Childhood primary renal tubular diseases are chronic kidney diseases characterized by impaired renal tubular reabsorption. Primary renal tubular disease has diverse clinical manifestations and lacks of specificity. Laboratory tests are limited，making it prone to missed diagnosis and misdiagnosis. Based on the current knowledge of renal tubular diseases，authors propose early warning signals of renal tubular diseases such as family history of primary tubular diseases，unexplained polyhydramnios during pregnancy，polydipsia，polyuria，delayed growth and development or rickets，decreased muscle strength and tone，unexplained electrolyte disturbance，hyperuricemia，acid-base disturbance，positive urine sugar test，renal tubular proteinuria，urinary imaging examination suggesting kidney stones，calcium deposition，renal cysts and early onset of eye，ear，joint and neuron injury.Meanwhile，some universal management strategies for primary renal tubular disease are proposed，emphasizing the importance of multidisciplinary collaboration，genetic testing and individualized intervention to improve the long-term prognosis of childhood primary renal tubular diseases.

Objective:To explore the expression and clinical significance of long non-coding RNA colorectal neoplasia differentially expressed (lncRNA CRNDE), microRNA-181a-5p (miR-181a-5p) and autophagy related 5 (ATG5) in the peripheral blood of patients with gouty arthritis (GA) patients.Methods:The clinical data, laboratory parameters and peripheral blood samples were collected from 40 patients with acute gout (AG), 40 patients with intermittent gout (IG) and 50 healthy subjects (HC). The expression levels of lncRNA CRNDE, miR-181a-5p and ATG5 mRNA were detected by real-time fluorescence quantification (RT-qPCR) and the expression level of ATG5 protein was detected by Western-blot. The expression levels of lncRNA CRNDE, miR-181a-5p, ATG5 mRNA were compared among the three groups and correlated with clinical indices, and a subject operating characteristic curve (ROC) was constructed to assess the value of lncRNA CRNDE, miR-181a-5p, ATG5 mRNA in the diagnosis of gout. Measurements conforming to normal distribution were analyzed using t test or ANOVA, data with non-normal distribution was analyzed using Mann-Whitney U test or Kruskal-Wallis H test, correlation analysis between variables was analyzed using Spearman's analysis, and the diagnostic value of each indicator was analyzed using ROC curve. Results:① The differences in the expression of lncRNA CRNDE, miR-181a-5p, and ATG5 mRNA between the three groups were statistically significant ( H=32.12, 57.73, 68.32, all P<0.001). Among them, lncRNA CRNDE expression level in the AG group was significantly higher than that in the IG group and healthy control group [61.95(11.39, 108.30)×10 -3, 25.71(15.40, 38.40)×10 -3, 13.80(3.97, 23.99)×10 -3; Z=-3.24, P=0.001; Z=-5.03, P<0.001], and the expression level of IG group was higher than that of healthy control group( Z=-3.56, P<0.001); miR-181a-5p and ATG5 mRNA expression levels in AG group were significantly lower than those in IG group and healthy control group [miR-181a-5p: 39.81(31.22, 69.38)×10 -3, 60.74(44.19, 90.35)×10 -3, 121.30(101.50, 316.90)×10 -3; Z=-3.01, P=0.030; Z=-6.93, P<0.001. ATG5 mRNA: 4.52(2.31, 26.63)×10 -3, 43.63(13.72, 102.70)×10 -3, 153.90(66.62, 365.80)×10 -3; Z=-5.47, -7.36, all P<0.001)], which were expressed at lower levels in the IG group than in the healthy controls ( Z=-5.25, -4.47, all P<0.001). The difference of ATG5 protein expression level among the three groups expressed was statistically significant ( F=6.24, P=0.030), and the AG group was higher than the healthy control group, and the difference was statistically significant [(0.96±0.13) vs.(0.61±0.04), t=4.25, P=0.013], but the difference between the IG group (0.78±0.15) and the AG group and the HC group was not statistically significant ( t=1.51, P=0.206; t=1.85, P=0138). ② Spearman correlation analysis showed that lncRNA CRNDE was negatively correlated with the expression levels of miR-181a-5p and ATG5 mRNA in gout patients ( r=-0.49, P<0.001; r=-0.35, P=0.002); miR-181a-5p was positively correlated with ATG5 mRNA expression levels ( r=0.64, P<0.001); lncRNA CRNDE expression level was positively correlated with ESR and WBC ( r=0.49, P<0.001; r=0.43, P=0.001); miR-181a-5p expression level was negatively correlated with ESR and WBC ( r=-0.29, P=0.009; r=-0.35, P=0.002), and ATG5 mRNA expression levels were negatively correlated with ESR, WBC, and GR ( r=-0.26, P=0.021; r=-0.26, P=0.024; r=-0.27, P=0.021). In the AG group lncRNA CRNDE was positively correlated with ESR and WBC ( r=0.36, P=0.022; r=0.36, P=0.026) and miR-181a-5p was negatively correlated with WBC ( r=-0.34, P=0.038) ③ ROC curve showed that the areas under ROC curve of lncRNA CRNDE, miR-181a-5p and ATG5 mRNA expression levels to predict gout were 0.764, 0.875 and 0.864, respectively. The area under ROC curve of gout predicted by the three combined was 0.928. Conclusion:lncRNA CRNDE, miR-181a-5p, and ATG5 may be involved in the pathoge-nesis of primary gouty arthritis, and are potential biological parameters for studying the pathogenesis of gout.

Objective:To investigate the expression of N6-methyladenosine(m6A) modification-related genes and their possible roles in peripheral blood mononuclear cells (PBMCs) of patients with primary gouty arthritis (GA).Methods:Forty-five patients each with acute gout (AG), intermittent gout (IG), and age-and gender-matched healthy controls (HC) were collected from the outpatient clinic of the Department of Rheumatology and Immunology of the Affiliated Hospital of Chuanbei Medical College between October and December of 2023. The expression levels of m6A modification-related genes (METTL3、METTL14、WTAP、FTO、ALKBH5、IGF2BP2、IGF2BP3、YTHDF1、YTHDC2) in PBMCs among the 3 groups were detected by RT-qPCR and correlation analysis with clinical indicators was performed. Measurements conforming to normal distribution were analyzed using ANOVA or t-tests, and data were analyzed using the Kruskal-Wallis H-test and Mann-Whitney U-test for data that is not-normaly distributed. The value of m6A modification-related genes for the diagnosis of GA was evaluated using subject characterization curve ROC. Results:①There were statistically significant differences in the expression of IGF2BP2 ( Z=-3.59, P<0.001)、WTAP ( Z=-5.25, P<0.001)、METTL14 ( Z=-3.62, P<0.001)、YTHDF1 ( Z=-2.12, P=0.034)and YTHDC2 ( Z=-2.00, P=0.045) in the disease group and the normal control group. Among them, the expression of IGF2BP2 in the GA group [28.08 (17.99, 47.06)×10 -4] was significantly higher than that in the HC group [19.23 (12.90, 25.78)×10 -4], and the expressions of WTAP、METTL14、YTHDF1 and YTHDC2 in the GA group [298.61 (213.61, 377.80)×10 -4, 9.94 (6.43, 13.46)×10 -4, 52.63 (28.22, 72.77)×10 -4, 40.24 (20.74, 73.32)×10 -4] were significantly lower than those in the HC group [398.45(339.88, 454.89)×10 -4, 13.27(11.07, 15.85)×10 -4, 64.43(43.61, 87.10)×10 -4, 53.11(36.37, 79.28)×10 -4]. Further subgroup analysis revealed statistically significant differences in the expression of IGF2BP2、WTAP、METTL14、YTHDF1 and YTHDC2 among the 3 groups ( H=19.62、31.73、13.14、16.64、28.90, all P≤0.001). The expressions of WTAP and METTL14 in the AG group [311.13(234.96, 426.67)×10 -4, Z=-3.27, P=0.001; 9.64 (5.21, 15.21)×10 -4, Z=-2.71, P=0.008] and IG group [272.27 (203.29, 347.95)×10 -4, Z=-5.78, P<0.001; 10.40(6.88, 12.88)×10 -4, Z=-3.54, P=0.003] were lower than those in the HC group [398.45 (339.88, 454.89)×10 -4, 13.27(11.07, 15.85)×10 -4]. However, there was no significant difference between AG and IG group ( P>0.05). Both YTHDF1 and YTHDC2 were significantly lower in the AG group [38.10(16.19, 56.78)×10 -4, 24.31 (14.35, 42.77)×10 -4] than those in the IG group [64.13 (48.28, 74.40)×10 -4(Z=-3.54, P<0.001, 65.49 (39.89, 91.23)×10 -4(Z=-4.96, P<0.001)] and HC group [64.43 (43.61, 86.92)×10 -4(Z=-3.51, P<0.001), 53.11 (36.37, 79.28)×10 -4(Z=-4.25, P<0.001)]. But there was no statistically significant difference between IG and HC groups ( P>0.05); IGF2BP2 was significantly lower in the AG group [25.32(16.40, 40.43)×10 -4, Z=-2.46, P=0.014] and HC group [19.23 (12.90, 25.78)×10 -4, Z=-4.54, P<0.001] than in the IG group [31.10(22.60, 49.58)×10 -4], but the comparison between AG and HC showed no statistically significant difference( P>0.05). ②Spearman correlation analysis showed that in GA patients, the expression of IGF2BP2、METTL14 and YTHDF1 was positively correlated with plasma glucose、blood uric acid(sUA) and total cholesterol level respectively ( r=0.22, P=0.037; r=0.38, P=0.003; r=0.23, P=0.034), and WTAP was negatively correlated with GLU ( r=-0.25, P=0.020). ③The ROC curve for the joint prediction of the five differential genes showed that the 95% CI for area under the curve in GA was 0.90 (0.84, 0.95). Conclusion:The m6A modification-related genes are abnormally expressed in GA and are correlated with clinical indicators such as GLU and UA, which are hypothesized to be involved in the pathogenesis of GA and have a certain reference value for the evaluation of metabolism in GA patients.

Objective:To evaluate the effect of preoperative mild cognitive impairment (MCI) on the potency of sevoflurane in inhibiting body movement responses during skin incision in aged female patients.Methods:This was a prospective study. Female American Society of Anesthesiologists Physical Status classification Ⅰ or Ⅱ patients, aged 60-75 yr, with body mass index of 18.5-23.9 kg/m 2, scheduled to undergo radical mastectomy between January 2022 and March 2023 in our hospital, were selected. The patient′s cognitive function was assessed using Mini-Mental State Examination and Montreal Cognitive Assessment. The patients were divided into 2 groups based on whether they had MCI or not before operation: normal group (group N) and MCI group (group M). General anesthesia was induced by inhaling 8% sevoflurane, and the laryngeal mask airway was inserted after they lost consciousness and their jaws relaxed. According to the Dixon′s up-and-down method, the end-tidal concentration of sevoflurane in the first patient was set at 2%. If the body movement response occurred, the concentration was increased by 2% in the next patient, otherwise the concentration was decreased by 2% in the next patient. The MAC and 95% confidence interval ( CI) of sevoflurane were calculated using the probability regression method. Results:The minimum alveolar concentration of sevoflurane was 1.60% (95% CI 1.48% -1.70%) in group N and 1.38% (95% CI 1.25%-1.49%) in group M, and there was statistically significant difference ( P<0.05). Conclusions:Preoperative MCI can increase the potency of sevoflurane in inhibiting body movement responses during skin incision in aged female patients.

Objective:To study the distribution of drug resistance genes and virulence genes in multidrug-resistant Salmonella typhimurium strains.Methods:A total of 96 strains of Salmonella typhimurium were collected，and drug sensitivity tests were performed to evaluate the drug resistance and multidrug-resistance of Salmonella typhimurium.Multidrug-resistant Salmonella typhimurium strains were selected to conducted whole genome sequencing，and the distribution of drug resistance genes and virulence genes in the strain were analyzed.Results:Salmonella typhimurium strains had the highest resistance rates to ampicillin and ampicillin/sulbactam，with 89.58% and 76.04%，respectively.Followed by trimethoprim/sulfamethoxazole，ceftriaxone，and aztreonam，with 47.92%，38.54% and 33.33%，respectively，and low resistance rates to ciprofloxacin and levofloxacin，with 8.33% and 4.17%，respectively.Ninety-six strains were all sensitive to carbapenem antibiotics and piperacillin/tazobactam.Fifty-seven strains（59.38%）of Salmonella typhimurium showed multidrug-resistance.Resistance genes were detected in all 57 multidrug-resistant Salmonella typhimurium strains,with higher carrier rates of 98.25%,77.19%,and 59.65% for aac(6')-Iaa,aadA22,and blaTEM-1B,respectively.The multidrug-resistant Salmonella typhimurium strains had the highest carrier rates for invA，sipA，sseL，and sopB.Conclusion:Multidrug-resistant Salmonella typhimurium strains have a high incidence and a high carrier rate for multiple drug resistance genes and virulence genes.The monitoring and prevention of Salmonella typhimurium should be strengthened in the clinic in order to reduce the spreading epidemic of multidrug-resistant strains.

Objective:To investigate the expression and clinical significance of decoy receptor 3 (DcR3) and its signal pathway-related molecules in PBMCs of patients with ankylosing spondylitis (AS).Methods:Peripheral blood samples, clinical data and laboratory test results were collected from 100 patients with ankylosing spondylitis [50 patients with AS activity (ASA), 50 patients with AS stability (ASS)], 30 patients with osteoarthritis and 30 patients with gouty arthritis (as disease control group), and 60 healthy controls (HC). The mRNA expression levels of DcR3 and its signal pathway related genes (DR3, TL1A, Fas, FasL, LIGHT, LIGHTR, LTβR) were measured by real-time fluorescence quantitative polymerase chain reaction. Measurement data among the three groups in normal distribution were analyzed by t test or one-way analysis of variance, pairwise comparisons using LSD- t test, non-normal distribution data were analyzed by Mann-Whitney test or Kruskal-Wallis H test, χ2 test was used for correlation analysis of categorical variables. Correlation analysis between variables were analyzed using Spearman correlation analysis. Results:① By comparing the AS group, disease control group and HC group, the expression levels of DcR3 mRNA and DR3 mRNA in the AS group were lower than those in disease control group and HC group, and DcR3 mRNA and DR3 mRNA in disease control group were lower than those in the HC group {DcR3mRNA: [6.21 (3.89, 10.70)]×10 -4vs [9.51 (5.89, 16.65)]×10 -4vs [17.81 (11.27, 24.20)]×10 -4, H=55.28, P<0.001; DR3 mRNA: [41.05 (24.09, 66.95)]×10 -4vs [58.28 (28.41, 94.38)]×10 -4vs [94.79 (54.07, 144.51)]×10 -4, H=37.10, P<0.001}. The expression level of TL1A mRNA in the AS group was higher than that in disease control group {[14.71(4.91, 42.22)]×10 -4vs [4.00(1.07, 16.60)]×10 -4vs [7.70 (3.52, 27.83)]×10 -4, H=17.71, P<0.001}; The expression level of Fas mRNA in AS group and disease control group was lower than that in HC group {[20.99(4.63, 62.89)]×10 -4vs [23.97(15.82, 38.99)]×10 -4vs [78.45 (27.32, 146.46)]×10 -4, H=31.17, P<0.001}. The expression level of FasL mRNA in AS group was higher than that in disease control group and HC group {[42.87(6.57, 91.21)]×10 -4vs [5.45(2.83, 10.32)]×10 -4vs [6.88 (4.57, 23.79)]×10 -4, H=46.42, P<0.001}. The expression level of LIGHTR mRNA in AS group was lower than that in disease control group {[52.66 (7.20, 143.21)]×10 -4vs [98.80 (53.11, 166.24)]×10 -4vs [63.47(40.85, 138.07)]×10 -4, H=11.96, P<0.001}. There were no significant differences in LIGHT mRNA and LTβR mRNA among all groups ( H=0.86, P>0.05; H=3.18, P>0.05). ②The expression levels of DcR3 mRNA, DR3 mRNA and Fas mRNA in ASA group and ASS group were lower than those in HC group. DcR3 mRNA in ASA group was higher than that in ASS group, and DR3 mRNA in ASA group was lower than that in ASS group {DcR3 mRNA: [7.28 (4.92, 16.56)]×10 -4vs [4.59 (2.49, 7.03)]×10 -4vs [17.81 (11.27, 24.20)]×10 -4, H=62.63, P<0.001; DR3 mRNA: [30.93(16.18, 66.66)]×10 -4vs [47.17(29.91, 67.40)]×10 -4vs [94.79(54.07, 144.51)]×10 -4, H=41.48, P<0.001; Fas mRNA: [20.04(3.29, 62.30)]×10 -4vs [22.49(5.63, 64.79)]×10 -4vs [78.45(27.32, 146.46)]×10 -4, H=23.54, P<0.001}. The expression levels of TL1A mRNA and LTβR mRNA in the ASA group were higher than those in the ASS group and the HC group {TL1A mRNA: [32.36(10.09, 97.84)]×10 -4vs [9.98(1.29, 21.63)]×10 -4vs [7.70(3.52,27.83)]×10 -4, H=21.14, P<0.001; LTβR mRNA: [6.13(2.16,20.06)×10 -4vs [2.13(0.53,8.04)]×10 -4vs [2.72 (1.24,5.73)]×10 -4, H=12.86, P<0.001}. The expression level of FasL mRNA in the ASA group and the ASS group was higher than that in the HC group {[60.70 (8.16, 106.16)]×10 -4vs [30.14 (5.37, 78.40)]×10 -4vs [6.88 (4.57, 23.79)]×10 -4, H=18.99, P<0.001}. The expression level of LIGHTR mRNA in ASS group was lower than that in HC group {[49.79(10.75, 168.48)]×10 -4vs [15.92(3.27, 105.91)]×10 -4vs [63.47(40.85, 138.07)]×10 -4, H=11.80, P<0.001]. There was no significant difference in LIGHT mRNA among all groups ( H=4.15, P>0.05). ③Spearman correlation analysis showed that DcR3 level was positively correlated with BASDAI score and hsCRP in AS patients ( r=0.52, P<0.001; r=0.35, P<0.01), and DR3 level was negatively correlated with BASDAI score, ESR and hsCRP level ( r=-0.28, P<0.001; r=-0.25, P<0.001; r=-0.31, P<0.001). TL1A was positively correlated with BASDAI score, ESR and hsCRP level ( r=0.23, P=0.046; r=0.26, P=0.015; r=0.25, P=0.017). Conclusion:DcR3 and its signal pathway-related molecules are differentially expressed in PBMCs of patients with AS, suggesting that they may participate in the occurrence and development of AS.

Objective:To analyze the disease characteristics and hospitalization burden of elderly inpatients with cerebrovascular disease, so as to provide basis for disease prevention, diagnosis, treatment and rehabilitation of elderly patients with multiple chronic conditions.Methods:The data of the first page of medical records of elderly inpatients with cerebrovascular disease from 2015 to 2020 in a comprehensive tertiary hospital in Jiangsu Province were retrospectively collected.Descriptive analysis, variance analysis and multiple linear regression analysis were carried out for the research objects using SPSS statistics and Python complex network methods.Results:A total of 14 657 elderly inpatients with cerebrovascular disease were included.From 2015 to 2020, the number of hospitalizations increased from 1 268 to 4 733, the average number of hospitalizations increased from 2.0 to 2.9, the average length of stay decreased from 11.9 days to 9.1 days, and the average number of illnesses increased from 1.9 to 4.9.The five most common comorbidities associated with cerebrovascular diseases were hypertension, diabetes, ischemic heart disease, other types of heart disease and other respiratory diseases.From 2015 to 2020, the average hospitalization costs of elderly cerebrovascular inpatients decreased from 20588.1 Chinese yuan(CYN)to 15580.9 Chinese yuan(CYN). The hospitalization cost was mainly composed of drug cost(46.6%), diagnosis cost(28.2%)and treatment cost(20.2%). There were significant differences in the average hospitalization expenses among patients with different gender, age, number of admissions, length of stay and number of diseases( P<0.05 for all). Gender, age, number of hospitalizations and length of stay had an impact on hospitalization expenses. Conclusions:The number of inpatients, comorbidities, and hospitalized times of elderly patients with cerebrovascular disease showed an increasing trend, while the number of hospitalization days and the average hospitalization cost showed a downward trend.Comorbidities associated with cerebrovascular diseases should be one of the concerns of chronic disease management in the elderly.

OBJECTIVE To compare characteristic chromatogram and the contents of multiple indicator components of Morus alba decoction powder and decoction at different decoction time， and to provide experimental basis for the development of M. alba decoction. METHODS Taking decoction powder and decoction at different decoction time as subject， HPLC characteristic chromatogram of 2 kinds of samples were established with Similarity Evaluation Software System of TCM Chromatographic Fingerprint （2012 version）， and similarity evaluation was performed. The contents of mulberroside A， geniposide， berberine， baicalin， quercetin and luteolin in decoction powder and decoction were determined by HPLC. The contents of each indicator component and the change of total content were as the evaluation indexes to compare the difference between the two substances during decoction. RESULTS The similarities of characteristic chromatogram of the two substances ranged from 0.943 to 1.000 and 0.975 to 0.998 at different decoction time， respectively. Six indicator components of the decoction powder dissolved faster and had higher contents. The contents of each indicator component in the decoction powder when decocting at 20 minutes was 1.1-1.5 times of the decoction when decocting at 50 min， and the total content in the decoction powder was 1.2 times of the decoction. CONCLUSIONS Compared with decoction， M. alba decoction powder has the advantages of shortening the decoction time and saving traditional Chinese medicine resources. The results of this study lay a research foundation for “Zungu” to develop its preparation.

Objective:To investigate the value of number of negative lymph nodes (NLNs) in predicting the prognosis of patients with esophageal cancer after neoadjuvant therapy and the construction of nomogram prodiction model.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 924 patients with esophageal cancer after neoadjuvant therapy uploaded to the Surveillance, Epidemiology, and End Results Database of the National Cancer Institute from 2004 to 2015 were collected. There were 1 624 males and 300 females, aged 63 (range, 23?85)years. All 1 924 patients were randomly divided into the training dataset of 1 348 cases and the validation dataset of 576 cases with a ratio of 7:3 based on random number method in the R software (3.6.2 version). The training dataset was used to constructed the nomogram predic-tion model, and the validation dataset was used to validate the performance of the nomogrram prediction model. The optimal cutoff values of number of NLNs and number of examined lymph nodes (ELNs) were 8, 14 and 10, 14, respectively, determined by the X-tile software (3.6.1 version), and then data of NLNs and ELNs were converted into classification variables. Observation indicators: (1) clinicopathological characteristics of patients in the training dataset and the validation dataset; (2) survival of patients in the training dataset and the validation dataset; (3) prognostic factors analysis of patients in the training dataset; (4) survival of patients in subgroup of the training dataset; (5) prognostic factors analysis in subgroup of the training dataset; (6) construction of nomogram prediction model and calibration curve. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the t test. Measurement data with skewed distribution were represented as M(range), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test. The Kaplan-Meier method was used to draw survival curve and Log-Rank test was used for survival analysis. The COX proportional hazard model was used for univariate and multivariate analyses. Based on the results of multivariate analysis, the nomogram prediction model was constructed. The prediction efficacy of nomogram prediction model was evaluated using the area under curve (AUC) of the receiver operating characteristic curve and the Harrell′s c index. Errors of the nomogram prediction model in predicting survival of patients for the training dataset and the validation dataset were evaluated using the calibration curve. Results:(1) Clinicopathological characteristics of patients in the training dataset and the validation dataset. There was no significant difference in clinicopatholo-gical characteristics between the 1 348 patients of the training dataset and the 576 patients of the validation dataset ( P>0.05). (2) Survival of patients in the training dataset and the validation dataset. All 1 924 patients were followed up for 50(range, 3?140)months, with 3-year and 5-year cumulative survival rate as 59.4% and 49.5%, respectively. The 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 in the training dataset was 46.7%, 62.0% and 66.0%, respectively, and the 5-year cumulative survival rate was 38.1%, 52.1% and 59.7%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=33.70, P<0.05). The 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 in the validation dataset was 51.1%, 54.9% and 71.2%, respectively, and the 5-year cumulative survival rate was 39.3%, 42.5% and 55.7%, respectively. There was a significant difference in the survival of these patients in the validation dataset ( χ2=14.49, P<0.05). The 3-year cumulative survival rate of patients with number of ELNs as <10, 10?14 and >14 in the training dataset was 53.9%, 60.0% and 62.7%, respectively, and the 5-year cumulative survival rate was 44.7%, 49.1% and 56.9%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=9.88, P<0.05). The 3-year cumulative survival rate of patients with number of ELNs as <10, 10?14 and >14 in the validation dataset was 56.2%, 47.9% and 69.3%, respectively, and the 5-year cumula-tive survival rate was 44.9%, 38.4% and 51.9%, respectively. There was a significant difference in the survival of these patients in the validation dataset ( χ2=9.30, P<0.05). (3) Prognostic factors analysis of patients in the training dataset. Results of multivariate analysis showed that gender, neoadjuvant pathological (yp) T staging, ypN staging (stage N1, stage N2, stage N3) and number of NLNs (8?14, >14) were independent influencing factors for the prognosis of patients with esophageal cancer after neoadjuvant therapy ( hazard ratio=0.65, 1.44, 1.96, 2.41, 4.12, 0.69, 0.56, 95% confidence interval as 0.49?0.87, 1.17?1.78, 1.59?2.42, 1.84?3.14, 2.89?5.88, 0.56?0.86, 0.45?0.70, P<0.05). (4) Survival of patients in subgroup of the training dataset. Of the patients with NLNs in the training dataset, the 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 was 61.1%, 71.6% and 76.8%, respectively, and the 5-year cumulative survival rate was 50.7%, 59.9% and 70.1%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=12.66, P<0.05). Of the patients with positive lymph nodes in the training dataset, the 3-year cumulative survival rate of patients with number of NLNs as <8, 8?14 and >14 was 26.1%, 42.9% and 44.7%, respectively, and the 5-year cumulative survival rate was 20.0%, 36.5% and 39.3%, respectively. There was a significant difference in the survival of these patients in the training dataset ( χ2=20.39, P<0.05). (5) Prognostic factors analysis in subgroup of the training dataset. Results of multivariate analysis in patients with NLNs in the training dataset showed that gender, ypT staging and number of NLNs (>14) were independent influencing factors for the prognosis of patients with esophageal cancer after neoadju-vant therapy ( hazard ratio=0.67, 1.44, 0.56, 95% confidence interval as 0.47?0.96, 1.09?1.90, 0.41?0.77, P<0.05). Results of multi-variate analysis in patients with positive lymph nodes in the training dataset showed that race as others, histological grade as G2, ypN staging as stage N3 and number of NLNs (8?14, >14) were independent influencing factors for the prognosis of patients with esophageal cancer after neoadjuvant therapy ( hazard ratio=2.73, 0.70, 2.08, 0.63, 0.59, 95% confidence interval as 1.43?5.21, 0.54?0.91, 1.44?3.02, 0.46?0.87, 0.44?0.78, P<0.05). (6) Construction of nomogram prediction model and calibration curve. Based on the multivariate analysis of prognosis in patients of the training dataset ,the nomogram prediction model for the prognosis of patients with esophageal cancer after neoadju-vant treatment was constructed based on the indicators of gender, ypT staging, ypN staging and number of NLNs. The AUC of nomogram prediction model in predicting the 3-, 5-year cumulative survival rate of patients in the training dataset and the validation dataset was 0.70, 0. 70 and 0.71, 0.71, respectively. The Harrell′s c index of nomogram prediction model of patients in the training dataset and the validation dataset was 0.66 and 0.63, respectively. Results of calibration curve showed that the predicted value of the nomogram prediction model of patients in the training dataset and the validation dataset was in good agreement with the actual observed value. Conclusion:The number of NLNs is an independent influencing factor for the prognosis of esophageal cancer patients after neoadjuvant therapy, and the nomogram prediction model based on number of NLNs can predict the prognosis of esophageal cancer patients after neoadjuvant therapy.

Objective:To explore the impact of weekend hospitalization on total hospitalization expenses for elderly patients with hip fracture under the geriatric orthopedic co-management.Methods:A retrospective analysis was conducted to analyze the clinical data of elderly patients with hip fracture who had been hospitalized for surgical treatment at Beijing Jishuitan Hospital from May 2015 to December 2020. They were divided into 2 groups based on their admission date. Group A was admitted from Monday to Thursday while Group B from Friday to Sunday. The general demographic data, diagnostic information, comorbidities, hospitalization expenses of the patients were collected. The differences in total hospitalization expenses, hospitalization time, rate of surgery within 48 hours and rate of hospital mortality between the 2 groups were analyzed by rank sum test, chi square test, correlation analysis, and multiple linear regression.Results:A total of 6,075 patients with hip fracture were included in this study, including 1,675 males and 4,400 females with a median age of 80 (74, 85) years. There were 3,935 ones in group A and 2,140 ones in group B. The total hospitalization expenses for group A was 58,160.52 (49,215.45, 72,748.94) yuan, insignificantly lower than those for Group B [58,412.90 (49,163.58, 72,712.61) yuan] ( P>0.05). The rate of surgery within 48 hours for group A was 75.8% (2,984/3,935), significantly higher than that for group B [49.3% (1,054/2,140)]. The hospitalization time for group A was 5 (4, 7) days, significantly less than that for group B [5 (4, 7) days] ( P<0.05). There was no significant difference in the rate of hospital mortality between the 2 groups ( P>0.05). Multiple linear regression analysis showed that total hospitalization expenses were significantly higher for patients admitted on weekends, hospitalization time was positively correlated with total hospitalization expenses, and total hospitalization expenses were significantly lower for the patients undergoing surgery within 48 hours ( P<0.05). Conclusion:Admission on weekends can increase total hospitalization expenses, prolong hospitalization time, and reduce rate of surgery within 48 hours for elderly patients with hip fracture.