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利用决策树模型指导胰腺癌患者胰十二指肠切除术后的干预措施。

Guiding post-pancreaticoduodenectomy interventions for pancreatic cancer patients utilizing decision tree models.

作者信息

Wang Haixin, Shen Bo, Jia Peiheng, Li Hao, Bai Xuemei, Li Yaru, Xu Kang, Hu Pengzhen, Ding Li, Xu Na, Xia Xiaoxiao, Fang Yong, Chen Hebing, Zhang Yan, Yue Shutong

机构信息

Department of Cadre Medical, The First Medical Centre, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.

Department of Respiratory and Critical Care Medicine, The Eighth Medical Centre, Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.

出版信息

Front Oncol. 2024 May 30;14:1399297. doi: 10.3389/fonc.2024.1399297. eCollection 2024.

Abstract

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is frequently diagnosed in advanced stages, necessitating pancreaticoduodenectomy (PD) as a primary therapeutic approach. However, PD surgery can engender intricate complications. Thus, understanding the factors influencing postoperative complications documented in electronic medical records and their impact on survival rates is crucial for improving overall patient outcomes.

METHODS

A total of 749 patients were divided into two groups: 598 (79.84%) chose the RPD (Robotic pancreaticoduodenectomy) procedure and 151 (20.16%) chose the LPD (Laparoscopic pancreaticoduodenectomy) procedure. We used correlation analysis, survival analysis, and decision tree models to find the similarities and differences about postoperative complications and prognostic survival.

RESULTS

Pancreatic cancer, known for its aggressiveness, often requires pancreaticoduodenectomy as an effective treatment. In predictive models, both BMI and surgery duration weigh heavily. Lower BMI correlates with longer survival, while patients with heart disease and diabetes have lower survival rates. Complications like delayed gastric emptying, pancreatic fistula, and infection are closely linked post-surgery, prompting conjectures about their causal mechanisms. Interestingly, we found no significant correlation between nasogastric tube removal timing and delayed gastric emptying, suggesting its prompt removal post-decompression.

CONCLUSION

This study aimed to explore predictive factors for postoperative complications and survival in PD patients. Effective predictive models enable early identification of high-risk individuals, allowing timely interventions. Higher BMI, heart disease, or diabetes significantly reduce survival rates in pancreatic cancer patients post-PD. Additionally, there's no significant correlation between DGE incidence and postoperative extubation time, necessitating further investigation into its interaction with pancreatic fistula and infection.

摘要

背景

胰腺导管腺癌(PDAC)常在晚期被诊断出来,这使得胰十二指肠切除术(PD)成为主要的治疗方法。然而,PD手术可能引发复杂的并发症。因此,了解电子病历中记录的影响术后并发症的因素及其对生存率的影响,对于改善患者的总体预后至关重要。

方法

总共749例患者被分为两组:598例(79.84%)选择机器人胰十二指肠切除术(RPD),151例(20.16%)选择腹腔镜胰十二指肠切除术(LPD)。我们使用相关性分析、生存分析和决策树模型来找出术后并发症和预后生存方面的异同。

结果

以侵袭性著称的胰腺癌通常需要胰十二指肠切除术作为有效的治疗方法。在预测模型中,BMI和手术时长都很重要。较低的BMI与较长的生存期相关,而患有心脏病和糖尿病的患者生存率较低。像胃排空延迟、胰瘘和感染等并发症在手术后密切相关,这引发了对其因果机制的猜测。有趣的是,我们发现鼻胃管拔除时间与胃排空延迟之间没有显著相关性,这表明在减压后应及时拔除。

结论

本研究旨在探索PD患者术后并发症和生存的预测因素。有效的预测模型能够早期识别高危个体,从而进行及时干预。较高的BMI、心脏病或糖尿病会显著降低胰腺癌患者PD术后的生存率。此外,胃排空延迟的发生率与术后拔管时间之间没有显著相关性,有必要进一步研究其与胰瘘和感染的相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81ba/11169653/9b5dcd046dbc/fonc-14-1399297-g001.jpg

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