1.Construction of Prognostic Prediction Model of Patients Undergoing Radical Gastrectomy of Gastric Cancer Based on the Prognostic Immune-Inflammation-Nutrition Score
Xinting LUO ; Hongbing WANG ; Yuanxuan ZHANG
Journal of Medical Research 2025;54(7):152-157,84
Objective To explore the survival prediction value of the prognostic immune-inflammatory-nutritional(PIIN)score for patients undergoing radical gastrectomy and construct a prognostic prediction model.Methods To retrospectively analyze the clinical data of 406 patients who underwent radical gastrectomy.Calculate the PIIN score based on fibrinogen(FIB),neutrophil to lymphocyte ra-tio(NLR),systemic immune-inflammation index(SII),albumin-bilirubin(ALBI)score,and prognostic nutritional index(PNI).According to the threshold of 31.4906,the patients were divided into the high-PIIN group and the low-PIIN group.Conduct univariate and multivariate analyses using COX regression analysis,draw the time-dependent receiver operating characteristic(TIME ROC)curve,and compare the prognostic values of various scoring systems.To construct a nomogram based on the PIIN score for risk grouping and sur-vival analysis.Results Multivariate analysis showed that nerve invasion or not,degree of differentiation,T stage,N stage,adjuvant chemotherapy status,and PIIN score were independent independent factors for the overall survival rate of gastric cancer patients.TIME ROC curve analysis indicated that the PIIN score was superior to other scoring systems in predicting survival.The areas under the curves(AUC)of the 1-year,3-year,and 5-year ROC curvesof the nomogram were 0.788,0.794 and 0.854 respectively.Moreover,there was a statistically significant difference in survival prognosis among different risk groups(P<0.0001).Conclusion The nomogram model based on the PIIN score has good predictive ability in predicting the survival of patients undergoing radical gastrectomy for gastric cancer.
2.Construction of Prognostic Prediction Model of Patients Undergoing Radical Gastrectomy of Gastric Cancer Based on the Prognostic Immune-Inflammation-Nutrition Score
Xinting LUO ; Hongbing WANG ; Yuanxuan ZHANG
Journal of Medical Research 2025;54(7):152-157,84
Objective To explore the survival prediction value of the prognostic immune-inflammatory-nutritional(PIIN)score for patients undergoing radical gastrectomy and construct a prognostic prediction model.Methods To retrospectively analyze the clinical data of 406 patients who underwent radical gastrectomy.Calculate the PIIN score based on fibrinogen(FIB),neutrophil to lymphocyte ra-tio(NLR),systemic immune-inflammation index(SII),albumin-bilirubin(ALBI)score,and prognostic nutritional index(PNI).According to the threshold of 31.4906,the patients were divided into the high-PIIN group and the low-PIIN group.Conduct univariate and multivariate analyses using COX regression analysis,draw the time-dependent receiver operating characteristic(TIME ROC)curve,and compare the prognostic values of various scoring systems.To construct a nomogram based on the PIIN score for risk grouping and sur-vival analysis.Results Multivariate analysis showed that nerve invasion or not,degree of differentiation,T stage,N stage,adjuvant chemotherapy status,and PIIN score were independent independent factors for the overall survival rate of gastric cancer patients.TIME ROC curve analysis indicated that the PIIN score was superior to other scoring systems in predicting survival.The areas under the curves(AUC)of the 1-year,3-year,and 5-year ROC curvesof the nomogram were 0.788,0.794 and 0.854 respectively.Moreover,there was a statistically significant difference in survival prognosis among different risk groups(P<0.0001).Conclusion The nomogram model based on the PIIN score has good predictive ability in predicting the survival of patients undergoing radical gastrectomy for gastric cancer.
3.Cryomaze ablation in treatment of elderly patients with mitral valve diseases combined with persistent or long-term persistent atrial fibrillation: A propensity-score matching study
Xinting CHEN ; Huishan WANG ; Jinsong HAN ; Zongtao YIN ; Yingjie ZHANG ; Yu LUO ; Hanqing LIANG ; Zhipeng GUO
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2022;29(06):748-754
Objective To evaluate the safety and efficacy of mitral valve surgery and cryoablation in elderly patients with mitral valve disease and persistent or long-term persistent atrial fibrillation. Methods From May 2014 to July 2018, 144 patients with mitral valve diseases combined with persistent or long-term persistent atrial fibrillation in the Department of Cardiothoracic Surgery, General Hospital of Northern Theater Command were selected. Among them, there were 69 patients in a non-elderly group (<60 years) including 18 males and 51 females aged 52.07±5.56 years, and 75 patients in an elderly group (≥60 years) including 32 males and 43 females aged 65.23±4.29 years. A propensity-score matching (PSM) study was conducted to eliminate confounding factors. Both groups underwent mitral valve surgery and cryoablation at the same time. A 2-year follow-up was conducted after discharge from the hospital, and the perioperative and postoperative efficacy indexes were compared between the two groups. Results After PSM analysis, there were 56 patients in each group. The sinus rhythm conversion rate of the two groups at each follow-up time point was above 85%, and the cardiac function was graded asⅠorⅡ, which was significantly improved compared with that before the surgery, but there was no statistical difference between the two groups (P>0.05). Among the perioperative indicators of the two groups, the elderly group had more coronary artery bypass graft surgeries and longer postoperative ICU stay time compared with the non-elderly group (P<0.05), and the differences in other indicators were not statistically different (P>0.05). Conclusion The mitral valve surgery and cryoablation in elderly patients with mitral valve diseases combined with persistent or long-term persistent atrial fibrillation are safe, and the short-term outcome is satisfactory.

Result Analysis
Print
Save
E-mail