Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

Objective:Near-infrared(NIR)spectroscopy technology faces the problem of insufficient model generalization due to individual differences in non-invasive blood glucose testing,in order to solve this problem,to improve data utilization,and to build predictive models with stronger generalization ability,this study introduces a transfer learning method to study the NIR spectroscopy non-invasive glucose testing.Methods:Migration learning is a machine learning technique that aims to improve task performance in the target domain by transferring knowledge from the source domain to the target domain.In this study,we used community population data as the source domain and student population data as the target domain to improve the performance of the noninvasive glucose detection model on the target domain.In order to verify the effectiveness of migration learning,this study compares the performance of the model before and after migration learning.Results:the model's performance on the noninvasive glucose detection task is significantly improved by the migration learning strategy,and the MAPE and MAE of the migrated model decreases by 52.5460％and 6.0805％,respectively,and the RMSE and MSE decreases by 10.7215％and 12.1135％.Conclusions:This study demonstrates the promising application of transfer learning in the field of non-invasive blood glucose detection,which is expected to realize portable and continuous blood glucose monitoring in the future by migrating the features that are difficult to access in the source domain but are related to blood glucose values to the target domain,which will greatly improve the quality of life of diabetic patients.Advances in noninvasive glucose testing technology will not only reduce patients' pain,but also provide a more convenient means of glucose monitoring,which will provide strong support for diabetes management.

Objective:To construct a maintenance management system based on Total Productive Maintenance(TPM)theory for large-scale medical equipment,and explore its application effect in the management for large-scale medical equipment.Methods:By building TPM management team,predicting equipment's failures,planning TPM management pathway for equipment,and implementing quality control to construct TPM management system for the large-scale medical equipment.A total of 547 large-scale medical equipment that were used in clinical practice at the First Affiliated Hospital of Harbin Medical University from February 2022 to July 2024 were selected.They were divided into conventional management mode(272 equipment)and TPM management mode(275 equipment)by using random number table method.The TPM management mode conducted management on the basis of TPM management system for large-scale medical equipment.The equipment configuration,operational quality,effectiveness of equipment maintenance,and maintenance quality of the two kinds of management modes were compared.Using a self-made satisfaction questionnaire to evaluate the satisfaction of management personnel who used equipment for the service quality of maintenance management of two management modes for medical equipment.Results:The average configuration rate,utilization rate,and operation rate of equipment that using TPM management mode were(4.81±0.94)%,(97.98±0.67)%,and(89.15±4.78)%,respectively,all which were higher than those that using conventional management mode.However,the average failure rate was(1.72±0.12)%,which was lower than that of using conventional management mode.The differences of the above indicators were statistically significant(t=39.942,80.213,23.188,71.723,P<0.05).The average values of the efficiency of equipment maintenance,the standardization of usage,timeliness of maintenance,and pass rate of quality inspection of TPM management mode were all higher than those of conventional management mode,and the differences were statistically significant(t=36.893,22.913,17.948,21.553,P<0.05).The response time,average repair rate of failure,and delivery cycle of accessories of equipment maintenance of TPM management mode were all lower than those of conventional management mode,while the quality score of maintenance service was higher than that of conventional management mode,and the differences were statistically significant(t=37.332,25.116,53.265,55.988,P<0.05).The satisfactions of management personnel who used equipment for preventive maintenance,preventive repair,usage management,fault repair,quality inspection,and post maintenance of equipment that adopted TPM management mode were all higher than those that adopted conventional management mode,and the differences were statistically significant(t=24.218,21.408,19.706,27.141,38.149,46.434,P<0.05).Conclusion:The maintenance management system based on TPM theory for large-scale medical equipment can effectively improve operation efficiency and maintenance quality of equipment,and reduce equipment's failure rate,and enhance the timeliness of maintenance services for equipment,and increase the satisfaction of management personnel in using equipment.

Taking Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine as an example,this paper sum-marizes the important role and practical experience of new cultural development in promoting the hospital's high-quality growth.It explores pathways for new cultural development to facilitate the high-quality advancement of integrated traditional Chinese and Western medicine hospitals,aiming to provide valuable practical guidance and theoretical support for such hospitals in the context of the new era.

Diabetic peripheral neuropathy (DPN) is one of the common chronic complications of diabetes, presenting with neuropathic pain, sensory abnormalities, and sensory loss, and may lead to foot infections, ulcers, or amputation in severe cases. Its pathogenesis remains unclear, with challenge in early diagnosis and limited treatment efficacy. Emerging evidences suggest that DPN involves in not only the peripheral nervous system but also the central nervous system (CNS). With advances in imaging technologies, multimodal MRI has become a key tool to investigate CNS involvement in DPN. This review summarizes the structural, functional, metabolic, and perfusion-related CNS changes in DPN patients based on structural MRI, functional MRI, MR spectroscopy, and perfusion-weighted imaging, aiming to help early detection, clinical subtyping, and personalized treatment of DPN.

Objective:To translate and adapt the postoperative recovery in children (PRiC) scale, developing a Chinese version for children undergoing dental treatment under general anesthesia (PRiC-DTGA) with validated psychometric properties.Methods:The PRiC scale underwent forward-backward translation using Brislin′s model. A convenience sample of DTGA patients from the Department of Anesthesiology, School of Stomatology, The Fourth Mility Force Medical University was enrolled for a cross-sectional survey on postoperative complications. Delphi expert consultation informed cultural adaptation based on survey findings to develop the PRiC-DTGA Chinese version. Psychometric validation included reliability and validity testing in a separate DTGA cohort at the same center (April-October 2024).Results:Results from the cross-sectionalsurvey of 231 children showed that 82.7% (191/231) of them hadat least one postoperative complication within 72 hours, and these complications were mainly mild local symptoms. Additionally, 358 copies of the Chinese version of the PRiC-DTGA scale were distributed; 21 invalid questionnaires with incomplete information were excluded, and a total of 337 cases were included inthe study. The final PRiC-DTGA comprised 22 items across three dimensions including physical comfort, social ability, and negative emotional. Exploratory factor analysis (EFA) confirmed all factor loadings>0.4. Confirmatory factor analysis (CFA) demonstrated adequate fit: χ 2/df=1.665, tucker-Lewis index (TLI)=0.924, comparative fit index (CFI)=0.896, standardized root mean square residual (SRMR)=0.041, and root mean square error of approximation (RMSEA)=0.044 (90% CI: 0.035-0.053). Reliability was strong with Cronbach′s α (total scale)=0.853, subscale α=0.632-0.723, split-half reliability=0.824. Validity indices met standards: scale-content validity index (S-CVI)=0.909, Item-CVI range=0.944-1.000, average variance extracted (AVE)=0.473-0.501, composite reliability (CR)=0.830-0.913. Conclusions:The systematically adapted PRiC-DTGA demonstrates robust reliability and validity, serving as an effective tool for assessing postoperative recovery quality in Chinese children following DTGA.

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

Objective:Near-infrared(NIR)spectroscopy technology faces the problem of insufficient model generalization due to individual differences in non-invasive blood glucose testing,in order to solve this problem,to improve data utilization,and to build predictive models with stronger generalization ability,this study introduces a transfer learning method to study the NIR spectroscopy non-invasive glucose testing.Methods:Migration learning is a machine learning technique that aims to improve task performance in the target domain by transferring knowledge from the source domain to the target domain.In this study,we used community population data as the source domain and student population data as the target domain to improve the performance of the noninvasive glucose detection model on the target domain.In order to verify the effectiveness of migration learning,this study compares the performance of the model before and after migration learning.Results:the model's performance on the noninvasive glucose detection task is significantly improved by the migration learning strategy,and the MAPE and MAE of the migrated model decreases by 52.5460％and 6.0805％,respectively,and the RMSE and MSE decreases by 10.7215％and 12.1135％.Conclusions:This study demonstrates the promising application of transfer learning in the field of non-invasive blood glucose detection,which is expected to realize portable and continuous blood glucose monitoring in the future by migrating the features that are difficult to access in the source domain but are related to blood glucose values to the target domain,which will greatly improve the quality of life of diabetic patients.Advances in noninvasive glucose testing technology will not only reduce patients' pain,but also provide a more convenient means of glucose monitoring,which will provide strong support for diabetes management.

Objective:Analysis of the composition of pathogen spectrum and prevalence characteristics in throat swabs of patients with acute respiratory infections (ARI) in Yucheng city, Henan province, from March to June 2023.Methods:After 1 153 throat swabs were collected from ARI patients in Yucheng, 18 respiratory pathogens were tested using a real-time fluorescence quantitative polymerase chain reaction (qPCR) method. The characterization of pathogens spectrum was analyzed.Results:A total of 1 153 throat swabs from ARI patients were collected from March to June 2023 in Yucheng, including 171 outpatients and 982 hospitalized patients. A total of 244 positive samples for common respiratory pathogens were detected (at least one pathogen per sample was detected). The total detection rate of respiratory pathogens was 21.16%, and the top three detection rates were, in descending order, human bocavirus (HBoV), enterovirus (EV), and human parainfluenza virus (HPIV). The main detection month for pathogens was May, with a detection rate of 42.3% (60/142). The main respiratory pathogens detected are HBoV, EV, and HPIV. The detection rate of the age group under 1 year old was the highest, at 25.1% (49/195), mainly consisting of HBoV, respiratory syncytial virus (RSV), and HPIV. The main clinical manifestations of respiratory pathogen-positive patients were fever and cough, and the clinical diagnosis was mainly lower respiratory tract infection, all of which were hospitalized patients.Conclusions:The respiratory pathogens in ARI patients were mainly HBoV, EV, and HPIV from March to June, 2023 in Yucheng. The peak of the epidemic was in May, mainly infecting children under 5 years of age.

OBJECTIVE: To explore prevalence, incidence and possible factors of immediate herniated discs after posterior cervical expansive open-door laminoplasty (EODL). METHODS: Totally 29 patients with cervical spinal stenosis and intervertebral disc herniation who underwent EODL from October 2020 to December 2021 were collected, including 24 males and 5 females, aged from 43 to 81 years old with an average of (61.3±9.0) years old;the courses of disease ranged from 1 to 120 months with an average of (36.4±37.0) months. Three or more intervertebral discs on C₃-C₇ were observed. The clinical efficacy was evaluated according to Japanese Orthopaedic Association (JOA) score before operation, 3 days and 1, 3, 6 and 12 months after operation, respectively. The changes of herniated disc before and after operation were measured by multipoint area method and two-dimensional distance method, and incidence and percentage of herniated disc regression were further calculated. Cervical imaging parameters such as Cobb angle (C₃-C₇), intervertebral angle, T₁ slope (T₁S), spinal canal sagittal diameter, K-line angle, dural sac sagittal diameter were measured and compared before and after operation. Pearson correlation was used to analyze correlation between cervical sagittal imaging parameters and disc herniation changes before and after operation. RESULTS: All patients obtained grade A wound healing, and 14 of them were followed up for 3(1.00, 5.25) months. There were no immediate or long-term postoperative complications. Totally 101 herniated intervertebral discs were measured, of which 79 regression numbers were obtained by area measurement. The number of intervertebral disc regressions by distance measurement was 77. There was no statistically significant difference in Cobb angle, intervertebral angle, T₁S and K-line angle of C₃-C₇ (P>0.05), however, there were statistically significant differences in sagittal diameter of spinal canal, sagittal diameter of dural sac, and JOA score before and after operation(P<0.05). The regression ratio of disc herniation ranged from 5% to 50%, and regression ratio of disc herniation was greater than 25% in 45.57%(36/79). Disc herniation in C_4,5 was positively correlated with sagittal plane diameter in C₅(r=0.423, P=0.028). There was a negative correlation between changes of C_3,4 and C_3,4 intervertebral angle (r=-0.450, P=0.041). The improvement rate of cervical JOA score immediately after operation was (59.54±15.07) %, and postoperative follow-up improved to (76.57±14.66) %. CONCLUSION Herniated disc regression immediately after EODL is a common occurrence, and EODL should be selected as far as possible under the premise of satisfying surgical indications. The regression of disc herniation is positively correlated with spinal canal sagittal diameter, and spinal canal should be enlarged as far as possible in the appropriate scope during EODL, so as to create more opportunities and conditions for disc regression and achieve better clinical results.
Humans ; Female ; Male ; Intervertebral Disc Displacement/diagnostic imaging* ; Spinal Stenosis/diagnostic imaging* ; Laminoplasty/methods* ; Middle Aged ; Aged ; Cervical Vertebrae/diagnostic imaging* ; Adult ; Aged, 80 and over ; Intervertebral Disc/surgery*