OBJECTIVE To systematically review the current application of discrete choice experiment （DCE） in the value assessment and preference measurement of orphan medicinal product （OMP）， and to provide a reference for the standardized use of this methodology in China. METHODS The systematic search was conducted across Chinese and English databases including CNKI， Wanfang Data， VIP， CBM， PubMed， Web of Science， Medline， and Embase. Original studies that employed DCE to evaluate the value or preferences related to OMP were included. The methodological quality and reporting completeness of the included studies were assessed using the ISPOR Conjoint Analysis Checklist and the DIRECT Checklist， respectively. Respondent populations， attribute setting， and the relative importance of attributes were summarized and analyzed. RESULTS Eight eligible studies were included； all studies demonstrated high-quality reporting and methodological rigor. Respondents comprised the general public， patients/caregivers， policymakers， and other stakeholders. The number of DCE attributes ranged from 4 to 13 （median＝7.5）. Through thematic synthesis， these attributes were categorized into three dimensions， namely “disease-related” “treatment-related” and “economic/financial-related” along with 14 secondary criteria. The most frequently included secondary criteria were treatment efficacy （13 occurrences）， disease severity （9 occurrences）， safety （7 occurrences）， unmet medical need （6 occurrences）， and treatment cost （5 occurrences）. Rankings of relative importance identified treatment efficacy as the most valued criterion across most studies， followed by health insurance financing. CONCLUSIONS DCE applications in the value assessment of OMP have begun to converge on a relatively consistent core attribute framework and selection preference. Future research should further promote the use of DCE to inform attribute and criterion selection in multi-criteria decision analysis frameworks for OMP.

PURPOSE: The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery. METHODS: A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications. RESULTS: In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram. CONCLUSION Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans ; COVID-19/complications* ; Male ; Female ; Middle Aged ; Postoperative Complications/epidemiology* ; SARS-CoV-2 ; Orthopedic Procedures/adverse effects* ; Aged ; Nomograms ; Adult ; Retrospective Studies ; Risk Factors

OBJECTIVE: To investigate the clinical features and risk factors associated with cutaneous chronic graft-versus-host disease (cGVHD) after allogeneic hematopoietic stem cell transplantation (allo-HSCT) in children. METHODS: A retrospective analysis was conducted on the clinical data of children who underwent allo-HSCT in the Wuhan Children's Hospital from August 1, 2016, to December 31, 2023, and were regularly followed up for 1 year or more. The differences in clinical features between children with and without cutaneous cGVHD were compared, and the risk factors affecting the occurrence of cutaneous cGVHD were analyzed. RESULTS: During the study period, 296 children received allo-HSCT. Until December 31, 2024, follow-up showed that 20 children (6.8%) developed cutaneous cGVHD, which manifested as cutaneous lichenification, hyperpigmentation, keratosis pilaris, sclerotic changes, and hair or nail involvement. According to their skin lesion area and degree of grading, 5 cases were mild, 10 cases were moderate, and 5 cases were severe. Multivariate logistic regression analysis revealed that female donors and previous acute GVHD were risk factors for the development of cutaneous cGVHD after allo-HSCT. All 20 children were treated with glucocorticoid ± calcineurin inhibitors (tacrolimus/cyclosporine) as first-line therapeutic agents. Only 1 child improved after first-line treatment. The remaining 19 children treated with a second-line regimen of combination interventions based on individualized status, including 10 children who could not tolerate hormonotherapy or first-line treatment, and showed no significant improvement after 3 months, as well as 9 children with multi-organ cGVHD. After comprehensive second-line treatment, 17 children showed improvement in cutaneous symptoms. There were 3 deaths, including 1 due to primary disease recurrence and 2 due to pulmonary infections. CONCLUSION The skin is the first manifestation and most common organ involved in cGVHD in children. Cutaneous cGVHD severely affects the daily activities of transplanted children and requires prolonged immunosuppressive therapy, but has a favorable prognosis. First-line treatments for adults are not applicable to children who usually require a combination treatment with multiple drugs.
Humans ; Graft vs Host Disease/etiology* ; Hematopoietic Stem Cell Transplantation/adverse effects* ; Retrospective Studies ; Risk Factors ; Female ; Child ; Skin Diseases/etiology* ; Chronic Disease ; Transplantation, Homologous ; Male ; Child, Preschool ; Adolescent

Objective:To construct a predictive model for mortality in patients with multiple trauma combined with thoracic injuries and evaluate its predictive value.Methods:A retrospective cohort study was conducted to analyze the clinical data of 184 patients with multiple trauma combined with thoracic injuries admitted to the International Zhuang Medicine Hospital Affiliated to Guangxi University of Chinese Medicine from April 2019 to December 2023, including 129 males and 55 females, aged 19-85 years [(46.1±13.7)years]. According to the prognostic outcomes at 3-month follow-up after discharge, the patients were divided into survival group ( n=145) and death group ( n=39). Data were recorded in both groups at admission, including gender, age, and cause of injury, laboratory tests such as systolic blood pressure, oxygen saturation (SaO 2), hemoglobin (Hb), neutrophil-to-lymphocyte ratio (NLR), and lactate, combined injuries such as the number of combined injuries, number of rib fracture, bilateral rib fracture, first-rib fracture, sternum fracture, thoracic vertebral fracture, bilateral pulmonary contusion, bilateral pneumothorax, subarachnoid hemorrhage, subdural hematoma, epidural hematoma, skull fracture, skull base fracture, cervical vertebral fracture, brain herniation, cerebral contusion, lumbar vertebral fracture, pelvic and abdominal cavity hematoma, liver injury, kidney injury, spleen injury, clavicle fracture, scapular fracture, femoral fracture, and pelvic fracture, and injury scores such as shock index (SI), modified shock index (MSI), injury severity score (ISS), revised trauma score (RTS), Glasgow coma score (GCS), and thoracic trauma severity (TTS) score. Univariate binary logistic regression analysis was used to screen for risk factors of death in patients with multiple trauma combined with thoracic injuries. LASSO regression and multivariate logistic regression analysis were employed to identify predictive variables and independent risk factors for mortality in those patients and to construct a regression equation. A nomogram prediction model based on the regression equation was developed using R language. Receiver operating characteristic (ROC) curves were plotted to evaluate the discrimination of the model. The ROC curves were internally validated using the Bootstrap method with 1 000 resamples. The calibration of the model was assessed using the Hosmer-Lemeshow (H-L) goodness-of-fit test. The clinical application value of the model was evaluated using decision curve analysis (DCA) and clinical impact curve (CIC) analysis. Results:There were statistically significant differences between the survival group and the death group in systolic blood pressure, SaO 2, NLR, lactate, number of combined injuries, subarachnoid hemorrhage, subdural hematoma, skull fracture, skull base fracture, brain herniation, liver injury, SI, MSI, ISS, RTS, GCS, and TTS ( P<0.05 or 0.01). The results of the univariate binary logistic regression analysis showed that the above-mentioned related variables except for systolic blood pressure were all significantly associated with death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Five predictive variables, TTS, GCS, brain herniation, ISS, and lactate were obtained in LASSO regression analysis. The results of the multivariate logistic regression analysis showed that GCS ( OR=0.70, 95% CI 0.58, 0.83), brain herniation ( OR=46.18, 95% CI 4.27, 499.26), TTS ( OR=1.71, 95% CI 1.30, 2.24), and lactate ( OR=1.35, 95% CI 1.01, 1.80) were independent risk factors for death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Based on the aforementioned independent risk factors, a regression formula was constructed as follows: P=e x/(1+e x), with the x=-0.36×"GCS"+3.83×"brain herniation"+0.53×"TTS"+0.30×"lactate levels"-11.03. The area under the ROC curve (AUC) of the predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on the equation was 0.97 (95% CI 0.93, 1.00). The AUC was internally validated using the Bootstrap method with 1 000 samples, resulting in an AUC of 0.97 (95% CI 0.91, 1.00). The results of the H-L goodness-of-fit test showed that the bias-corrected calibration curve of the model was in good consistence with the actual curve and both of them were close to the ideal curve. In the evaluation of the clinical application value of the predictive model, the DCA results showed that the predictive model could achieve good clinical net benefit. The CIC results showed that when the threshold probability was greater than 0.7, the model-identified high-risk patients for death highly matched the patients who actually died. Conclusion:The predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on GCS, brain herniation, TTS, and lactate has good predictive performance and clinical application value.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To construct a predictive model for mortality in patients with multiple trauma combined with thoracic injuries and evaluate its predictive value.Methods:A retrospective cohort study was conducted to analyze the clinical data of 184 patients with multiple trauma combined with thoracic injuries admitted to the International Zhuang Medicine Hospital Affiliated to Guangxi University of Chinese Medicine from April 2019 to December 2023, including 129 males and 55 females, aged 19-85 years [(46.1±13.7)years]. According to the prognostic outcomes at 3-month follow-up after discharge, the patients were divided into survival group ( n=145) and death group ( n=39). Data were recorded in both groups at admission, including gender, age, and cause of injury, laboratory tests such as systolic blood pressure, oxygen saturation (SaO 2), hemoglobin (Hb), neutrophil-to-lymphocyte ratio (NLR), and lactate, combined injuries such as the number of combined injuries, number of rib fracture, bilateral rib fracture, first-rib fracture, sternum fracture, thoracic vertebral fracture, bilateral pulmonary contusion, bilateral pneumothorax, subarachnoid hemorrhage, subdural hematoma, epidural hematoma, skull fracture, skull base fracture, cervical vertebral fracture, brain herniation, cerebral contusion, lumbar vertebral fracture, pelvic and abdominal cavity hematoma, liver injury, kidney injury, spleen injury, clavicle fracture, scapular fracture, femoral fracture, and pelvic fracture, and injury scores such as shock index (SI), modified shock index (MSI), injury severity score (ISS), revised trauma score (RTS), Glasgow coma score (GCS), and thoracic trauma severity (TTS) score. Univariate binary logistic regression analysis was used to screen for risk factors of death in patients with multiple trauma combined with thoracic injuries. LASSO regression and multivariate logistic regression analysis were employed to identify predictive variables and independent risk factors for mortality in those patients and to construct a regression equation. A nomogram prediction model based on the regression equation was developed using R language. Receiver operating characteristic (ROC) curves were plotted to evaluate the discrimination of the model. The ROC curves were internally validated using the Bootstrap method with 1 000 resamples. The calibration of the model was assessed using the Hosmer-Lemeshow (H-L) goodness-of-fit test. The clinical application value of the model was evaluated using decision curve analysis (DCA) and clinical impact curve (CIC) analysis. Results:There were statistically significant differences between the survival group and the death group in systolic blood pressure, SaO 2, NLR, lactate, number of combined injuries, subarachnoid hemorrhage, subdural hematoma, skull fracture, skull base fracture, brain herniation, liver injury, SI, MSI, ISS, RTS, GCS, and TTS ( P<0.05 or 0.01). The results of the univariate binary logistic regression analysis showed that the above-mentioned related variables except for systolic blood pressure were all significantly associated with death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Five predictive variables, TTS, GCS, brain herniation, ISS, and lactate were obtained in LASSO regression analysis. The results of the multivariate logistic regression analysis showed that GCS ( OR=0.70, 95% CI 0.58, 0.83), brain herniation ( OR=46.18, 95% CI 4.27, 499.26), TTS ( OR=1.71, 95% CI 1.30, 2.24), and lactate ( OR=1.35, 95% CI 1.01, 1.80) were independent risk factors for death in patients with multiple trauma combined with thoracic injuries ( P<0.05 or 0.01). Based on the aforementioned independent risk factors, a regression formula was constructed as follows: P=e x/(1+e x), with the x=-0.36×"GCS"+3.83×"brain herniation"+0.53×"TTS"+0.30×"lactate levels"-11.03. The area under the ROC curve (AUC) of the predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on the equation was 0.97 (95% CI 0.93, 1.00). The AUC was internally validated using the Bootstrap method with 1 000 samples, resulting in an AUC of 0.97 (95% CI 0.91, 1.00). The results of the H-L goodness-of-fit test showed that the bias-corrected calibration curve of the model was in good consistence with the actual curve and both of them were close to the ideal curve. In the evaluation of the clinical application value of the predictive model, the DCA results showed that the predictive model could achieve good clinical net benefit. The CIC results showed that when the threshold probability was greater than 0.7, the model-identified high-risk patients for death highly matched the patients who actually died. Conclusion:The predictive model for mortality in patients with multiple trauma combined with thoracic injuries based on GCS, brain herniation, TTS, and lactate has good predictive performance and clinical application value.

Formaldehyde is a prevalent organic solvent in industrial and indoor environment,which can seriously harm human health,so it is of great significance to develop highly sensitive formaldehyde sensors with fast response,low detection limit and long life.In this study,the NiO-In2O3 composite structure was prepared using indium-based metal organic framework(In-MOF)as the precursor,and the formaldehyde gas sensor was constructed with In2O3 and NiO-In2O3 composite structure as the sensitive material.The results demonstrated that the In2O3 material had a microflower-like structure,while the NiO-In2O3 composite structure was composed of NiO nanoparticles attached to the surface of In2O3.The sensor exhibited excellent detection performance for formaldehyde in the environment of relative humidity of 33%and 75%,especially the response characteristic of the NiO-In2O3 composite structure sensor to formaldehyde was considerably better than that of the In2O3 sensor under the same test conditions,which was closely related to the catalytic effect of NiO and the heterogeneous structure formed between NiO and In2O3.The NiO-In2O3 composite structure sensor had a response value of 21.3 and 12.6 to 10 μL/L formaldehyde when the relative humidity was 33%and 75%at 200℃.The response/recovery time was 4/6 s and 7/10 s,and the limit of detection(LOD)was 1.2×10-7 μL/L and 4.1×10-5 μL/L respectively.Meanwhile,the sensor had excellent selectivity and long-term stability.This sensor showed a wide application prospect in the field of high-performance detection of low concentration of formaldehyde gas.

Odontogenic maxillary sinusitis(OMS)is a subtype of maxillary sinusitis(MS).It is actually inflammation of the maxillary sinus that secondary to adjacent infectious maxillary dental lesion.Due to the lack of unique clinical features,OMS is difficult to distinguish from other types of rhinosinusitis.Besides,the characteristic infectious pathogeny of OMS makes it is resistant to conventional therapies of rhinosinusitis.Its current diagnosis and treatment are thus facing great difficulties.The multi-disciplinary cooperation between otolaryngologists and dentists is absolutely urgent to settle these questions and to acquire standardized diagnostic and treatment regimen for OMS.However,this disease has actually received little attention and has been underrepresented by relatively low publication volume and quality.Based on systematically reviewed literature and practical experiences of expert members,our consensus focuses on characteristics,symptoms,classification and diagnosis of OMS,and further put forward multi-disciplinary treatment decisions for OMS,as well as the common treatment complications and relative managements.This consensus aims to increase attention to OMS,and optimize the clinical diagnosis and decision-making of OMS,which finally provides evidence-based options for OMS clinical management.

Objective To analyze the cognition level of health care workers(HCWs)and the management status of various levels of medical institutions towards allergy reactions to commonly used antimicrobial agents.Methods HCWs and clinical pharmacists who were related to the diagnosis and treatment of antimicrobial agents in 14 medical institutions of city-level and autonomous prefectures in Gansu Province were randomly selected for a questionnaire survey.The survey contents included respondents'basic information,criteria for judging antimicrobial allergy,awareness on procedures related to antimicrobial allergy,and antimicrobial management level of different levels of medical institutions.Results A total of 8 670 valid questionnaires from HCWs were collected,including 3 300 phy-sicians,5 024 nurses and 328 pharmacists.160,775,2 123 and 5 612 HCWs were with senior,associate,interme-diate and junior professional titles,respectively.87.66％of the HCWs received relevant training on antimicrobial management in the past two years,the proportion of HCWs from different levels of medical institutions who have received training on antimicrobial management in the past two years was statistically significant different(x2=42.668,P＜0.001).HCWs with senior professional titles had the highest proportion of receiving relevant training(93.75％),there was a statistically significant difference in the proportion of receiving antimicrobial management training among HCWs with different professional titles in the past two years(x2=69.782,P＜0.001).50.98％of HCWs were not clear about penicillin allergy,and most of whom were with junior professional titles,accounting for 68.52％.25.19％of HCWs expressed uncertainty about whether patients with penicillin allergy could use cephalosporins,225 of whom were with associate professional titles,accounting for 29.03％of the total number of HCWs with associate profe-ssional titles.6.11％of HCWs had no experience in skin test procedure;46.94％of HCWs expressed that their medical institutions had no or unclear about whether their medical institutions had an antimicrobial allergy assess-ment team.Conclusion HCWs'judgment on allergy reactions to commonly used antimicrobial agents and aware-ness on antimicrobial application is not high enough,and the overall management level of antimicrobial allergy in all levels of medical institutions is poor.The popularity of antimicrobial allergy assessment teams is not high,and there is an urgent need to strengthen supervision,management,training,et al.