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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Matsui, Hiroto Shindo, Yoshitaro Yamada, Daisaku Ogihara, Hiroyuki Tokumitsu, Yukio Nakajima, Masao Iida, Michihisa Suzuki, Nobuaki Takeda, Shigeru Nakagami, Yuki Kobayashi, Shogo Eguchi, Hidetoshi Ioka, Tatsuya Hamamoto, Yoshihiko Nagano, Hiroaki |
| Abstract | Background Since clinically relevant postoperative pancreatic fistula (CR-POPF) can cause intra-abdominal hemorrhage and abscesses, leading to surgery-related deaths after pancreaticoduodenectomy (PD), its preoperative prediction is important to develop strategies for surgical procedures and perioperative management. This study aimed to establish a novel prediction model for CR-POPF using preoperative markers. Methods On a training set of 180 patients who underwent PD at the Yamaguchi University Hospital, a combination of CR-POPF predictors were explored using the leave-one-out method with a unique discrete Bayes classifier. This predictive model was confirmed using a validation set of 366 patients who underwent PD at the Osaka University Hospital. Results In the training set, CR-POPF occurred in 60 (33%) of 180 patients and 130 (36%) of 366 patients in the validation set using selected markers. In patients with pancreatic ductal adenocarcinoma (PDAC), the main pancreatic duct (MPD) index showed the highest prognostic performance and could differentiate CR-POPF with 87% sensitivity and 81% specificity among 84 patients in the training set. In the validation set, the sensitivity and specificity of the MPD index-based model for 130 PDAC samples were 93% and 87%, respectively. In patients with non-PDAC, the MPD index/body mass index (BMI) combination showed the highest prognostic performance and could differentiate CR-POPF with 84% sensitivity and 57% specificity among 96 patients in the training set. In the validation set, the sensitivity and specificity of the MPD index/BMI-based model for 236 non-PDAC samples were 85% and 53%, respectively. Conclusion We developed a novel prediction model for pancreatic fistulas after PD using only preoperative markers. The MPD index and MPD index/BMI combination will be useful for CR-POPF assessment in PDAC and non-PDAC samples, respectively. |
| Related Links | https://bmcsurg.biomedcentral.com/counter/pdf/10.1186/s12893-023-02213-1.pdf |
| Ending Page | 10 |
| Page Count | 10 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| ISSN | 14712482 |
| DOI | 10.1186/s12893-023-02213-1 |
| Journal | BMC Surgery |
| Issue Number | 1 |
| Volume Number | 23 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2023-10-12 |
| Access Restriction | Open |
| Subject Keyword | Surgery Internal Medicine Postoperative pancreatic fistula Pancreaticoduodenectomy Discrete Bayes classifier Prediction model |
| Content Type | Text |
| Resource Type | Article |
| Subject | Surgery |
| Journal Impact Factor | 1.6/2023 |
| 5-Year Journal Impact Factor | 1.9/2023 |
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