Analysis of risk factors of acute respiratory failure after radical resection of esophageal cancer by two methods
"<b>Objective</b> To analyze the risk factors of acute respiratory failure (ARF) after radical resection for esophageal cancer by combining logistic regression analysis and association rule analysis. <b>Methods</b> The clinical data of 146 patients after radical resect...
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The Editorial Department of Chinese Journal of Clinical Research
2025-01-01
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| Series: | Zhongguo linchuang yanjiu |
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| Online Access: | http://zglcyj.ijournals.cn/zglcyj/ch/reader/create_pdf.aspx?file_no=20250113&year_id=2025&quarter_id=1&falg=1 |
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| _version_ | 1849722259015467008 |
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| author | LEI Xiuwen, ZHU Xiaolei, TIAN Long |
| author_facet | LEI Xiuwen, ZHU Xiaolei, TIAN Long |
| author_sort | LEI Xiuwen, ZHU Xiaolei, TIAN Long |
| collection | DOAJ |
| description | "<b>Objective</b> To analyze the risk factors of acute respiratory failure (ARF) after radical resection for esophageal cancer by combining logistic regression analysis and association rule analysis.
<b>Methods</b> The clinical data of 146 patients after radical resection for esophageal cancer in Zhangye People's Hospital Affiliated to Hexi University from June 2019 to June 2022 were retrospectively studied. Patients were divided into the ARF group ( n =49) and the non-ARF group ( n =97). Univariate analysis of risk factors for ARF was performed, and multivariate analysis was performed by logistic regression in two groups. The FP-Growth algorithm program was compiled in Python, and the association rule analysis was performed to calculate the effective strong association rules between the clinical features in the ARF group.
<b>Results</b> Logistic regression analysis showed that the risk factors of ARF were smoking history ( OR =3.039,P =0.018), anastomotic fistula( OR =5.041,P ＜0.01), thoracic adhesion ( OR =7.993,P ＜0.01) and hypoproteinemia ( OR =3.831,P ＜0.01). The analysis of association rules showed that there were 11 effective strong association rules between clinical features: (1) the two rules were age (60~69 years old) ∩ ARF, smoking history ∩ARF, lung surgery history ∩ARF, operation duration(≥3 h) ∩ ARF, anastomotic fistula ∩ARF, thoracic adhesion ∩ARF, hypoproteinemia ∩ARF, and their confidenceC value (i.e., the probability of ARF occurrence) was 0.73~0.85; (2) the three rules were age (60~69 years old)∩ lung surgery history ∩ARF, lung surgery history ∩ thoracic adhesion ∩ARF, operation duration (≥3 h) ∩ hypoproteinemia ∩ARF, smoking history ∩ hypoproteinemia ∩ARF, and theirC value increased to 0.94 and above.
<b>Conclusion</b> Compared with logistic regression analysis, the two rules in the association rule analysis are more abundant, and the results of the three rules further narrow the high-risk range of ARF. The combination of the two methods is conducive to the joint screening of risk factors for ARF after radical resection for esophageal cancer, and the three rules are more valuable in guiding clinical intervention."
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| format | Article |
| id | doaj-art-da7e962b94c84d50a3d34ba080dfd82c |
| institution | DOAJ |
| issn | 1674-8182 |
| language | zho |
| publishDate | 2025-01-01 |
| publisher | The Editorial Department of Chinese Journal of Clinical Research |
| record_format | Article |
| series | Zhongguo linchuang yanjiu |
| spelling | doaj-art-da7e962b94c84d50a3d34ba080dfd82c2025-08-20T03:11:24ZzhoThe Editorial Department of Chinese Journal of Clinical ResearchZhongguo linchuang yanjiu1674-81822025-01-01381626610.13429/j.cnki.cjcr.2025.01.013Analysis of risk factors of acute respiratory failure after radical resection of esophageal cancer by two methodsLEI Xiuwen, ZHU Xiaolei, TIAN Long0Department of Cardiothoracic Oncology, Zhangye People's Hospital Affiliated to Hexi University, Zhangye, Gansu 734000, China"<b>Objective</b> To analyze the risk factors of acute respiratory failure (ARF) after radical resection for esophageal cancer by combining logistic regression analysis and association rule analysis. <b>Methods</b> The clinical data of 146 patients after radical resection for esophageal cancer in Zhangye People's Hospital Affiliated to Hexi University from June 2019 to June 2022 were retrospectively studied. Patients were divided into the ARF group ( n =49) and the non-ARF group ( n =97). Univariate analysis of risk factors for ARF was performed, and multivariate analysis was performed by logistic regression in two groups. The FP-Growth algorithm program was compiled in Python, and the association rule analysis was performed to calculate the effective strong association rules between the clinical features in the ARF group. <b>Results</b> Logistic regression analysis showed that the risk factors of ARF were smoking history ( OR =3.039,P =0.018), anastomotic fistula( OR =5.041,P ＜0.01), thoracic adhesion ( OR =7.993,P ＜0.01) and hypoproteinemia ( OR =3.831,P ＜0.01). The analysis of association rules showed that there were 11 effective strong association rules between clinical features: (1) the two rules were age (60~69 years old) ∩ ARF, smoking history ∩ARF, lung surgery history ∩ARF, operation duration(≥3 h) ∩ ARF, anastomotic fistula ∩ARF, thoracic adhesion ∩ARF, hypoproteinemia ∩ARF, and their confidenceC value (i.e., the probability of ARF occurrence) was 0.73~0.85; (2) the three rules were age (60~69 years old)∩ lung surgery history ∩ARF, lung surgery history ∩ thoracic adhesion ∩ARF, operation duration (≥3 h) ∩ hypoproteinemia ∩ARF, smoking history ∩ hypoproteinemia ∩ARF, and theirC value increased to 0.94 and above. <b>Conclusion</b> Compared with logistic regression analysis, the two rules in the association rule analysis are more abundant, and the results of the three rules further narrow the high-risk range of ARF. The combination of the two methods is conducive to the joint screening of risk factors for ARF after radical resection for esophageal cancer, and the three rules are more valuable in guiding clinical intervention." http://zglcyj.ijournals.cn/zglcyj/ch/reader/create_pdf.aspx?file_no=20250113&year_id=2025&quarter_id=1&falg=1radical resection for esophageal canceracute respiratory failurerisk factorlogistic regression analysisassociation rule analysis |
| spellingShingle | LEI Xiuwen, ZHU Xiaolei, TIAN Long Analysis of risk factors of acute respiratory failure after radical resection of esophageal cancer by two methods Zhongguo linchuang yanjiu radical resection for esophageal cancer acute respiratory failure risk factor logistic regression analysis association rule analysis |
| title | Analysis of risk factors of acute respiratory failure after radical resection of esophageal cancer by two methods |
| title_full | Analysis of risk factors of acute respiratory failure after radical resection of esophageal cancer by two methods |
| title_fullStr | Analysis of risk factors of acute respiratory failure after radical resection of esophageal cancer by two methods |
| title_full_unstemmed | Analysis of risk factors of acute respiratory failure after radical resection of esophageal cancer by two methods |
| title_short | Analysis of risk factors of acute respiratory failure after radical resection of esophageal cancer by two methods |
| title_sort | analysis of risk factors of acute respiratory failure after radical resection of esophageal cancer by two methods |
| topic | radical resection for esophageal cancer acute respiratory failure risk factor logistic regression analysis association rule analysis |
| url | http://zglcyj.ijournals.cn/zglcyj/ch/reader/create_pdf.aspx?file_no=20250113&year_id=2025&quarter_id=1&falg=1 |
| work_keys_str_mv | AT leixiuwenzhuxiaoleitianlong analysisofriskfactorsofacuterespiratoryfailureafterradicalresectionofesophagealcancerbytwomethods |