BackgroundThe purpose of this study was to investigate the predictive value of the modified systemic inflammation score (mSIS) in postoperative unplanned admission to the intensive care unit (ICU) in patients with non-small-cell lung cancer (NSCLC).MethodsThe clinical data of 1,321 patients with NSCLC treated with thoracic surgery in our hospital from August 2019 to June 2021 were analyzed retrospectively. The preoperative mSIS, which takes into account the serum albumin (ALB) level and lymphocyte-to-monocyte ratio (LMR), was recorded as 0, 1 or 2 and then was used to identify high-risk patients with unplanned admission to the ICU. The independent risk factors for unplanned admission to the ICU in patients with NSCLC after surgery were identified by multivariate logistic regression analysis.ResultsA total of 1,321 patients, including 549 (41.6%) males and 772 (58.4%) females, were included. The median age was 57 years (range 16–95 years). The incidence of unplanned admission to the ICU in patients with mSIS = 2 was significantly higher than that in those with mSIS = 0 and mSIS = 1. The multivariate analysis showed that an mSIS of 2 (OR = 3.728; P = 0.004; 95% CI, 1.520–9.143), an alcohol consumption history (OR = 2.791, P = 0.011; 95% CI, 1.262–6.171), intraoperative infusion volume (OR = 1.001, P = 0.021; 95% CI, 1.000–1.001) and preoperative underlying diseases (OR = 3. 57, P = 0.004; 95% CI, 1.497–8.552) were independent risk factors for unplanned admission to the ICU after lung cancer surgery. In addition, the multivariate logistic regression model showed that the C-statistic value was 0.799 (95% CI: 0.726∼0.872, P < 0.001).ConclusionsThe mSIS scoring system can be used as a simplified and effective predictive tool for unplanned ICU admission in patients with NSCLC.
Background and purposeUnnecessary surgery can be avoided, and more appropriate treatment plans can be developed for patients if the efficacy of neoadjuvant immunochemotherapy for esophageal cancer (EC) can be predicted before surgery. The purpose of this study was to evaluate the ability of machine learning models based on delta features of immunochemotherapy CT images to predict the efficacy of neoadjuvant immunochemotherapy in patients with esophageal squamous cell carcinoma (ESCC) compared with machine learning models based solely on postimmunochemotherapy CT images.Materials and methodsA total of 95 patients were enrolled in our study and randomly divided into a training group (n = 66) and test group (n = 29). We extracted preimmunochemotherapy radiomics features from preimmunochemotherapy enhanced CT images in the preimmunochemotherapy group (pregroup) and postimmunochemotherapy radiomics features from postimmunochemotherapy enhanced CT images in the postimmunochemotherapy group (postgroup). We then subtracted the preimmunochemotherapy features from the postimmunochemotherapy features and obtained a series of new radiomics features that were included in the delta group. The reduction and screening of radiomics features were carried out by using the Mann-Whitney U test and LASSO regression. Five pairwise machine learning models were established, the performance of which was evaluated by receiver operating characteristic (ROC) curve and decision curve analyses.ResultsThe radiomics signature of the postgroup was composed of 6 radiomics features; that of the delta-group was composed of 8 radiomics features. The area under the ROC curve (AUC) of the machine learning model with the best efficacy was 0.824 (0.706-0.917) in the postgroup and 0.848 (0.765-0.917) in the delta group. The decision curve showed that our machine learning models had good predictive performance. The delta group performed better than the postgroup for each corresponding machine learning model.ConclusionWe established machine learning models that have good predictive efficacy and can provide certain reference values for clinical treatment decision-making. Our machine learning models based on delta imaging features performed better than those based on single time-stage postimmunochemotherapy imaging features.
Background As the preoperative examination of esophageal cancer has improved, the likelihood of finding diseases in other organs that require surgical treatment has also increased. The purpose of this study was to explore the feasibility of combined surgery for esophageal cancer by analyzing the occurrence of postoperative complications in patients with esophageal cancer. Methods The clinical characteristics of 1566 patients with esophageal cancer who underwent thoracic surgery in our hospital between January 2017 and September 2022 were analyzed retrospectively. The feasibility of combined surgery for esophageal cancer was analyzed by comparing postoperative complications in patients who underwent simple esophageal cancer surgery (SEC) with those in patients who underwent combined surgery for esophageal cancer (COEC). The tendency scores of patients in the COEC and SEC groups (1:2) were matched to balance the confounding clinical factors, and the difference in postoperative complications was further analyzed. Moreover, we performed a subgroup analysis of esophagectomy combined with lung resection (ECL). In addition, the independent risk factors for postoperative Clavien–Dindo ≥ grade III complications of esophageal cancer were analyzed by multivariate logistic regression. Results A total of 1566 patients (1147 (73.2%) males and 419 (26.8%) females), with an average age of 64.2 years, were analyzed. There was no significant difference in postoperative complications between the SEC and COEC groups according to the Clavien-Dindo classification (P=0.713). An analysis of the complications revealed that those in the COEC group had a higher incidence of lung consolidation than those in the SEC group (P=0.007). However, when we performed propensity score matching (PSM) on the SEC and COEC groups, there was still no significant difference in complications according to the Clavien–Dindo classification (P=0.346); furthermore, when a detailed analysis of complications was performed, there was no significant difference between the two. In subgroup analysis, after we performed PSM in ECL patients and SEC patients, we also found no significant difference in postoperative complications between patients with ECL and patients with SEC. In addition, we found that a history of diabetes (OR=1.604, P=0.029, 95% CI=1.049–2.454), a history of coronary heart disease (OR=1.592, P=0.046, 95% CI=1.008–2.515), diffusing capacity of the lungs for carbon monoxide (DLCO) (OR=0.916, P=0.024, 95% CI=0.849–0.988), and ALB level (OR=0.955, P=0.007, 95% CI=0.924–0.987) were independent factors that influenced postoperative complications in esophageal cancer patients with grade III or higher complications. Conclusion Combined surgery for esophageal cancer does not increase the incidence of postoperative complications. In addition, a history of diabetes mellitus or coronary heart disease, carbon monoxide dispersion, and preoperative ALB level are independent risk factors for grade III or higher postoperative complications of esophageal cancer.
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