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Jin Q, Zhang J, Jin J, Zhang J, Fei S, Liu Y, Xu Z, Shi Y. Preoperative body composition measured by bioelectrical impedance analysis can predict pancreatic fistula after pancreatic surgery. Nutr Clin Pract 2024. [PMID: 39010727 DOI: 10.1002/ncp.11192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 06/23/2024] [Accepted: 06/25/2024] [Indexed: 07/17/2024] Open
Abstract
BACKGROUND Postoperative pancreatic fistula (POPF) remains one of the most severe complications after pancreatic surgery. The methods for predicting pancreatic fistula are limited. We aimed to investigate the predictive value of body composition parameters measured by preoperative bioelectrical impedance analysis (BIA) on the development of POPF. METHODS A total of 168 consecutive patients undergoing pancreatic surgery from March 2022 to December 2022 at our institution were included in the study and randomly assigned at a 3:2 ratio to the training group and the validation group. All data, including previously reported risk factors for POPF and parameters measured by BIA, were collected. Risk factors were analyzed by univariable and multivariable logistic regression analysis. A prediction model was established to predict the development of POPF based on these parameters. RESULTS POPF occurred in 41 of 168 (24.4%) patients. In the training group of 101 enrolled patients, visceral fat area (VFA) (odds ratio [OR] = 1.077, P = 0.001) and fat mass index (FMI) (OR = 0.628, P = 0.027) were found to be independently associated with POPF according to multivariable analysis. A prediction model including VFA and FMI was established to predict the development of POPF with an area under the receiver operating characteristic curve (AUC) of 0.753. The efficacy of the prediction model was also confirmed in the internal validation group (AUC 0.785, 95% CI 0.659-0.911). CONCLUSIONS Preoperative assessment of body fat distribution by BIA can predict the risk of POPF after pancreatic surgery.
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Affiliation(s)
- Qianwen Jin
- Department of Clinical Nutrition, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jun Zhang
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jiabin Jin
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jiaqiang Zhang
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Si Fei
- Department of Clinical Nutrition, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yang Liu
- Department of Clinical Nutrition, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Zhiwei Xu
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yongmei Shi
- Department of Clinical Nutrition, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Department of Clinical Nutrition, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
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Yang F, Windsor JA, Fu DL. Optimizing prediction models for pancreatic fistula after pancreatectomy: Current status and future perspectives. World J Gastroenterol 2024; 30:1329-1345. [PMID: 38596504 PMCID: PMC11000089 DOI: 10.3748/wjg.v30.i10.1329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/15/2024] [Accepted: 02/25/2024] [Indexed: 03/14/2024] Open
Abstract
Postoperative pancreatic fistula (POPF) is a frequent complication after pancreatectomy, leading to increased morbidity and mortality. Optimizing prediction models for POPF has emerged as a critical focus in surgical research. Although over sixty models following pancreaticoduodenectomy, predominantly reliant on a variety of clinical, surgical, and radiological parameters, have been documented, their predictive accuracy remains suboptimal in external validation and across diverse populations. As models after distal pancreatectomy continue to be progressively reported, their external validation is eagerly anticipated. Conversely, POPF prediction after central pancreatectomy is in its nascent stage, warranting urgent need for further development and validation. The potential of machine learning and big data analytics offers promising prospects for enhancing the accuracy of prediction models by incorporating an extensive array of variables and optimizing algorithm performance. Moreover, there is potential for the development of personalized prediction models based on patient- or pancreas-specific factors and postoperative serum or drain fluid biomarkers to improve accuracy in identifying individuals at risk of POPF. In the future, prospective multicenter studies and the integration of novel imaging technologies, such as artificial intelligence-based radiomics, may further refine predictive models. Addressing these issues is anticipated to revolutionize risk stratification, clinical decision-making, and postoperative management in patients undergoing pancreatectomy.
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Affiliation(s)
- Feng Yang
- Department of Pancreatic Surgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
| | - John A Windsor
- Surgical and Translational Research Centre, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1142, New Zealand
| | - De-Liang Fu
- Department of Pancreatic Surgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai 200040, China
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Nakajima T, Ikuta S, Fujikawa M, Ikuta L, Matsuki G, Ichise N, Kasai M, Okamoto R, Nakamoto Y, Aihara T, Yanagi H, Yamanaka N. High hand grip strength is a significant risk factor and a useful predictor of postoperative pancreatic fistula following pancreaticoduodenectomy. Langenbecks Arch Surg 2024; 409:85. [PMID: 38438660 DOI: 10.1007/s00423-024-03274-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 02/27/2024] [Indexed: 03/06/2024]
Abstract
BACKGROUND Postoperative pancreatic fistula (POPF) is one of the most critical complications of pancreaticoduodenectomy (PD). Studies on predictive factors for POPF that can be identified preoperatively are limited. Recent reports have highlighted the association between the preoperative nutritional status, including sarcopenia, and postoperative complications. We examined preoperative risk factors for POPF after PD, focusing on nutritional indicators. METHODS A total of 153 consecutive patients who underwent PD at our institution were enrolled in this study. Preoperative nutritional parameters, including hand grip strength (HGS) and skeletal muscle mass as components of sarcopenia, were incorporated into the analysis. POPFs were categorized according to the International Study Group of Pancreatic Fistula (ISGPF) definition as biochemical (grade A) or clinically relevant (CR-POPF; grades B and C). RESULTS Thirty-seven of the 153 patients (24.1%) fulfilled the ISGPF definition of CR-POPF postoperatively. In the univariate analysis, the incidence of CR-POPF was associated with male sex, non-pancreatic tumor diseases, a high body mass index, a high HGS and a high skeletal muscle mass index. In the multivariate analysis, non-pancreatic tumor diseases and an HGS ≥23.0 kg were selected as independent risk factors for CR-POPF (P <0.05). CONCLUSIONS A high HGS, a screening tool for sarcopenia, was a risk factor for CR-POPF. It can accurately serve as a useful predictor of POPF risk in patients undergoing PD. These results highlight the potential of sarcopenia to reduce the incidence of POPF and highlight the need to clarify the mechanism of POPF occurrence.
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Affiliation(s)
- Takayoshi Nakajima
- Department of Surgery, Meiwa Hospital, 4-31 Agenaruo-cho, Nishinomiya, Hyogo, 663-8186, Japan.
| | - Shinichi Ikuta
- Department of Surgery, Meiwa Hospital, 4-31 Agenaruo-cho, Nishinomiya, Hyogo, 663-8186, Japan
| | - Masataka Fujikawa
- Department of Surgery, Meiwa Hospital, 4-31 Agenaruo-cho, Nishinomiya, Hyogo, 663-8186, Japan
| | - Lisa Ikuta
- Department of Surgery, Meiwa Hospital, 4-31 Agenaruo-cho, Nishinomiya, Hyogo, 663-8186, Japan
| | - Goshi Matsuki
- Department of Surgery, Meiwa Hospital, 4-31 Agenaruo-cho, Nishinomiya, Hyogo, 663-8186, Japan
| | - Noriko Ichise
- Department of Surgery, Meiwa Hospital, 4-31 Agenaruo-cho, Nishinomiya, Hyogo, 663-8186, Japan
| | - Meidai Kasai
- Department of Surgery, Meiwa Hospital, 4-31 Agenaruo-cho, Nishinomiya, Hyogo, 663-8186, Japan
| | - Ryo Okamoto
- Department of Surgery, Meiwa Hospital, 4-31 Agenaruo-cho, Nishinomiya, Hyogo, 663-8186, Japan
| | - Yoshihiko Nakamoto
- Department of Surgery, Meiwa Hospital, 4-31 Agenaruo-cho, Nishinomiya, Hyogo, 663-8186, Japan
| | - Tsukasa Aihara
- Department of Surgery, Meiwa Hospital, 4-31 Agenaruo-cho, Nishinomiya, Hyogo, 663-8186, Japan
| | - Hidenori Yanagi
- Department of Surgery, Meiwa Hospital, 4-31 Agenaruo-cho, Nishinomiya, Hyogo, 663-8186, Japan
| | - Naoki Yamanaka
- Department of Surgery, Meiwa Hospital, 4-31 Agenaruo-cho, Nishinomiya, Hyogo, 663-8186, Japan
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Lee W, Park HJ, Lee HJ, Song KB, Hwang DW, Lee JH, Lim K, Ko Y, Kim HJ, Kim KW, Kim SC. Deep learning-based prediction of post-pancreaticoduodenectomy pancreatic fistula. Sci Rep 2024; 14:5089. [PMID: 38429308 PMCID: PMC10907568 DOI: 10.1038/s41598-024-51777-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 01/09/2024] [Indexed: 03/03/2024] Open
Abstract
Postoperative pancreatic fistula is a life-threatening complication with an unmet need for accurate prediction. This study was aimed to develop preoperative artificial intelligence-based prediction models. Patients who underwent pancreaticoduodenectomy were enrolled and stratified into model development and validation sets by surgery between 2016 and 2017 or in 2018, respectively. Machine learning models based on clinical and body composition data, and deep learning models based on computed tomographic data, were developed, combined by ensemble voting, and final models were selected comparison with earlier model. Among the 1333 participants (training, n = 881; test, n = 452), postoperative pancreatic fistula occurred in 421 (47.8%) and 134 (31.8%) and clinically relevant postoperative pancreatic fistula occurred in 59 (6.7%) and 27 (6.0%) participants in the training and test datasets, respectively. In the test dataset, the area under the receiver operating curve [AUC (95% confidence interval)] of the selected preoperative model for predicting all and clinically relevant postoperative pancreatic fistula was 0.75 (0.71-0.80) and 0.68 (0.58-0.78). The ensemble model showed better predictive performance than the individual ML and DL models.
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Affiliation(s)
- Woohyung Lee
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Asan Medical Center, Brain Korea21 Project, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea
| | - Hyo Jung Park
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea
| | - Hack-Jin Lee
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Asan Medical Center, Brain Korea21 Project, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea
- R&D Team, DoAI Inc., Seongnam-si, Gyeonggi-do, Republic of Korea
| | - Ki Byung Song
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Asan Medical Center, Brain Korea21 Project, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea
| | - Dae Wook Hwang
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Asan Medical Center, Brain Korea21 Project, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea
| | - Jae Hoon Lee
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Asan Medical Center, Brain Korea21 Project, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea
| | - Kyongmook Lim
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Asan Medical Center, Brain Korea21 Project, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea
- R&D Team, DoAI Inc., Seongnam-si, Gyeonggi-do, Republic of Korea
| | - Yousun Ko
- Department of Convergence Medicine and Radiology, Research Institute of Radiology and Institute of Biomedical Engineering, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Hyoung Jung Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea
| | - Kyung Won Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea.
| | - Song Cheol Kim
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Asan Medical Center, Brain Korea21 Project, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea.
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Alhulaili ZM, Linnemann RJ, Dascau L, Pleijhuis RG, Klaase JM. A Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis analysis to evaluate the quality of reporting of postoperative pancreatic fistula prediction models after pancreatoduodenectomy: A systematic review. Surgery 2023; 174:684-691. [PMID: 37296054 DOI: 10.1016/j.surg.2023.04.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 03/06/2023] [Accepted: 04/27/2023] [Indexed: 06/12/2023]
Abstract
BACKGROUND Postoperative pancreatic fistula is a frequent and potentially lethal complication after pancreatoduodenectomy. Several models have been developed to predict postoperative pancreatic fistula risk. This study was performed to evaluate the quality of reporting of postoperative pancreatic fistula prediction models after pancreatoduodenectomy using the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist that provides guidelines on reporting prediction models to enhance transparency and to help in the decision-making regarding the implementation of the appropriate risk models into clinical practice. METHODS Studies that described prediction models to predict postoperative pancreatic fistula after pancreatoduodenectomy were searched according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The TRIPOD checklist was used to evaluate the adherence rate. The area under the curve and other performance measures were extracted if reported. A quadrant matrix chart is created to plot the area under the curve against TRIPOD adherence rate to find models with a combination of above-average TRIPOD adherence and area under the curve. RESULTS In total, 52 predictive models were included (23 development, 15 external validation, 4 incremental value, and 10 development and external validation). No risk model achieved 100% adherence to the TRIPOD. The mean adherence rate was 65%. Most authors failed to report on missing data and actions to blind assessment of predictors. Thirteen models had an above-average performance for TRIPOD checklist adherence and area under the curve. CONCLUSION Although the average TRIPOD adherence rate for postoperative pancreatic fistula models after pancreatoduodenectomy was 65%, higher compared to other published models, it does not meet TRIPOD standards for transparency. This study identified 13 models that performed above average in TRIPOD adherence and area under the curve, which could be the appropriate models to be used in clinical practice.
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Affiliation(s)
- Zahraa M Alhulaili
- Department of Hepato-Pancreato-Biliary Surgery and Liver Transplantation, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Ralph J Linnemann
- Department of Hepato-Pancreato-Biliary Surgery and Liver Transplantation, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Larisa Dascau
- Department of Surgery, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Rick G Pleijhuis
- Department of Internal Medicine, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Joost M Klaase
- Department of Hepato-Pancreato-Biliary Surgery and Liver Transplantation, University of Groningen, University Medical Center Groningen, the Netherlands.
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Perra T, Sotgiu G, Porcu A. Sarcopenia and Risk of Pancreatic Fistula after Pancreatic Surgery: A Systematic Review. J Clin Med 2022; 11:jcm11144144. [PMID: 35887908 PMCID: PMC9319174 DOI: 10.3390/jcm11144144] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/06/2022] [Accepted: 07/14/2022] [Indexed: 12/22/2022] Open
Abstract
Postoperative pancreatic fistula (POPF) is one of the most critical complications after pancreatic surgery. The relationship between sarcopenia and outcomes following this type of surgery is debated. The aim of this review was to assess the impact of sarcopenia on the risk of POPF. A literature search was performed using the PubMed database and the reference lists of relevant articles to identify papers about the impact of sarcopenia on POPF in pancreatic surgery. Twenty-one studies published between 2016 and 2021 with a total of 4068 patients were included. Some studies observed a significant difference in the incidence of POPF between the sarcopenic and non-sarcopenic patients undergoing pancreatoduodenectomy. Interestingly, there was a trend of a lower POPF rate in sarcopenic patients than in non-sarcopenic patients. Only one study included patients undergoing distal pancreatectomy specifically. The role of sarcopenia in surgical outcomes is still unclear. A combination of objective CT measurements could be used to predict POPF. It could be assessed by routine preoperative staging CT and could improve preoperative risk stratification in patients undergoing pancreatic surgery.
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Development of a prediction model of pancreatic fistula after duodenopancreatectomy and soft pancreas by assessing the preoperative image. Langenbecks Arch Surg 2022; 407:2363-2372. [DOI: 10.1007/s00423-022-02564-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 05/19/2022] [Indexed: 10/18/2022]
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