ObjectiveTo explore the therapeutic mechanism of Bushen Huoxue prescription from the perspective of bone metabolism by observing the clinical efficacy of this prescription in treating femoral head necrosis （ONFH， syndrome of liver and kidney deficiency） and its influences on bone metabolism indexes： N-terminal propeptide （PINP） and β-collagen degradation product （β-CTX）. MethodSixty-six ONFH patients with the syndrome of liver and kidney deficiency in Zhengzhou Traditional Chinese Medicine Hospital of Orthopedics from December 2021 to September 2022 were selected. The patients were randomized into an experimental group and a control group by the parallel control method， with 33 patients in each group. The experimental group received Bushen Huoxue prescription orally， while the control group received Xianlinggubao Capsules orally， with a treatment cycle of 6 months. The visual analogue scale （VAS） score， Harris score， Association Research Circulation Osseous （ARCO） staging， imaging changes， quantitative scores of TCM symptoms， and serum levels of PINP and β-CTX were determined before and after treatment. The occurrence of adverse events and reactions was recorded. ResultThe total response rate in the experimental group was 83.87% （26/31）， which was higher than that （68.75%， 22/32） in the control group （Z=-2.096， P<0.05）. After treatment， the single and total scores of TCM symptoms， VAS score， and β-CTX level decreased in the two groups （P<0.05）. Moreover， the decreases in the scores of hip pain， lower limb mobility， soreness of waist and knees， and lower limb flaccidity， total score of TCM symptoms， VAS score， and β-CTX level in the experimental were larger than those in the control group （P<0.05）. After treatment， the imaging results showed no significant improvement in the two groups. The Harris score and PINP level in both groups increased after treatment （P<0.05）， and the increases were more obvious in the experimental group than in the control group （P<0.05）. No serious adverse event or adverse reaction appeared during the observation period. ConclusionBushen Huoxue prescription can relieve pain and TCM symptoms and improve the hip joint function in treating ONFH patients with the syndrome of liver and kidney deficiency. It can inhibit the development of ONFH， increase PINP， and decrease β-CTX. No obvious side effect appears during the clinical observation period， which shows that Bushen Huoxue prescription has good safety.

Objective:To investigate the influencing factors for microvascular invasion (MVI) in hepatocellular carcinoma based on three-dimensional visualization and the construction of its nomogram model.Methods:The retrospective cohort study method was conducted. The clinico-pathological data of 190 patients with hepatocellular carcinoma who were admitted to Henan University People′s Hospital from May 2018 to May 2021 were collected. There were 148 males and 42 females, aged (58±12)years. The 190 patients were randomly divided into the training set of 133 cases and the validation set of 57 cases by the method of random number table in the ratio of 7:3. The abdominal three-dimensional visualization system was used to characterize the tumor morphology and other imaging features. Observation indicators: (1) analysis of influencing factors for MVI in hepatocellular carcinoma; (2) construction and evaluation of nomogram model of MVI in hepatocellular carcinoma. Measurement data with normal distribution were expressed as Mean± SD, and independent sample t test was used for comparison between groups. Measurement data with skewed distribution were expressed as M( Q1, Q3), and non-parametric rank sum test was used for comparison between groups. Count data were expressed as absolute numbers, and the chi-square test was used for comparison between groups. Corresponding statistical methods were used for univariate analysis. Binary Logistic regression model was used for multivariate analysis. Receiver operator characteristic (ROC) curves were plotted, and the nomogram model was assessed by area under the curve (AUC), calibration curve, and decision curve. Results:(1) Analysis of influencing factors for MVI in hepatocellular carcinoma. Among 190 patients with hepatocellular carcinoma, there were 97 cases of positive MVI (including 63 cases in the training set and 34 cases in the validation set) and 93 cases of negative MVI (including 70 cases in the training set and 23 cases in the validation set). Results of multivariate analysis showed that alpha-fetoprotein, vascular endothelial growth factor, tumor volume, the number of tumors, and tumor morphology were independent factors affecting the MVI of patients with hepatocellular carcinoma ( odds ratio=5.06, 3.62, 1.00, 2.02, 2.59, 95% confidence interval as 1.61-15.90, 1.28-10.20, 1.00-1.01, 1.02-3.98, 1.03-6.52, P<0.05). (2) Construction and evaluation of nomogram model of MVI in hepatocellular carcinoma. The results of multivariate analysis were incorporated to construct a nomogram prediction model for MVI of hepatocellular carcinoma. ROC curves showed that the AUC of the training set of nomogram model was 0.85 (95% confidence interval as 0.79-0.92), the optimal fractional cutoff based on the Jordon′s index was 0.51, the sensitivity was 0.71, and the specificity was 0.84. The above indicators of validation set were 0.92 (95% confidence interval as 0.85-0.99), 0.50, 0.90, and 0.82, respectively. The higher total score of the training set suggested a higher risk of MVI in hepatocellular carcinoma. The calibration curves of both training and validation sets of nomogram model fitted well with the standard curves and have a high degree of calibration. The decision curve showed a high net gain of nomogram model. Conclusions:Alpha-fetoprotein, vascular endothelial growth factor, tumor volume, the number of tumors, and tumor morphology are independent influencing factors for MVI in patients with hepatocellular carcinoma. A nomogram model constructed based on three-dimensional visualized imaging features can predict MVI in hepatocellular carcinoma.

Objective:To evaluate the use of serosa muscular layers circumferential incision combined with mucosal layer cutting and closure by laparoscopic or robotic surgery for gastrointestinal mesenchymal tumors at difficult sites of the stomach.Methods:From Jul 2019 to Apr 2021, 18 gastric mesenchymal tumor patients undergoing serosa muscular layers circumferential incision combined with mucosal layer cutting and closure by laparoscopic or robotic surgery at the Department of Surgery, the Fourth Hospital of Hebei Medical University were retrospectively analyzed.Results:All 18 patients had successful surgery, including 7 cases of robotic surgery, 11 cases of laparoscopic surgery, and there was no conversion to open surgery. Tumors were at the gastric in cardia, 8 cases at the gastric body and lesser curvature in 4 cases, and at the gastric antrum in 6 cases, respectively. Eleven cases were of endogenous and 7 cases were of dumbbell type. The average operation time was (99±29) min, the intraoperative blood loss was (10±5) ml, the first time taking food per mouth was (2.0±1.0) d, and the postoperative hospital stay was (4.9 ± 1.2) d. Pathology showed gastrointestinal stromal tumor in 11 cases, leiomyoma in 5 cases and schwannoma in 2 cases. All were with negative margins. The average tumor diameter was (4.7±1.4) cm. The median follow-up time was 16.5 months, and there was no sign of tumor recurrence or metastasis.Conclusion:The serosa muscular layers circumferential incision combined with mucosal layer cutting and closure technique in laparoscopic or robotic surgery is a safe and feasible procedure for treating gastrointestinal mesenchymal tumor at difficult sites of the stomach.

Objective:To explore the risk factors of lymphatic fistula after radical gastric cancer operation.Methods:We retrospectively analyze the clinicopathological data of gastric cancer patients who underwent radical surgery from May, 2019 to May, 2020 at the Third Department of Surgery, Fourth Hospital of Hebei Medical University, and analyze the risk factors impacting postoperative lymphatic leakage,for the establishment of the risk prediction scoring model.Results:A total of 487 patients with gastric cancer underwent radical gastrectomy, of which 32 patients (6.6%) had lymphatic leakage . Multivariate logistic regression analysis showed that hypoproteinemia before surgery (95% CI: 1.222-7.357, P=0.016), the lesion is located in the cardia-fundus of the stomach (95% CI: 1.117-6.788, P=0.028),stage T3-T4 (95% CI: 1.149-25.676, P=0.033), operation time ≥4 h (95% CI: 1.469-11.480, P=0.007), combined organ resection (95% CI: 1.106-12.886, P=0.034), D2+ lymph node dissection (95% CI: 1.969-11.510, P=0.001), anemia (95% CI: 1.271-9.392, P=0.015) were an independent risk factors. Equation based on multi-factor Logistic regression: logit( P)=-9.624+1.098×X 1+1.013×X 2+1.692×X 3+1.413×X 4+1.328×X 5+1.560×X 6+1.240×X 7 was estaslished, using Hosmer. Lemeshow test detects the goodness of fit of the regression equation ( P=0.348). The area under the ROC curve was 0.856 (95% CI: 0.787-0.926, P<0.001); the probability of lymphatic leakage when scores ≥4 points was 14.1%, when scores <4 points ,the probability of leakage was 2.5%. Conclusion:A risk prediction scoring model for lymphatic leakage after radical gastrectomy, can identify patients with high risk after surgery

Objective:To investigate the clinical value of systemic immune-inflammation index (SII) based on peripheral blood neutrophils, lymphocytes and platelets counts in predicting the prognosis of patients with gastric cancer after radical resection.Methods:From January 1, 2012 to January 1, 2015, the data of 2 273 patients with gastric cancer who underwent radical surgery at the Third Department of Surgery of the Fourth Hospital of Hebei Medical University were retrospectively analyzed. SII value was calculated according to the formula (SII=neutrophil cell count (×10 9/L)×platelet cell count (×10 9/L)/lymphocyte count (×10 9/L)). According to receiver operating characteristic curve (ROC), the optimal cut-off value of SII was determined and the patients were divided into high SII group and low SII group. Chi-square test was used to compare the clinicopathological characteristics and prognosis of the two groups. Kaplan-Meier method was applied to draw survival curve, log-rank test was used for univariate survival analysis, and Cox regression model was used for multivariate survival analysis. The ROC of preoperative SII, pathological TNM stage and their combination for predicting prognosis and recurrence were drawn, and the area under the curve (AUC) values were calculated to compare the predictive power of the three. Results:According to the ROC, the optimal cut-off value of SII was 589.5, and there were 1 180 cases (51.91%) in the high SII (SII≥589.5) group and 1 093 cases (48.09%) in the low SII (SII<589.5) group. Compared with those of the low SII group, the maximum diameter of gastric cancer in the high SII group was mostly ≥5 cm (49.04%, 536/1 093 vs. 56.27%, 664/1 180), the histological types were mostly poorly differentiated to undifferentiated (55.63%, 608/1 093 vs. 61.19%, 722/1 180), the depth of tumor invasion was mainly from T4a to T4b (45.11%, 493/1 093 vs. 54.837%, 647/1 180), and the rate of lymph node metastasis, pathological TNM stage, rate of vascular infiltration, incidence of nerve invasion, Ki-67 expression level, serum carcinoembryonic antigen level and carbohydrate antigen 19-9 level in the high SII group were all higher than those in the low SII group (67.70%, 740/1 093 vs. 80.68%, 952/1 180; 57.64%, 630/1 093 vs. 71.10%, 839/1 180; 55.54%, 607/1 093 vs. 67.03%, 791/1 180; 53.89%, 589/1 093 vs. 64.32%, 759/1 180; 45.29%, 495/1 093 vs. 56.69%, 669/1 180; 56.91%, 622/1 093 vs. 63.20%, 734/1 180; 53.25%, 582/1 093 vs. 57.97%, 684/1 180), and the differences were statistically significant ( χ2=8.842, 11.097, 7.225, 21.467, 50.200, 44.984, 31.687, 25.594, 29.549, 6.612 and 5.119, all P<0.05). The 5-year overall survival rate and disease-free survival rate of the low SII group were 75.66% and 67.61%, respectively, which were both higher than those of the high SII group, (24.92% and 23.31%, respectivily), the differences were statistically significant ( χ2=620.700 and 413.00, both P<0.01). The results of multivariate Cox regression analysis showed that tumor histological type, depth of invasion, pathological TNM stage, vascular invasion and preoperative SII were independent risk factors for postoperative prognosis and recurrence of patients with gastric cancer (odds ratios were 4.126, 2.255, 5.123, 3.826, 6.126, 4.683, 2.472, 5.224, 4.416, 6.212, respectively; 95% confidence interval 2.123 to 9.721, 1.632 to 7.427, 3.325 to 10.211, 2.321 to 9.322, 4.127 to 13.782, 2.561 to 9.418, 1.322 to 6.289, 3.315 to 11.526, 2.213 to 9.382, 4.474 to 13.541; all P<0.05). The predictive power of preoperative SII (AUC=0.842, 0.815) and pathological TNM stage (AUC=0.881, 0.827) for the 5-year overall survival and disease-free survival of patients with gastric cancer after radical resection was similar, however the predictive power of combination of the two (AUC=0.943, 0.895) was higher than that of preoperative SII and pathological TNM stage alone. Conclusions:Preoperative SII is an independent risk factor for the prognosis of patients with gastric cancer after radical resection, combined with parthological TNM stage can be used as an indicator to predict the prognosis and recurrence of patients.

Objective:To investigate the application value of individualized full-course nutritional intervention in neoadjuvant concurrent chemoradiotherapy (nCRT) for locally advanced Siewert type Ⅱ and Ⅲ adenocarcinoma of esophagogastric junction (AEG).Methods:The perspec-tive randomized control study was conducted. The clinicopathological data of 90 patients with locally advanced Siewert type Ⅱ and Ⅲ AEG who underwent nCRT in the Fourth Hospital of Hebei Medical University from February 2012 to December 2018 were selected. Patient were divided into two groups with 1:1 according to random number table. Patients undergoing nCRT combined with individualized full-course nutritional intervention were allocated into experimental group, and patients undergoing nCRT combined with common nutritional intervention were allocated into control group. Observation indicators: (1) grouping situations of the enrolled patients; (2) changing situations of nutritional status and quality of life of patients in nCRT and preoperative waiting period; (3) efficacy evaluation and adverse effects of nCRT; (4) surgical and recovery situations. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the t test. Measurement date with skewed distribution were represented as M ( P25, P75) or M (range), and comparison between groups was conducted using the Mann-Whitney U test. Count data were represented as absolute numbers or percentages, and comparison between groups was conducted using the chi-square test or Fisher exact probability. Comparison of ordinal data was conducted using the non-parameter rank sum test. Repeated measurement data were analyzed using the repeated ANOVA. Results:(1) Grouping situations of the enrolled patients: a total of 90 patients were selected for eligibility. There were 77 males and 13 females, aged from 26 to 74 years, with a median age of 62 years. Of 90 patients, there were 45 cases in the experimental group and 45 cases in the control group. (2) Changing situations of nutritional status and quality of life of patients in nCRT and preoperative waiting period: ① during the nCRT treatment (week 3, week 6) and the preoperative waiting period (week 9, week 12, week 15), the body mass was (67±10)kg, (66±9)kg, (67±10)kg, (68±10)kg, (70±10)kg for the experi-mental group, respectively, and (65±9)kg, (59±8)kg, (62±8)kg, (64±8)kg, (66±9)kg for the control group. The multivariate test was conducted based on the mauchly's test of sphericity for the body mass ( χ2=195.010, P<0.05). There were significant differences in the time effect, interaction effect, intervention effect of body mass changing between the two groups ( F=93.974, 60.638, 4.144, P<0.05). ② During the nCRT treatment (week 3, week 6) and the preoperative waiting period (week 9, week 12, week 15), the total protein was (66±4)g/L, (65±4)g/L, (65±4)g/L, (68±4)g/L, (71±5)g/L for the experimental group, respectively, and (65±4)g/L, (62±5)g/L, (63±5)g/L, (65±5)g/L, (67±6)g/L for the control group. The multivariate test was conducted based on the mauchly's test of sphericity for the total protein ( χ2=652.524, P<0.05). There were significant differences in the time effect, interaction effect, interven-tion effect of total protein changing between the two groups ( F=672.507, 6.424, 5.057, P<0.05). ③ During the nCRT treatment (week 3, week 6) and the preoperative waiting period (week 9, week 12, week 15), the albumin was (40±3)g/L, (38±4)g/L, (38±4)g/L, (39±4)g/L, (40±4)g/L for the experimental group, respectively, and (39±4)g/L, (35±5)g/L, (36±4)g/L, (36±4)g/L, (37±5)g/L for the control group. The multivariate test was conducted based on the mauchly's test of sphericity for the albumin ( χ2=289.324, P<0.05). There were significant differences in the time effect, interaction effect, intervention effect of albumin changing between the two groups ( F=4 210.683, 5.013, 7.330, P<0.05). ④ During the nCRT treatment (week 3, week 6) and the preoperative waiting period (week 9, week 12, week 15), the prealbumin was (228±41)mg/L, (222±56)mg/L, (223±47)mg/L, (227±46)mg/L, (233±53)mg/L for the experimental group, respectively, and (202±49)mg/L, (174±68)mg/L, (179±54)mg/L, (185±51)mg/L, (193±57)mg/L for the control group. The multi-variate test was conducted based on the mauchly's test of sphericity for the prealbumin ( χ2=297.324, P<0.05). There were significant differences in the time effect, interaction effect, intervention effect of prealbumin changing between the two groups ( F=871.545, 6.111, 14.426, P<0.05). ⑤ During the nCRT treatment (week 3, week 6) and the preoperative waiting period (week 9, week 12, week 15), the hemoglobin was (124±14)g/L, (121±14)g/L, (125±13)g/L, (127±13)g/L, (128±13)g/L for the experimental group, respectively, and (121±18)g/L, (114±14)g/L, (116±14)g/L, (117±16)g/L, (118±22)g/L for the control group. The multivariate test was conducted based on the mauchly's test of sphericity for the hemoglobin ( χ2=257.560, P<0.05). There were significant differences in the time effect, interaction effect, intervention effect of hemoglobin changing between the two groups ( F=2 533.553, 4.142, 4.985, P<0.05). ⑥ During the nCRT treatment (week 3, week 6) and the preopera-tive waiting period (week 9, week 12, week 15), the patient-generated subjective global assessment (PG-SGA) score was 4.4±1.2,6.3±1.4, 5.5±1.4, 4.3±1.4, 3.4±1.7 for the experimental group, respec-tively, and 4.9±1.2, 7.4±1.7, 7.3±1.6, 6.3±1.4, 6.0±1.5 for the control group. The multivariate test was conducted based on the mauchly's test of sphericity for the PG-SGA score ( χ2=289.543, P<0.05). There were significant differences in the time effect, interaction effect, intervention effect of PG-SGA score changing between the two groups ( F=648.583, 41.906, 26.098, P<0.05). ⑦ During the nCRT treatment (week 3, week 6) and the preoperative waiting period (week 9, week 12, week 15), the quality of life questionnaire of stomach (QLQ-ST022) score was 13±3, 16±6, 16±4, 14±4, 12±5 for the experimental group, respectively, and 15±4, 21±6, 20±4, 17±4, 15±5 for the control group. The multivariate test was conducted based on the mauchly's test of sphericity for the QLQ-STO22 ( χ2=279.865, P<0.05). There were significant differences in the time effect, interaction effect, interven-tion effect of QLQ-STO22 changing between the two groups ( F=710.238, 7.261, 16.794, P<0.05). (3) Efficacy evaluation and adverse effects of nCRT: there were 25 patients and 20 cases of the experimental group with partial response and stable disease, showing the objective response rate and disease control rate as 55.6%(25/45)and 100.0%(45/45). There were 18 patients and 27 cases of the control group with partial response and stable disease, showing the objective response rate and disease control rate as 40.0%(18/45)and 100.0%(45/45). There was no significant difference in the nCRT efficacy between the two groups ( P>0.05). Cases with leukopenia, neutropenia, anemia, nausea, and loss of appetite were 27, 25, 19, 30, 34 for the experimental group, versus 37, 34, 29, 39, 42 for the control group, showing significant differences between the two groups ( χ2=5.409, 3.986, 4.464, 5.031, 5.414, P<0.05). (4) Surgical and recovery situations: patients of the experimental group underwent surgeries successfully. Two patients of the control group diagnosed with peritoneal metastasis after laparoscopic exploration underwent conversion therapy and no surgery, the other 43 patients underwent surgeries. The time to postoperative gastric tube removal, time to postopera-tive drainage tube removal, time to postoperative first flatus, time to postoperative first defecation, duration of postoperative hospital stay were 2.0 days (1.5 days, 3.0 days), 6.0 days (5.0 days,11.0 days), 2.0 days (1.5 days, 2.5 days), 2.0 days (1.5 days, 2.5 days), 7.0 days (6.0 days,14.0 days) for the experimental group, versus 3.0 days (2.0 days,4.0 days), 7.0 days (5.5 days,14.0 days), 2.0 days (1.5 days,3.0 days), 3.0 days (2.0 days,3.5 days), 8.0 days (6.0 days, 17.0 days) for the control group, showing significant differences between the two groups ( Z=-3.477, -4.398, -3.068, -5.786, -3.395, P<0.05). Conclusion:For AEG patients undergoing nCRT, the individualized full-course nutrition intervention involving nutritionists is beneficial to improve the nutritional status, reduce adverse reactions, and improve the quality of life of the patients, promote postoperative short-term recovery. Registry: this study was registered at clinicaltrials.gov in United States, with the registry number of NCT01962246.

Objective:To investigate the clinically relevant factors of progressive disease (PD) after neoadjuvant therapy for locally advanced gastric cancer.Methods:From Jun 2011 to Mar 2016, 569 patients with locally advanced gastric cancer(cT3/4N0/+ M0) admitted to the Fourth Hospital of Hebei Medical University were retrospectively analyzed .Results:All 569 patients completed neoadjuvant therapy, 59 patients (10.4%) had PD. Univariate analysis showed that tumor size (χ 2=10.091, P=0.001), pathological type (χ 2=4.110, P=0.043), Borrmann type (χ 2=91.941, P=0.001), pre-treatment cT stage (χ 2=7.980, P=0.005) were associated with PD after neoadjuvant therapy for gastric cancer. The results of multi-factor regression analysis showed that pathological type, Borrmann type, pre-treatment cT stage were independent factors influencing the occurrence of PD after neoadjuvant therapy for advanced gastric cancer. The overall survival and progression-free suruival time of patients with PD is significantly shorter than that of patients without PD . Conclusion:The pathological type, Borrmann typing and pre-treatment cT stage are the influencing factors for the occurrence of PD after neoadjuvant treatment in advanced gastric cancer, and the prognosis of PD patients is poor.

Objective:To investigate the risk factors of pancreatic fistula after radical resection of gastric cancer, and to establish a risk prediction scoring model for pancreatic fistula.Methods:The clinico-pathological data of 312 patients with gastric cancer admitted to the Fourth Hospital of Hebei Medical University from January 2019 to January 2020 were retrospectively analyzed. Multiple factor logistic regression model was used to analyze the risk factors of pancreatic fistula after radical resection of gastric cancer, and a risk prediction scoring model based on the risk factors was established. Hosmer-Lemeshow test was used to detect the goodness of fit of regression equation, and receiver operating characteristics (ROC) curve was used to evaluate the distinction degree of regression equation.Results:Among 312 patients with gastric cancer, 27 cases (8.65%) had pancreatic fistula after radical resection of gastric cancer. Multiple factor logistic regression analysis showed that male patients ( OR = 5.312, 95% CI 1.532-18.420, P = 0.008), age ≥ 60 years old ( OR = 4.928, 95% CI 1.493-16.250, P = 0.009), preoperative diabetes mellitus ( OR = 3.062, 95% CI 1.091-8.589, P = 0.034), lesion location in the gastric body-gastric antrum ( OR = 3.121, 95% CI 1.052-9.251, P = 0.040), intraoperative omental bursa resection ( OR = 6.209, 95% CI 2.084-18.478, P = 0.001), intraoperative lymph node dissection at D2+ station ( OR = 3.114, 95% CI 1.044-9.281, P = 0.042), intraoperative combined organ resection ( OR = 5.063, 95% CI 1.473-17.400, P = 0.010), preoperative TNM stage Ⅲ ( OR = 4.973, 95% CI 1.189-20.792, P = 0.028) were independent risk factors for pancreatic fistula after radical resection of gastric cancer. A risk prediction equation of pancreatic fistula after radical resection of patients with gastric cancer was established: P = -8.619+1.670X 1+1.595X 2+1.119X 3+1.138X 4+1.826X 5+1.136X 6+1.622X 7+1.604X 8; factor X was set as a binomial assignment (0 or 1); X1-X8 were listed as follows respectively: gender (the male was 1), age (≥60 years old was 1), preoperative diabetes history (yes was 1), lesion location (gastric body-gastric antrum was 1), intraoperative resection of omental bursa or not (yes was 1), intraoperative lymph node dissection at D2+ station or not (yes was 1), intraoperative combined organ resection or not (yes was 1), preoperative TNM stage (stage Ⅲ was 1). The goodness of fit of regression equation was high ( P = 0.395). The area under the curve of ROC by using risk prediction scoring model to judge pancreatic fistula was 0.916 (95% CI 0.872-0.960, P<0.01). The probability of pancreatic fistula in patients with score ≥ 5 was 40.90%, and the probability of pancreatic fistula in patients with score < 5 was 3.35%. Conclusions:The occurrence of pancreatic fistula after radical resection of gastric cancer is closely related to a variety of risk factors. By establishing a risk prediction scoring model for pancreatic fistula after radical resection of gastric cancer, it is helpful to effectively identify patients with high risk of pancreatic fistula after radical surgery during the perioperative period.

BACKGROUND: Childhood adversities pose deleterious consequences on health and well-being, but limited studies explore whether unique patterns of adverse childhood experiences (ACEs) impact the mental health of emerging adults and the mediating role of current stressful events (CSEs). This study examined classes of ACEs and how they relate to CSEs, psychological distress, and subjective well-being among Eritrean College undergraduates. METHODS: Cross-sectional data on ACEs, CSEs, symptoms of psychological distress, and subjective well-being were collected from a national sample of college students (N = 507). We identified ACE patterns using latent class analysis and further examined whether CSEs mediated the effects of ACE classes on psychological distress and subjective well-being. RESULTS: 86.4% of the sample experienced at least one ACE. Collective violence, domestic violence, and physical abuse were the most common ACEs. Three subgroups, low ACEs (66.3%), household violence (19.1%), and multiple ACEs (14.6%) were identified. We found that relative to low ACEs, household violence (β = 0.142, 95% CI 0.046, 0.248) and multiple ACEs (β = 0.501, 95% CI 0.357, 0.666) indirectly influenced psychological distress through CSEs, and CSEs mediated the relationships between household violence (β = -0.096, 95% CI -0.176, -0.033), multiple ACEs (β = -0.338, 95% CI -0.498, -0.210), and subjective well-being. However, there were nonsignificant relative direct effects of ACE patterns on both psychological distress and subjective well-being. CONCLUSIONS Experiencing multiple ACEs and household violence in conjunction with CSEs significantly predict psychological distress and subjective well-being. Contextual interventions for the early identification of ACEs and the management of CSEs may play a crucial role in the prevention of mental health problems.
Adolescent ; Adult ; Adverse Childhood Experiences/statistics & numerical data* ; Cross-Sectional Studies ; Female ; Health Status ; Humans ; Latent Class Analysis ; Male ; Mental Health/statistics & numerical data* ; Models, Psychological ; Prevalence ; Stress, Psychological/psychology* ; Students/statistics & numerical data* ; Universities ; Young Adult