Objective:Acute kidney injury(AKI) is a common complication after cardiac surgery, and associated with increased risk of development of chronic kidney disease and mortality in the long term. Neutrophil percentage-to-albumin ratio(NPAR) is a new inflammatory marker that has been used to predict the poor prognosis of patients with cardiovascular disease or shock. However, the relationship between NPAR and AKI in patients with cardiac surgery has not been established. The aim was to evaluate the relationship between NPAR and AKI after cardiac surgery.Methods:Data of all adult patients underwent cardiac surgery with cardiopulmonary bypass from January 1, 2006 to December 31, 2018 were extracted from electronic medical record system of the Guangdong Provincial People's Hospital and retrospectively analyzed. The outcome of interest was AKI diagnosed by using the criteria of Kidney Disease Improving Global Outcomes. Logistic regression was used to assess the relationship between NPAR and postoperative AKI while adjust for potential confounders. In addition, restricted cubic spline(RCS) was utilized to provide a flexible description of the association of the preoperative NPAR and AKI. Results:Totally, 24 178 patients were analyzed. The incidence of AKI was 30.1%. Compared with patients without AKI, those with AKI were older and had higher rates of males, left ventricular ejection fraction(LVEF) less than or equal to 0.60, estimated glomerular filtration rate less than 90 ml·min -1·1.73 m -2, hypertension, diabetes, emergency surgery, preoperative critical illness, and reoperation. The baseline serum creatinine, serum uric acid, cardiopulmonary bypass time and postoperative mechanical ventilation time were higher or longer in AKI patients than those in none AKI patients. Then, patients were divided into four groups based on NPAR quartiles. After adjusting for confounding factors using logisitc regression, compared with patients with NPAR in group 3(1.551.97), respectively. The RCS showed a U-shaped nonlinear relationship( P for nonlinear less than 0.001) between NPAR and AKI after adjusting for potential confounding factors. RCS indicated the NPAR of 1.77 was the lowest risk for AKI. When NPAR less than 1.77, per 1-standard deviation(SD) increase in NPAR, the risk of AKI decreased by 23.2%( OR=0.768, 95% CI: 0.687, 0.859). Conversely, when NPAR above 1.77, per one SD increase in NPAR, the risk of AKI increased by 25.9%( OR=1.259, 95% CI: 1.166, 1.36). Conclusion:A U-shaped relationship between NPAR and AKI after cardiac surgery was shown. The appropriate value for NPAR might be 1.77. The risk of AKI might be increased, when less or above this value. NPAR might be used as an effective and economical tool to identify AKI risk among individuals with cardiac surgery, as well as to formulate individualized prevention and intervention strategy.

Objective:Using Mendelian randomization analysis to investigate the unidirectional causal effects of gut microbiota on gout and serum uric acid levels.Methods:The Mendelian randomization analysis was conducted using summary statistics from genome-wide association studies (GWAS). The gut microbiota was used as the exposure factor, with gout and serum uric acid levels as the outcomes, utilizing the MiBioGen Consortium, FinnGen GWAS, and CKDGen Consortium meta-analysis databases. The analysis was performed using inverse variance weighted (IVW) method, MR-Egger, and weighted median (WM) approach. Additionally, sensitivity analysis was conducted by excluding heterogeneity and horizontal pleiotropy. This study used RStudio 4.3.1 software for analysis.Results:The IVW results confirmed that 17 microbiota taxa were associated with gout, including class Verrucomicrobiaceae [ OR(95% CI)=1.162(1.004, 1.344), P=0.044], family Verrucomicrobiaceae [ OR(95% CI)=1.161(1.004, 1.344), P=0.044], genus Akkermansia [ OR(95% CI)=1.162(1.004, 1.344), P=0.044], genus Collinsella [ OR(95% CI)=1.257(1.043, 1.516), P=0.016], genus Eubacterium hallii group [ OR(95% CI)=1.226(1.022, 1.471), P=0.027], genus Howardella [ OR(95% CI)=1.094(1.001, 1.195), P=0.046], genus Ruminococcaceae UCG010 [ OR(95% CI)=1.317(1.089, 1.593), P=0.004], order Clostridiales [ OR(95% CI)=1.182(1.007,1.387), P=0.041], order Verrucomicrobiales [ OR(95% CI)=1.162(1.004, 1.344), P=0.044], class Melainabacteria [ OR(95% CI)=0.894(0.804, 0.994), P=0.038], family Streptococcaceae [ OR(95% CI)=0.851(0.727, 0.996), P=0.044], unknown family [ OR(95% CI)=0.890(0.800, 0.989), P=0.030], genus Streptococcus [ OR(95% CI)=0.836(0.710, 0.983), P=0.030], unknown genus [ OR(95% CI)=0.890(0.800, 0.989), P=0.030], genus Victivallis [ OR(95% CI)=0.857(0.736, 0.998), P=0.046], order Gastranaerophilales [ OR(95% CI)=0.890(0.800,0.989), P=0.030], and phylum Bacteroidetes [ OR(95% CI)=0.827(0.692, 0.989), P=0.037]. Additionally, 5 microbiota taxa were associated with serum uric acid levels: phylum Actinobacteria [ OR(95% CI)=0.963(0.925, 0.992), P=0.027], family ⅩⅢ [ OR(95% CI)=0.965(0.932, 1.008), P=0.035], genus Escherichia Shigella [ OR(95% CI)=1.047(1.005,1.089), P=0.034], genus Lachnospiraceae FCS020 group [ OR(95% CI)=0.974(0.941, 1.003), P=0.028], and genus Lachnospiraceae NC2004 group [ OR(95% CI)=0.966(0.943, 0.995), P=0.018]. No abnormalities in SNPs were found in the sensitivity analysis. Conclusion:An increase in the levels of class Verrucomicrobiae, family Verrucomicrobiaceae, genus Akkermansia, and genus Escherichia Shigella is associated with an increased risk of gout or serum uric acid levels, while an increase in the levels of class Melainabacteria, family Streptococcaceae, unknown family, phylum Actinobacteria, and family ⅩⅢ is associated with a decreased risk of gout or serum uric acid levels.

Objective:Acute kidney injury(AKI) is a common complication after cardiac surgery, and associated with increased risk of development of chronic kidney disease and mortality in the long term. Neutrophil percentage-to-albumin ratio(NPAR) is a new inflammatory marker that has been used to predict the poor prognosis of patients with cardiovascular disease or shock. However, the relationship between NPAR and AKI in patients with cardiac surgery has not been established. The aim was to evaluate the relationship between NPAR and AKI after cardiac surgery.Methods:Data of all adult patients underwent cardiac surgery with cardiopulmonary bypass from January 1, 2006 to December 31, 2018 were extracted from electronic medical record system of the Guangdong Provincial People's Hospital and retrospectively analyzed. The outcome of interest was AKI diagnosed by using the criteria of Kidney Disease Improving Global Outcomes. Logistic regression was used to assess the relationship between NPAR and postoperative AKI while adjust for potential confounders. In addition, restricted cubic spline(RCS) was utilized to provide a flexible description of the association of the preoperative NPAR and AKI. Results:Totally, 24 178 patients were analyzed. The incidence of AKI was 30.1%. Compared with patients without AKI, those with AKI were older and had higher rates of males, left ventricular ejection fraction(LVEF) less than or equal to 0.60, estimated glomerular filtration rate less than 90 ml·min -1·1.73 m -2, hypertension, diabetes, emergency surgery, preoperative critical illness, and reoperation. The baseline serum creatinine, serum uric acid, cardiopulmonary bypass time and postoperative mechanical ventilation time were higher or longer in AKI patients than those in none AKI patients. Then, patients were divided into four groups based on NPAR quartiles. After adjusting for confounding factors using logisitc regression, compared with patients with NPAR in group 3(1.551.97), respectively. The RCS showed a U-shaped nonlinear relationship( P for nonlinear less than 0.001) between NPAR and AKI after adjusting for potential confounding factors. RCS indicated the NPAR of 1.77 was the lowest risk for AKI. When NPAR less than 1.77, per 1-standard deviation(SD) increase in NPAR, the risk of AKI decreased by 23.2%( OR=0.768, 95% CI: 0.687, 0.859). Conversely, when NPAR above 1.77, per one SD increase in NPAR, the risk of AKI increased by 25.9%( OR=1.259, 95% CI: 1.166, 1.36). Conclusion:A U-shaped relationship between NPAR and AKI after cardiac surgery was shown. The appropriate value for NPAR might be 1.77. The risk of AKI might be increased, when less or above this value. NPAR might be used as an effective and economical tool to identify AKI risk among individuals with cardiac surgery, as well as to formulate individualized prevention and intervention strategy.

Objective:To develop a quality control model for anal sphincter ultrasound images and validate its diagnostic performance across multiple centers.Methods:A retrospective analysis was conducted on anal sphincter ultrasound images from seven medical centers in China between May 2019 and June 2022. A total of 7 040 images from 3 116 patients were included and divided into a training set（4 912 images）and a validation set（2 128 images）. The images were classified as standard or non-standard images by three experts. Three models were developed based on different image feature extraction methods：a single-branch model，a multi-branch weighted model，and a multi-branch ensemble model. The diagnostic performance of each model was evaluated using the area under the ROC curve（AUC），sensitivity，specificity，accuracy，positive predictive value，and negative predictive value，respectively. The optimal model was selected and compared with the performance of 4 doctors with varying experience levels. Sixty days later，the images with the assistance of the model's output were reassessed by the doctors to evaluate its impact on manual quality control.Results:① Among the 3 models，the multi-branch ensemble model demonstrated the highest AUC and sensitivity，with an AUC of 0.966（95% CI=0.958 - 0.974），a sensitivity of 91.83%，and a specificity of 91.41%. This model was named M quality. ② M quality's AUC was slightly lower than that of Senior A and B（0.966 vs. 0.976，0.976，and P<0.05），its sensitivity was slightly lower than that of Senior A（91.83% vs. 95.61%， P<0.001）but comparable to Senior B（91.83% vs. 92.89%， P=0.315），its specificity was slightly lower than Senior A and B（91.41% vs. 94.44%，98.18%，and P<0.05）. However，M quality significantly outperformed Junior A and B in AUC and sensitivity（AUC：0.966 vs. 0.850，0.818；sensitivity：91.83% vs. 84.90%，61.46%；all P<0.001），its specificity was higher than that of Junior A（91.41% vs. 80.28%， P<0.001）but lower than that of Junior B（91.41% vs. 95.96%， P<0.001）. ③ With model assistance，Senior B's sensitivity（92.89% vs. 94.20%， P=0.001）and Senior A's specificity（94.44% vs. 96.56%， P<0.001）improved significantly. Junior A and B showed significant improvements in AUC and sensitivity（AUC：0.931 vs. 0.850，0.914 vs. 0.818；sensitivity：91.83% vs. 84.90%，89.53% vs. 61.46%；all P<0.001）. After model assistance，Junior A's specificity increased（93.62% vs. 80.28%， P<0.001），while Junior B's specificity decreased（91.60% vs. 95.96%， P=0.013）. Conclusions:This study develops a quality control model for anal sphincter ultrasound images with robust diagnostic performance，approaching the level of seniors. The model significantly enhances the image quality assessment capabilities of juniors，demonstrating promising clinical application potential.

Objective:Using Mendelian randomization analysis to investigate the unidirectional causal effects of gut microbiota on gout and serum uric acid levels.Methods:The Mendelian randomization analysis was conducted using summary statistics from genome-wide association studies (GWAS). The gut microbiota was used as the exposure factor, with gout and serum uric acid levels as the outcomes, utilizing the MiBioGen Consortium, FinnGen GWAS, and CKDGen Consortium meta-analysis databases. The analysis was performed using inverse variance weighted (IVW) method, MR-Egger, and weighted median (WM) approach. Additionally, sensitivity analysis was conducted by excluding heterogeneity and horizontal pleiotropy. This study used RStudio 4.3.1 software for analysis.Results:The IVW results confirmed that 17 microbiota taxa were associated with gout, including class Verrucomicrobiaceae [ OR(95% CI)=1.162(1.004, 1.344), P=0.044], family Verrucomicrobiaceae [ OR(95% CI)=1.161(1.004, 1.344), P=0.044], genus Akkermansia [ OR(95% CI)=1.162(1.004, 1.344), P=0.044], genus Collinsella [ OR(95% CI)=1.257(1.043, 1.516), P=0.016], genus Eubacterium hallii group [ OR(95% CI)=1.226(1.022, 1.471), P=0.027], genus Howardella [ OR(95% CI)=1.094(1.001, 1.195), P=0.046], genus Ruminococcaceae UCG010 [ OR(95% CI)=1.317(1.089, 1.593), P=0.004], order Clostridiales [ OR(95% CI)=1.182(1.007,1.387), P=0.041], order Verrucomicrobiales [ OR(95% CI)=1.162(1.004, 1.344), P=0.044], class Melainabacteria [ OR(95% CI)=0.894(0.804, 0.994), P=0.038], family Streptococcaceae [ OR(95% CI)=0.851(0.727, 0.996), P=0.044], unknown family [ OR(95% CI)=0.890(0.800, 0.989), P=0.030], genus Streptococcus [ OR(95% CI)=0.836(0.710, 0.983), P=0.030], unknown genus [ OR(95% CI)=0.890(0.800, 0.989), P=0.030], genus Victivallis [ OR(95% CI)=0.857(0.736, 0.998), P=0.046], order Gastranaerophilales [ OR(95% CI)=0.890(0.800,0.989), P=0.030], and phylum Bacteroidetes [ OR(95% CI)=0.827(0.692, 0.989), P=0.037]. Additionally, 5 microbiota taxa were associated with serum uric acid levels: phylum Actinobacteria [ OR(95% CI)=0.963(0.925, 0.992), P=0.027], family ⅩⅢ [ OR(95% CI)=0.965(0.932, 1.008), P=0.035], genus Escherichia Shigella [ OR(95% CI)=1.047(1.005,1.089), P=0.034], genus Lachnospiraceae FCS020 group [ OR(95% CI)=0.974(0.941, 1.003), P=0.028], and genus Lachnospiraceae NC2004 group [ OR(95% CI)=0.966(0.943, 0.995), P=0.018]. No abnormalities in SNPs were found in the sensitivity analysis. Conclusion:An increase in the levels of class Verrucomicrobiae, family Verrucomicrobiaceae, genus Akkermansia, and genus Escherichia Shigella is associated with an increased risk of gout or serum uric acid levels, while an increase in the levels of class Melainabacteria, family Streptococcaceae, unknown family, phylum Actinobacteria, and family ⅩⅢ is associated with a decreased risk of gout or serum uric acid levels.

Objective:To develop a quality control model for anal sphincter ultrasound images and validate its diagnostic performance across multiple centers.Methods:A retrospective analysis was conducted on anal sphincter ultrasound images from seven medical centers in China between May 2019 and June 2022. A total of 7 040 images from 3 116 patients were included and divided into a training set（4 912 images）and a validation set（2 128 images）. The images were classified as standard or non-standard images by three experts. Three models were developed based on different image feature extraction methods：a single-branch model，a multi-branch weighted model，and a multi-branch ensemble model. The diagnostic performance of each model was evaluated using the area under the ROC curve（AUC），sensitivity，specificity，accuracy，positive predictive value，and negative predictive value，respectively. The optimal model was selected and compared with the performance of 4 doctors with varying experience levels. Sixty days later，the images with the assistance of the model's output were reassessed by the doctors to evaluate its impact on manual quality control.Results:① Among the 3 models，the multi-branch ensemble model demonstrated the highest AUC and sensitivity，with an AUC of 0.966（95% CI=0.958 - 0.974），a sensitivity of 91.83%，and a specificity of 91.41%. This model was named M quality. ② M quality's AUC was slightly lower than that of Senior A and B（0.966 vs. 0.976，0.976，and P<0.05），its sensitivity was slightly lower than that of Senior A（91.83% vs. 95.61%， P<0.001）but comparable to Senior B（91.83% vs. 92.89%， P=0.315），its specificity was slightly lower than Senior A and B（91.41% vs. 94.44%，98.18%，and P<0.05）. However，M quality significantly outperformed Junior A and B in AUC and sensitivity（AUC：0.966 vs. 0.850，0.818；sensitivity：91.83% vs. 84.90%，61.46%；all P<0.001），its specificity was higher than that of Junior A（91.41% vs. 80.28%， P<0.001）but lower than that of Junior B（91.41% vs. 95.96%， P<0.001）. ③ With model assistance，Senior B's sensitivity（92.89% vs. 94.20%， P=0.001）and Senior A's specificity（94.44% vs. 96.56%， P<0.001）improved significantly. Junior A and B showed significant improvements in AUC and sensitivity（AUC：0.931 vs. 0.850，0.914 vs. 0.818；sensitivity：91.83% vs. 84.90%，89.53% vs. 61.46%；all P<0.001）. After model assistance，Junior A's specificity increased（93.62% vs. 80.28%， P<0.001），while Junior B's specificity decreased（91.60% vs. 95.96%， P=0.013）. Conclusions:This study develops a quality control model for anal sphincter ultrasound images with robust diagnostic performance，approaching the level of seniors. The model significantly enhances the image quality assessment capabilities of juniors，demonstrating promising clinical application potential.

Objective:To investigate the risk factors of acute symptomatic seizures (ASS) and epilepsy in children with myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD).Methods:A ambispective cohort study was used including 74 children with MOGAD who were admitted to the Department of Pediatrics of Peking University First Hospital from January 2013 to June 2023 and were followed up. Demographic information, clinical information, treatment status, ASS and epilepsy status were collected. The clinical phenotypes were classified. According to the presence or absence of ASS in the course of disease, the children and the course of disease were divided into groups with and without ASS. Chi-square test, Fisher exact test and Mann Whitney U test were used to analyze the correlation between symptoms and auxiliary examination characteristics and the occurrence of ASS in the two groups of children. Multivariate Logistic regression analysis was used for multivariate analysis. Results:The onset age of the 74 children with MOGAD was 6.58 (3.80, 9.67) years, including 38 females (51.4%) and 36 males (48.6%). The duration of the final follow-up was 2.67 (1.10, 4.12) years, with a total of 239 times acute clinical episodes. ASS occurred in 39.2% (29/74) children during the course of disease and in 29.3% (70/239) of attacks. The common phenotypes were ADEM (67 times (28.0%)), optic neuritis (37 times (15.4%)) and cerebral cortical encephalitis (31 times (13.0%)) in 239 times acute clinical episodes. The incidence of ASS in ADEM and cerebral cortical encephalitis phenotype was 28.4%(19/67) and 100.0% (31/31), respectively. Multivariate analysis showed that cortical involvement on magnetic resonance imaging during clinical attacks was an independent risk factor for ASS ( β=-1.49, OR=0.23) after excluding attacks involving only optic nerve or spinal cord (49 episodes). During the follow-up, 5 children (6.8%) had epilepsy, and all children with epilepsy had multiple clinical attacks of MOGAD and previous ASS. Conclusions:Cortical involvement on magnetic resonance imaging during clinical episodes is an independent risk factor for ASS in children with MOGAD. All MOGAD children with epilepsy had ASS and multiple MOGAD clinical episodes in the past.

Objective:To construct a nomogram model for predicting the risk of leukopenia among tuberculosis patients receiving anti-tuberculosis therapy.Methods:A total of 2 681 tuberculosis patients admitted to the affiliated Dongyang Hospital of Wenzhou Medical University from Jan 2013 to Jun 2024，were enrolled in this study. All cases received first line anti-tuberculosis treatment and were randomly divided into training（ n=1 876）and validation groups（ n=805）at a ratio of 7∶3. The endpoint was the occurrence of leukopenia during anti-tuberculosis therapy. In the training group，the predictors were screened by Lasso regression and multivariable Logistic regression analysis，and used to establish a nomogram prediction model. The discrimination power，fitness and clinical applicability were evaluated using the receiver operating characteristic（ROC）curve，calibration curve and decision curve analysis，respectively. Several machine learning models based on different methods（random forest，support vector machine，extreme gradient boosting and naive Bayes）were also constructed in the validation group. Results:There were 15.0%（273/1 876）and 15.9%（128/805）of cases developing leukopenia during anti-tuberculosis therapy in the training group and validation groups，respectively. Following Lasso regression analysis，the multivariable Logistic regression analysis showed that age ≥65 years（ OR=2.997，95% CI 2.185-4.128），alcohol consumption（ OR=4.803，95% CI 3.502-6.593）and diabetes（ OR= 5.459，95% CI 3.914-7.621）were risk factors related to the occurrence of leukopenia；while the higher levels of baseline hemoglobin（ OR=0.979，95% CI 0.971-0.987）and platelet count（ OR=0.996，95% CI 0.995-0.998）were protective factors. Based on these five factors，a nomogram prediction model was developed. The areas under ROC curve（AUCs）were 0.836（95% CI 0.810-0.863）and 0.818（95% CI 0.776-0.860）in the training group and the validation group，respectively. Moreover，this model had good fitness and clinical applicability. The discrimination power of nomogram model was comparable to those of machine learning models. Conclusion:The established nomogram model in this study has good discrimination power，calibration ability and clinical applicability for predicting the risk of leucopenia in tuberculosis patients undergoing anti-tuberculosis therapy.

A 82-year-old man was admitted to hospital with fever,unresponsiveness,elevated hypersensitive C-reactive protein and neutrophile granulocyte.Ceftriaxone was administrated by intravenous dripping in the emergency room,but the effect was not satisfactory.Following his admission to the ward,cefoperazone sulbactam were given.Elizabethkingia meningoseptica was identified by blood culture and further confirmed by 16S rRNA sequencing.The lumbar puncture showed that cerebrospinal fluid pressure was 80 mmH2O(1 mmH2O=0.0098 kPa)and biochemical results were normal.After 11 days of cefoperazone sulbactam treatment,the patient was discharged with negative blood culture.The hypersensitive C-reactive protein and neutrophile granulocyte had also declined.The patient received levofloxacin tablets for anti-infection treatment for 14 d after discharge.No signs of infection were observed in three months'following up.

Objective To study the correlation between single nucleotide polymorphisms at loci rs4535211,rs75885714,and rs7653834 of phosphatidylinositol-specific phospholipase 2 (PLCL2) gene and large artery atherosclerotic (LAA) ischemic stroke.Methods A total of 105 patients with newly diagnosed LAA ischemic stroke admitted to the Second Affiliated Hospital of Xinjiang Medical University from July 2021 to July 2022 were selected as the observation group,and 103 patients with gender and age matching phys-ical examination in this hospital during the same period were selected as the control group. The clinical data and serum inflammatory markers were collected and compared between the two groups.Genotypes of PLCL2 gene rs4535211,rs75885714 and rs7653834 loci in the two groups were detected,and genotype and allele fre-quencies were calculated.Results The levels of C-reactive protein (CRP),interleukin-6 (IL-6),neutrophil to lymphocyte ratio (NLR),monocyte to high-density lipoprotein-cholesterol ratio (MHR),platelet to lympho-cyte ratio (PLR) and D-dimer in the observation group were higher than those in the control group.The level of high density lipoprotein-cholesterol (HDL-C) was lower than that of the control group (P<0.05). rs7653834 locus was C/C,C/T,T/T genotypes,and the difference between the two groups was statistically significant (P<0.05).The levels of C/C,T/C and T/T genotypes NLR and PLR at rs7653834 locus were sta-tistically significant between the two groups (P<0.05).The analysis results of co-dominant model,dominant model and overdominant model showed that there was statistical significance in rs7653834 locus genotype be-tween the two groups (P<0.05).Conclusion There may be a potential association between rs7653834 locus polymorphism of PLCL2 gene and LAA type ischemic stroke.