ObjectiveTo study the relationship between plasma cardiac troponin I (cTnI) and global registry of acute coronary events (GRACE) risk score in patients with acute non ST segment elevation myocardial infarction (NSTEMI),and to assess the value of low GRACE risk score combined with plasma cTnI concentration in predicting hospital cardiovascular events in NSTEMI patients. MethodA total of 168 patients with NSTEMI treated between January 2011 and December 2012 were included in this study. Their serum CTnI level was measured instantly and on the second day (within 24 hours) to get the peak value. GRACE risk score was calculated by computer rating software. According to the GRACE risk score,risk stratification was performed,and patients were divided into low-risk group (n=48),middle-risk group (n=75) and high-risk group (n=45). Routine treatment was carried out for the patients during hospitalization. ResultsThe serum cTnI peak value was higher in high-risk patients than that in low-risk patients and middle-risk patients (P<0.05). The cTnI peak value was significantly higher in the middle-risk patients than in the low-risk patients (P<0.05). The incidence of major adverse cardiovascular events (MACE) in low-risk patients with higher serum cTnI peak value was relatively higher. Age,hyperlipidemia,and serum cTnI were closely related to MACE (P<0.05). ConclusionsFor NSTEMI patients with a low GRACE score,the MACE rate increases with the increase of serum cTnI concentration. GRACE low score and cTnI concentration have a certain clinical value in assessing the risk of MACE in NSTEMI patients.
Objective To introduce a simple preoperative risk score for esophageal cancer (PRSEC) and its relationship with the prognosis of patients who underwent resection of esophageal carcinoma. Methods We retrospectively analyzed the clinical data of 498 patients receiving resection of esophageal carcinoma between 2005 and 2015 in our hospital. They were divided into three groups (PRSEC1, PRSEC2 and PRSEC3 groups) according to the results of PRSEC (revised cardiac risk index, model for end-stage liver disease score and pulmonary function test). Their overall survival (OS) and disease-free survival (DFS) were measured to find the relationship between the PRSEC and prognosis of patients. Results The mortality, morbidity, DFS and OS were correlative with the PRSEC. Therefore the PRSEC can be used to predict the short-term outcome. The patients with score 2 or 3 had higher risk of mortality and morbidity than those with score 1. In addition, the DFS and OS of patients with higher score were shorter (P<0.001). Conclusion The PRSEC is easy and efficient and can predict the morbidity, mortality, and long-term outcomes for the patients with resection of esophageal carcinoma.
Objective To explore the influencing factors of pancreatic fistula after pancreaticoduodenectomy (PD), and to compare the incidence of pancreatic fistula after pancreaticoduodenectomy with internal drainage of main pancreatic duct and external drainage according to the pancreatic fistula risk score (FRS) system, to provide the basis for the best drainage scheme in clinic. Methods The clinical data of 76 patients with PD who treated in the Affiliated Hospital of Xuzhou Medical University from January 2016 to December 2017 were analyzed retrospectively, to explore the risk factors of pancreatic fistula. Single factor analysis was based on group chi-square test or Fisher exact probability method, and multivariate analysis was based on unconditioned logistic regression model. According to the results of FRS, the difference of pancreatic fistula in different risk groups was explored. The statistical method was chi-square test. Results The incidence of pancreatic fistula after PD was 31. 5% in 76 patients.Univariate analysis showed that the diameter of the main pancreatic duct and the texture of the pancreas were the related factors affecting the occurrence of pancreatic fistula after PD (P<0.05), and the soft pancreas was the independent risk factor for the occurrence of pancreatic fistula after PD (OR=3.886, P=0.011). There was no significant difference in the incidence of postoperative pancreatic fistula between the internal drainage group and the external drainage group (P>0.05). There was no pancreatic fistula occurred in the patients with negligible risk. The incidence of postoperative pancreatic fistula in patients with high risk of external drainage group was only 12.5%, comparing with patients in internal drainage group (63.6%), the difference was statistically significant (P=0.026). There was no significant difference in the incidence of postoperative pancreatic fistula between patients in the external drainage group with moderate risk and low risk compared with the corresponding patients in the internal drainage group (P>0.05). Conclusions Pancreatic texture was an independent risk factor for pancreatic fistula after PD. External drainage maybe more effective than internal drainage in preventing pancreatic fistula after PD in patients with high risk of FRS.
ObjectiveTo establish the gene-based esophageal cancer (ESCA) risk score prediction models via whole transcriptome analysis to provide ideas and basis for improving ESCA treatment strategies and patient prognosis.MethodsRNA sequencing data of esophageal squamous cell carcinoma (ESCC), esophageal adenocarcinoma (EAC) and adjacent tissues were obtained from The Cancer Genome Atlas database. The edgeR method was used to screen out the differential genes between ESCA tissue and normal tissue, and the key genes affecting the survival status of ESCC and EAC patients were initially identified through univariate Cox regression analysis. The least absolute shrinkage and selection operator regression analysis and multivariate Cox regression analysis were used to further screen genes and establish ESCC and EAC risk score prediction models.ResultsThe risk score prediction models were the independent prognostic factors for ESCA, and the risk score was significantly related to the survival status of patients. In ESCC, the risk score was related to T stage. In EAC, the risk score was related to lymph node metastasis, distant metastasis and clinical stage. The constructed nomogram based on risk score showed good predictive ability. In ESCC, the risk score was related to tumor immune cell infiltration and the expression of immune checkpoint genes. However, this feature was not obvious in EAC.ConclusionThe ESCC and EAC risk score prediction models have shown good predictive capabilities, which provide certain inspiration and basis for optimizing the management of ESCA and improving the prognosis of patients.
ObjectiveTo onstructe a prognostic model for gastric cancer based on disulfidoptosis-related genes. MethodsFirstly, transcriptome data and clinical data were obtained from the TCGA and GEO databases to explore the expression of disulfidoptosis-related genes in gastric cancer tissues and normal tissues, as well as their impact on the overall survival (OS) of gastric cancer patients. Subsequently, two clusters of disulfidoptosis-related gene were determined by consensus clustering, key genes were further selected by using LASSO regression, and a multivariate Cox proportional hazards regression model was constructed to predict OS. ResultsAmong the 24 kinds of disulfidoptosis-associated genes, 16 exhibited statistically significant differences in expression between gastric cancer tissues and normal tissues (P<0.05), and results of univariate Cox proportional hazards regression model showed that 9 kinds of disulfidoptosis-associated genes were associated with OS (P<0.05). The 24 kinds of disulfidoptosis-associated genes were grouped into 2 clusters by using the consensus clustering algorithm, with 299 differentially expressed genes between the two clusters. In the training set, 14 genes were determined by using LASSO regression to construct the OS prediction model, and risk scores were calculated. The OS of the high-risk group was significantly worse than that of the low-risk group (P<0.05), and this prediction model also had a high area under the curve value in the validation set. ConclusionsThe OS prediction model based on disulfidoptosis-associated genes can predict the prognosis of gastric cancer patients.