Assessment of systemic immune-inflammation index in predicting postoperative pulmonary complications in patients undergoing lung cancer resection
Surgery(2022)
Abstract
Background: Hematological inflammatory parameters, including neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio, are good predictors of postoperative pulmonary complications after lung cancer resection. However, the clinical value of the systemic immune-inflammation index has not been extensively studied. Methods: We retrospectively analyzed a cohort of patients that underwent lung cancer resection in our center, and we analyzed the hematological inflammatory parameters (including systemic immune inflammation index) and postoperative pulmonary complications after lung cancer resection. The receiver operating characteristic curve was applied to determine the best cut-off value. Multivariable analysis was applied to assess which of the factors was the most important. Results: Two hundred and four patients were enrolled in this study. Of these, 47 postoperative pulmonary complications events were observed in 40 patients in this cohort. Surgery method, white blood cell count, albumin, forced expiratory volume in 1 second, carbon monoxide diffusing capacity, intensive care unit stay, and systemic immune-inflammation index were found to be significantly different between the postoperative pulmonary complications and non-postoperative pulmonary complications groups. We then used the receiver operating characteristic curves and the Youden index to determine the best cutoff value. Multivariable analysis revealed that systemic immune-inflammation index and forced expiratory volume in 1 second were the most important predictive factors of postoperative pulmonary complications after lung cancer resection. Conclusion: Hematological inflammatory parameters of systemic immune-inflammation index and forced expiratory volume in 1 second could be a favorable index to predict postoperative pulmonary complications after lung cancer resection. (c) 2022 Elsevier Inc. All rights reserved.
MoreTranslated text
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined