Objective To investigate alterations in serum NOV/CCN3 levels among women during mid-to-late pregnancy and elucidate its association with gestational diabetes mellitus(GDM)and pregnancy outcomes.Methods Based on the results of an oral glucose tolerance test(OGTT),we categorized 252 pregnant women into two groups:the GDM group and the control group.Within the GDM group,participants were further stratified based on pre-pregnancy body mass index levels and pregnancy outcomes.We collected clinical data for all study subjects and compared differences in general information,biochemical indicators,as well as NOV/CCN3 levels between these groups.Results The serum levels of NOV/CCN3 in the GDM group were significantly higher compared to those in the control group(P<0.001).Spearman correlation analysis revealed a positive association between serum NOV/CCN3 and pre-pregnancy body weight,pre-pregnancy body mass index,insulin resistance index,and total cholesterol;while a negative correlation was observed with insulin sensitivity index(P<0.05).Logistic regression analysis demonstrated that NOV/CCN3 is an independent risk factor for the development of GDM[OR=1.097,95%CI(1.020～1.179),P=0.013],as well as adverse pregnancy outcomes in GDM patients[OR=1.032,95%CI(1.020～1.045),P<0.001].ROC analysis indicated AUCs of 0.840 and 0.784 for these associations respectively(P<0.05).Conclusions Serum levels of NOV/CCN3 in pregnant women at mid-to late-stage are associated with obesity,insulin resistance,and glucose-lipid metabolism,suggesting a potential role of NOV/CCN3 in glycolipid metabolism during gestational diabetes mellitus(GDM).These findings provide novel insights for assessing the occurrence of GDM and predicting pregnancy outcomes in mid-to late-stage pregnancies.

Objective : To investigate the prevalence of negative emotions in hospitalized youth patients with type 2 diabetes(T2DM) and its correlation with coping strategies and psychological resilience. Methods : 141 youth T2DM patients who met the research standards were selected. Blood glucose related indicators, blood pressure, body mass index(BMI), diabetes chronic complications screening results and other data were collected. The basic information and disease related information questionnaire, self-rating depression scale(SDS), self-rating anxiety scale(SAS), diabetes distress scale(DDS), medical coping modes questionnaire(MCMQ) and Connor-Davidson resilience scale(CD-RISC) were completed. Results: Among 141 hospitalized youth T2DM patients, 37.6% were combined with depression, 32.6% were combined with anxiety, and 35.5% were combined with diabetic distress(DD). Univariate analysis showed that systolic blood pressure(P<0.01), educational level, and the form of hospitalization expenses(P<0.05) were significantly correlated with depression. Marital status(P<0.01), family residence, blood glucose monitoring methods, and the last fasting blood glucose(P<0.05) were significantly correlated with anxiety. BMI, whether it was first diagnosed or treated(P<0.01), gender, occupation, disease course, weekly blood glucose monitoring frequency, and the presence of chronic complications(P<0.05) were significantly correlated with DD. In multivariate analysis, systolic blood pressure(P<0.01), educational level, and the form of hospitalization expenses were significantly correlated with depression, marital status(P<0.05) was significantly correlated with anxiety; BMI and weekly blood glucose monitoring frequency(P<0.01) were significantly correlated with DD. SDS, SAS, total scores and dimensions of DDS were negatively correlated with the total score and dimensions of CD-RISC(rs=-0.182--0.467, P<0.05 or 0.01), and positively correlated with the yielding coping strategies(rs=0.177-0.271,P<0.05 or 0.01). SAS,total scores and dimensions of DDS were positively correlated with avoiding coping strategies(rs=0.237-0.419,P<0.05 or 0.01). The total and dimensions of CD-RISC were positively correlated with facing coping strategies(rs=0.215-0.349,P<0.05 or 0.01),and negatively correlated with yielding coping strategies(rs=-0.234--0.325,P<0.01). Conclusion More than 30% of hospitalized youth T2DM may experience negative emotions such as depression,anxiety,and DD. The occurrence of negative emotions in such patients may be related to disease management or socio-economic issues such as systolic blood pressure,educational level,hospitalization expenses,marital status,BMI,and frequency of blood glucose monitoring,as well as decreased psychological resilience and negative coping strategies.

Medical record homepage is a core basis for healthcare quality management, medical insurance payment, and public hospital performance evaluation.The completeness and accuracy of its data directly affect the medical quality and economic benefits of hospitals. Since July 2022, a tertiary hospital had built an auxiliary decision-making system for diagnosis omissions based on artificial intelligence technology, which was officially launched in January 2023. The system aimed to improve the quality of data on the first page of medical records and ensure reasonable payment by medical insurance. This system was built on the hospital′s electronic medical records, and integrated natural language processing, medical knowledge graphs and deep learning technologies to create three engines: diagnosis omission recognition, ICD coding and DRG grouping. The diagnosis omission recognition engine identified both explicit and implicit omitted diagnoses by using a context semantic analysis model and a contrastive learning framework for dual judgment. It also interacted with the ICD coding and DRG grouping engines to enhance the accuracy of DRG grouping. Since its launched, the system has achieved remarkable results. A comparative analysis revealed that the rate of missing diagnoses on hospital medical record homepages has decreased from 31.31% during January to September 2022 to 12.34% during the same period in 2023, and the quality control time for a single medical record had been reduced from 20 minutes to 5 minutes. Additionally, a simulation calculation showed that the system-assisted DRG grouping can increase the hospital′s medical insurance surplus. The system could provide reference and guidance for public hospitals in China to improve the quality of the homepage of medical records and better adapt to medical insurance payment reform.

Objective:To explore associated factors of post-discharge depressive symptom severity in patients with bipolar disorder.Methods:A longitudinal follow-up was conducted to investigate the demographic,behavioral,and clinical characteristics,and social function among discharged patients with bipolar disorder who met the DSM-5 diagnostic criteria.Clinical characteristics were assessed with the Hamilton Depression Scale(HAMD)and Brief Psychiatric Rating Scale(BPRS).Single factor and multivariate regression were carried out to explore the associat-ed factors of depressive symptom severity in patients with bipolar disorder.Results:A total of 298 discharged pa-tients with bipolar disorder were face-to-face interviewed to complete the follow-up survey.At follow-up time,psy-chotic symptoms(standardized(β)=0.18),housework((β)=0.23),social interaction((β)=0.17)and BPRS total score((β)=0.46)were positively associated with HAMD total score.Productive labor and work((β)=-0.27)and person-al life management((β)=-0.15)were negatively associated with HAMD total scores.Conclusion:Post-discharge depressive symptom severity in bipolar disorder patients is influenced by multiple factors.Effective management of psychotic symptoms,combined with enhanced community-based social rehabilitation and functional recovery,may help reduce the persistence or worsening of depressive symptoms and improve prognosis.

Objective:To explore associated factors of post-discharge depressive symptom severity in patients with bipolar disorder.Methods:A longitudinal follow-up was conducted to investigate the demographic,behavioral,and clinical characteristics,and social function among discharged patients with bipolar disorder who met the DSM-5 diagnostic criteria.Clinical characteristics were assessed with the Hamilton Depression Scale(HAMD)and Brief Psychiatric Rating Scale(BPRS).Single factor and multivariate regression were carried out to explore the associat-ed factors of depressive symptom severity in patients with bipolar disorder.Results:A total of 298 discharged pa-tients with bipolar disorder were face-to-face interviewed to complete the follow-up survey.At follow-up time,psy-chotic symptoms(standardized(β)=0.18),housework((β)=0.23),social interaction((β)=0.17)and BPRS total score((β)=0.46)were positively associated with HAMD total score.Productive labor and work((β)=-0.27)and person-al life management((β)=-0.15)were negatively associated with HAMD total scores.Conclusion:Post-discharge depressive symptom severity in bipolar disorder patients is influenced by multiple factors.Effective management of psychotic symptoms,combined with enhanced community-based social rehabilitation and functional recovery,may help reduce the persistence or worsening of depressive symptoms and improve prognosis.

Objective To investigate alterations in serum NOV/CCN3 levels among women during mid-to-late pregnancy and elucidate its association with gestational diabetes mellitus(GDM)and pregnancy outcomes.Methods Based on the results of an oral glucose tolerance test(OGTT),we categorized 252 pregnant women into two groups:the GDM group and the control group.Within the GDM group,participants were further stratified based on pre-pregnancy body mass index levels and pregnancy outcomes.We collected clinical data for all study subjects and compared differences in general information,biochemical indicators,as well as NOV/CCN3 levels between these groups.Results The serum levels of NOV/CCN3 in the GDM group were significantly higher compared to those in the control group(P<0.001).Spearman correlation analysis revealed a positive association between serum NOV/CCN3 and pre-pregnancy body weight,pre-pregnancy body mass index,insulin resistance index,and total cholesterol;while a negative correlation was observed with insulin sensitivity index(P<0.05).Logistic regression analysis demonstrated that NOV/CCN3 is an independent risk factor for the development of GDM[OR=1.097,95%CI(1.020～1.179),P=0.013],as well as adverse pregnancy outcomes in GDM patients[OR=1.032,95%CI(1.020～1.045),P<0.001].ROC analysis indicated AUCs of 0.840 and 0.784 for these associations respectively(P<0.05).Conclusions Serum levels of NOV/CCN3 in pregnant women at mid-to late-stage are associated with obesity,insulin resistance,and glucose-lipid metabolism,suggesting a potential role of NOV/CCN3 in glycolipid metabolism during gestational diabetes mellitus(GDM).These findings provide novel insights for assessing the occurrence of GDM and predicting pregnancy outcomes in mid-to late-stage pregnancies.

Medical record homepage is a core basis for healthcare quality management, medical insurance payment, and public hospital performance evaluation.The completeness and accuracy of its data directly affect the medical quality and economic benefits of hospitals. Since July 2022, a tertiary hospital had built an auxiliary decision-making system for diagnosis omissions based on artificial intelligence technology, which was officially launched in January 2023. The system aimed to improve the quality of data on the first page of medical records and ensure reasonable payment by medical insurance. This system was built on the hospital′s electronic medical records, and integrated natural language processing, medical knowledge graphs and deep learning technologies to create three engines: diagnosis omission recognition, ICD coding and DRG grouping. The diagnosis omission recognition engine identified both explicit and implicit omitted diagnoses by using a context semantic analysis model and a contrastive learning framework for dual judgment. It also interacted with the ICD coding and DRG grouping engines to enhance the accuracy of DRG grouping. Since its launched, the system has achieved remarkable results. A comparative analysis revealed that the rate of missing diagnoses on hospital medical record homepages has decreased from 31.31% during January to September 2022 to 12.34% during the same period in 2023, and the quality control time for a single medical record had been reduced from 20 minutes to 5 minutes. Additionally, a simulation calculation showed that the system-assisted DRG grouping can increase the hospital′s medical insurance surplus. The system could provide reference and guidance for public hospitals in China to improve the quality of the homepage of medical records and better adapt to medical insurance payment reform.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

To summarize the nursing care experience of a case of idiopathic multicentric Castleman's disease TAFRO syndrome complicated with diffuse alveolar hemorrhage.Key points of nursing:prone position ventilation with high blood risk nursing observation and bleeding prevention;early rehabilitation exercise and the reduction of the lymphedema;the optimization of transitional care to avoid unplanned returns to the ICU.The patient was transferred to the respiratory ward for further treatment after 19 days,and 33 days later,she recovered and was discharged.At 1 month of follow-up after discharge,the patient recovered well.

Trigeminal neuralgia(TN)has a high incidence rate and severe pain in facial pain.From the angle of etiology,primary TN pathogenesis is not yet clear,often associated with neurovascular compression.Secondary TN is associated with multiple sclerosis or cerebellopontine angle tumors and herpes zoster infec-tion.The cause of idiopathic TN is unclear.Drug therapy and surgical intervention are commonly used in clini-cal treatment,but many patients have no cure and the pain comes repeatedly.Artificial intelligence(AI)has been widely used in different medical fields to achieve the accurate diagnosis,treatment regimen optimization and comprehensive assessment.This article aims to review the application progress of artificial intelligence in the diagnosis and treatment of TN.