Objective:To investigate the prognostic factors for esophageal cancer after radical resection and the application value of machine learning prediction model.Methods:The retrospective cohort study was conducted. The clinicopatholigical data of 406 esophageal cancer patients who were admitted to Qilu Hospital of Shandong University from January 2018 to March 2022 were collected. There were 357 males and 49 females, aged (64±8)years. All patients underwent radical resection of esophageal cancer. The 406 patients were randomly divided into a training set of 285 cases and a validation set of 121 cases at a 7∶3 ratio based on a random number table. The training set was used to construct prediction model, and the validation set was used to validate prediction model. Patients were divided into high-risk group and low-risk group based on risk scores. Observation indicators: (1) follow-up of patients and analysis of influencing factors for prognosis; (2) construction and validation of machine learning prediction models. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Comparison of ordinal data between groups was conducted using the rank sum test. The Kaplan-Meier method was used to calculate survival rate and plot survival curve, and the Log-rank test was used for survival analysis. The Cox proportional hazard regression model was used for univariate and multivariate analyses. Independent influencing factors were included, and data processing, machine learning model construction, and visualization were performed using R packages including random survival forest (RSF), gradient boosting machine (GBM), least absolute shrinkage and selection operator Cox regression (LASSO-Cox), Cox proportional hazards model boosting (CoxBoost), survival support vector machine (survivalsvm), extreme gradient boosting (XGBoost), supervised principal component analysis (SuperPC), and Cox partial least squares regression (plsRcox). Receiver operating characteristic (ROC) curves were drawn, and sensitivity, specificity, and area under the curve (AUC) were calculated. The Delong test was used to assess the differences in AUC among different models in the training set, and the time-dependent ROC was used to compare the predictive performance of different models. Calibration curves were used to evaluate model accuracy, and decision curve analysis (DCA) was used to evaluate overall net benefit. Results:(1) Follow-up of patients and analysis of influencing factors for prognosis. All 406 patients were followed up postoperatively for 28(range, 6-36)months, with 1- and 3-year overall survival rate of 86.5% and 40.9%, respectively. The 285 patients in the training set were followed up postoperatively for 30(range, 6-36)months, with 1- and 3-year overall survival rate of 85.1% and 35.5%, respectively. The 121 patients in the validation set were followed up postoperatively for 25(range, 6-36)months, with 1- and 3-year overall survival rate of 87.0% and 43.2%, respectively. There was no significant difference in postoperative overall survival rate between the training set and the validation set ( χ2=3.20, P>0.05). Results of multivariate analysis showed that left thoracic surgical approach, preopera-tive neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia were independent risk factors affecting postoperative survival of 285 patients in the training set ( hazard ratio=1.466, 1.037, 1.482, 1.549, 5.268, 7.727, 22.202, 2.539, 2.686, 1.425, 95% confidence interval as 1.026-2.096, 1.003-1.073, 1.008-2.179, 1.105-2.170, 1.201-23.099, 1.833-32.576, 4.734-104.128, 1.577-4.087, 1.631-4.422, 1.018-1.994, P<0.05). (2) Construction and validation of machine learning prediction models. Independent risk factors affecting postoperative survival were included to construct RSF, GBM, LASSO-Cox, CoxBoost, survivalsvm, XGBoost, SuperPC, and plsRcox machine learning prediction models. Results of Delong test showed that there were significant differences in the AUC of RSF and GBM from the other six models ( P<0.05). Results of time-dependent ROC curve showed that all 8 machine learning predic-tion models had good discriminative ability in the training cohort, among which the RSF machine learning prediction model had the best predictive performance. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postoperative 1-, 2-, and 3-year overall survival in the training cohort, with high consistency with actual results. Results of decision curve analysis showed that within a threshold range of 0-0.80, the RSF machine learning prediction model provided a better overall net benefit. Further analysis showed that in the validation set, the AUC of RSF machine learning prediction model for postoperative 1-, 2-, and 3-year survival prediction were 0.786 (95% confidence interval as 0.609-0.962), 0.774 (95% confidence interval as 0.676-0.873), and 0.750 (95% confidence interval as 0.652-0.848), respectively. Results of calibration curve showed that the RSF machine learning prediction model fitted well for predicting postopera-tive 1-, 2-, and 3-year overall survival in the validation set, with high consistency with actual results. In the training set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score <11.7 as the low-risk group. The median survival times of the two groups were 18.0 months and >36.0 months, respectively, showing a significant difference between them ( χ2=73.30, P<0.05). In the validation set, the optimal cutoff value of the RSF machine learning prediction model risk score was 11.7. Patients with risk score ≥11.7 were classified as the high-risk group, and those with risk score<11.7 as the low-risk group. The median survival times of the two groups were 17.0 months and>36.0 months for the high-risk and low-risk groups, respectively, showing a significant difference between them ( χ2=35.20, P<0.05). Conclusions:Left thoracic surgical approach, preoperative neutrophil count, vascular invasion, perineural invasion, pathological T2-4 stage, pathological N2-3 stage, and postoperative pneumonia are independent risk factors affecting survival of esophageal cancer patients after radical resection. The RSF machine learning prediction model constructed based on these factors can effectively distinguish the survival prognosis of high-risk and low-risk patients.

Objective:To develop a simplified confocal laser endomicroscopy (CLE)-based healing scoring system for assistant diagnosis of deep remission in ulcerative colitis (UC).Methods:CLE images from consecutive UC patients in clinical remission or mild activity and healthy controls undergoing CLE at Peking University First Hospital from January 2017 to December 2019 were retrospectively analyzed. According to the diagnosis of inflammation in intestinal segments in the medical records of UC patients, CLE images were divided into two groups, the involved group (inflamed UC segment) and the control group (segments from healthy individuals and non-inflamed UC segments). CLE features differentiating the groups were identified, and univariable regression analysis was used to obtain indicators related to unhealed histological inflammation (Geboes score>2.0), forming a simplified CLE healing score using the significant indicators, and receiver operator characteristic (ROC) curve was drawn.Results:The study included 53 UC patients and 14 healthy controls, yielding 201 CLE segments (42 healthy, 69 non-inflamed, 90 inflamed). Eight CLE features differed significantly between the involved and the control groups ( P<0.001), including crypt distortion, crypt lumen irregularity, crypt proximity, crypt sparsity, crypt lumen fluorescein leakage, vascular fluorescein leakage, increased vessel diameter, and cellular infiltration. Univariable regression analysis indicated there were 4 indicators related to histological inflammation, including crypt distortion ( P=0.025, OR=3.613, 95% CI:1.174-11.114), crypt lumen irregularity ( P=0.021, OR=4.081, 95% CI: 1.233-13.511), crypt fluorescein leakage ( P=0.011, OR=5.486, 95% CI: 1.468-20.494) and increased vessel diameter ( P=0.002, OR=7.724, 95% CI: 2.062-28.938). These 4 indicators were combined to form a simplified CLE healing score and a ROC curve was plotted with AUC of 0.769 (95% CI:0.654-0.833). The optimal threshold for histological healing was the absence of all four features (score=0), with sensitivity and specificity of 83.1% (59/71) and 42.1% (8/19), respectively. Conclusion:The simplified CLE score demonstrates high sensitivity and correlates positively with histological healing, supporting its utility as an adjunct tool for assessing deep remission in UC.

Objective To explore the predictive value of dose surface histogram(DSH)in image guided radiotherapy(IGRT)for radiotherapy-induced acute radiation proctitis(ARP)in cervical cancer(CCA).Methods Totally 380 patients with CCA IGRT admitted to some hospital from May 2019 to May 2023 were selected prospectively and randomly divided into a control group(n=1 80)and an experimental group(n=200).The patients in the 2 groups were followed up and the incidence rates of ARP were counted,and rectal dose distribution was evaluated using dose volume histogram(DVH)in the control group and DSH in the experimental group.The predictive values of DVH and DSH for ARP were evaluated and compared using ROC curves.Statistical analysis was performed using SPSS 21.0 software.Results The two groups did not have statistically significant difference in the incidence rate of ARP(P＞0.05),while there were significant differences in the evaluation indicators of the rectal dose distribution(P＜0.05).V40,V50,S40 and S50 proved to have low predictive values for grade Ⅰ-Ⅳ ARP with AUC 0.700(P＜0.05);V60 and S60 had moderate predictive values for grade Ⅰ-Ⅳ ARP with AUC greater than 0.700 and less than or equal to 0.900(P＜0.05);V70,V78,S70 and S7s showed high predictive values for grade Ⅰ-Ⅳ ARP with AUC higher than 0.900(P＜0.05).Delong's test results indicated that DVH and DSH had no significant differences in AUC when used to predict gradeⅠ-Ⅳ ARP(allP＞0.05).Conclusion DSH is essentially the same as DVH when used for the prediction of grade Ⅰ-Ⅳ ARP due to CCA IGRT,and thus can be used for the supplementation and optimization of radiotherapy planning systems.[Chinese Medical Equipment Journal,2025,46(3):48-53]

Objective To investigate the effect of intravenous injection of remifentanil on the comfort level of birth-giving women with scarred uterus undergoing cesarean section.Methods A total of 82 birth-giving women with scarred uterus who underwent cesarean section in the Suqian Hospital of Jiangsu Provincial People's Hospital from October 2021 to September 2023 were selected and randomly divided into the observation group and the control group(with 41 cases in each group).Before skin resection of cesarean section,the birth-giving women of the observation group were injected with 0.05 μg·kg-1·min-1 remifentanil intravenously until the end of the operation,and these in the control group was injected with the same amount of normal saline.The vital signs and pain at different time points,traction reaction and occurrence of maternal and infant complications were compared between the two groups.Results The mean arterial pressure(MAP),heart rate(HR),pain visual analogue scale(VAS)score and incidence of traction reactions at abdominal exploration in the observation group were significantly lower than those in the control group(P<0.05).There was no significant difference in the neonatal umbilical vein pH value,umbilical vein blood pulse oximetry saturation(SPO2),Apgar scores 1 minute and 5 minutes after birth of newborn,or nausea,vomiting and respiratory depression of birth-giving women between the two groups(P>0.05).Conclusion For birth-giving women with scar uterus who underwent cesarean section,intravenous injection of 0.05 μg·kg-1·min-1 of reifentanil can reduce the fluctuation of vital signs,significantly relieve the traction reaction at abdominal exploration,with a few maternal and infant complications,which is conducive to improving the comfort level of the birth-giving women.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1％of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9％)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5％)was lower than that in inpatient children(31.5％).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1％)than in inpatient children(59.4％).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14％,11.7％,47.8％in outpatients,but 24.2％,20.6％,and 52.8％in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.

Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)％.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0％vs 29.5％).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7％vs 7.8％,0.8％vs 0.1％,both P＜0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)％with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9％and 1.8％,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1％).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10％.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P＜0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.

Objective To analyze the risk factors of permanent hypoparathyroidism(pHPP)after total thyroidectomy in patients with thyroid cancer and establish a nomogram prediction model.Methods A total of 245 patients with thyroid cancer who received total thyroidectomy in our hospital were enrolled between January 2020 and January 2024.According to presence or absence of postoperative pHPP,patients were divided into the pHPP group and the non-pHPP group.The influencing factors of postoperative pHPP in patients with thyroid cancer were analyzed by univariate and multivariate Logistic regression analysis.The nomogram prediction model for postoperative pHPP in patients with thyroid cancer was constructed and varified,and efficiency of the model was evaluated.Results In 245 patients with thyroid cancer,the incidence of pHPP within 6 months after surgery was 10.20%(25/245).Univariate analysis showed that there were significant differences in tumor size,surgical method,central lymph node dissection,use of nano carbon tracer,envelope invasion,parathyroid excision by mistake,Hashimoto thyroiditis,serum calcium and parathyroid hormone at 1 d after surgery between the two groups(P＜0.05),but there were no significant differences in gender,age,smoking,drinking,extraglandular invasion,parathyroid autologous transplantation,preoperative vitamin D or serum phosphorus at 1 d after surgery between the two groups(P＞0.05).Multivariate analysis showed that maximum tumor diameter≥4 cm,routine and open total thyroidectomy,central lymph node dissection,no use of nano carbon tracer and parathyroid excision by mistake were all independent risk factors for postoperative pHPP in patients with thyroid cancer(P＜0.05).Results of nomogram prediction model showed that C-index was 0.921,the corrected curve was close to ideal curve,and AUC of nomogram model for predicting postoperative pHPP was 0.926(95%CI:0.871-0.981).Conclusion The nomogram prediction model constructed based on independent risk factors of postoperative pHPP has good predictive efficiency in patients with thyroid cancer.

Objective To explore the mechanism of honey-processed Hedysari Radix in the regulation of intestinal immunity in rats with spleen qi deficiency,which was based on G protein-coupled receptor 41(GPR41)/GPR43-mediated mitogen-activated protein kinase(MAPK)signaling pathway.Methods The three-factor composite modeling method of eating disorder,diarrhea and fatigue was used to establish a model of spleen qi deficiency,and the rats were randomly divided into model,honey-processed Hedysari Radix,probiotics and blank groups with 15 rats per group.The honey-processed Hedysari Radix group was given by gavage 12.6 g·kg-1 aqueous extract of honey-processed Hedysari Radix.The probiotics group was given 0.625 g·kg-1 bifidobacterium triple viable solution by gavage.The blank and model groups were given the same dose of distilled water by gavage.Four groups were treated for 15 d with once a day.The expression levels of GPR41,GPR43,P38 MAPK,c-Jun N-terminal kinase(JNK)and extracellular regulatory protein kinase 1/2(ERK1/2)in colon tissues were detected by Western blotting.Results The relative expression levels of GPR41 in the blank,model,honey-processed Hedysari Radix and probiotics groups were 0.95±0.07,0.45±0.03,0.84±0.19 and 0.86±0.20;the relative expression levels of GPR43 were 1.17±0.11,0.41±0.06,0.66±0.03 and 0.57±0.01;the phosphorylated ERK1/2/ERK1/2 ratios were 0.16±0.01,0.43±0.01,0.39±0.01 and 0.36±0.02;the phosphorylated JNK/JNK ratios were 0.58±0.05,1.47±0.10,0.90±0.11 and 0.90±0.11;the phosphorylated P38 MAPK/P38 MAPK ratios were 1.77±0.33,3.19±0.03,2.01±0.17 and 2.23±0.59,respectively.Compared with the model group,the differences of above indexes were statistically significant in the honey-processed Hedysari Radix and probiotics groups(P＜0.05,P＜0.01).Conclusion The mechanism of honey-processed Hedysari Radix regulating intestinal immunity in rats with spleen qi deficiency is related to the regulation of GPR41/GPR43 mediated MAPK signaling pathway.

Objective To summarize the magnetic resonance imaging(MRI)features of spinal adnexal tuberculosis in order to improve its early diagnosis.Methods Totally 21 spinal adnexal tuberculosis patients confirmed at some hospital from January 2019 to October 2023 had their clinical data and MRI images analyzed retrospectively to determine the basic clinical characteristics and MRI features.Results Of the 21 patients,8 ones had sudden lower extremity weakness and pyramidal tract signs,and the remaining 13 ones had no significant symptoms of neurologic deficit.The lesion involvement ranged from C4 to L5 vertebrae,with the involvement of lumbar segments in 13 cases,thoracic segments in 6 cases and cervical segments in 2 cases.There were 15 cases that had tuberculosis involving in only a single spinal adnexa and peripheral soft tissue,4 cases in 2 vertebrae and 2 cases in 3 vertebrae.There were 9 cases involving in pedicles,8 cases in vertebral plates and some cases involving in sphenoid process,transverse process or facet joints.The MRI features of spinal adnexal tuberculosis included the tuberculosis-infected bone showing slightly low signals on T1WI while slightly high signals on T2WI,edge enhancement by enhanced scan and edema and abscess of paravertebral soft tissue and intra-and extradural tuberculous abscess displayed clearly by the fat suppression and diffusion weighted imaging sequences of T2WI.Conclusion MRI effectively detects the abnormal signs of bone and soft tissue of spinal adnexal tuberculosis.The MRI findings of spinal adnexal tuberculosis are of characteristics,and MRI can be used as the first choice for imaging examination and differential diagnosis to realize early detection of spinal adnexal tuberculosis.[Chinese Medical Equipment Journal,2025,46(1):55-59]