Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

Objective To investigate the clinical features and related risk factors of osteoporosis and osteoporotic fracture (OPF) in patients with rheumatic diseases (RD),and the fracture predictive values of fracture risk assessment tool fracture risk assessment (FRAX(R))for Han patients.Methods A total of 313 untreated RD patients were included.Each individual BMD was measured at lumbar spine and femoral neck with Dual-energy X-ray absorptionary.Ten-year probability of fracture (％) was calculated by fracture risk assessment tool FRAX(R) of Chinese model.Each individual previous fracture was confirmed by X-ray or CT examination.The associations between BMD,FRAX),previous fracture and age,bone mass index,nationality,erythrocyte sedimentation rate (ESR) and RD types were analyzed.T test or Wilcoxon test was used to compare the difference between groups for statistical analysis.Pearson/Spearman rank order and binary regression were used to analyze the correlations between variables of normal/non-normal and two classification distribution.Results ① The BMD of patients with untreated RD was significantly lower than that of control group (P=0.000).Individuals diagnosed with "osteopenia" in the RD group and control group were accounted for 39.3％ (123/313) and 15.8％ (47/296) respectively.Individuals diagnosed with "osteoporosis" in RD group and control group were accounted for 11.5％ (36/313) and 5.4％ (16/296) respectively.② The next 10-year probability of the hip (Z=-2.28,P=0.02) and major osteoporotic fracture (Z=-1.98,P=0.03) were higher than those of the control group,as well as the actual incidence of OPF (x2=25.11,P=0.00),the difference was statistically significant.③ 27.3％(18/66) and 55.0％(11/20) of the previous OPF patients in RD group and control group achieved the diagnostic criteria of "high risk" of hip fracture.And 12.1％ (8/66) and 35.0％ (7/20) achieved the "high risk" of major osteoporotic fracture.④ Patients with RA,SLE and pSS had significantly increased risk of fracture.Ten-year fracture risks were negatively related to advanced age,female gender and ESR.Conclusion Bone loss and increased fracture risk are prevalent in the early stage of untreated rheumatism patients.RA,SLE plays an important role in low bone mass.The FRAX China model may underestimate 10-year fracture probability of RD patients and controls.Further explore should be done to predict the FRAX China model on different areas and different RDs.

Objective: In order to evaluate the therapeutic effects and safety of denosumab and bisphosphonates in glucocorticoid induced osteoporosis patients. Methods: Standard studies were obtained by searching CNKI, CBM, VIP, Wanfang, Pubmed, Embase and Cochrane databases. Results: Three RCTs with 869 patients were included in this study. It showed that the mean changes of lumbar spine, total hip and femoral neck bone mineral density (BMD) for patients in denosumab group were increased by 2.47%, 1.43% and 1.07% respectively compared to those of bisphosphonates group.There was no statistically significant difference between patients receiving denosumab and those receiving bisphosphonate in terms of adverse events and serious adverse events. Conclusions Denosumab has an effective increase for lumbar spine, total hip and femoral neck bone mineral density, and the safety of both is similar.