, diet and lifestyles by using the network analysis method which has achieved great success in the field of psychology in recent years.Method:A questionnaire survey was conducted in two military units using the cluster sampling method during July 2020, and a total of 1 805 subjects were included. Functional gastrointestinal disease symptoms were evaluated with the Gastrointestinal Symptom Rating Scale (GSRS). The state, trait anxiety scale and stress response scale were used to evaluate the mental and psychological state by self-evaluation. R was used to build the network and calculate statistical parameters.Results:1 486 of the 1 805 subjects (82.3%) had experienced functional gastrointestinal diseases symptoms within 2 weeks, but most of them were mild. Network analysis shows that there was a strong interaction between digestive system symptoms with different clinical manifestations (Spearman coefficient ranges 0.31-0.56). There was a clear relationship between functional gastrointestinal symptoms and mental and psychological factors (Spearman coefficient ranges 0.16-0.27), but there was no clear interaction with diet, age, education level, body mass index, etc. Functional gastrointestinal diseases symptoms were connected with mental and psychological factors through two nodes: stress and indigestion. The stability coefficient of node strength correlation was 0.75, indicating that the network was stable.Conclusions:The current study revealed the network structure and features of functional gastrointestinal diseases symptoms with mental and psychological factors. The key linking nodes provided potential interfering target for controlling functional gastrointestinal symptoms related to mental and psychological factors.