Objective To establish a prediction model for the 1-, 3-, and 5-year survival rates in patients with gastric cancer liver metastases (GCLM) by analyzing prognostic factors based on the Surveillance, Epidemiology, and End Results (SEER) database. Methods Clinical and pathological data from 591 patients diagnosed with GCLM between 2010 and 2015 were obtained from the SEER database. The population was randomly divided into a training cohort and an internal validation cohort at a 7 to 3 ratio. Independent predictors of GCLM were analyzed using univariate and multifactorial Cox regression. Consequently, nomograms were constructed. The model's accuracy was verified by calibration curve, ROC curve, and the C-index, and the clinical utility of the model was analyzed through decision curve analysis. Results Tumor differentiation grade, surgical status, and chemotherapy were significantly associated with the prognosis of GCLM patients, and these three factors were included in constructing the prognostic model and plotting the nomogram. The C-index was 0.706 (95%CI 0.677 to 0.735) and 0.749 (95%CI 0.710 to 0.788) for the training set and the internal validation cohort, respectively. The results of the ROC curve analysis indicated that the area under the curve (AUC) was over 0.7 at 1, 3, and 5 years for both the training and validation cohorts. Conclusion The prediction model of the GCLM is developed based on the 3 factors, i.e., tumor differentiation grade, surgery, and chemotherapy, and shows good prediction accuracy and thus may promote clinical decision making and individualized treatment of GCLM patients.
Objective To investigate the effect of monocyte count to high density lipoprotein ratio (MHR) on early complications after off-pump coronary artery bypass grafting and to explore the predictive factors for early complications in patients after off-pump coronary artery bypass grafting. Methods The clinical data of patients who underwent simple off-pump coronary artery bypass grafting from October 2021 to September 2023 in our hospital were retrospectively analyzed. The patients were divided into a low value group and a high value group according to the median MHR value. The clinical data of the two groups were compared, and binary logistic regression analysis was used to explore the and predictors of atrial fibrillation (AF) and acute kidney injury (AKI) after coronary artery bypass grafting. Results A total of 220 patients were included, with a median MHR of 0.48. There were 108 patients in the low value group (MHR<0.48), including 71 males and 37 females, with an average age of 65.28±7.85 years. There were 112 patients in the high-value group (MHR≥0.48), including 84 males and 28 females, with an average age of 64.57±8.75 years. There was no statistical difference between the two groups in terms of general basic data such as gender or age (P>0.05). The incidence of postoperative AF and AKI in the high-value group was significantly higher than that in the low-value group (P<0.05), and no statistical difference in terms of other postoperative complications was observed. Binary logistic regression analysis showed that MHR was a risk factor for postoperative AKI and postoperative AF (P<0.05). Conclusion The study shows that MHR is a risk factor for new-onset AF and AKI after coronary artery bypass grafting.