Jatin Singh, Xin Meng, Joseph K. Leader, John Ryan, Ernest G. Chan, Norihisa Shigemura, Chadi A. Hage, Pablo G. Sanchez, Jiantao Pu
{"title":"基于 CT 的肺大小匹配在系统性硬化肺移植延迟胸腔闭合中的应用","authors":"Jatin Singh, Xin Meng, Joseph K. Leader, John Ryan, Ernest G. Chan, Norihisa Shigemura, Chadi A. Hage, Pablo G. Sanchez, Jiantao Pu","doi":"10.1111/ctr.70041","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Purpose</h3>\n \n <p>Delayed chest closure (DCC) during lung transplantation (LTx) is a controversial surgical approach that lacks research in systemic sclerosis (SSc) patients. We investigated outcomes, clinical risk factors, and CT-based lung size-matching parameters associated with DCC in SSc recipients.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>This retrospective study included 92 SSc recipients (age 51 years ± 10, 56/92 (61.0%) females) who underwent bilateral LTx between 2007 and 2020. Of the recipients, 34.8% (32/92) underwent DCC. Recipient lung and chest cavity volumes were automatically computed from CT imaging using deep learning algorithms. Survival between groups was compared using Kaplan–Meier analysis. Multivariate logistic regression was used to identify risk factors and predict DCC occurrence using preoperative variables.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Recipients who underwent DCC had longer <i>total vent duration</i> (<i>p</i> = 0.001), more use of <i>postoperative mechanical support</i> (<i>p</i> = 0.001), longer <i>ICU length of stay</i> (<i>p</i> = 0.008), and lower incidence of <i>pneumonia</i> post-operation (<i>p</i> = 0.031). No significant difference in survival was observed between DCC and PCC recipients at 30 days (<i>p</i> = 0.713), 90 days (<i>p</i> = 0.267), 1 year (<i>p</i> = 0.941), and 5 years (<i>p</i> = 0.651). Clinical risk factors for DCC included <i>BMI ></i> <i>30 kg/m</i><sup>2</sup> (<i>p</i> = 0.009)<i>, tracheostomy</i> (<i>p</i> = 0.002)<i>, atrial fibrillation</i> (<i>p</i> = 0.012), decreased <i>preoperative FEV1/FVC</i> (<i>p</i> = 0.013), and <i>previous chest operation</i> (<i>p</i> = 0.020). Two CT-based measurements of lung matching were significantly associated with DCC occurrence (<i>p</i> = 0.021 and 0.050). The regression model achieved a mean AUC of 0.82 (0.70, 0.94) in retrospectively predicting DCC occurrence.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>SSc recipients undergoing DCC have similar survival rates but experience more complications than PCC recipients. Clinical risk factors and CT-based size matching can be leveraged to predict DCC pre-transplant.</p>\n </section>\n </div>","PeriodicalId":10467,"journal":{"name":"Clinical Transplantation","volume":"38 12","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CT-Based Lung Size Matching in Delayed Chest Closure for Systemic Sclerosis Lung Transplantation\",\"authors\":\"Jatin Singh, Xin Meng, Joseph K. Leader, John Ryan, Ernest G. Chan, Norihisa Shigemura, Chadi A. Hage, Pablo G. Sanchez, Jiantao Pu\",\"doi\":\"10.1111/ctr.70041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Purpose</h3>\\n \\n <p>Delayed chest closure (DCC) during lung transplantation (LTx) is a controversial surgical approach that lacks research in systemic sclerosis (SSc) patients. We investigated outcomes, clinical risk factors, and CT-based lung size-matching parameters associated with DCC in SSc recipients.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>This retrospective study included 92 SSc recipients (age 51 years ± 10, 56/92 (61.0%) females) who underwent bilateral LTx between 2007 and 2020. Of the recipients, 34.8% (32/92) underwent DCC. Recipient lung and chest cavity volumes were automatically computed from CT imaging using deep learning algorithms. Survival between groups was compared using Kaplan–Meier analysis. Multivariate logistic regression was used to identify risk factors and predict DCC occurrence using preoperative variables.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Recipients who underwent DCC had longer <i>total vent duration</i> (<i>p</i> = 0.001), more use of <i>postoperative mechanical support</i> (<i>p</i> = 0.001), longer <i>ICU length of stay</i> (<i>p</i> = 0.008), and lower incidence of <i>pneumonia</i> post-operation (<i>p</i> = 0.031). No significant difference in survival was observed between DCC and PCC recipients at 30 days (<i>p</i> = 0.713), 90 days (<i>p</i> = 0.267), 1 year (<i>p</i> = 0.941), and 5 years (<i>p</i> = 0.651). Clinical risk factors for DCC included <i>BMI ></i> <i>30 kg/m</i><sup>2</sup> (<i>p</i> = 0.009)<i>, tracheostomy</i> (<i>p</i> = 0.002)<i>, atrial fibrillation</i> (<i>p</i> = 0.012), decreased <i>preoperative FEV1/FVC</i> (<i>p</i> = 0.013), and <i>previous chest operation</i> (<i>p</i> = 0.020). Two CT-based measurements of lung matching were significantly associated with DCC occurrence (<i>p</i> = 0.021 and 0.050). The regression model achieved a mean AUC of 0.82 (0.70, 0.94) in retrospectively predicting DCC occurrence.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>SSc recipients undergoing DCC have similar survival rates but experience more complications than PCC recipients. Clinical risk factors and CT-based size matching can be leveraged to predict DCC pre-transplant.</p>\\n </section>\\n </div>\",\"PeriodicalId\":10467,\"journal\":{\"name\":\"Clinical Transplantation\",\"volume\":\"38 12\",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-11-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Transplantation\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/ctr.70041\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SURGERY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Transplantation","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/ctr.70041","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SURGERY","Score":null,"Total":0}
CT-Based Lung Size Matching in Delayed Chest Closure for Systemic Sclerosis Lung Transplantation
Purpose
Delayed chest closure (DCC) during lung transplantation (LTx) is a controversial surgical approach that lacks research in systemic sclerosis (SSc) patients. We investigated outcomes, clinical risk factors, and CT-based lung size-matching parameters associated with DCC in SSc recipients.
Methods
This retrospective study included 92 SSc recipients (age 51 years ± 10, 56/92 (61.0%) females) who underwent bilateral LTx between 2007 and 2020. Of the recipients, 34.8% (32/92) underwent DCC. Recipient lung and chest cavity volumes were automatically computed from CT imaging using deep learning algorithms. Survival between groups was compared using Kaplan–Meier analysis. Multivariate logistic regression was used to identify risk factors and predict DCC occurrence using preoperative variables.
Results
Recipients who underwent DCC had longer total vent duration (p = 0.001), more use of postoperative mechanical support (p = 0.001), longer ICU length of stay (p = 0.008), and lower incidence of pneumonia post-operation (p = 0.031). No significant difference in survival was observed between DCC and PCC recipients at 30 days (p = 0.713), 90 days (p = 0.267), 1 year (p = 0.941), and 5 years (p = 0.651). Clinical risk factors for DCC included BMI >30 kg/m2 (p = 0.009), tracheostomy (p = 0.002), atrial fibrillation (p = 0.012), decreased preoperative FEV1/FVC (p = 0.013), and previous chest operation (p = 0.020). Two CT-based measurements of lung matching were significantly associated with DCC occurrence (p = 0.021 and 0.050). The regression model achieved a mean AUC of 0.82 (0.70, 0.94) in retrospectively predicting DCC occurrence.
Conclusion
SSc recipients undergoing DCC have similar survival rates but experience more complications than PCC recipients. Clinical risk factors and CT-based size matching can be leveraged to predict DCC pre-transplant.
期刊介绍：
Clinical Transplantation: The Journal of Clinical and Translational Research aims to serve as a channel of rapid communication for all those involved in the care of patients who require, or have had, organ or tissue transplants, including: kidney, intestine, liver, pancreas, islets, heart, heart valves, lung, bone marrow, cornea, skin, bone, and cartilage, viable or stored.
Published monthly, Clinical Transplantation’s scope is focused on the complete spectrum of present transplant therapies, as well as also those that are experimental or may become possible in future. Topics include:
Immunology and immunosuppression;
Patient preparation;
Social, ethical, and psychological issues;
Complications, short- and long-term results;
Artificial organs;
Donation and preservation of organ and tissue;
Translational studies;
Advances in tissue typing;
Updates on transplant pathology;.
Clinical and translational studies are particularly welcome, as well as focused reviews. Full-length papers and short communications are invited. Clinical reviews are encouraged, as well as seminal papers in basic science which might lead to immediate clinical application. Prominence is regularly given to the results of cooperative surveys conducted by the organ and tissue transplant registries.
Clinical Transplantation: The Journal of Clinical and Translational Research is essential reading for clinicians and researchers in the diverse field of transplantation: surgeons; clinical immunologists; cryobiologists; hematologists; gastroenterologists; hepatologists; pulmonologists; nephrologists; cardiologists; and endocrinologists. It will also be of interest to sociologists, psychologists, research workers, and to all health professionals whose combined efforts will improve the prognosis of transplant recipients.
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