Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background::Limited information exists regarding the impact of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection on psoriasis patients. The objective of this study was to identify clinical factors associated with the prognosis of psoriasis following SARS-CoV-2 infection.Methods::A retrospective, multicenter study was conducted between March and May 2023. Univariable and multivariable logistic regression analyses were employed to identify factors associated with coronavirus disease 2019 (COVID-19)-related psoriasis outcomes. The study included 2371 psoriasis patients from 12 clinical centers, with 2049 of them having been infected with SARS-CoV-2.Results::Among the infected groups, lower exacerbation rates were observed in individuals treated with biologics compared to those receiving traditional systemic or nonsystemic treatments (22.3% [236/1058] vs. 39.8% [92/231] vs. 37.5% [140/373], P <0.001). Psoriasis progression with lesions (adjusted odds ratio [OR] = 8.197, 95% confidence interval [95% CI] = 5.685–11.820, compared to no lesions), hypertension (adjusted OR = 1.582, 95% CI = 1.068–2.343), traditional systemic (adjusted OR = 1.887, 95% CI= 1.263–2.818), and nonsystemic treatment (adjusted OR= 1.602, 95% CI= 1.117–2.297) were found to be associated with exacerbation of psoriasis after SARS-CoV-2 infection, but not biologics (adjusted OR = 0.931, 95% CI = 0.680–1.274, compared to no treatment), according to multivariable logistic regression analysis. Conclusions::A reduced risk of psoriasis exacerbation after SARS-CoV-2 infection was observed with biologics compared to traditional systemic and nonsystemic treatments. Significant risk factors for exacerbation after infection were identified as existing psoriatic lesions and hypertension.

Objective To investigate the risk factors for bronchopulmonary dysplasia(BPD)in twin preterm infants with a gestational age of<34 weeks,and to provide a basis for early identification of BPD in twin preterm infants in clinical practice.Methods A retrospective analysis was performed for the twin preterm infants with a gestational age of<34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020.According to their conditions,they were divided into group A(both twins had BPD),group B(only one twin had BPD),and group C(neither twin had BPD).The risk factors for BPD in twin preterm infants were analyzed.Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins.Results A total of 904 pairs of twins with a gestational age of<34 weeks were included in this study.The multivariate logistic regression analysis showed that compared with group C,birth weight discordance of>25%between the twins was an independent risk factor for BPD in one of the twins(OR=3.370,95%CI:1.500-7.568,P<0.05),and high gestational age at birth was a protective factor against BPD(P<0.05).The conditional logistic regression analysis of group B showed that small-for-gestational-age(SGA)birth was an independent risk factor for BPD in individual twins(OR=5.017,95%CI:1.040-24.190,P<0.05).Conclusions The development of BPD in twin preterm infants is associated with gestational age,birth weight discordance between the twins,and SGA birth.

Objective To investigate the clinical effect of orthopedic robot combined with Starr pelvic reduction frame in the treatment of Tile type C pelvic ring fracture.Methods From October 2019 to May 2021,14 patients with type C pelvic ring fracture were treated with robotic combined with Starr pelvic reduction frame,including 9 males and 5 females.The age ranged from 33 to 69 years.All the 14 patients had fresh closed fractures without femur,tibia and fibula fracture.Surgery was complet-ed from 4 to 7 d after hospital admission.During the operation,the X-ray carbon bed was used,the pelvic ring was reduced by Starr pelvis reduction frame,and pelvic ring fracture was treated by orthopedic robot.Operation time,bleeding volume,fluo-roscopy times of single screw placement,fracture reduction quality,affected limb function and complications were observed.Radiological reduction was evaluated using Matta scoring standard,and clinical efficacy was evaluated by Majeed pelvic func-tion scoring system at the final follow-up.Results All of 14 patients successfully completed the operation,the operation time was 84 to 141 min,the bleeding volume was 20 to 50 ml,and the fluoroscopy times of single screw insertion was 4 to 9 times.All of 14 patients were followed up for 12 to 24 months.The healing time was 3 to 7 months.No complications such as fracture of internal fixation,screw loosening,infection and nerve injury were found.According to the evaluation criteria of Matta imag-ing reduction,9 cases were excellent,4 cases were good,and 1 case was fair.At the final follow-up,Majeed pelvic function scoring system was used:10 cases were excellent,4 cases were good.Conclusion The treatment of type C pelvic ring fracture with robotic combined Starr pelvis reduction frame is simple,time-saving,less trauma,less complications and effective.

Objective: To analyze and compare therapy responses, outcomes, and incidence of severe hematologic adverse events of flumatinib and imatinib in patients newly diagnosed with chronic phase chronic myeloid leukemia (CML) . Methods: Data of patients with chronic phase CML diagnosed between January 2006 and November 2022 from 76 centers, aged ≥18 years, and received initial flumatinib or imatinib therapy within 6 months after diagnosis in China were retrospectively interrogated. Propensity score matching (PSM) analysis was performed to reduce the bias of the initial TKI selection, and the therapy responses and outcomes of patients receiving initial flumatinib or imatinib therapy were compared. Results: A total of 4 833 adult patients with CML receiving initial imatinib (n=4 380) or flumatinib (n=453) therapy were included in the study. In the imatinib cohort, the median follow-up time was 54 [interquartile range (IQR), 31-85] months, and the 7-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.2%, 88.4%, 78.3%, and 63.0%, respectively. The 7-year FFS, PFS, and OS rates were 71.8%, 93.0%, and 96.9%, respectively. With the median follow-up of 18 (IQR, 13-25) months in the flumatinib cohort, the 2-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.4%, 86.5%, 58.4%, and 46.6%, respectively. The 2-year FFS, PFS, and OS rates were 80.1%, 95.0%, and 99.5%, respectively. The PSM analysis indicated that patients receiving initial flumatinib therapy had significantly higher cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) and higher probabilities of FFS than those receiving the initial imatinib therapy (all P<0.001), whereas the PFS (P=0.230) and OS (P=0.268) were comparable between the two cohorts. The incidence of severe hematologic adverse events (grade≥Ⅲ) was comparable in the two cohorts. Conclusion: Patients receiving initial flumatinib therapy had higher cumulative incidences of therapy responses and higher probability of FFS than those receiving initial imatinib therapy, whereas the incidence of severe hematologic adverse events was comparable between the two cohorts.
Adult ; Humans ; Adolescent ; Imatinib Mesylate/adverse effects* ; Incidence ; Antineoplastic Agents/adverse effects* ; Retrospective Studies ; Pyrimidines/adverse effects* ; Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy* ; Treatment Outcome ; Benzamides/adverse effects* ; Leukemia, Myeloid, Chronic-Phase/drug therapy* ; Aminopyridines/therapeutic use* ; Protein Kinase Inhibitors/therapeutic use*

Objective:To study the application of antimony cerium catalytic spectrophotometry using a fully automatic biochemical analyzer (hereinafter referred to as this method) in the determination of water iodine.Methods:Based on the principle of antimony cerium reoxidation reduction reaction catalyzed by iodine, the iodine content in water was determined in the range of 0 - 100 μg/L iodine mass concentration. The detection limit, precision and accuracy (determination of standard substances GBW09113j and GBW09114j for iodine composition analysis in water and the experiment of standard recovery) of this method were verified. This method was compared with the arsenic and cerium catalytic spectrophotometry recommended by the National Reference Laboratory for Iodine Deficiency Disorders.Results:Within the range of 0 - 100 μg/L iodine mass concentration, the qualitative and quantitative detection limits of this method were 0.81 and 2.70 μg/L, respectively (sampling quantity was 35 μl). In the precision experiment, the relative standard deviation of water samples with different iodine mass concentrations ranged from 1.2% to 4.0%. The determination results of the standard substances GBW09113j and GBW09114j for iodine composition analysis in water were both within the given standard value range. The standard recovery rates of water samples with low, medium and high iodine mass concentrations ranged from 101.0% to 106.0%, and the total average standard recovery rate was 103.2%. The results of the method comparison experiment showed that there was no statistically significant difference in the results of water iodine determination between the two methods ( t = - 0.78, P = 0.779). Conclusion:This method has a low detection limit, high precision and good accuracy, making it suitable for the detection of large quantities of samples in the monitoring of iodine deficiency disorders.

Ankylosing spondylitis (AS) combined with spinal fractures with thoracic and lumbar fracture as the most common type shows characteristics of unstable fracture, high incidence of nerve injury, high mortality and high disability rate. The diagnosis may be missed because it is mostly caused by low-energy injury, when spinal rigidity and osteoporosis have a great impact on the accuracy of imaging examination. At the same time, the treatment choices are controversial, with no relevant specifications. Non-operative treatments can easily lead to bone nonunion, pseudoarthrosis and delayed nerve injury, while surgeries may be failed due to internal fixation failure. At present, there are no evidence-based guidelines for the diagnosis and treatment of AS combined with thoracic and lumbar fracture. In this context, the Spinal Trauma Academic Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate the Clinical guideline for the diagnosis and treatment of adult ankylosing spondylitis combined with thoracolumbar fracture ( version 2023) by following the principles of evidence-based medicine and systematically review related literatures. Ten recommendations on the diagnosis, imaging evaluation, classification and treatment of AS combined with thoracic and lumbar fracture were put forward, aiming to standardize the clinical diagnosis and treatment of such disorder.