Establishment of risk prediction model of postoperative pancreatic fistula after pancreatoduodenectomy: 2016 edition of definition and grading system of pancreatic fistula: a single center experience with 223 cases

Incidence of clinically relevant postoperative pancreatic fistula in patients undergoing open and minimally invasive pancreatoduodenectomy: a population-based study

Purpose

Postoperative pancreatic fistula (POPF) remains a devastating complication of pancreatoduodenectomy (PD). Minimally invasive PD (MIPD), including laparoscopic (LPD) and robotic (RPD) approaches, have comparable POPF rates to open PD (OPD). However, we hypothesize that the likelihood of having a more severe POPF, as defined as clinically relevant POPF (CR-POPF), would be higher in an MIPD relative to OPD.

Methods

The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) targeted pancreatectomy dataset (2014-2020) was reviewed for any POPF after OPD. Propensity score matching (PSM) compared MIPD to OPD, and then RPD to LPD.

Results

Among 3,083 patients who developed a POPF, 2,843 (92.2%) underwent OPD and 240 (7.8%) MIPD; of these, 25.0% were LPD (n = 60) and 75.0% RPD (n = 180). Grade B POPF was observed in 45.4% (n = 1,400), and grade C in 6.0% (n = 185). After PSM, MIPD patients had higher rates of CR-POPF (47.3% OPD vs. 54.4% MIPD, p = 0.037), as well as higher reoperation (9.1% vs. 15.3%, p = 0.006), delayed gastric emptying (29.2% vs. 35.8%, p = 0.041), and readmission rates (28.2% vs. 35.1%, p = 0.032). However, CR-POPF rates were comparable between LPD and RPD (56.8% vs. 49.3%, p = 0.408).

Conclusion

The impact of POPF is more clinically pronounced after MIPD than OPD with a more complex postoperative course. The difference appears to be attributed to the minimally invasive environment itself as no difference was noted between LPD and RPD. A clear biological explanation of this clinical observation remains missing. Further studies are warranted.

Optimizing prediction models for pancreatic fistula after pancreatectomy: Current status and future perspectives

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.

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

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.

Artificial Intelligence and Big Data Technologies in the Construction of Surgical Risk Prediction Model for Patients with Coronary Artery Bypass Grafting

The objective of this work was to predict the risk of mortality rate in patients with coronary artery bypass grafting (CABG) based on the risk prediction model of CABG using artificial intelligence (AI) and big data technologies. The clinical data of 2,364 patients undergoing CABG in our hospital from January 2019 to August 2021 were collected in this work. Based on AI and big data technology, business requirement analysis, system requirement analysis, complication prediction module, big data mining technology, and model building are carried out, respectively; the successful CABG risk prediction system includes case feature analysis service, risk warning service, and case retrieval service. The commonly used precision, recall, and F1-score were adopted to evaluate the quality of the gradient-boosted tree (GBT) model. The analysis proved that the GBT model was the best in terms of precision, F1-score, and area under the receiver operating characteristic curve (ROC). According to the CABG risk prediction model, 1,382 patients had a score of <0, 463 patients had a score of 0 ≤ score ≤ 2, 252 patients had a score of 2 < score ≤ 5, and 267 patients had a score of >5, which were stratified into four groups: A, B, C, and D. The actual number of in-hospital deaths was 25, and the in-hospital mortality rate was 1.05%. The mortality rate predicted by the CABG risk prediction model was 2.67 ± 1.82% (95% confidential interval (CI) (2.87-2.98)), which was higher than the actual value. The CABG risk prediction model showed the credible results only in group B with AUC = 0.763 > 0.7. In group B, 3 patients actually died, the actual mortality rate was 0.33%, and the predicted mortality rate was 0.96 ± 0.78 (95% CI (0.82-0.87)), which overestimated the mortality rate of patients in group B. It successfully constructed a CABG risk prediction model based on the AI and big data technologies, which would overestimate the mortality of patients with intermediate risk, and it is suitable for different types of heart diseases through continuous research and development and innovation, and provides clinical guidance value.

Risk factors for achieving textbook outcome after laparoscopic duodenum-preserving total pancreatic head resection: a retrospective cohort study

INTRODUCTION

The risk factors for achieving textbook outcome (TO) after laparoscopic duodenum-preserving total pancreatic head resection (LDPPHR-t) are unknown, and no relevant articles have been reported so far. The aim of this study was to identify the risk factors for achieving TO after LDPPHR-t.

METHODS

The risk factors for achieving TO after LDPPHR-t were retrospectively evaluated by logistic regression analysis in 31 consecutive patients from May 2020 to December 2021.

RESULTS

All LDPPHR-t procedures were successfully performed without conversion. There was no death within 90 days after surgery and no readmission within 30 days after discharge. The percentage of achieving TO after LDPPHR-t was 61.3% (19/31). Among the six TO items, the postoperative complication of grade B/C postoperative pancreatic fistula (POPF) occurred most frequently with 22.6%, followed by grade B/C bile leakage with 19.4%, Clavien-Dindo≥III complications with 19.4%, and grade B/C postpancreatectomy hemorrhage with 16.1%. POPF was the major obstacle to achieve TO after LDPPHR-t. Placing an endoscopic nasobiliary drainage (ENBD) catheter and prolonged operation time (>311 min) were significantly associated with the decreased probability of achieving TO after LDPPHR-t (odd ratio (OR), 25.775; P =0.012 and OR, 16.378; P =0.020, respectively). Placing an ENBD catheter was the only significant independent risk factor for POPF after LDPPHR-t (OR, 19.580; P =0.017). Bile leakage was the independent risk factor for postpancreatectomy hemorrhage after LDPPHR-t (OR, 15.754; P =0.040). The prolonged operation time was significantly correlated with Clavien-Dindo grade≥III complications after LDPPHR-t (OR, 19.126; P =0.024).

CONCLUSION

Placing the ENBD catheter was the independent risk factor for POPF and achieving TO after LDPPHR-t. In order to reduce POPF and increase the probability of achieving TO, placing an ENBD catheter should be avoided prior to LDPPHR-t.

Effects of body mass index and serum albumin on overall survival in patients with cancer undergoing pancreaticoduodenectomy: a single-center retrospective cohort study

Objectives

We aimed to explore whether body mass index (BMI) and albumin were associated with overall survival (OS) in individuals who underwent pancreaticoduodenectomy (PD) for cancer.

Methods

Three-hundred twenty-nine consecutive patients who underwent PD for cancer were enrolled from January 2020 to December 2020. All clinicopathological information was extracted based on medical records. The survival follow-ups were regularly performed and ended on June 30, 2021. The Kaplan-Meier survival analysis and univariate and multivariate Cox proportional-hazards models were used to assess the association of BMI and albumin with OS.

Results

Of the 329 patients, 186 (56.5%) were male, and median age at admission was 65.0 (56.0–71.0) years. There were 258 patients (78.4%) with BMI < 25.0 kg/m² and 89 patients (27.05%) with albumin < 35.0 g/L respectively. In overall cohort, BMI < 25.0 kg/m² was associated with OS (adjusted HR = 3.516, 95% CI = 1.076–11.492, P = 0.037). In contrast, albumin < 35.0 g/L did not affect OS. Subgroup analysis showed, in patients with pancreas lesion, BMI < 25.0 kg/m² had a higher risk for OS compared to BMI ≥ 25.0 kg/m² (adjusted HR = 3.209, 95% CI = 0.985–10.451, P = 0.048), while albumin < 35.0 g/L was not linked to OS. In patients with lesion in ampulla of Vater, duodenum, or common bile duct, there was no significant association of BMI and albumin with OS.

Conclusions

BMI, rather than serum albumin, was associated with OS in patients who underwent PD for cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02678-z.