Risk Factors and a New Prediction Model for Pancreatic Fistula After Pancreaticoduodenectomy

Impact of soft pancreas on pancreaticoduodenectomy outcomes and the development of the preoperative soft pancreas risk score

Backgrounds/Aims

Pancreatic texture is difficult to predict without palpation. Soft pancreatic texture is associated with increased post-operative complications, including postoperative pancreatic fistula (POPF), cardiac, and respiratory complications. We aimed to develop a calculator predicting pancreatic texture using patient factors and to illustrate complications from soft pancreatic texture following pancreaticoduodenectomy.

Methods

Data was collected from the 2016 to 2021 American College of Surgeons National Surgical Quality Improvement database including 17,706 pancreaticoduodenectomy cases. Patients were categorized into two cohorts based on pancreatic texture (9,686 hard, 8,020 soft). Multivariable modeling assessed the impact of patient factors on complications, mortality, and pancreatic texture. These preoperative factors were integrated into a risk calculator (preoperative soft pancreas risk score [PSPRS]) that predicts pancreatic texture.

Results

Patients with a soft pancreas had higher rates of postoperative complications compared to those with a hard pancreas (56.5% vs 42.2%; p < 0.001), particularly a threefold increase in POPF rate, and at least a twofold increase in rates of acute kidney injury, deep organ space infection, septic shock, and prolonged length of stay. Female sex (odds ratio [OR]: 1.14, confidence interval [CI]: 1.06-1.22, p < 0.001) and higher body mass index (OR: 1.12, CI: 1.09-1.16, p < 0.001) were independently associated with a soft pancreas. PSPRS ≥6 correctly identified >40% of patients preoperatively as having a hard pancreas (68.9% specificity).

Conclusions

A soft pancreas was independently associated with serious postoperative complications. Our results were integrated into a risk calculator predicting pancreatic texture from preoperative patient factors, potentially enhancing preoperative counseling and surgical decision-making.

Risk stratification of postoperative pancreatic fistula and other complications following pancreatoduodenectomy. How far are we? A scoping review

PURPOSE

Pancreatoduodenectomy (PD) is a challenging procedure which is associated with high morbidity rates. This study was performed to make an overview of risk factors included in risk stratification methods both logistic regression models and models based on artificial intelligence algorithms to predict postoperative pancreatic fistula (POPF) and other complications following PD and to provide insight in the extent to which these tools were validated.

METHODS

Five databases were searched to identify relevant studies. Calculators, equations, nomograms, and artificial intelligence models that addressed POPF and other complications were included. Only PD resections were considered eligible. There was no exclusion of the minimally invasive techniques reporting PD resections. All other pancreatic resections were excluded.

RESULTS

90 studies were included. Thirty-five studies were related to POPF, thirty-five studies were related to other complications following PD and twenty studies were related to artificial intelligence predication models after PD. Among the identified risk factors, the most used factors for POPF risk stratification were the main pancreatic duct diameter (MPD) (80%) followed by pancreatic texture (51%), whereas for other complications the most used factors were age (34%) and ASA score (29.4%). Only 26% of the evaluated risk stratification tools for POPF and other complications were externally validated. This percentage was even lower for the risk models using artificial intelligence which was 20%.

CONCLUSION

The MPD was the most used factor when stratifying the risk of POPF followed by pancreatic texture. Age and ASA score were the most used factors for the stratification of other complications. Insight in clinically relevant risk factors could help surgeons in adapting their surgical strategy and shared decision-making. This study revealed that the focus of research still lies on developing new risk models rather than model validation, hampering clinical implementation of these tools for decision support.

Dual-layer nanofibrous PCL/gelatin membrane as a sealant barrier to prevent postoperative pancreatic leakage

Post-operative pancreatic leakage is a severe surgical complication that can cause internal bleeding, infections, multiple organ damage, and even death. To prevent pancreatic leakage and enhance the protection of the suture lining and tissue regeneration, a dual-layer nanofibrous membrane composed of synthetic polymer polycaprolactone (PCL) and biopolymer gelatin was developed. The fabrication of this dual-layer (PGI-PGO) membrane was achieved through the electrospinning technique, with the inner layer (PGI) containing 2% PCL (w/v) and 10% gelatin (w/v), and the outer layer (PGO) containing 10% PCL (w/v) and 10% gelatin (w/v) in mixing ratios of 2:1 and 1:1, respectively. Experimental results indicated that a higher gelatin content reduced fiber diameter enhanced the hydrophilicity of the PGI layer compared to the PGO layer, improved the membrane's biodegradability, and increased its adhesive properties. In vitro biocompatibility assessments with L929 fibroblast cells showed enhanced cell proliferation in the PGI-PGO membrane. In vivo studies confirmed that the PGI-PGO membrane effectively protected the suture line without any instances of leakage and promoted wound healing within four weeks post-surgery. In conclusion, the nanofibrous PGI-PGO membrane demonstrates a promising therapeutic potential to prevent postoperative pancreatic leakage.

Impact of overweight on patients undergoing laparoscopic pancreaticoduodenectomy: analysis of surgical outcomes in a high-volume center

BACKGROUND

The feasibility and safety of laparoscopic pancreaticoduodenectomy (LPD) in overweight patients is still controversial. This study was designed to analyze the impact of overweight on surgical outcomes in patients undergoing LPD.

METHODS

Data from patients who underwent LPD between January 2018 and July 2022 were analyzed retrospectively. A 1:1 propensity score-matching (PSM) analysis was performed to minimize bias between groups.

RESULTS

A total of 432 patients were enrolled, with a normal weight group (n = 241) and an overweight group (n = 191). After matching, 144 patients were enrolled in each group. The results showed that the incidence of clinically relevant postoperative pancreatic fistula (CR-POPF) and delayed gastric emptying (DGE) was significantly higher in the overweight group compared to the normal weight group (P = 0.036). However, there were no significant differences in perioperative mortality (1.4% vs. 2.1%, P = 0.652) and long-term survival outcomes between malignancy patients with different body mass index (BMI) before and after PSM (all P > 0.05).

CONCLUSIONS

It is safe and feasible for overweight patients to undergo LPD with mortality and long-term survival outcomes comparable to the normal weight group. High-quality prospective randomized controlled trials are still needed.

Identifying the risk factors for pancreatic fistula after laparoscopic pancreaticoduodenectomy in patients with pancreatic cancer

BACKGROUND

Laparoscopic pancreaticoduodenectomy (LPD) is a surgical procedure for treating pancreatic cancer; however, the risk of complications remains high owing to the wide range of organs involved during the surgery and the difficulty of anastomosis. Pancreatic fistula (PF) is a major complication that not only increases the risk of postoperative infection and abdominal hemorrhage but may also cause multi-organ failure, which is a serious threat to the patient's life. This study hypothesized the risk factors for PF after LPD.

AIM

To identify the risk factors for PF after laparoscopic pancreatoduodenectomy in patients with pancreatic cancer.

METHODS

We retrospectively analyzed the data of 201 patients admitted to the Fudan University Shanghai Cancer Center between August 2022 and August 2023 who underwent LPD for pancreatic cancer. On the basis of the PF's incidence (grades B and C), patients were categorized into the PF (n = 15) and non-PF groups (n = 186). Differences in general data, preoperative laboratory indicators, and surgery-related factors between the two groups were compared and analyzed using multifactorial logistic regression and receiver-operating characteristic (ROC) curve analyses.

RESULTS

The proportions of males, combined hypertension, soft pancreatic texture, and pancreatic duct diameter ≤ 3 mm; surgery time; body mass index (BMI); and amylase (Am) level in the drainage fluid on the first postoperative day (Am > 1069 U/L) were greater in the PF group than in the non-PF group (P < 0.05), whereas the preoperative monocyte count in the PF group was lower than that in the non-PF group (all P < 0.05). The logistic regression analysis revealed that BMI > 24.91 kg/m² [odds ratio (OR) =13.978, 95% confidence interval (CI): 1.886-103.581], hypertension (OR = 8.484, 95%CI: 1.22-58.994), soft pancreatic texture (OR = 42.015, 95%CI: 5.698-309.782), and operation time > 414 min (OR = 15.41, 95%CI: 1.63-145.674) were risk factors for the development of PF after LPD for pancreatic cancer (all P < 0.05). The areas under the ROC curve for BMI, hypertension, soft pancreatic texture, and time prediction of PF surgery were 0.655, 0.661, 0.873, and 0.758, respectively.

CONCLUSION

BMI (> 24.91 kg/m²), hypertension, soft pancreatic texture, and operation time (> 414 min) are considered to be the risk factors for postoperative PF.

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.

Robotic enucleation & uncinectomy of complex lesions of the proximal pancreas

BACKGROUND

Malignant tumours within the proximal pancreas traditionally require pancreaticoduodenectomy (PD) for cure. For smaller lesions with borderline malignant potential the risk/benefit of PD becomes difficult to justify. Robotic approaches to these lesions allow for parenchymal preserving resection with reduced complication profile without oncological compromise.

METHODS

A review of a single surgeons prospectively collated database across two institutions of consecutive robotic enucleations or parenchyma preserving resections of the proximal pancreas was performed between July 2018 and October 2021. Standard demographic data, preoperative variables, intraoperative parameters, post-operative outcomes, morbidity and mortality were recorded.

RESULTS

Thirteen patients (8 female and 5 male) underwent robotic enucleation (EN) (8) and/or uncinectomy (UN) (5) in the proximal pancreas. Mean BMI was 32(kg/m2 ). Three patients (21%) underwent preoperative prophylactic pancreatic duct stenting. One patient required conversion to open. The median operative time in the EN group was 170 min (108-224 min) and the UN group was 160 min (110-204 min). The majority (8) of lesions were pNETs. Three lesions were IPMNs, with 1 solitary fibrous tumour and a serous cystic neoplasm (SCN) respectively. Median tumour size was 23 mm (11-58 mm) in the EN group, and 27 mm (17-38 mm) in the UN group. Ten of 13 patients had an R0 resection. There was no mortality in our series. Four (31%) patients across both groups developed clinically relevant POPF while none developed new endocrine or exocrine insufficiency. Average outpatient follow-up has been 6 months (1-18 months).

CONCLUSION

A robotic approach in proximal parenchymal preserving pancreatectomy is expanding, safe and feasible.

Development of a Nomogram to Predict Clinically Relevant Postoperative Pancreatic Fistula After Pancreaticoduodenectomy on the Basis of Visceral Fat Area and Magnetic Resonance Imaging

BACKGROUND

The aim of this study was to develop a nomogram to predict the risk of developing clinically relevant postoperative pancreatic fistula (CR-POPF) after pancreaticoduodenectomy (PD) using preoperative clinical and imaging data.

METHODS

The data of 205 patients were retrospectively analyzed, randomly divided into training (n = 125) and testing groups (n = 80). The patients' preoperative laboratory indicators, preoperative clinical baseline data, and preoperative imaging data [enhanced computed tomography (CT), enhanced magnetic resonance imaging (MRI)] were collected. Univariate analyses combined with multivariate logistic regression were used to identify the independent risk factors for CR-POPF. These factors were used to train and validate the model and to develop the risk nomogram. The area under the curve (AUC) was used to measure the predictive ability of the models. The integrated discrimination improvement index (IDI) and decision curve analysis (DCA) were used to assess the clinical feasibility of the nomogram in relation to five other models established in literature.

RESULTS

CT visceral fat area (P = 0.014), the pancreatic spleen signal ratio on T1 fat-suppressed MRI sequences (P < 0.001), and CT main pancreatic duct diameter (P = 0.001) were identified as independent prognostic factors and used to develop the model. The final nomogram achieved an AUC of 0.903. The IDI and DCA showed that the nomogram outperformed the other five CR-POPF models in the training and testing cohorts.

CONCLUSION

The nomogram achieved a superior predictive ability for CR-POPF following PD than other models described in literature. Clinicians can use this simple model to optimize perioperative planning according to the patient's risk of developing CR-POPF.

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.

Preoperative NLR and PLR are predictive of clinically relevant postoperative pancreatic fistula

Background

Clinically relevant postoperative pancreatic fistula (CR-POPF) is a dreaded complication following pancreatic surgery. Several scores attempt to predict CR-POPF occurrence to better manage outcomes in patients undergoing pancreaticoduodenectomy (PD). In our study, we investigate the prognostic role of several demographic and clinico-pathological variables. We focus on clinical biomarkers, the Neutrophil-to-Lymphocytes Ratio (NLR) and Platelet-to-Lymphocyte ratio (PLR), which can be easily used in predicting CR-POPF occurrence.

Methods

Patients who underwent a PD with curative intent at our institution, between 2008 and 2018 were reviewed. Statistical analysis was conducted to determine the association between various demographic and clinico-pathological variables, with the occurrence of clinically significant POPF.

Results

117 patients underwent a PD at our institution. Statistically significant associations on multivariate analysis were observed for the absence of preoperative diabetes mellitus, a pathological stage ≥III, an elevated NLR (> 4) and an elevated PLR (> 158).

Conclusion

The NLR and PLR are predictive of CR-POPF occurrence following PD. These readily available biomarkers can add value to risk stratification tools to assess CR-POPF occurrence and individualize patient care plans.