To interpret the evidence-to-decision （EtD） framework and to illustrate its application in traditional Chinese medicine （TCM） guideline development using the example of the Pharmacovigilance Guideline of Chinese Patent Medicine， thereby providing methodological references for TCM guideline standardization. Based on the core three stages of the EtD framework （formulating the question， making an assessment of the evidence， and drawing conclusions）， critical decision points and evaluation evidence within the evidence-translation process were systematically addressed， aligning with the purpose， scope， and key questions of the guideline. Qualitative research methods， such as the nominal group technique， were employed to formulate recommendations. The analysis was conducted based on the EtD framework. During question formulation， the specific characteristics and practical needs of pharmacovigilance for Chinese patent medicines were clarified， focusing on the core objective of safety assurance throughout the product lifecycle. In the evidence assessment， multi-source evidence was integrated， including policy documents， literature research， and expert consensus， completing the evidence evaluation. Finally， in recommendation-forming， dispersed research evidence and expert experience were synthesized into consensus， culminating in the guideline's completion through solicitation of opinions and peer review. The EtD framework provides a structured tool for evidence-to-decision translation in TCM guideline development， effectively enhancing the transparency and scientific rigor of the process. Therefore， it is recommended that TCM guideline development adopt the EtD framework to improve the evidence-to-decision process with TCM characteristics.

To standardize the clinical application of oral Chinese patent medicines （CPMs）， and address the safety issues arising from their dosage form characteristics， irrational clinical use， and the lack of targeted pharmacovigilance systems， the China Association of Chinese Medicine organized the formulation and release of Pharmacovigilance Guidelines for Clinical Application of Oral Chinese Patent Medicines， aiming to inform the safe clinical use of oral CPMs and related pharmacovigilance work. According to the principles of GB/T1.1—2020 and the Drug Administration Law of the People's Republic of China （2019 revision）， the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences， led a drafting group comprising 18 institutions. After multiple rounds of expert interviews， literature retrieval， evidence screening， and extensive solicitation of opinions， the Guidelines were registered internationally. Systematic standardization focused on safety monitoring， risk identification， assessment， control， and other aspects. The Guidelines clarified the characteristics of oral CPMs in terms of safety monitoring， known risks， and potential risks， compared to non-oral CPMs. Then， risk control measures were proposed， including medication in special populations and irrational medication. As a special guideline for pharmacovigilance in the clinical application of oral CPMs， the Guidelines systematically construct a technical system in line with the characteristics of traditional Chinese medicine （TCM）， which is essential for improving the clinical safety management of oral CPMs and provides an important reference for medical institutions， pharmaceutical manufacturers， and regulatory authorities.

To interpret the evidence-to-decision （EtD） framework and to illustrate its application in traditional Chinese medicine （TCM） guideline development using the example of the Pharmacovigilance Guideline of Chinese Patent Medicine， thereby providing methodological references for TCM guideline standardization. Based on the core three stages of the EtD framework （formulating the question， making an assessment of the evidence， and drawing conclusions）， critical decision points and evaluation evidence within the evidence-translation process were systematically addressed， aligning with the purpose， scope， and key questions of the guideline. Qualitative research methods， such as the nominal group technique， were employed to formulate recommendations. The analysis was conducted based on the EtD framework. During question formulation， the specific characteristics and practical needs of pharmacovigilance for Chinese patent medicines were clarified， focusing on the core objective of safety assurance throughout the product lifecycle. In the evidence assessment， multi-source evidence was integrated， including policy documents， literature research， and expert consensus， completing the evidence evaluation. Finally， in recommendation-forming， dispersed research evidence and expert experience were synthesized into consensus， culminating in the guideline's completion through solicitation of opinions and peer review. The EtD framework provides a structured tool for evidence-to-decision translation in TCM guideline development， effectively enhancing the transparency and scientific rigor of the process. Therefore， it is recommended that TCM guideline development adopt the EtD framework to improve the evidence-to-decision process with TCM characteristics.

To standardize the clinical application of oral Chinese patent medicines （CPMs）， and address the safety issues arising from their dosage form characteristics， irrational clinical use， and the lack of targeted pharmacovigilance systems， the China Association of Chinese Medicine organized the formulation and release of Pharmacovigilance Guidelines for Clinical Application of Oral Chinese Patent Medicines， aiming to inform the safe clinical use of oral CPMs and related pharmacovigilance work. According to the principles of GB/T1.1—2020 and the Drug Administration Law of the People's Republic of China （2019 revision）， the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences， led a drafting group comprising 18 institutions. After multiple rounds of expert interviews， literature retrieval， evidence screening， and extensive solicitation of opinions， the Guidelines were registered internationally. Systematic standardization focused on safety monitoring， risk identification， assessment， control， and other aspects. The Guidelines clarified the characteristics of oral CPMs in terms of safety monitoring， known risks， and potential risks， compared to non-oral CPMs. Then， risk control measures were proposed， including medication in special populations and irrational medication. As a special guideline for pharmacovigilance in the clinical application of oral CPMs， the Guidelines systematically construct a technical system in line with the characteristics of traditional Chinese medicine （TCM）， which is essential for improving the clinical safety management of oral CPMs and provides an important reference for medical institutions， pharmaceutical manufacturers， and regulatory authorities.

Objective To investigate the relationship between occurrence of heart failure (HF) and blood pressure variability in patients with hypertension complicated with unstable angina pectoris (UA). Methods The data of 385 patients with hypertension and UA admitted to the Nantong Third People's Hospital from January 2022 to January 2024 were collected and analyzed. After discharge, the enrolled patients were followed up for 1 year via outpatient visits or telephone calls. The study endpoint was new-onset HF. The relationship of blood pressure variability with new-onset HF was analyzed. Results According to the clinical risk stratification of UA, the blood pressure variability in the high-risk group was higher than that in the low-risk group and the medium-risk group (P<0.05). There were 46 cases (11.94%) of new-onset HF among 385 UA patients with hypertension. After adjusting for confounding factors, the risk of new-onset HF in UA patients with hypertension was increased with the increases of 24 h systolic blood pressure standard deviation (24 h SSD) [HR (95% CI)=4.20 (2.33-14.79)] and nighttime systolic blood pressure standard deviation (nSSD) [HR (95% CI)=1.94 (1.53-2.46)] (P<0.05). Receiver operating characteristic (ROC) curve indicated that the AUCs of Model 1 and Model 2 in predicting new-onset HF were 0.776 and 0.869, and 95% CI values were 0.707-0.844 and 0.820-0.918, respectively. The AUC of Model 2 was higher than that of Model 1 (Z/P=3.734/<0.001). Conclusion For patients with hypertension complicated with unstable angina pectoris, the blood pressure variability indicators at admission have high predictive value on new-onset heart failure.

Objective To investigate the prognosis and its influencing factors in patients with hypertension complicated with heart failure (HF). Methods A total of 381 patients with hypertension and HF who were treated in our hospital from March 2022 to April 2025 were chosen. The patients were followed up for the prognosis within 6 months and split into good prognosis group (n=266) and poor prognosis group (n=115). The clinical data of the two groups were compared and analyzed. Multivariate Logistic regression analysis was used to determine the influencing factors of poor prognosis. Results The group with poor prognosis had higher proportions of atrial fibrillation and New York Heart Association (NYHA) Class III-IV, as well as increased left ventricular end-diastolic diameter (LVED), left ventricular end-systolic diameter (LVES), interventricular septum thickness (IVS), and left ventricular posterior wall thickness (LVPW) compared to the group with good prognosis (P<0.05). Additionally, levels of systolic blood pressure (SBP), N-terminal pro-B-type natriuretic peptide (NT-proBNP), total cholesterol (TC), low-density lipoprotein (LDL), creatinine (Cr) were elevated (P<0.05), while left ventricular ejection fraction (LVEF) was decreased (P<0.05). NYHA classification, LVEF, LVED, LVPW, NT-proBNP were independent influencing factors of poor prognosis in patients with hypertension complicated with HF (P<0.05). Conclusion NYHA classification, LVEF, LVED, LVPW and NT-proBNP are closely related to the poor prognosis of patients with hypertension and HF.

Under the current upsurge of cross-disciplinary research between artificial intelligence （AI） and traditional Chinese medicine （TCM）， the inheritance of academic thought in TCM is confronted with the deep-seated predicament of cognitive paradigm dislocation. The existing AI model is based on the classical reasoning mode of formal logic and statistical probability， which is difficult to adapt to the nonlinear and holistic cognitive logic of TCM with image-based thinking and syndrome-differentiated treatment as the core， resulting in systematic misreading and loss of the core essence in digital inheritance. Based on this， this paper proposes to construct a new cognitive model oriented towards the context of TCM. Its essence is not to have AI imitate the thinking of TCM， but to establish an auxiliary understanding framework based on semantic mapping and relational reasoning. It is advocated that the role of AI should be reconstructed from a knowledge substitute to a clinical interactor， and its application boundary in the inheritance of TCM wisdom should be clarified. By establishing the theoretical framework and practical path of human-computer collaboration， this paper aims to provide a scientific basis for realizing the deep integration of AI technology and the academic thought in TCM.

Under the current upsurge of cross-disciplinary research between artificial intelligence （AI） and traditional Chinese medicine （TCM）， the inheritance of academic thought in TCM is confronted with the deep-seated predicament of cognitive paradigm dislocation. The existing AI model is based on the classical reasoning mode of formal logic and statistical probability， which is difficult to adapt to the nonlinear and holistic cognitive logic of TCM with image-based thinking and syndrome-differentiated treatment as the core， resulting in systematic misreading and loss of the core essence in digital inheritance. Based on this， this paper proposes to construct a new cognitive model oriented towards the context of TCM. Its essence is not to have AI imitate the thinking of TCM， but to establish an auxiliary understanding framework based on semantic mapping and relational reasoning. It is advocated that the role of AI should be reconstructed from a knowledge substitute to a clinical interactor， and its application boundary in the inheritance of TCM wisdom should be clarified. By establishing the theoretical framework and practical path of human-computer collaboration， this paper aims to provide a scientific basis for realizing the deep integration of AI technology and the academic thought in TCM.

By systematically analyzing the bottlenecks in current traditional Chinese medicine （TCM） efficacy evaluation， this study addresses the limitations of TCM efficacy assessment methods in terms of individualization， holism， and complexity representation. Drawing on the concepts and methodologies of evidence-based medicine and systems biology， this paper proposes a new evaluation path by integrating multidisciplinary technologies such as big data， artificial intelligence （AI）， omics techniques， and bioinformatics， and encompassing from foundational data， individualized evaluation， and mechanistic analysis to evidence translation. The path first integrates real-world data， multi-omics profiling， and dynamic monitoring via smart devices to construct a high-dimensional dynamic data foundation. Subsequently， leveraging this foundation， it combines digital twins， dynamic symptom networks， and reinforcement learning to develop a dynamic efficacy evaluation method based on individual self-reference， enabling a shift from group mean comparisons to individual potential outcome comparisons. Furthermore， adopting the systems biology paradigm， it employs dynamic omics monitoring and deep learning models to dissect the synergistic mechanisms of TCM compound prescriptions from network regulation， emergent effects， and dynamic evolution dimensions. Finally， it enhances real-world evidence strength through target trial emulation and causal inference， achieving model iteration via incremental learning. This path aims to advance efficacy evaluation from "point validation" to "systematic characterization" and from "outcome assessment" to "process mechanism elucidation，" providing methodological support for the modernization of TCM.

In recent years, hybrid brain-computer interfaces (BCIs) have gained significant attention due to their demonstrated advantages in increasing the number of targets and enhancing robustness of the systems. However, Existing studies usually construct BCI systems using intense auditory stimulation and strong central visual stimulation, which lead to poor user experience and indicate a need for improving system comfort. Studies have proved that the use of peripheral visual stimulation and lower intensity of auditory stimulation can effectively boost the user's comfort. Therefore, this study used high-frequency peripheral visual stimulation and 40-dB weak auditory stimulation to elicit steady-state visual evoked potential (SSVEP) and auditory steady-state response (ASSR) signals, building a high-comfort hybrid BCI based on weak audio-visual evoked responses. This system coded 40 targets via 20 high-frequency visual stimulation frequencies and two auditory stimulation frequencies, improving the coding efficiency of BCI systems. Results showed that the hybrid system's averaged classification accuracy was (78.00 ± 12.18) %, and the information transfer rate (ITR) could reached 27.47 bits/min. This study offers new ideas for the design of hybrid BCI paradigm based on imperceptible stimulation.
Brain-Computer Interfaces ; Humans ; Evoked Potentials, Visual/physiology* ; Acoustic Stimulation ; Photic Stimulation ; Electroencephalography ; Evoked Potentials, Auditory/physiology* ; Adult