1.Multi-dimensional Holographic Characterization of Zhejiang Characteristic Atractylodis Macrocephalae Rhizoma with Nine-time Repeating Steaming and Processing
Xin WU ; Cuiwei CHEN ; Qiao YU ; Chao FENG ; Hongyan ZHANG ; Yan CHEN ; Caihua SUN ; Gang CAO
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(6):197-205
ObjectiveHistorically documented Zhejiang Atractylodis Macrocephalae Rhizoma(Baizhu) possesses premium characteristics such as phoenix-like head and crane-like neck, pronounced sweetness, and fragrant aroma. However, its current market circulation is low, and the processed products with Zhejiang-style characteristics are at the risk of being lost. This study aims to preserve the ancient Zhejiang-style processing techniques and evaluate them using modern scientific methods. MethodsMultidimensional intelligent sensory evaluation was used to digitally characterize the "quality-structure" of the external appearance of nine-steamed and nine-processed Baizhu medicinal materials(intermediate processed products) and the "odor-taste" of the internal quality of its decoction pieces(slices), and the appearance parameters were digitally characterized by colorimeter, texture analyzer, electronic nose and electronic tongue, the chemical composition was analyzed via ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry(UPLC-Q-TOF-MS/MS). Then, cluster analysis on the differences in odor between the medicinal materials(intermediate processed products) and decoction pieces(slices) of nine-steamed and nine-processed Baizhu was conducted, as well as the differences in taste between water-soluble and alcohol-soluble extracts of the decoction pieces(slices), and the correlation analysis of chroma value-alcohol-soluble extract content-component response value. ResultsThe nine-steamed and nine-processed Baizhu had a dark brown to black epidermis, a brownish-yellow to brownish-gray cross-section, a slightly tough texture, a faint odor, and a slightly sweet, bitter and pungent taste. Texture analyzer measurements revealed minimal adhesion and maximum recovery in the middle section of the characteristic processed Baizhu, consistent with the processing endpoint of thorough steaming and cooking. The head section showed the highest internal hardness, elasticity and chewiness, indicating a denser texture in this area. The electronic nose sensor could clearly distinguish the difference between the medicinal materials and its decoction pieces, with a more significant clustering effect at 60 ℃ for 30 minutes compared to ambient temperature headspace for 2 hours, highlighting the significant impact of the baking degree before slicing on the quality. The electronic tongue taste signal map clearly distinguished the differences between water-soluble and alcohol-soluble extracts of nine-steamed and nine-processed Baizhu decoction pieces, and the addition of auxiliary materials during processing could enhance its alcohol-soluble extract content. A total of 82 chemical components were identified in the characteristic processed Baizhu. After processing, the contents of 58 components increased, while 24 components decreased. Correlation analysis revealed significant negative correlations(P<0.01) between ethanol-soluble extract content and colorimetric values of brightness(L*), yellow-bule value(b*), and total color difference(E*ab). E*ab showed marked negative correlations(P<0.05) with the response values of isochlorogenic acid A and C. ConclusionThis study establishes a modern intelligent sensory evaluation model for multidimensional holographic characterization of nine-steamed and nine-processed Baizhu, clarifying the correlation between increased isochlorogenic acid content and the visual color appearance after different steaming cycles, as well as its intrinsic alcohol-soluble extracts. This provides a reference for quality evaluation and processing standards of the Zhejiang-style characteristic processed products.
2.Longitudinal Association of Changes in Metabolic Syndrome with Cognitive Function: 12-Year Follow-up of the Guangzhou Biobank Cohort Study
Yu Meng TIAN ; Wei Sen ZHANG ; Chao Qiang JIANG ; Feng ZHU ; Ya Li JIN ; Shiu Lun Au YEUNG ; Jiao WANG ; Kar Keung CHENG ; Tai Hing LAM ; Lin XU
Diabetes & Metabolism Journal 2025;49(1):60-79
Background:
The association of changes in metabolic syndrome (MetS) with cognitive function remains unclear. We explored this association using prospective and Mendelian randomization (MR) studies.
Methods:
MetS components including high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), waist circumference (WC), fasting plasma glucose (FPG), and triglycerides were measured at baseline and two follow-ups, constructing a MetS index. Immediate, delayed memory recall, and cognitive function along with its dimensions were assessed by immediate 10- word recall test (IWRT) and delayed 10-word recall test (DWRT), and mini-mental state examination (MMSE), respectively, at baseline and follow-ups. Linear mixed-effect model was used. Additionally, the genome-wide association study (GWAS) of MetS was conducted and one-sample MR was performed to assess the causality between MetS and cognitive function.
Results:
Elevated MetS index was associated with decreasing annual change rates (decrease) in DWRT and MMSE scores, and with decreases in attention, calculation and recall dimensions. HDL-C was positively associated with an increase in DWRT scores, while SBP and FPG were negatively associated. HDL-C showed a positive association, whereas WC was negatively associated with increases in MMSE scores, including attention, calculation and recall dimensions. Interaction analysis indicated that the association of MetS index on cognitive decline was predominantly observed in low family income group. The GWAS of MetS identified some genetic variants. MR results showed a non-significant causality between MetS and decrease in DWRT, IWRT, nor MMSE scores.
Conclusion
Our study indicated a significant association of MetS and its components with declines in memory and cognitive function, especially in delayed memory recall.
3.Association between nonalcoholic fatty liver disease and incidence of inflammatory bowel disease: a nationwide population‑based cohort study
Ying-Hsiang WANG ; Chi-Hsiang CHUNG ; Tien-Yu HUANG ; Chao-Feng CHANG ; Chi-Wei YANG ; Wu-Chien CHIEN ; Yi-Chiao CHENG
Intestinal Research 2025;23(1):76-84
Background/Aims:
Nonalcoholic fatty liver disease (NAFLD) is a common disease with severe inflammatory processes associated with numerous gastrointestinal diseases, such as inflammatory bowel disease (IBD). Therefore, we investigated the relationship between NAFLD and IBD and the possible risk factors associated with the diagnosis of IBD.
Methods:
This longitudinal nationwide cohort study investigated the risk of IBD in patients with NAFLD alone. General characteristics, comorbidities, and incidence of IBD were also compared.
Results:
Patients diagnosed with NAFLD had a significant risk of developing IBD compared to control individuals, who were associated with a 2.245-fold risk of the diagnosis of IBD and a 2.260- and 2.231-fold of increased diagnosis of ulcerative colitis and Crohn’s disease, respectively (P< 0.001). The cumulative risk of IBD increased annually during the follow-up of patients with NAFLD (P< 0.001).
Conclusions
Our results emphasize that NAFLD significantly impacts its incidence in patients with NAFLD. If patients with NAFLD present with risk factors, such as diabetes mellitus and dyslipidemia, these conditions should be properly treated with regular follow-ups. Furthermore, we believe that these causes may be associated with the second peak of IBD.
4.Predictive Modeling of Symptomatic Intracranial Hemorrhage Following Endovascular Thrombectomy: Insights From the Nationwide TREAT-AIS Registry
Jia-Hung CHEN ; I-Chang SU ; Yueh-Hsun LU ; Yi-Chen HSIEH ; Chih-Hao CHEN ; Chun-Jen LIN ; Yu-Wei CHEN ; Kuan-Hung LIN ; Pi-Shan SUNG ; Chih-Wei TANG ; Hai-Jui CHU ; Chuan-Hsiu FU ; Chao-Liang CHOU ; Cheng-Yu WEI ; Shang-Yih YAN ; Po-Lin CHEN ; Hsu-Ling YEH ; Sheng-Feng SUNG ; Hon-Man LIU ; Ching-Huang LIN ; Meng LEE ; Sung-Chun TANG ; I-Hui LEE ; Lung CHAN ; Li-Ming LIEN ; Hung-Yi CHIOU ; Jiunn-Tay LEE ; Jiann-Shing JENG ;
Journal of Stroke 2025;27(1):85-94
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.
5.Impact of iron-deficiency anemia on short-term outcomes after resection of colorectal cancer liver metastasis: a US National (Nationwide) Inpatient Sample (NIS) analysis
Ko-Chao LEE ; Yu-Li SU ; Kuen-Lin WU ; Kung-Chuan CHENG ; Ling-Chiao SONG ; Chien-En TANG ; Hong-Hwa CHEN ; Kuan-Chih CHUNG
Annals of Coloproctology 2025;41(2):119-126
Purpose:
Colorectal cancer (CRC) often spreads to the liver, necessitating surgical treatment for CRC liver metastasis (CRLM). Iron-deficiency anemia is common in CRC patients and is associated with fatigue and weakness. This study investigated the effects of iron-deficiency anemia on the outcomes of surgical resection of CRLM.
Methods:
This population-based, retrospective study evaluated data from adults ≥20 years old with CRLM who underwent hepatic resection. All patient data were extracted from the 2005–2018 US National (Nationwide) Inpatient Sample (NIS) database. The outcome measures were in-hospital outcomes including 30-day mortality, unfavorable discharge, and prolonged length of hospital stay (LOS), and short-term complications such as bleeding and infection. Associations between iron-deficiency anemia and outcomes were determined using logistic regression analysis.
Results:
Data from 7,749 patients (representing 37,923 persons in the United States after weighting) were analyzed. Multivariable analysis revealed that iron-deficiency anemia was significantly associated with an increased risk of prolonged LOS (adjusted odds ratio [aOR], 2.76; 95% confidence interval [CI], 2.30–3.30), unfavorable discharge (aOR, 2.42; 95% CI, 1.83–3.19), bleeding (aOR, 5.05; 95% CI, 2.92–8.74), sepsis (aOR, 1.60; 95% CI, 1.04–2.46), pneumonia (aOR, 2.54; 95% CI, 1.72–3.74), and acute kidney injury (aOR, 1.71; 95% CI, 1.24–2.35). Subgroup analyses revealed consistent associations between iron-deficiency anemia and prolonged LOS across age, sex, and obesity status categories.
Conclusion
In patients undergoing hepatic resection for CRLM, iron-deficiency anemia is an independent risk factor for prolonged LOS, unfavorable discharge, and several critical postoperative complications. These findings underscore the need for proactive anemia management to optimize surgical outcomes.
6.Jiebiao Qingli Decoction Regulates TLR7/MAPK/NF-κB Pathway to Prevent and Treat Pneumonia Induced by IAV Infection
Yu MING ; Yichuan MA ; Ruiqi YAO ; Yan CHAO ; Hongchun ZHANG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(11):173-181
ObjectiveTo explore the mechanism of Jiebiao Qingli decoction (JQD) in treating pneumonia caused by influenza A virus (IAV) infection. MethodsA total of 132 Balb/c mice were randomly assigned into normal control (NC), model control (IAV), oseltamivir (OSV, 37.5 mg·kg-1), and high-, medium-, low-dose JQD (H-, M-, and L-JQD: 6.05, 3.02, and 1.51 g·kg-1, respectively) groups. The NC group was treated with normal saline nasal drops, and the other groups were intranasally inoculated with A/Brisbane/02/2018 (H1N1) [pdm09-like virus (H1N1)] for the modeling of IAV infection. Two hours post-modeling, the NC and IAV groups were administrated with normal saline by gavage, while other groups received corresponding drugs for 7 d. The body mass, survival status, and deaths of mice were recorded daily during the administration of the drugs. On days 3 and 7, the lung index was measured for mice in each group. Pathological changes in the lung tissue were observed via hematoxylin-eosin staining. Real-time fluorescence quantitative polymerase chain reaction (Real-time PCR) was conducted to measure the viral load (IAV-M) and the mRNA levels of Toll-like receptor 7 (TLR7), p38 mitogen-activated protein kinase (p38 MAPK), and nuclear factor-kappa B (NF-κB) in the lung tissue. Western blot was employed to measure the protein levels of p38 MAPK and NF-κB. Enzyme-linked immunosorbent assay was used to quantify serum levels of interleukin-2 (IL-2), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). ResultsCompared with the NC group, the IAV group showed reduced survival quality and survival days (P<0.01), lung congestion, inflammatory cell infiltration, elevated lung index (P<0.01), increased viral load (P<0.01), upregulated TLR7, p38 MAPK, and NF-κB levels (P<0.05, P<0.01), decreased IL-2 level (P<0.01), and elevated IL-6 and TNF-α levels (P<0.01). Compared with the IAV group, H-JQD prolonged survival days (P<0.05). All JQD groups alleviated pathological changes in the lung tissue and reduced the lung index (P<0.01). M-JQD and H-JQD decreased the viral load (P<0.01). H-JQD downregulated the mRNA levels of TLR7, p38 MAPK, and NF-κB (P<0.05, P<0.01) and the protein levels of p38 MAPK and NF-κB (P<0.01), increased the serum IL-2 level (P<0.01), and lowered the IL-6 and TNF-α levels (P<0.05, P<0.01). M-JQD downregulated the mRNA level of NF-κB (P<0.01) and the protein level of p38 MAPK (P<0.05), elevated the IL-2 level (P<0.01), and lowered the TNF-α level (P<0.01). ConclusionM- and H-JQD can prevent and control IAV infection-induced pneumonia dose-dependently by inhibiting the TLR7/MAPK/NF-κB signaling pathway, increasing IL-2, and reducing excessive secretion of IL-6 and TNF-α.
7.Jiebiao Qingli Decoction Regulates TLR7/MAPK/NF-κB Pathway to Prevent and Treat Pneumonia Induced by IAV Infection
Yu MING ; Yichuan MA ; Ruiqi YAO ; Yan CHAO ; Hongchun ZHANG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(11):173-181
ObjectiveTo explore the mechanism of Jiebiao Qingli decoction (JQD) in treating pneumonia caused by influenza A virus (IAV) infection. MethodsA total of 132 Balb/c mice were randomly assigned into normal control (NC), model control (IAV), oseltamivir (OSV, 37.5 mg·kg-1), and high-, medium-, low-dose JQD (H-, M-, and L-JQD: 6.05, 3.02, and 1.51 g·kg-1, respectively) groups. The NC group was treated with normal saline nasal drops, and the other groups were intranasally inoculated with A/Brisbane/02/2018 (H1N1) [pdm09-like virus (H1N1)] for the modeling of IAV infection. Two hours post-modeling, the NC and IAV groups were administrated with normal saline by gavage, while other groups received corresponding drugs for 7 d. The body mass, survival status, and deaths of mice were recorded daily during the administration of the drugs. On days 3 and 7, the lung index was measured for mice in each group. Pathological changes in the lung tissue were observed via hematoxylin-eosin staining. Real-time fluorescence quantitative polymerase chain reaction (Real-time PCR) was conducted to measure the viral load (IAV-M) and the mRNA levels of Toll-like receptor 7 (TLR7), p38 mitogen-activated protein kinase (p38 MAPK), and nuclear factor-kappa B (NF-κB) in the lung tissue. Western blot was employed to measure the protein levels of p38 MAPK and NF-κB. Enzyme-linked immunosorbent assay was used to quantify serum levels of interleukin-2 (IL-2), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). ResultsCompared with the NC group, the IAV group showed reduced survival quality and survival days (P<0.01), lung congestion, inflammatory cell infiltration, elevated lung index (P<0.01), increased viral load (P<0.01), upregulated TLR7, p38 MAPK, and NF-κB levels (P<0.05, P<0.01), decreased IL-2 level (P<0.01), and elevated IL-6 and TNF-α levels (P<0.01). Compared with the IAV group, H-JQD prolonged survival days (P<0.05). All JQD groups alleviated pathological changes in the lung tissue and reduced the lung index (P<0.01). M-JQD and H-JQD decreased the viral load (P<0.01). H-JQD downregulated the mRNA levels of TLR7, p38 MAPK, and NF-κB (P<0.05, P<0.01) and the protein levels of p38 MAPK and NF-κB (P<0.01), increased the serum IL-2 level (P<0.01), and lowered the IL-6 and TNF-α levels (P<0.05, P<0.01). M-JQD downregulated the mRNA level of NF-κB (P<0.01) and the protein level of p38 MAPK (P<0.05), elevated the IL-2 level (P<0.01), and lowered the TNF-α level (P<0.01). ConclusionM- and H-JQD can prevent and control IAV infection-induced pneumonia dose-dependently by inhibiting the TLR7/MAPK/NF-κB signaling pathway, increasing IL-2, and reducing excessive secretion of IL-6 and TNF-α.
8.In situ Analytical Techniques for Membrane Protein Interactions
Zi-Yuan KANG ; Tong YU ; Chao LI ; Xue-Hua ZHANG ; Jun-Hui GUO ; Qi-Chang LI ; Jing-Xing GUO ; Hao XIE
Progress in Biochemistry and Biophysics 2025;52(5):1206-1218
Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.
9.Clinical Phenotype Identification and Validation of Patients with Sepsis in the Intensive Care Unit
Chao GONG ; Na YU ; Haoran CHEN
Medical Journal of Peking Union Medical College Hospital 2025;16(3):710-721
To identify and validate the clinical phenotypes of patients with sepsis in the intensive care unit(ICU). We applied unsupervised machine learning algorithms (K-means clusteringand hierarchical clustering) to identify the phenotypes of sepsis patients in the Medical Information Mart for Intensive Care Ⅳ (MIMIC-Ⅳ) 2.2 database, based on 89 clinical features including demographic characteristics, laboratory indicators and treatment measures on the first day in ICU. Then, supervised machine learning algorithms (lightweight gradient boosting machine) were used for the prediction of the patient's phenotypes, and were further combined with SHAP (Shapely Additive eXplanations) for the identification of important features. Finally, traditional statistical methods were used to validate the differences in clinical characteristics and clinical outcomes among the phenotypes. We identified three phenotypes in 22 517 sepsis patients. The phenotype 1 patients had the highest risk of death (28-day mortality of 46.4%), dominated by abnormal renal function and elevated disease severity scores, while the phenotype 3 patients had the lowest risk of death (28-day mortality of 11.2%), and the best neurological function score. Using interpretable machine learning, we identified six features (all the worst value on the first day) that showed good performance in phenotypic identification(AUC≥0.89) and phenotypic prognostic prediction (AUC≥0.74): anion gap, blood urea nitrogen, creatinine, Glasgow Coma Scale score, prothrombin time, and Sequential Organ Failure Assessment score. The mortality risk of phenotype 3 patients was the lowest at 28 days, 60 days, 90 days, and 1 year after ICU discharge ( Using machine learning methods, we successfully identified three clinical phenotypes of sepsis patients with different clinical characteristics and prognosis and screened out six key clinical features, which are expected to play an important role in the phenotype classification and prognostic assessment of sepsis and are conducive to individualized treatment.
10.Predictive Modeling of Symptomatic Intracranial Hemorrhage Following Endovascular Thrombectomy: Insights From the Nationwide TREAT-AIS Registry
Jia-Hung CHEN ; I-Chang SU ; Yueh-Hsun LU ; Yi-Chen HSIEH ; Chih-Hao CHEN ; Chun-Jen LIN ; Yu-Wei CHEN ; Kuan-Hung LIN ; Pi-Shan SUNG ; Chih-Wei TANG ; Hai-Jui CHU ; Chuan-Hsiu FU ; Chao-Liang CHOU ; Cheng-Yu WEI ; Shang-Yih YAN ; Po-Lin CHEN ; Hsu-Ling YEH ; Sheng-Feng SUNG ; Hon-Man LIU ; Ching-Huang LIN ; Meng LEE ; Sung-Chun TANG ; I-Hui LEE ; Lung CHAN ; Li-Ming LIEN ; Hung-Yi CHIOU ; Jiunn-Tay LEE ; Jiann-Shing JENG ;
Journal of Stroke 2025;27(1):85-94
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.

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