Objective:To systematically evaluate the psychological experience of financial toxicity in breast cancer patients.Methods:A computer search was conducted in Web of Science, PubMed, Cochrane Library, Embase, CINAHL, China National Knowledge Infrastructure, China Biology Medicine disc, Wanfang, and VIP for qualitative studies on the psychological experience of financial toxicity among breast cancer patients up to April 15, 2023. The Joanna Briggs Institute's quality assessment criteria for qualitative research were used for literature quality evaluation, and an aggregative integration method was applied for data analysis.Results:Ten studies were included, from which 56 distinct themes were extracted. These themes were consolidated into 11 new categories, forming three integrated results: multidimensional negative experiences in coping with financial toxicity, needs and expectations in dealing with financial toxicity, and strategies for dealing with financial toxicity.Conclusions:Breast cancer patients face varying degrees of financial toxicity, negatively impacting their physical and mental health. Healthcare professionals should pay close attention to the characteristics and needs of patients coping with financial toxicity. Continuous assessment of their financial status and implementation of comprehensive intervention strategies and measures through multiple channels and approaches are needed to help reduce the issues of financial toxicity.

Objective:To establish a nomogram model for predicting the risk of sepsis in diabetic foot patients, and to provide reference for clinical prevention and treatment.Methods:The clinical data of 430 patients with diabetic foot who were hospitalized in Chu Hsien-I Memorial Hospital of Tianjin Medical University from January 2022 to March 2023 were reviewed and collected, including age, gender, past medical history, smoking and drinking history, family history, diabetes course, Texas grade of diabetic foot and laboratory indicators within 24 hours after admission. Patients were divided into sepsis group and non-sepsis group according to the presence or absence of sepsis during hospitalization. The differences in clinical data between the two groups were compared. Multivariate Logistic regression analysis was used to screen the influencing factors of sepsis in patients with diabetic foot during hospitalization, and a nomogram predictive model was established. The performance of the prediction model was evaluated by receiver operator characteristic curve (ROC curve), calibration curve and decision curve analysis (DCA). Internal validation was performed by using Bootstrap method.Results:A total of 430 patients were enrolled, among which 90 patients developed sepsis during hospitalization and 340 patients did not. There were statistically significant differences in diabetes course, Texas grade of diabetic foot, white blood cell count (WBC), neutrophil count (NEU), lymphocyte count (LYM), neutrophil to lymphocyte ratio (NLR), hemoglobin (Hb), albumin (Alb), glycosylated hemoglobin (HbA1c), C-reactive protein (CRP), and blood urea nitrogen (BUN) between the two groups. Multivariate Logistic regression analysis showed that diabetes course [odds ratio ( OR) = 2.774, 95% confidence interval (95% CI) was 1.053-7.308, P = 0.039], Texas grade of diabetic foot ( OR = 2.312, 95% CI was 1.014-5.273, P = 0.046), WBC ( OR = 1.160, 95% CI was 1.042-1.291, P = 0.007), HbA1c ( OR = 1.510, 95% CI was 1.278-1.784, P < 0.001), CRP ( OR = 1.007, 95% CI was 1.000-1.014, P = 0.036) were independent risk factors for sepsis in patients with diabetic foot during hospitalization, while Alb was a protective factor ( OR = 0.885, 95% CI was 0.805-0.972, P = 0.011). A nomogram predictive model was constructed based on the above 6 indicators. The ROC curve showed that the area under ROC curve (AUC) of the nomogram predictive model for identifying the sepsis patients was 0.919 (95% CI was 0.889-0.948). The AUC of the nomogram predictive model after internal verification was 0.918 (95% CI was 0.887-0.946). Hosmer-Lemeshow test showed χ2 = 2.978, P = 0.936, indicating that the calibration degree of the predictive model was good. Calibration curve showed that the predicted probability of sepsis was in good agreement with the actual probability. DCA curve showed that the nomogram predictive model had good clinical usefulness. Conclusion:The nomogram predictive model based on the risk factors of diabetes course, Texas grade of diabetic foot, WBC, HbA1c, CRP and Alb has good predictive value for the occurrence of sepsis in patients with diabetic foot during hospitalization, which is helpful for clinical screening of the possibility of diabetic foot patients progressing to sepsis, and timely personalized intervention for different patients.

Objective:To analyze the correlation between body fat distribution measured by quantitative CT (QCT) and body mass index in adults receiving physical examination.Methods:It was a cross-sectional study. From January to December 2021, 3 205 adults undergoing physical examination who met the inclusion criteria and underwent chest CT and QCT examination in the health management discipline of Henan Provincial People′s Hospital were selected as the research objects. The general data were collected; and the subcutaneous fat area, visceral fat area, total abdominal fat area, liver fat content, abdominal obesity and fatty liver detection rate were measured by QCT. According to body mass index, the subjects were divided into normal group (18.5-<24.0 kg/m 2, 1 343 cases), overweight group (24.0-<28.0 kg/m 2, 1 427 cases) and obesity group (≥28.0 kg/m 2, 435 cases). One-way analysis of variance and χ2 test were used to compare the differences of QCT indexes among the three groups. Pearson and Spearman correlation analysis were used to evaluate the correlation between QCT indexes and body mass index. Receiver operating characteristic (ROC) curve was drawn to analyze the diagnostic effect of QCT on obesity and fatty liver. Results:Subcutaneous fat area, visceral fat area, total abdominal fat area, liver fat content, abdominal obesity and fatty liver detection rate in obese group were all significantly higher than those in overweight group and normal group [males, (147.60±46.44) vs (104.33±27.68), (73.46±22.65) cm 2; (297.46±54.70) vs (229.40±53.12), (159.57±49.68) cm 2; (445.06±70.24) vs (333.73±62.91), (233.02±61.87) cm 2; 11.30% (7.90%, 15.55%) vs 8.75% (6.50%, 11.70%), 6.60% (4.80%, 8.70%); 100.0% vs 96.0%, 64.0%; 92.9% vs 86.7%, 73.3%; females, (213.96±48.61) vs (155.85±35.31), (107.24±31.01) cm 2; (185.41±43.88) vs (142.48±41.75), (96.56±36.50) cm 2; (399.37±68.07) vs (298.33±56.86), (203.80±57.53) cm 2; 9.80% (6.90%, 13.30%) vs 7.30% (5.05%, 9.80%), 5.40%(3.50%, 7.20%); 96.4% vs 74.8%, 28.9%; 87.3% vs 75.6%, 56.5%], and were all positively correlated with body mass index (males, r/ rs=0.709, 0.738, 0.831, 0.402, 0.464, 0.225; females, r/ rs=0.798, 0.695, 0.841, 0.416, 0.605, 0.276) (all P<0.001). In both male and female subjects, the detection rates of obesity based on QCT were significantly higher than those based on body mass index (male, 86.9% vs 16.6%; female, 49.3% vs 8.9%), and the detection rates of fatty liver based on QCT were significantly higher than those based on ultrasound (male, 83.6% vs 57.1%; female, 65.2% vs 27.6%) (all P<0.001). ROC curve showed that when the visceral fat area of 142 cm 2 was used as the cut-off value for the diagnosis of obesity in male subjects, the sensitivity and specificity was 100% and 15.8%, respectively; and when the cut-off value of liver fat content 5.0% was used to diagnose fatty liver, the sensitivity and specificity was 88.9% and 25.1%, respectively. When the visceral fat area of 115 cm 2 was set as the cut-off value for the diagnosis of obesity in female subjects, the sensitivity and specificity was 96.4% and 55.3%, respectively; when the liver fat content of 5.0% was set as the cut-off value for the diagnosis of fatty liver, the sensitivity and specificity was 83.7% and 43.2%, respectively. Conclusions:The indexes of abdominal fat and liver fat measured by QCT in adults receiving physical examination are all positively correlated with body mass index. The effect of QCT in the diagnosis of obesity and fatty liver are both better than body mass index and ultrasound.

Objective:To analyze the distribution of body fat with quantitative computed tomography (QCT) in people with normal body mass index (BMI).Methods:A cross-sectional study was conducted in the physical examination population who underwent chest CT and QCT examination in the Department of Health Management, Henan Provincial People′s Hospital from January to December in 2021, and 1 395 physical examination subjects who met the inclusion criteria were selected as the research subjects. The subjects were divided into five groups according to their age. The general data of the subjects were collected. The total abdominal fat area (TFA), visceral fat area (VFA), subcutaneous fat area (SFA), total abdominal muscle area (TMA) and muscle fat content (MFC) in the subjects were measured by QCT. One-way analysis of variance, Welch test and Kruskal-Wallis test were used to compare the above QCT measurement indexes between the two genders among different age groups with normal BMI. Pearson correlation analysis was used to analyze the correlation between VFA and sarcopenia indexes. Multivariate linear regression was used to analyze the relationship between VFA and linear correlation variables in the related indicators of sarcopenia.Results:There were significant differences in TFA, VFA, TMA and SMI among different age groups in subjects with normal BMI (all P<0.05). Pearson correlation analysis showed that VFA was negatively correlated with TMA in some age groups (male: 18-39 years group: r=-0.351; 40-49 years group: r=-0.278; 60-69 years group: r=-0.245; female:40-49 years group: r=-0.251; 50-59 years group: r=-0.270;≥70 years group: r=-0.391; all P<0.01); it was negatively correlated with SMI (male: 18-39 years group: r=-0.352; 40-49 years group: r=-0.340; 50-59 years group: r=-0.266; 60-69 years group: r=-0.316; female: 40-49 years group: r=-0.240; 50-59 years group: r=-0.284; all P<0.001); it was positively correlated with MFC (male: 18-39 years group: r=0.342; 40-49 years group: r=0.291; female: 50-59 years group: r=0.133; 60-69 years group: r=0.284; all P<0.05). Multivariate linear regression analysis showed that VFA was independently and negatively correlated with SMI in both men and women after adjusting for age interference factors (male B=-1.881, t=-6.025, P<0.001; female B=-0.603, t=-2.887, P=0.004), and it was independently positively correlated with MFC (male B=1.230, t=4.271, P<0.001;female B=0.893, t=3.836, P<0.001). There was an independent negative correlation between VFA and TMA in male subjects ( B=0.263, t=2.478, P=0.013). Conclusions:VFA is correlated with TMA, SMI and MFC in people with normal BMI. Regardless of gender, SMI has a negative effect on VFA, and MFC has a positive effect on VFA.

Objective To study the clinical characteristics and related factors affecting the severity of acute tinnitus in patients.Methods A retrospective analysis was conducted on the data of 319 patients with acute tinni-tus.All patients had detailed case history,including basic patient information,tinnitus location,course of disease,acoustic characteristics of tinnitus,hearing loss,combined headache,dizziness,aural fallness,earache and other symptoms,as well as accompanying clinical diseases.All patients completed the tinnitus handicap inventory(THI),generalized anxiety disorder(GAD-7),patient health questionnaire(PHQ-9),pittsburgh sleep quality index(PSQI),hyperacusis questionnaire(HQ),type D personality scale-14(DS-14),etc.The mild tinnitus group was determined based on a THI score of ≤36.The moderate tinnitus group was determined based on a THI score of 38～56.The severe to extremely severe tinnitus group was determinded based on THI 56～100.THI grouping was used as the dependent variable and the above factors as independent variables.The correlation between each factor and the severity of acute tinnitus was analyzed using ordered multinomial logistic regression.Results Among 319 patients with acute tinnitus,158(49.5％)were in the mild tinnitus group,and 72(22.6％)were in the moderate tinnitus group,and 89(27.9％)were in severe to extremely severe tinnitus group.Ordered multinomial logistic re-gression analysis found that hyperacusis(OR=3.921),anxiety(OR=2.495),depression(OR=2.921),and D-type personality(OR=0.349)were associated with the severity of acute tinnitus(P＜0.05),with more serere tin-nitus in these patients.Conclusion Hyperacusis,anxiety,depression,and D-type personality may be factors that affect the severity of acute tinnitus,so high attention should be paid when treating patients with acute tinnitus.

Objective To explore the value of machine learning(ML)models based on non-contrast CT(NCCT)radiomics features for predicting the severity of acute phase traumatic brain injury(TBI).Methods Totally 600 TBI patients were retrospectively collected as observation group,other 65 TBI patients were taken as external validation set,while 50 TBI patients were prospectively enrolled as prospective validation set.Patients in observation group were divided into high-risk subgroup(n=240)and low-risk subgroup(n=360)according to Glasgow outcome scale(GOS)at discharge.The severity of acute phase TBI in observation group was assessed by doctor A and B with the same criteria,then an artificial model was established based on clinical and NCCT data at the time of first diagnosis using logistic regression(LR)method for predicting the severity of acute phase TBI.Patients in observation group were divided into training set(n=420,including 168 in high-risk subgroup and 252 in low-risk subgroup)and test set(n=180,including 72 in high-risk subgroup and 108 in low-risk subgroup)at the ratio of 7∶3.Based on NCCT of training set,radiomics features were extracted and selected,and LR,support vector machine(SVM),random forest(RF)and K-nearest neighbor(KNN)were used to establish 4 ML models.The efficacies of the above models were validated in test set,external validation set(including 34 cases of high-risk and 31 cases of low-risk TBI)and prospective validation set(including 21 cases of high-risk and 29 cases of low-risk TBI),respectively.Results The area under the curve(AUC)of doctor A and B for evaluating the severity of acute phase TBI in observation group was 0.606 and 0.771,respectively,of artificial model was 0.824.Based on NCCT in training set,6 optimal radiomics features were selected to construct LR,SVM,RF and KNN ML models,with AUC of 0.983,0.971,0.970 and 0.984 in test set,respectively,while the AUC of artificial model was 0.708.The AUC of LR,SVM,RF,KNN ML models and artificial model in external validation set was 0.879,0.881,0.984,0.863 and 0.733,while in prospective validation set was 0.984,0.873,0.982,0.897 and 0.704,respectively.Conclusion ML models based on CT radiomics could effectively predict the severity of acute phase TBI.

Objective To explore the effects and mechanism of Baitouweng Decoction in intestinal mucosal healing in mice with ulcerative colitis(UC)based on RIPK1/RIPK3/MLKL signaling pathway.Methods Totally 30 C57BL/6 male mice were randomly divided into control group,model group,Baitouweng Decoction group,infliximab group and combination group(Baitouweng Decoction+infliximab),with 6 mice in each group.A mouse model of UC was established by free administration of 3.5%sodium gluconate sulfate solution for 7 days.After modeling,Baitouweng Decoction group was given 8 g/kg Baitouweng Decoction solution by gavage daily,while the infliximab group was given 5 mg/kg infliximab intraperitoneal injection,the combination group was given synchronous gastric and intraperitoneal injection,while the control group and model group were given equal volume of normal saline by gavage for 7 consecutive days.The body mass of mice was recorded daily,fecal characteristics were observed,and disease activity index(DAI)score was performed,colon length was measured after intervention,ELISA was used to detect the contents of serum interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α),RT-qPCR was used to detect mRNA expressions of RIPK1,RIPK3 and MLKL in colon tissue,Western blot and immunofluorescence staining were used to detect the expressions of RIPK1,RIPK3 and MLKL protein in colon tissue.Results Compared with the control group,the model group mice showed a decrease in body mass(P<0.01),an increase in DAI score(P<0.01),a shortened colon length(P<0.01),and an increase in serum IL-6 and TNF-α content(P<0.01);colonic mucosal was destructed,with disappearance of crypts and glandular structures,extensive infiltration of inflammatory cells,and increased pathological score of colon tissue(P<0.01);the mRNA and protein expressions of RIPK1,RIPK3 and MLKL in colon tissue increased(P<0.01,P<0.05).Compared with the model group,the body mass of mice in each treatment group increased(P<0.01),and the DAI score decreased(P<0.01),colon length increased(P<0.01),and the contents of serum IL-6 and TNF-α decreased(P<0.05,P<0.01);the destruction of the colonic mucosal barrier was reduced,the pathological score of colon tissue was reduced(P<0.05);the expressions of RIPK1,RIPK3 and MLKL mRNA and protein in colon tissue decreased(P<0.05,P<0.01).Conclusion Baitouweng Decoction can alleviate intestinal mucosal damage and inflammation in UC mice,and its mechanism may be related to the inhibition of the RIPK1/RIPK3/MLKL signaling pathway.

Objective The long-term epidemiological and etiological characteristics of hand, foot and mouth disease (HFMD) in Huai’an, Jiangsu were analyzed to provide scientific evidence for the prevention of HFMD. Methods The data of HFMD reports, etiological diagnosis and in Huai’an from 2009 to 2022 were described and analyzed. Results A total of 78 535 cases were reported from 2009 to 2022 , with 14-year average annual incidence rate of 114.71/100 000. Before 2020, the incidence rate of HFMD in Huai’an showed the epidemic intensity increased every other year on the whole, and the average annual incidence rate during the COVID-19 pandemic (2020-2022) (55.69/100 000) was significantly lower than that in previous years (2009-2019) (129.95/100 000). The joinpoint regression analysis showed that the best fitting model from 2009 to 2022 had no joinpoints, APC=AAPC=-1.24%. The overall trend showed a monotonously decreasing trend, but the trend was not statistically significant. The male-to-female distribution ratio was 1.53:1, and the age distribution was mainly under 5 years old, especially in scattered children. The epidemic season was from April to July. The results of etiological surveillance showed that the co-epidemic of Coxsackievirus A16 (CV-A16) and Enterovirus A71 (EV-A71) during the early stages had changed to the co-epidemic of CV-A16 and CV-A6 in the current period. Conclusion The burden of HFMD in Huai’an was large, and the epidemic intensity increased every other year was affected by the COVID-19 pandemic. The epidemiological features after the COVID-19 pandemic should be further monitored.

Epilepsy is a kind of brain dysfunction syndrome characterized by paroxysmal,transient,repetitive and rigid characteristics caused by abnormal discharge of highly synchronized neurons in the brain.Epilepsy is often accompanied by cognitive dysfunction.At present,anti-seizure medications are the most important methods of clinical treatment.Most of the traditional anti-seizure medications can cause cognitive dysfunction,and the influence of new anti-seizure medications on cognitive function is not completely clear.This paper reviews the influence of new anti-seizure medications on cognitive function and the possible related mechanisms of action based on relevant literature at home and abroad.It is expected that clinicians should pay attention to cognitive function in the process of diagnosis and treatment of epilepsy,and help clinicians realize the influence of anti-seizure medications on cognitive function,and rationally choose anti-seizure medications for patients.

Objective To explore the content and the psychometric properties of assessment tools used for evaluating functioning and adaptive behavior in school-age children with intellectual and developmental disabilities within educational settings. Methods The most used assessment tools included Vineland Adaptive Behavior Scales(VABS),Supports Intensity Scale for Children(SIS-C),Strengths and Difficulties Questionnaire(SDQ)and Repetitive Behavior Scale-Revised(RBS-R),for assessing functioning and adaptive behavior children with intellectual and developmental disabili-ties.Employing the framework and methods of the International Classification of Functioning,Disability,and Health(ICF),this research encoded and categorized the assessment dimensions and items of the four tools,and explored their psychometric properties. Results VABS's assessment content was solely focused on activities and participation,including speaking(d330),con-versation(d350),toileting(d530),eating(d550),drinking(d560),basic interpersonal interactions(d710),com-plex interpersonal interactions(d720),changing and maintaining body positions(d410-d429),carrying,moving and handing objects(d430-d449),and walking and moving(d450-d469).SIS-C assessed activities and participa-tion,and environmental factors,including washing oneself(d510),caring for body parts(d520),community life(d910),using transportation(d470),school education(d820),basic learning(d130-d159),looking after one's health(d570),basic interpersonal interactions(d710),and products and technology for education(e130).SDQ fo-cused on body functions,and activities and participation,including emotional functions(b152),global psychoso-cial functions(b122),attention functions(b140),and basic interpersonal interactions(d710).RBS-R focused on body functions,and activities and participation,including involuntary movement reaction functions(b755),invol-untary movement functions(b765),looking after one's health(d570),energy and drive functions(b130),under-taking a single task(d210),carrying out daily routine(d230),attention functions(b140),and handling stress and other psychological demands(d240).VABS was characterized by good specificity and excellent sensitivity.SIS-C demonstrated very good internal consistency,reliability and validity.SDQ was good in internal consistency,with excellent credibility and validity.RBS-R showed good internal consistency,reliability and validity. Conclusion SDQ and RBS-R cover both body functions,and activities and participation,SIS-C covers activity and par-ticipation,and environmental factors,while VABS solely assesses activities and participation.In terms of body functions,the assessment items primarily focus on mental functions(b130-b189)and movement functions(b750-b799).For activities and participation,the tools assess content across eight domains of functioning.Regarding en-vironmental factors,the assessment content mainly includes products and technology for education(e130),as well as design,construction and building products and technology of buildings for public use(e150).VABS,SIS-C,SDQ,and RBS-R are all norm-referenced measures,with moderate to excellent internal consistency,and good to excellent reliability and validity.