Implementation science (IS) aims to systematically analyze and address the real-world gaps from evidence to practice and the influencing factors of the context. It is necessary to carry out qualitative research to gather relevant implementation outcomes. Nevertheless, traditional qualitative analysis has issues such as consuming a great deal of time and energy, and it is unable to promptly provide the crucial data required for implementation science research. The Rapid Qualitative Analysis (RQA) method, through semi-structured interviews and the adoption of techniques such as immediate data condensation and matrix analysis, can effectively shorten the cycle of qualitative data collection and data processing. RQA can promptly identify social determinants of health such as structural barriers, facilitators, and the behavioral characteristics of target groups. It provides a real-time basis for public health decision-making, the interpretation of complex social phenomena, and the process and effectiveness evaluation of research projects. Although RQA is difficult to conduct in-depth theoretical analysis based on grounded theory, its efficiency and flexibility make it the preferred tool for large-scale and time-sensitive research. Thus, it has been widely applied in implementation science research. This paper sorts out the core concepts and commonly used technical methods of RQA, as well as the differences between RQA and traditional qualitative analysis. It also explores the applications of RQA in intervention optimization, process evaluation, and implementation outcome evaluation. By integrating specific cases, this paper clarifies its application value in the field of implementation science. In the future, it is advisable to explore the integration of RQA with technologies such as artificial intelligence and big data, in order to bridge the gap between the transformation of scientific research achievements into practice. Under circumstances of limited resources or tight time constraints, RQA can be used to efficiently conduct implementation science research, providing convenient and scientific methodological and technical support for accelerating evidence-based practice.

Traditional Chinese medicine （TCM） clinical trials face challenges such as low participant compliance， insufficient geographical coverage， and cost-effectiveness imbalances. Decentralized clinical trials （DCT）， enabled by digital technology for remote data collection and monitoring， offer a new direction for TCM clinical trial research. This article systematically reviews three novel clinical trial design models. Combining the holistic concept and indivi-dualized treatment characteristics of TCM， it analyzes the challenges currently faced in TCM DCT practice， including the digitization and standardization of TCM theory， data security， privacy protection and patient engagement difficu-lties， insufficient ethical review and regulatory system adaptation， inadequate personnel training， and a shortage of interdisciplinary talent. Addressing these challenges， the article proposes methodological recommendations for DCT implementation that align with the principles of TCM diagnosis and treatment. These recommendations include promoting the intelligentization and standardization of TCM practices， constructing a full-chain data security and privacy protection system， improving the ethical framework and clarifying regulatory responsibilities， and cultivating and building interdisciplinary talent and capabilities， which provide theoretical and technical references for establishing standardized DCT practices in TCM.

Traditional Chinese medicine （TCM） clinical trials face challenges such as low participant compliance， insufficient geographical coverage， and cost-effectiveness imbalances. Decentralized clinical trials （DCT）， enabled by digital technology for remote data collection and monitoring， offer a new direction for TCM clinical trial research. This article systematically reviews three novel clinical trial design models. Combining the holistic concept and indivi-dualized treatment characteristics of TCM， it analyzes the challenges currently faced in TCM DCT practice， including the digitization and standardization of TCM theory， data security， privacy protection and patient engagement difficu-lties， insufficient ethical review and regulatory system adaptation， inadequate personnel training， and a shortage of interdisciplinary talent. Addressing these challenges， the article proposes methodological recommendations for DCT implementation that align with the principles of TCM diagnosis and treatment. These recommendations include promoting the intelligentization and standardization of TCM practices， constructing a full-chain data security and privacy protection system， improving the ethical framework and clarifying regulatory responsibilities， and cultivating and building interdisciplinary talent and capabilities， which provide theoretical and technical references for establishing standardized DCT practices in TCM.

Objective To understand the current situation and dynamic changing trends of healthcare-associated infection(HAI)in a tertiary first-class hospital in the northwest of Hunan Province from 2015 to 2024,and provide scientific basis for optimizing infection control strategies.Methods A single-day cross-sectional survey method was employed to investigate the HAI prevalence rates of hospitalized patients on the given survey day each year from 2015 to 2024.The standardized survey protocol on prevalence rate issued by the National Medical Institution Infec-tion Surveillance Network was strictly adhered,lanqingting real-time HAI monitoring management platform was adopted to retrieve cases from the hospital information system,and R4.2.2 was applied for statistical analysis.Results From 2015 to 2024,the prevalence rate of HAI decreased from 3.03％in 2015 to 1.76％in 2024(Z=-3.37,P＜0.001),and the HAI case prevalence rate decreased from 3.55％in 2015 to 2.20％in 2024(Z=-2.81,P=0.005).Department of critical care medicine continuously had the highest HAI case prevalence rate,which presented a downward trend over time(Z=-2.84,P=0.004).The main site of HAI was lower respiratory tract,accounting for 39.36％to 48.15％,bloodstream infection increased from 3.57％in 2015-2016 to 10.60％in 2023-2024(Z=2.41,P=0.016).A total of 302 strains of HAI pathogens were detected,including 212 strains(70.20％)of Gram-negative bacteria,mainly Pseudomonas aeruginosa(n=55,18.21％),Escherichia coli(n=45,14.90％),Acinetobacter baumannii(n=33,10.93％),and Klebsiella pneumoniae(n=31i,10.26％).65 strains(21.52％)of Gram-positive bacteria were identified,with Enterococcus faecium(n=19,6.29％)and Staphylococcus aureus(n=18,5.96％)accounting for the highest proportions.25 fungal strains(8.28％)were detected,mainly Candi-da albicans(n=11,3.64％).The use rate of antimicrobial agents showed a downward trend over the past decade(Z=-4.01,P＜0.001).Therapeutic antimicrobial use accounting for 82.42％,and its proportion increased over time(Z=6.02,P＜0.001).Prophylactic antimicrobial use accounted for 16.42％,showing a decreasing trend(Z=-2.75,P＜0.001).The pathogen detection rate presented an upward trend over the past decade(Z=13.01,P＜0.001).Conclusion The prevalence rate and case prevalence rate of HAI present a downward trend in this hospi-tal.In the future,it is necessary to establish a monitoring data-based dynamic analysis mechanism,achieve timely feedback and intervention in data monitoring,pay attention to high-risk links in department of critical care medicine,implement precise prevention and control mearsures,perform targeted prevention and control for lower respiratory tract,urinary tract,and bloodstream infection,optimize diagnosis and treatment processes,use antimicrobial agents rationally,and pay attention to the prevalence trend of Gram-negative bacteria.

Digital health technology has gradually become a new healthcare vehicle for prehabilitation management of cancer patients. This paper reviews the application types, methods and effects of digital health technology in the prehabilitation management of cancer patients, and puts forward corresponding suggestions for the existing problems, with a view to provid reference for the research on digital prehabilitation in China.

Objective To establish a combined model of spectral CT multi-parameters and clinical features to distinguish between gastric poorly cohesive carcinoma and tubular adenocarcinoma.Methods A total of 87 patients with gastric cancer confirmed by postoperative pathology were retrospectively selected,including 26 patients with poorly cohesive carcinoma and 61 patients with tubular adenocarcinoma.Predictors were identified by univariate and multivariate logistic regression analyses,and a combined model was established.The area under the curve(AUC)of receiver operating characteristic(ROC)curve was used to evaluate the differential diagnostic efficiency of the parameters and the model.The AUC was compared by DeLong method.Results The gender[odds ratio(OR)5.124,P=0.004],normalized iodine density in the arterial phase(nIoDAP)(OR 5.789,P=0.017),arterial enhancement fraction(AEF)(OR 7.007,P=0.002)and ΔIoD(OR 0.025,P=0.021)were identified as independent predictors for poorly cohesive carcinoma by logistic regression analysis.The AUC of combined model established by four variables in distinguishing poorly cohesive carcinoma and tubular adenocarcinoma was 0.837[95％confidence interval(CI)0.716-0.907],which was significantly higher than that of single tumor spectral CT parameters(P＜0.01).Conclusion The combined model based on patients'gender and tumor spectral CT parameters(nIoDAP,AEF and ΔIoD)can effectively distinguish gastric poorly cohesive carcinoma and tubular adenocarcinoma,providing a basis for gastric cancer patients'individualized treatment strategy.

Objective To understand the current situation and dynamic changing trends of healthcare-associated infection(HAI)in a tertiary first-class hospital in the northwest of Hunan Province from 2015 to 2024,and provide scientific basis for optimizing infection control strategies.Methods A single-day cross-sectional survey method was employed to investigate the HAI prevalence rates of hospitalized patients on the given survey day each year from 2015 to 2024.The standardized survey protocol on prevalence rate issued by the National Medical Institution Infec-tion Surveillance Network was strictly adhered,lanqingting real-time HAI monitoring management platform was adopted to retrieve cases from the hospital information system,and R4.2.2 was applied for statistical analysis.Results From 2015 to 2024,the prevalence rate of HAI decreased from 3.03％in 2015 to 1.76％in 2024(Z=-3.37,P＜0.001),and the HAI case prevalence rate decreased from 3.55％in 2015 to 2.20％in 2024(Z=-2.81,P=0.005).Department of critical care medicine continuously had the highest HAI case prevalence rate,which presented a downward trend over time(Z=-2.84,P=0.004).The main site of HAI was lower respiratory tract,accounting for 39.36％to 48.15％,bloodstream infection increased from 3.57％in 2015-2016 to 10.60％in 2023-2024(Z=2.41,P=0.016).A total of 302 strains of HAI pathogens were detected,including 212 strains(70.20％)of Gram-negative bacteria,mainly Pseudomonas aeruginosa(n=55,18.21％),Escherichia coli(n=45,14.90％),Acinetobacter baumannii(n=33,10.93％),and Klebsiella pneumoniae(n=31i,10.26％).65 strains(21.52％)of Gram-positive bacteria were identified,with Enterococcus faecium(n=19,6.29％)and Staphylococcus aureus(n=18,5.96％)accounting for the highest proportions.25 fungal strains(8.28％)were detected,mainly Candi-da albicans(n=11,3.64％).The use rate of antimicrobial agents showed a downward trend over the past decade(Z=-4.01,P＜0.001).Therapeutic antimicrobial use accounting for 82.42％,and its proportion increased over time(Z=6.02,P＜0.001).Prophylactic antimicrobial use accounted for 16.42％,showing a decreasing trend(Z=-2.75,P＜0.001).The pathogen detection rate presented an upward trend over the past decade(Z=13.01,P＜0.001).Conclusion The prevalence rate and case prevalence rate of HAI present a downward trend in this hospi-tal.In the future,it is necessary to establish a monitoring data-based dynamic analysis mechanism,achieve timely feedback and intervention in data monitoring,pay attention to high-risk links in department of critical care medicine,implement precise prevention and control mearsures,perform targeted prevention and control for lower respiratory tract,urinary tract,and bloodstream infection,optimize diagnosis and treatment processes,use antimicrobial agents rationally,and pay attention to the prevalence trend of Gram-negative bacteria.

Objective:To develop an artificial intelligence (AI)-guided intravitreal injection robot system to accurately detect the injection point on the ocular surface and guide the robotic arm to complete the intravitreal injection positioning task through 3D position calculation.Methods:The Dikablis subset of the TEyeD dataset was used.Training set, testing set, and validation set were constructed by using equal interval sampling strategy.The system read the ocular surface color RGB image with an RGBD camera, then used a PatchCrop-Transformer-based injection point detection algorithm to detect and locate key points such as the pupil, iris, and eyelid in the image.Next, it extracted the local 3D point cloud data near the injection point based on the depth information obtained by the camera.Through principal component analysis (PCA) of the local area point cloud data, the injection point and injection direction were determined.The key information was then passed to the robotic arm system.The end of the robotic arm adopted a remote center of motion (RCM) mechanism.After solving the forward and inverse kinematics, the joint movement path was obtained, and the robotic arm was controlled to move to 2 cm above the injection point.After confirmation by the doctor, the insertion, injection, and withdrawal operations were completed to ensure the stability and repeatability of the injection process.The mean square error (MSE) of key points localization and the success detection rate (SDR) within different pixel error ranges (2, 5, and 10 pixels) of the study method were compared with those of the NFDP, SLPT, and StarLoss methods, and the effects of random weight enhancement, fixed weight enhancement, and no enhancement methods on the MSE of key points localization were evaluated.The repeatability and absolute positioning accuracy of the robotic arm system were also evaluated.Results:After adding random weight enhancement, the model of this study outperformed the fixed weight enhancement and no enhancement methods in both MSE and SDR.The MSEs of the model proposed in this study for overall eye, pupil, and iris localization were 4.25, 2.41, and 1.54, respectively, which were lower than those of the NFDP, StarLoss, and SLPT methods.Within the error ranges of 5 and 10 pixels, the SDRs of the model proposed in this study were 72.09% and 92.68%, respectively, which were higher than those of the NFDP, StarLoss, and SLPT methods.The single-axis repeatability errors and absolute positioning errors of the robotic arm were within ±5 μm.Conclusions:The AI-guided intravitreal injection robot system integrates RGBD images to achieve automatic recognition of the ocular injection point and high-precision motion control through RCM mechanism design and corresponding kinematic solution methods.

Digital health technology has gradually become a new healthcare vehicle for prehabilitation management of cancer patients. This paper reviews the application types, methods and effects of digital health technology in the prehabilitation management of cancer patients, and puts forward corresponding suggestions for the existing problems, with a view to provid reference for the research on digital prehabilitation in China.

This case report describes the diagnostic and therapeutic management of a 67-year-old fe-male with a 40-year history of Sj?gren disease(SjD)who was hospitalized for evaluation of recurrent fever lasting over one month.The patient's initial diagnosis of SjD was established four decades earlier based on clinical manifestations,serological findings,and evidence of glandular damage.Her clinical presenta-tion included recurrent parotid gland enlargement accompanied by sicca symptoms,notably persistent xerostomia and xerophthalmia,followed by progressive dental caries.Serological studies demonstrated positivity for antinuclear antibodies,anti-SSA/Ro,and anti-α-fodrin antibodies.Objective assessments confirmed significant ocular involvement(Schirmer's test≤5 mm/5 min)and pulmonary interstitial changes on chest CT,consistent with the 2016 American College of Rheumatology and European League Against Rheumatism(ACR/EULAR)classification criteria for SjD.The patient's condition remained sta-ble under low-dose corticosteroids and disease-modifying anti-rheumatic drugs(DMARDs)until the re-cent onset of prolonged fever,necessitating evaluation for fever of unknown origin.Differential diagnoses considered disease flare,infection,and malignancy.The European Sj?gren's Syndrome Disease Activity Index(ESSDAI)score was 5 points,indicating moderate systemic disease activity.Initial laboratory in-vestigations revealed no evidence of infection,and empirical anti-infective therapy proved ineffective.No-tably,despite the absence of lymphadenopathy,laboratory findings including borderline positive IgM λ M-protein,elevated lactate dehydrogenase,hyperferritinemia,and increased β2-microglobulin levels raised suspicion for lymphoproliferative disorders,given the established association between SjD and lymphoma.Bone marrow aspiration showed no significant abnormalities,but PET/CT imaging detected hypermetabolic lesions in the left breast and right distal femur,suggesting potential malignancy.Subse-quent histopathological examination of the breast lesion confirmed non-Hodgkin's lymphoma(NHL),specifically diffuse large B-cell lymphoma(DLBCL)of the germinal center B-cell(GCB)subtype.Treatment with R-CHOP chemotherapy(rituximab,cyclophosphamide,doxorubicin,vincristine,and prednisone)induced complete metabolic remission after three cycles.However,she subsequently developed treatment-related complications,including myelosuppression and pulmonary infection.This case underscores the importance of maintaining a high index of suspicion for atypical site involvement in SjD patients,particularly when lymphoma risk factors are present.Comprehensive differential diagnosis should include lymphoma and other malignancies,and the diagnostic value of PET/CT and histopatholog-ical examination in disease evaluation is emphasized.SjD complicated by breast lymphoma is exceptional-ly rare,and its pathogenesis may involve lymphocytic infiltration,abnormal activation of lymphocytes,formation of ectopic germinal centers in the breast,and eventual malignant transformation.These mecha-nisms require further investigation through clinical and basic research studies.