ObjectiveTo systematically evaluate the methodological quality and measurement properties of traditional Chinese medicine （TCM） syndrome efficacy evaluation scales， and to provide evidence-based references for selecting high-quality assessment tools in TCM clinical practice. MethodsChina National Knowledge Infrastructure （CNKI）， Wanfang Data， VIP Database， Chinese Biomedical Literature Database （CBM）， PubMed， the Cochrane Library， Embase， and Web of Science were searched from inception to April 2， 2025， for studies evaluating the measurement properties of TCM syndrome efficacy evaluation scales. Data were extracted， and the methodological quality and measurement properties of the included scales were assessed according to the consensus-based standards for the selection of health measurement instruments （COSMIN）. Recommendation levels were formulated based on the grading of evidence. ResultsA total of 46 studies were included， involving 22 generic syndrome efficacy evaluation scales and 24 disease-specific syndrome efficacy evaluation scales. None of the scales reported cross-cultural validity or measurement error. According to the recommendation grades， 2 scales met Grade A recommendations and are suggested for clinical use； 38 scales were classified as Grade B， indicating potential applicability but requiring further validation； and 6 scales were classified as Grade C， suggesting the need for further refinement. ConclusionExisting TCM syndrome efficacy evaluation scales exhibit substantial variability in methodological quality， incomplete reporting of measurement properties， and insufficient attention to scale revision. Future efforts should emphasize standardized design in the development of TCM syndrome scales， strengthen validation procedures for key measurement properties， and prioritize dynamic revision of scales， thereby providing high-quality tools to support the precise evaluation of syndrome efficacy.

ObjectiveTo investigate the effect and underlying mechanism of the Wulao Qisun prescription on pathological new bone formation in ankylosing spondylitis （AS）. MethodsSynovial fibroblasts were isolated from the hip joints of AS patients and observed under a microscope to assess cell morphology. The cells were identified using immunofluorescence staining. The isolated AS fibroblasts were divided into blank group， low drug-containing serum group， medium drug-containing serum group， high drug-containing serum group， and positive drug group. After drug intervention， cell proliferation was measured using the cell counting kit-8 （CCK-8） assay to observe fibroblast growth and determine the optimal intervention time. Alkaline phosphatase （ALP） activity was measured using the alkaline phosphatase assay. Protein expression of osteocalcin （OCN）， osteopontin （OPN）， and runt-related transcription factor 2 （Runx2） was detected by Western blot. The mRNA expression levels of Wnt5a， β-catenin， and Dickkopf-1 （DKK-1） were measured by real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsCompared with the blank group， each drug-containing serum group of Wulao Qisun prescription and the positive drug group inhibited the proliferation of AS fibroblasts and reduced ALP expression （P<0.01）. Compared with the blank group， the low drug-containing serum group of Wulao Qisun prescription downregulated β-catenin mRNA expression （P<0.05）. The medium and high drug-containing serum groups and the positive drug group significantly downregulated Wnt5a and β-catenin mRNA expression （P<0.05， P<0.01）， with the positive drug group showing the most pronounced effect （P<0.01）. The high drug-containing serum group and the positive drug group significantly upregulated DKK-1 mRNA expression （P<0.01）. Compared with the blank group， the low drug-containing serum group of Wulao Qisun prescription inhibited the expression of OPN and Runx2 proteins （P<0.05， P<0.01）， while the medium and high drug-containing serum groups and the positive drug group inhibited the expression of OCN， OPN， and Runx2 proteins （P<0.05， P<0.01）. ConclusionThe Wulao Qisun prescription can inhibit the proliferation and osteogenic differentiation of AS fibroblasts， thereby delaying the formation of pathological new bone in AS. The possible mechanism involves the regulation of Wnt/β-catenin-related gene expression， further inhibiting the transcription of downstream target genes.

Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.