Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective To investigate the association between obstructive sleep apnea hypopnea syndrome （OSAHS） and white matter lesions （WMLs）. Methods A total of 91 patients who attended Department of Neurology and Department of Epilepsy and Sleep Disorders in The Second Affiliated Hospital of Harbin Medical University from June 2019 to December 2020 and met the diagnostic criteria for WMLs were enrolled as WMLs group， and 61 patients without WMLs were enrolled as control group. All subjects underwent brain MRI and PSG examinations， and related data were collected， including demographic data， past history， personal history， laboratory examination， and imaging findings. Results The WMLs group had a prevalence rate of OSAHS of 92.3% and an AHI of （32.85±19.86） events/hour on PSG， which were significantly higher than those in the control group （P<0.05）. The Spearman rank correlation analysis showed a strong positive correlation between WMLs severity and OSAHS severity（r=0.602 52，P<0.0001）. Conclusion The WMLs group is more susceptible to OSAHS than the control group， and the severity of WMLs is positively correlated with the severity of OSAHS.

With the intensification of population aging in our country, stroke incidence is increasing year by year, and most patients leave behind varying degrees of sequelae; and motor function disorder is one of the common sequelae, which seriously affects the quality of life of patients. Motor function rehabilitations have become indispensable treatments for stroke patients. Accurately and objectively assessing the performance of motor function trehabilitations in stroke patients will help to formulate more reasonable rehabilitation plans. This article reviews the existing rehabilitation assessment techniques and their advantages and disadvantages, aiming to provide guidance for the assessment of motor function rehabilitations in stroke patients and lay a foundation for future development of stroke rehabilitations.

This case report summarized the resuscitation and nursing care of a patient who experienced sudden syncope due to central venous catheter(CVC)removal distress syndrome following coronary artery bypass grafting.Nursing key points:rapidly recognize the patient's CVC removal distress syndrome;continuously monitor circulatory and respiratory functions,maintain circulatory stability,and ensure airway patency;Implement a multi-modal treatment strategy for neurological protection to improve neurological outcomes;Initiate early rehabilitation therapy to promote limb function recovery;Prevent CVC removal distress syndrome.Following emergency rescue and meticulous nursing care,the patient was discharged,on the 34th hospital day with recovery.

This case report summarized the resuscitation and nursing care of a patient who experienced sudden syncope due to central venous catheter(CVC)removal distress syndrome following coronary artery bypass grafting.Nursing key points:rapidly recognize the patient's CVC removal distress syndrome;continuously monitor circulatory and respiratory functions,maintain circulatory stability,and ensure airway patency;Implement a multi-modal treatment strategy for neurological protection to improve neurological outcomes;Initiate early rehabilitation therapy to promote limb function recovery;Prevent CVC removal distress syndrome.Following emergency rescue and meticulous nursing care,the patient was discharged,on the 34th hospital day with recovery.

With the intensification of population aging in our country, stroke incidence is increasing year by year, and most patients leave behind varying degrees of sequelae; and motor function disorder is one of the common sequelae, which seriously affects the quality of life of patients. Motor function rehabilitations have become indispensable treatments for stroke patients. Accurately and objectively assessing the performance of motor function trehabilitations in stroke patients will help to formulate more reasonable rehabilitation plans. This article reviews the existing rehabilitation assessment techniques and their advantages and disadvantages, aiming to provide guidance for the assessment of motor function rehabilitations in stroke patients and lay a foundation for future development of stroke rehabilitations.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

The International Federation of Gynecology and Obstetrics (FIGO) staging of endometrial cancer (EC) is regarded as a crucial tool for guiding treatment, evaluating prognosis, and advancing clinical research. It is a concept of shared importance among gynecologic oncologists, pathologists, and patients with EC. In June 2023, the International Federation of Gynecology and Obstetrics released a new staging system for EC. This review aims to discuss comprehensively the developmental trajectory of FIGO staging for EC, focusing on the differences between the 2023 FIGO and earlier staging systems, and delineating the advantages and disadvantages of incorporating various pathological factors and molecular subtypes into staging. The article emphasizes the progress made with the updated 2023 FIGO version in improving prognostic prediction accuracy for patients with EC. However, as the staging categories expand, their complexity becomes increasingly apparent, potentially impacting health care professionals’ accurate understanding and application of staging. Moreover, unresolved issues persist regarding histological types and grading, lymphovascular space invasion, and molecular subtypes, as well as distinguishing between low-grade endometrioid carcinomas confined to the uterus and ovaries, which may affect the personalized management of patients with EC. In the future, these issues still require extensive clinical research and specific data for validation or confirmation, presenting a challenge shared by gynecologic oncologists and pathologists.

Objective: In the present study, molecular subtypes were determined, programmed deathligand 1 (PD-L1) and tumor-associated immune cells (TAICs) were quantitatively detected, and their effect on prognosis in uterine carcinosarcoma (UCS) was analyzed. Methods: The study included 65 UCS cases. Direct sequencing of POLE exonuclease domain and immunohistochemistry of mismatch repair (MMR) deficiency proteins and p53 were used to stratify molecular subtypes. QuPath was used for quantitative immunohistochemical detection of PD-L1 and TAICs. The chi square test was used to determine the association between molecular subtypes and expression of PD-L1 and TAICs. The Kaplan–Meier method and Cox proportional hazards regression were used for plotting and survival analysis. Results: In 65 UCS cases, 1 case (1.5%) was POLE ultramutated (POLEmut) subtype, 11 cases (16.9%) were deficient MMR (dMMR) subtype, 32 cases (49.3%) were p53 mutant (p53mut) subtype, and 21 cases (32.3%) were nonspecific molecular profile (NSMP) subtype. The positive density of PD-L1 in tumor (p=0.022), CD8 in stroma (p=0.036), and CD163 in stroma (p=0.025) were significantly associated with molecular subtypes. The patients with POLEmut and dMMR subtypes had a relatively better prognosis trend than patients with NSMP and p53mut subtypes. The patients with high positive density of PD-L1 in tumor had significantly better prognosis; however, high positive density of CD163 in stroma showed significantly worse prognosis. Conclusion UCS could be classified into four molecular subtypes associated with prognosis.PD-L1 and M2 macrophages could effectively predict the prognosis of patients with UCS.

Objective:To investigate the predictive value of heparin binding protein(HBP) combined with pediatric sequential organ failure assessment(pSOFA) in children with sepsis.Methods:Children with sepsis admitted to PICU of Hunan Provincial People's Hospital (the First Affiliated Hospital of Hunan Normal University) from January 2021 to June 2022 were selected as study group,while those who underwent elective surgery for inguinal hernia and assessment of precocious puberty and short stature during the same period were selected as control group.All children with sepsis were divided into sepsis group and septic shock group according to their severity as well as survival group and death group according to prognosis.The study group was monitored for HBP on the 1st,3rd,and 7th day of admission,while the control group was monitored for HBP on the 1st day of admission.Patients in the sepsis group received pSOFA scores immediately after admission.The laboratory results and HBP concentrations were compared between groups，and a joint model was established in combination with pSOFA to observe its predictive performance in sepsis prognosis.Results:A total of 50 children with sepsis were included in study group，including 45 children with sepsis and five children with septic shock.There were 27 males and 23 females，aged 1 month～13 years（median age two years）.There were 7 deaths in this study，including two patients with sepsis and five patients with septic shock.The HBP concentration in the study group was significantly higher than that in the control group on the 1st day，and the HBP concentration in the group gradually decreased with the prolongation of hospital stay.The concentration of HBP on the first day of septic shock group was higher than that of sepsis group，and the difference was statistically significant（ P<0.001）.The concentration of HBP on the 1st day in the sepsis death group was significantly higher than that in the sepsis survival group（ P=0.023）.The receivor operator characteristic curve analysis showed that HBP and pSOFA had good predictive value for the death of children with sepsis，and the joint model of HBP and pSOFA（75.1×pSOFA-0.1×HBP）had the best predictive performance for the death of children with sepsis，but there was no significant difference with the pSOFA. Conclusion:The HBP level significantly increases in children with sepsis，and gradually decreases with the length of hospital stay，and HBP has great value in predicting the outcome of death in children with sepsis，and the combination of pSOFA could improve its predictive ability of death,but not better than pSOFA.