ABSTRACT
BACKGROUND: Postoperative delirium, particularly prevalent in elderly patients after abdominal cancer surgery, presents significant challenges in clinical management. AIM: To develop a synthetic minority oversampling technique (SMOTE)-based model for predicting postoperative delirium in elderly abdominal cancer patients. METHODS: In this retrospective cohort study, we analyzed data from 611 elderly patients who underwent abdominal malignant tumor surgery at our hospital between September 2020 and October 2022. The incidence of postoperative delirium was recorded for 7 d post-surgery. Patients were divided into delirium and non-delirium groups based on the occurrence of postoperative delirium or not. A multivariate logistic regression model was used to identify risk factors and develop a predictive model for postoperative delirium. The SMOTE technique was applied to enhance the model by oversampling the delirium cases. The model's predictive accuracy was then validated. RESULTS: In our study involving 611 elderly patients with abdominal malignant tumors, multivariate logistic regression analysis identified significant risk factors for postoperative delirium. These included the Charlson comorbidity index, American Society of Anesthesiologists classification, history of cerebrovascular disease, surgical duration, perioperative blood transfusion, and postoperative pain score. The incidence rate of postoperative delirium in our study was 22.91%. The original predictive model (P1) exhibited an area under the receiver operating characteristic curve of 0.862. In comparison, the SMOTE-based logistic early warning model (P2), which utilized the SMOTE oversampling algorithm, showed a slightly lower but comparable area under the curve of 0.856, suggesting no significant difference in performance between the two predictive approaches. CONCLUSION: This study confirms that the SMOTE-enhanced predictive model for postoperative delirium in elderly abdominal tumor patients shows performance equivalent to that of traditional methods, effectively addressing data imbalance.
ABSTRACT
Cisplatin and other platinum-based drugs are used frequently for treatment of lung cancer. However, their clinical performance are usually limited by drug resistance or toxic effects. Carnosic acid, a polyphenolic diterpene isolated from Rosemary (Rosemarinus officinalis), has been reported to have several pharmacological and biological activities. In the present study, the combination effect of cisplatin plus carnosic acid on mouse LLC (Lewis lung cancer) xenografts and possible underlying mechanism of action were examined. LLC-bearing mice were treated with intraperitoneal injection with cisplatin, oral gavage with carnosic acid, or combination with cisplatin and carnosic acid, respectively. Combination of carnosic acid and cisplatin yielded significantly better anti-growth and pro-apoptotic effects on LLC xenografts than drugs alone. Mechanistic study showed that carnosic acid treatment boosted the function of CD8+ T cells as evidenced by higher IFN-γ secretion and higher expression of FasL, perforin as well as granzyme B. In the meantime, the proportion of MDSC (myeloid-derived suppressor cells) in tumor tissues were reduced by carnosic acid treatment and the mRNA levels of iNOS2, Arg-1, and MMP9, which are the functional markers for MDSC, were reduced. In conclusion, our study proved that the functional suppression of MDSC by carnosic acid promoted the lethality of CD8+ T cells, which contributed to the enhancement of anti-lung cancer effect of cisplatin.