Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

OBJECTIVE: To determine risk factors for cutout failure in geriatric intertrochanteric fracture patients after cephalomedullary nail fixation. METHODS: A retrospective review of 518 elderly patients who underwent cephalomedullary nail fixation for intertrochanteric fractures between January 2008 and August 2018 was conducted, including 167 males and 351 females, age from 65 to 97 years old. All patients were followed up for at least one year after surgery and divided into a healed group and a cutout group based on whether the hip screw cutout occurred. Among all patients, 10 cases experienced hip screw cutout. The general information, surgical data, and radiological data of the two groups were compared, and risk factors influencing hip screw cutout were analyzed. Propensity score matching was then performed on the cutout group based on gender, age, body mass index(BMI), and American Society of Anesthesiologists(ASA), and 40 patients from the healed group were matched at a ratio of 1∶4. Key risk factors affecting hip screw cutout were further analyzed. Multivariable logistic regression analysis was conducted to evaluate associations between variables and cutout failure. RESULTS: There were no statistically significant differences between the healed group and the cutout group in terms of age, gender, BMI, ASA, and AO classification. However, statistically significant differences were observed between the two groups in terms of reduction quality(P=0.003) and tip-apex distance(TAD), P<0.001. Multivariate analysis identified poor reduction quality OR=23.138, 95%CI(2.163, 247.551), P=0.009 and TAD≥25 mm OR=30.538, 95%CI(2.935, 317.770), P=0.004 as independent risk factors for cutout failure. CONCLUSION The present study identified poor reduction quality and TAD≥25 mm as factors for cutout failure in geriatric intertrochanteric fractures treated with cephalomedullary nails. Further studies are needed to calculate the optimal TAD for cephalomedullary nails.
Humans ; Male ; Female ; Hip Fractures/surgery* ; Aged, 80 and over ; Aged ; Risk Factors ; Retrospective Studies ; Fracture Fixation, Intramedullary/adverse effects* ; Bone Nails ; Bone Screws

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Objective To evaluate the efficacy and safety of brexpiprazole in treating acute schizophrenia.Methods Patients with schizophrenia were randomly divided into treatment group and control group.The treatment group was given brexpiprozole 2-4 mg·d-1 orally and the control group was given aripiprazole 10-20 mg·d-1orally,both were treated for 6 weeks.Clinical efficacy of the two groups,the response rate at endpoint,the changes from baseline to endpoint of Positive and Negative Syndrome Scale(PANSS),Clinical Global Impression-Improvement(CGI-S),Personal and Social Performance scale(PSP),PANSS Positive syndrome subscale,PANSS negative syndrome subscale were compared.The incidence of treatment-related adverse events in two groups were compared.Results There were 184 patients in treatment group and 186 patients in control group.After treatment,the response rates of treatment group and control group were 79.50％(140 cases/184 cases)and 82.40％(150 cases/186 cases),the scores of CGI-I of treatment group and control group were(2.00±1.20)and(1.90±1.01),with no significant difference(all P＞0.05).From baseline to Week 6,the mean change of PANSS total score wese(-30.70±16.96)points in treatment group and(-32.20±17.00)points in control group,with no significant difference(P＞0.05).The changes of CGI-S scores in treatment group and control group were(-2.00±1.27)and(-1.90±1.22)points,PSP scores were(18.80±14.77)and(19.20±14.55)points,PANSS positive syndrome scores were(-10.30±5.93)and(-10.80±5.81)points,PANSS negative syndrome scores were(-6.80±5.98)and(-7.30±5.15)points,with no significant difference(P＞0.05).There was no significant difference in the incidence of treatment-related adverse events between the two group(69.00％vs.64.50％,P＞0.05).Conclusion The non-inferiority of Brexpiprazole to aripiprazole was established,with comparable efficacy and acceptability.

Objective To investigate the correlation between serum vascular endothelial growth factor(VEGF),Cystatin C(CysC),and retinol-binding protein(RBP)levels and the pathology and prognosis of chronic glomerulonephritis(CGN).Methods A total of 102 patients with CGN diagnosed and treated between June 2020 and August 2022 were selected as study participants and assigned to the observation group,which was divided according to pathological types into the mesangial proliferative nephritis(MSPGN,n=35),mesangial capillary glomerulonephritis(MPGN,n=23),membranous nephropathy(MN,n=23),and focal segmental glomerulosclerosis(FSGS,n=17)groups.Healthy subjects(n=51)were selected as the control group.Changes in serum VEGF,CysC,and RBP levels were compared,and the correlation between VEGF,CysC,and RBP levels and pathological scores was analyzed using the Pearson method.All patients were followed up for 12 months and divided according to prognoses into a progression group(n=28)and no progression/remission group(n=74).The effects of VEGF,CysC,and RBP levels on the prognosis of patients with CGN were analyzed using Cox multifactor risk regression.The area under the curve(AUC),sensitivity,and specificity of VEGF,CysC,RBP,and the combined prognoses of patients with CGN were analyzed using a receiver operating characteristic(ROC)curve.Results The VEGF,CysC,and RBP levels were higher in the observation group than in the control group(P<0.05).The VEGF,and CysC,levels in the FSGS group were higher than those in the MSPGN,MPGN,and MN groups(P<0.05).The level of RBP in FSGS group was higher than that in MSPGN group(P<0.05).Pearson correlation analysis showed that VEGF,CysC,and RBP levels were positively correlated with the pathological scores(P<0.05).The VEGF,CysC,and RBP levels were higher in the progression group than in the no progression/remission group(P<0.05).Multivariate Cox regression analysis showed that increased VEGF,CysC,and RBP levels were risk factors for the prognosis of patients with CGN(P<0.05).The ROC curve analysis showed that the AUC values predicted by VEGF,CysC,RBP,and the combination of the three were 0.828,0.844,0.760,and 0.940,respectively(P<0.05);sensitivity was 75.00%,71.40%,57.10%,and 89.30%,respectively,and specificity was 93.20%,93.20%,95.90%,and 89.20%,respectively.Conclusion Serum VEGF,CysC,and RBP are highly expressed in patients with CGN,and high pathological scores are associated with increased levels,thus also affecting patient prognosis.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*