Nomogram for predicting postoperative pancreatic fistula

A Comparison of Preoperative Predictive Scoring Systems for Postoperative Pancreatic Fistula after Pancreaticoduodenectomy Based on a Single-Center Analysis

Background: Postoperative pancreatic fistula (POPF) after pancreaticoduodenectomy (PD) is associated with major postoperative morbidity and mortality. Several scoring systems have been described to stratify patients into risk groups according to the risk of POPF. The aim of this study was to compare scoring systems in patients who underwent a PD. Methods: A total of 196 patients undergoing PD from July 2019 to June 2022 were identified from a prospectively maintained database of the University Hospital Ghent. After performing a literature search, four validated, solely preoperative risk scores and the intraoperative Fistula Risk Score (FRS) were included in our analysis. Furthermore, we eliminated the variable blood loss (BL) from the FRS and created an additional score. Univariate and multivariate analyses were performed for all risk factors, followed by a ROC analysis for the six scoring systems. Results: All scores showed strong prognostic stratification for developing POPF (p < 0.001). FRS showed the best predictive accuracy in general (AUC 0.862). FRS without BL presented the best prognostic value of the scores that included solely preoperative variables (AUC 0.783). Soft pancreatic texture, male gender, and diameter of the Wirsung duct were independent prognostic factors on multivariate analysis. Conclusions: Although all predictive scoring systems stratify patients accurately by risk of POPF, preoperative risk stratification could improve clinical decision-making and implement preventive strategies for high-risk patients. Therefore, the preoperative use of the FRS without BL is a potential alternative.

Analysis of factors influencing pancreatic fistula after minimally invasive pancreaticoduodenectomy and establishment of a new prediction model for clinically relevant pancreatic fistula

BACKGROUND

Postoperative pancreatic fistula (POPF) is the most prevalent complications following minimally invasive pancreaticoduodenectomy (MIPD). Only one model related to MIPD exists, and previous POPF scoring prediction methods are based on open pancreaticoduodenectomy patients. Our objectives are to determine the variables that may increase the probability of pancreatic fistula following MIPD and to develop and validate a POPF predictive risk model.

METHODS

Data from 432 patients who underwent MIPD between July 2015 and May 2022 were retrospectively collected. A nomogram prediction model was created using multivariate logistic regression analysis to evaluate independent factors for POPF in patients undergoing MIPD in the modeling cohort. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) and the calibration curve were used to verify the nomogram prediction model internally and externally within the modeling cohort and the verification cohort.

RESULTS

Multivariate logistic regression analysis showed that body mass index (BMI), albumin, triglycerides, pancreatic duct diameter, pathological diagnosis and intraoperative bleeding were independent variables for POPF. On the basis of this information, a model for the prediction of risks associated with POPF was developed. In accordance with the ROC analysis, the modeling cohort's AUC was 0.819 (95% CI 0.747-0.891), the internal validation cohort's AUC was 0.830 (95% CI 0.747-0.912), and the external validation cohort's AUC was 0.793 (95% CI 0.671-0.915). Based on the calibration curve, the estimated values of POPF have a high degree of concordance with the actual values that were measured.

CONCLUSIONS

This model for predicting the probability of pancreatic fistula following MIPD has strong predictive capacity and can provide a trustworthy predictive method for the early screening of high-risk patients with pancreatic fistula after MIPD and timely clinical intervention.

Perioperative pancreaticoduodenectomy management strategy focusing on postoperative early drain colonization

PURPOSE

Pancreatoduodenectomy (PD) is a highly invasive procedure. Intra-abdominal infections and pancreatic fistulas are strongly correlated complications. In the present study, we identified the risk factors for postoperative early drain colonization (POEDC) and established a perioperative management strategy.

METHODS

A total of 205 patients who underwent pancreatoduodenectomy were included in the study. POEDC was defined as a positive drain fluid culture before postoperative day (POD) 4. We retrospectively investigated the correlation between POEDC, postoperative outcomes, and clinical factors.

RESULTS

POEDC was observed in 26 patients (12.6%) with poor postoperative outcomes, including pancreatic fistulas (P < 0.001). A multivariate analysis demonstrated a correlation between these postoperative outcomes and the age (P = 0.002), body mass index (BMI) (P = 0.002), procalcitonin (PCT) level (P < 0.001), and drain amylase level on POD 1 (P = 0.032). Enterococcus was detected most frequently, being found in 15 patients.

CONCLUSION

We observed a strong correlation between POEDC and poor postoperative outcomes. The BMI, age, and PCT and drain amylase level on POD 1 should be considered POEDC risk factors, with the need to propose an antibiotic perioperative strategy. POEDC control may represent the key to improving postoperative outcomes after PD.

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.

Development and validation of a network calculator model for safety and efficacy after pancreaticoduodenectomy in the elderly patients with pancreatic head cancer

BACKGROUND

Benefiting from increased life expectancy and improved perioperative management, more elderly patients with pancreatic head cancer (PHC) underwent pancreaticoduodenectomy (PD). However, individualized predictive models for the safety and efficacy of PD is still lacking. this study aimed to developed three safety- and efficacy-related risk calculators for elderly (> = 65 years) PHC patients.

METHODS

This study was designed with two research cohorts, namely, the training cohort and the validation cohort, and comprises four general steps: (1) Risk factors were analyzed for the incidence of postoperative complications, cancer-specific survival (CSS), and overall survival (OS) in the training cohort (N = 271) using logistic and Cox-regression analysis. (2) Nomograms were then plotted based on the above results. (3) The accuracy of the developed nomogram models was then verified with the validation cohort (N = 134) data using consistency index (C-index) and calibration curves. (4) We then evaluated the efficacy of these nomograms using decision curve analysis (DCA) in both the training and validation cohorts, and ultimately constructed three online calculators based on these nomograms.

RESULTS

We identified ASA, diabetes, smoking, and lymph node invasion as predisposing risk factors for postoperative complications, and the predictive factors that affected both OS and CSS were ASA, diabetes, BMI, CA19-9 level, and tumor diameter. By integrating the above risk factors, we constructed three nomograms on postoperative complication, CSS, and OS. The C-index for complication, CSS, and OS were 0.824, 0.784, and 0.801 in the training cohort and 0.746, 0.718, and 0.708 in the validation cohort. Moreover, the validation curves and DCA demonstrated good calibration and robust compliance in both training and validation cohorts. We then developed three web calculators (https://caiming.shinyapps.io/CMCD/, https://caiming.shinyapps.io/CMCSS/, and https://caiming.shinyapps.io/CMOS/) to facilitate the use of the nomograms.

CONCLUSIONS

The calculators demonstrated promising performance as an tool for predicting the safety and efficacy of PD in elderly PHC patients.

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.

Postoperative pancreatitis and pancreatic fistulae: a review of current evidence

OBJECTIVES

Postoperative pancreatic fistula (POPF) represents one of the most severe complications following pancreatic surgery. Despite being a leading cause of morbidity and mortality, its pathophysiology is poorly understood. In recent years, there has been growing evidence to support the role of postoperative or post-pancreatectomy acute pancreatitis (PPAP) in the development of POPF. This article reviews the contemporary literature on POPF pathophysiology, risk factors, and prevention strategies.

METHODS

A literature search was conducted using electronic databases, including Ovid Medline, EMBASE, and Cochrane Library, to retrieve relevant literature published between 2005 and 2023. A narrative review was planned from the outset.

RESULTS

A total of 104 studies fulfilled criteria for inclusion. Forty-three studies reported on technical factors predisposing to POPF, including resection and reconstruction technique and adjuncts for anastomotic reinforcement. Thirty-four studies reported on POPF pathophysiology. There is compelling evidence to suggest that PPAP plays a critical role in the development of POPF. The acinar component of the remnant pancreas should be regarded as an intrinsic risk factor; meanwhile, operative stress, remnant hypoperfusion, and inflammation represent common mechanisms for acinar cell injury.

CONCLUSIONS

The evidence base for PPAP and POPF is evolving. Future POPF prevention strategies should look beyond anastomotic reinforcement and target underlying mechanisms of PPAP development.

Multidimensional Nomogram to Predict Postoperative Pancreatic Fistula after Minimally Invasive Pancreaticoduodenectomy

BACKGROUND

Clinically relevant postoperative pancreatic fistula (CR-POPF) is an inherently severe risk of pancreatic resection. Previous research has proposed models that identify risk factors and predict CR-POPF, although these are rarely applicable to minimally invasive pancreaticoduodenectomy (MIPD). This study aimed to evaluate the individual risks of CR-POPF and to propose a nomogram for predicting POPF in MIPD.

PATIENTS AND METHODS

We retrospectively reviewed the medical records of 429 patients who underwent MIPD. In the multivariate analysis, the Akaike information criterion stepwise logistic regression method was used to select the final model to develop the nomogram.

RESULTS

Of 429 patients, 53 (12.4%) experienced CR-POPF. On multivariate analysis, pancreatic texture (p = 0.001), open conversion (p = 0.008), intraoperative transfusion (p = 0.011), and pathology (p = 0.048) were identified as independent predictors of CR-POPF. The nomogram was developed based on patient, pancreatic, operative, and surgeon factors by using the following four additional clinical factors as variables: American Society of Anesthesiologists class ≥ III, size of pancreatic duct, type of surgical approach, and < 40 cases of MIPD experience.

CONCLUSIONS

A multidimensional nomogram was developed to predict CR-POPF after MIPD. This nomogram and calculator can help surgeons anticipate, select, and manage critical complications.

Prediction of postoperative pancreatic fistula and pancreatitis after pancreatoduodenectomy or distal pancreatectomy: A review

BACKGROUND AND OBJECTIVE

Postoperative pancreatic fistula (POPF) is the leading cause of morbidity and early mortality in patients undergoing pancreatic resection. In addition, recent studies have identified postoperative acute pancreatitis (POAP) as an independent contributor to morbidity. Most perioperative mitigation strategies experimented for POPF have been shown to be in vain with no consensus on the best perioperative management. Clinical prediction models have been developed with the hope of identifying high POPF risk patients with the leading idea of finding subpopulations possibly benefiting from pre-existing or novel mitigation strategies. The aim of this review was to map out the existing prediction modeling studies to better understand the current stage of POPF prediction modeling, and the methodology behind them.

METHODS

A narrative review of the existing POPF prediction model studies was performed. Studies published before September 2022 were included.

RESULTS

While the number of POPF prediction models for pancreatoduodenectomy has increased, none of the currently existing models stand out from the crowd. For distal pancreatectomy, two unique POPF prediction models exist, but due to their freshness, no further external validation or adoption in clinics or research has been reported. There seems to be a lack of adherence to correct methodology or reporting guidelines in most of the studies, which has rendered external validity-if assessed-low. Few of the most recent studies have demonstrated preoperative assessment of pancreatic aspects from computed tomography (CT) scans to provide relatively strong predictors of POPF.

CONCLUSIONS

Main goal for the future would be to reach a consensus on the most important POPF predictors and prediction model. At their current state, few models have demonstrated adequate transportability and generalizability to be up to the task. Better understanding of POPF pathophysiology and the possible driving force of acute inflammation and POAP might be required before such a prediction model can be accessed.

Personal predictive model based on systemic inflammation markers for estimation of postoperative pancreatic fistula following pancreaticoduodenectomy

BACKGROUND

Postoperative pancreatic fistula (PF) is a serious life-threatening complication after pancreaticoduodenectomy (PD). Our research aimed to develop a machine learning (ML)-aided model for PF risk stratification.

AIM

To develop an ML-aided model for PF risk stratification.

METHODS

We retrospectively collected 618 patients who underwent PD from two tertiary medical centers between January 2012 and August 2021. We used an ML algorithm to build predictive models, and subject prediction index, that is, decision curve analysis, area under operating characteristic curve (AUC) and clinical impact curve to assess the predictive efficiency of each model.

RESULTS

A total of 29 variables were used to build the ML predictive model. Among them, the best predictive model was random forest classifier (RFC), the AUC was [0.897, 95% confidence interval (CI): 0.370–1.424], while the AUC of the artificial neural network, eXtreme gradient boosting, support vector machine, and decision tree were between 0.726 (95%CI: 0.191–1.261) and 0.882 (95%CI: 0.321–1.443).

CONCLUSION

Fluctuating serological inflammatory markers and prognostic nutritional index can be used to predict postoperative PF.

Prophylactic octreotide for postoperative pancreatic fistula in patients with pancreatoduodenectomy: Risk-stratified analysis

BACKGROUND

Postoperative pancreatic fistula is one of the most critical complications following pancreatic surgery. This study aimed to evaluate the utility of selective prophylactic octreotide for patients at high risk of developing postoperative pancreatic fistula.

METHODS

From June 2019 to July 2020, 263 patients underwent pancreatoduodenectomy with pancreatojejunostomy at Samsung Medical Center. The individual fistula risk scores were calculated using a previously developed nomogram. The clinicopathological data of the patients were retrospectively reviewed.

RESULTS

There were 81 patients in the low-risk group and 182 patients in the high-risk group. No statistically significant differences were found in the rates of clinically relevant postoperative pancreatic fistula between octreotide group and the control group in all patients (15.0% vs 14.7%, P = .963) and in the high-risk group (16.1% vs 23.6%, P = .206). In risk factor analysis, postoperative octreotide was not an independent risk factor for clinically relevant pancreatic fistula in all patients and the high-risk group. Drain fluid amylase levels on the first postoperative day were significantly associated with clinically relevant postoperative pancreatic fistula, regardless of the individual risk.

CONCLUSIONS

The selective use of octreotide, even in high-risk patients, showed no protective effect against pancreatic fistula. Therefore, the routine use of postoperative octreotide is not recommended.

The net parenchymal thickness predicts pancreatic fistula after pancreaticoduodenectomy: a retrospective cohort study of objective data

BACKGROUND

The clinically relevant postoperative pancreatic fistula (CR-POPF) is still a challenging complication of pancreaticoduodenectomy (PD). This study aims to explore the predictors of CR-POPF after PD, including net parenchymal thickness (NPT) of pancreatic neck.

METHODS

The consecutive patients who underwent PD at a tertiary hospital were retrospectively reviewed. Univariate and multivariate analyses were conducted on the perioperative data, which was mainly extracted from the objective data, containing the results from the laboratory tests and the imaging examination. NPT refers to the total thickness of pancreatic gland excluding main pancreatic duct (MPD) at the CT film.

RESULTS

Univariate analyses showed that total serum bilirubin (TBiL) and albumin (ALB) levels, MPD size and NPT were significantly different between the patients with and without CR-POPF. The white blood cell count, the rate of intra-abdominal infection (IAI) and the postoperative length of hospital stay (LOS) were associated with the incidence of CR-POPF. The proportion of patients with pancreatic adenocarcinoma or chronic pancreatitis was significantly lower in the CR-POPF group than in the non-CR-POPF group. Multivariate analyses manifested that ALB ≤35 g/L and NPT >10 mm were two of the independent risk factors for CR-POPF.

CONCLUSION

Preoperative ALB ≤35 g/L and NPT > 10 mm were both the independent predictors of CR-POPF. CR-POPF was associated with the higher IAI rate and the extended LOS.

Perioperative risk of pancreatic head resection-nomogram-based prediction of severe postoperative complications as a decisional aid for clinical practice

PURPOSE

To develop nomograms for pre- and early-postoperative risk assessment of patients undergoing pancreatic head resection.

METHODS

Clinical data from 956 patients were collected in a prospectively maintained database. A test (n = 772) and a validation cohort (n = 184) were randomly generated. Uni- and multi-variate analysis and nomogram construction were performed to predict severe postoperative complications (Clavien-Dindo Grades III-V) in the test cohort. External validation was performed with the validation cohort.

RESULTS

We identified ASA score, indication for surgery, body mass index (BMI), preoperative white blood cell (WBC) count, and preoperative alkaline phosphatase as preoperative factors associated with an increased perioperative risk for complications. Additionally to ASA score, BMI, indication for surgery, and the preoperative alkaline phosphatase, the following postoperative parameters were identified as risk factors in the early postoperative setting: the need for intraoperative blood transfusion, operation time, maximum WBC on postoperative day (POD) 1-3, and maximum serum amylase on POD 1-3. Two nomograms were developed on the basis of these risk factors and showed accurate risk estimation for severe postoperative complications (ROC-AUC-values for Grades III-V-preoperative nomogram: 0.673 (95%, CI: 0.626-0.721); postoperative nomogram: 0.734 (95%, CI: 0.691-0.778); each p ≤ 0.001). Validation yielded ROC-AUC-values for Grades III-V-preoperative nomogram of 0.676 (95%, CI: 0.586-0.766) and postoperative nomogram of 0.677 (95%, CI: 0.591-0.762); each p = 0.001.

CONCLUSION

Easy-to-use nomograms for risk estimation in the pre- and early-postoperative setting were developed. Accurate risk estimation can support the decisional process, especially for IPMN-patients with an increased perioperative risk.

External validation of postoperative pancreatic fistula prediction scores in pancreatoduodenectomy: a systematic review and meta-analysis

BACKGROUND

Multiple risk scores claim to predict the probability of postoperative pancreatic fistula (POPF) after pancreatoduodenectomy. It is unclear which scores have undergone external validation and are the most accurate. The aim of this study was to identify risk scores for POPF, and assess the clinical validity of these scores.

METHODS

Areas under receiving operator characteristic curve (AUROCs) were extracted from studies that performed external validation of POPF risk scores. These were pooled for each risk score, using intercept-only random-effects meta-regression models.

RESULTS

Systematic review identified 34 risk scores, of which six had been subjected to external validation, and so included in the meta-analysis, (Tokyo (N=2 validation studies), Birmingham (N=5), FRS (N=19), a-FRS (N=12), m-FRS (N=3) and ua-FRS (N=3) scores). Overall predictive accuracies were similar for all six scores, with pooled AUROCs of 0.61, 0.70, 0.71, 0.70, 0.70 and 0.72, respectively. Considerably heterogeneity was observed, with I2 statistics ranging from 52.1-88.6%.

CONCLUSION

Most risk scores lack external validation; where this was performed, risk scores were found to have limited predictive accuracy. . Consensus is needed for which score to use in clinical practice. Due to the limited predictive accuracy, future studies to derive a more accurate risk score are warranted.

Preemptive Administration of Albumin during Pancreatectomy Does Not Reduce Postoperative Complications: A Prospective Randomized Controlled Trial

Despite the empirical use of human albumin during pancreatectomy to replace intraoperative volume loss while preventing fluid overload and edema, its impact on postoperative outcomes remains unclear. In addition, most previous studies have focused on the effects of therapeutic albumin usage. Here, we investigated whether preemptive administration of human albumin to prevent edema during pancreatectomy could reduce the incidence of moderate postoperative complications. Adult patients undergoing pancreatectomy were assigned to either the albumin group (n = 100) or the control group (n = 100). Regardless of the preoperative albumin level, 200 mL of 20% albumin was administered to the albumin group after induction of anesthesia. The primary outcome was the incidence of moderate postoperative complications as defined by a Clavien–Dindo classification grade ≥ 2 at discharge. Intraoperative net-fluid balance, a known risk factor of postoperative complication after pancreatectomy, was lower in the albumin group than in the control group (p = 0.030), but the incidence of moderate postoperative complications was not different between the albumin and control groups (47/100 vs. 38/100, respectively; risk ratio: 1.24, 95% CI: 0.89 to 1.71; p = 0.198). Therefore, preemptive administration of human albumin to prevent fluid overload and edema during pancreatectomy is not recommended because of its lack of apparent benefit in improving postoperative outcomes.

Development and validation of risk prediction nomogram for pancreatic fistula and risk-stratified strategy for drainage management after pancreaticoduodenectomy

BACKGROUND

Postoperative pancreatic fistula (POPF) is the major complication following pancreaticoduodenectomy (PD). We sought to develop and validate a risk prediction model for POPF after PD with the aim of determining personal risk probability and proposing a novel strategy for intraoperative placement and/or early-removal of prophylactic drainage.

METHODS

Data from 993 patients undergoing PD from January 2012 to December 2016 were retrospectively analyzed. Patients were randomly assigned to either training cohort or validation cohort. A nomogram was formulated based on the results from multivariable regression model for prediction of POPF. Internal and external validation were carried out with calibration plot respectively.

RESULTS

POPF occurred in 162 (16.3%) patients. The final pre-/intra-operative prediction model included alanine transaminase level [odds ratio (OR) 1.00, 95% confidence interval (CI): 1.00-1.00, P=0.023], combined portal-superior mesenteric vein resection (OR 0.22, 95% CI: 0.05-0.95, P=0.043), pancreatic duct diameter (OR 1.48, 95% CI: 1.11-1.96, P=0.007), intraoperative colloid infusion (OR 1.00, 95% CI: 1.00-1.00, P=0.001), pathology (OR 1.71, 95% CI: 1.09-2.66, P=0.018). The area under the curve (AUC) was 0.667 in the training cohort and 0.621 in the validation cohort. The final postoperative prediction model included pancreatic duct diameter (OR 1.58, 95% CI: 1.14-2.19, P=0.006), intraoperative colloid infusion (OR 2.52, 95% CI: 1.26-5.06, P=0.009), drainage fluid amylase on postoperative day 3 (POD3) (OR 4.70, 95% CI: 3.30-6.70, P<0.001), and neutrophil count on POD3 (OR 2.83, 95% CI: 1.63-4.93, P<0.001). The AUC was 0.809 in the training cohort and 0.797 in the validation cohort. Based on these variables, two nomogram prediction models were developed respectively. The calibration plot of the two models showed a good correlation between the expected risk and the actual risk in the low-risk range. Our risk-stratified strategy for drain management according to nomograms may be beneficial for 34.5% of patients.

CONCLUSIONS

Our study formulated and validated two nomogram models for predicting POPF that performed particularly well in the low-risk range. This tool may allow surgeons to propose a risk stratified strategy for intraoperative drain placement and early drain removal, which may be beneficial for a substantial proportion of patients.

Revisiting the Pancreatic Fistula Risk Score: Clinical Nomogram Accurately Assesses Risk

OBJECTIVES

Surgeons have created numerous iterations of the pancreatic fistula risk score (FRS) to predict risk for clinically relevant postoperative pancreatic fistula (CR-POPF). The multitude of often conflicting models makes it difficult for surgeons to apply data in clinical practice.

METHODS

We conducted a retrospective cohort study utilizing National Surgical Quality Improvement Program data from 2015 to 2018. The study included patients undergoing pancreaticoduodenectomy. Missing data were resolved with multiple imputations.

RESULTS

The study included 5975 patients; 1018 (17%) had a CR-POPF. On multivariate analysis, male sex (odds ratio (OR) 1.60 CI: 1.29-1.98 P < .001), obesity (OR 1.65 CI: 1.31-2.08 P < .001), and soft gland texture (OR 3.21 CI: 2.45-4.23 P < .001) were all associated with increased odds of a CR-POPF. Variables not associated with CR-POPF included diabetes, preoperative bilirubin, preoperative albumin, and American Society of Anesthesiologists (ASA) classification. On multivariate analysis, duct diameter >6 mm (OR .52 CI: .34-.77 P = .001), pancreatic adenocarcinoma pathology (OR .67 CI: .53-.84 P < .001), and neoadjuvant treatment (OR .71 CI: .51-.98 P = .042) were all associated with decreased odds of a CR-POPF. We constructed a clinically relevant nomogram from this model known as the Portland FRS. Model characteristics were superior to previously published FRS models. The area under the curve (AUC) for the Portland FRS was .72 (CI: .704-.737). In comparison, AUCs for the Alternative and Seoul FRS were .70 and .64, respectively.

CONCLUSION

Utilizing readily available clinical data, the Portland FRS can accurately predict the risk for pancreatic fistula. The nomogram may assist surgeons in patient counseling and perioperative management.

Lymphopenia following pancreaticoduodenectomy is associated with pancreatic fistula formation

Backgrounds/Aims

Post-operative pancreatic fistulas (POPF) are a major source of morbidity following pancreaticoduodenectomy (PD). This study aims to investigate if persistent lymphopenia, a known marker of sepsis, can act as an additional marker of POPF with clinical implications that could help direct drain management.

Methods

A retrospective chart review of all patients who underwent PD in a single hospital network from 2008 to 2018. Persistent lymphopenia was defined as lymphopenia beyond post-operative day #3.

Results

Of the 201 patients who underwent PD during the study period 161 patients had relevant laboratory data, 81 of whom had persistent lymphopenia. 17 patients with persistent lymphopenia went on to develop a POPF, compared to 7 patients without. Persistent lymphopenia had a negative predictive value of 91.3%. Multivariate analysis revealed only persistent lymphopenia as being independently associated with POPF (HR 2.57, 95% CI 1.07-6.643, p=0.039). Patients with persistent lymphopenia were more likely to have a complication requiring intervention (56.8% vs 35.0%, p<0.001).

Conclusions

Persistent lymphopenia is a readily available early marker of POPF that holds the potential to identify clinically relevant POPF in patients where no surgical drain is present, and to act as an adjunct of drain amylase helping to guide drain management.

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

Aim

In order to find the risk factors of postoperative pancreatic fistula (POPF) after pancreaticoduodenectomy (PD) according to the latest definition and grading system of International Study Group of Pancreatic Surgery (ISGPS) (version 2016) and propose a nomogram for predicting POPF.

Methods

We conducted a retrospective analysis of 232 successive cases of PD performed at our hospital by the same operator from August 2012 to June 2020. POPF was diagnosed in accordance with the latest definition of pancreatic fistula from the ISGPS. The risk factors of POPF were analyzed by univariate and multivariate logistic regression analysis. A nomogram model to predict the risk of POPF was constructed based on significant factors.

Results

There were 18 cases of POPF, accounting for 7.8% of the total. Among them, 17 cases were classified into ISGPF grade B and 1 case was classified into ISGPF grade C. In addition, 35 cases were classified into biochemical leak. Univariate and multivariate analysis showed that hypertension, non-diabetes, no history of abdominal surgery, antecolic gastrojejunostomy and soft pancreas were independent risk factors of POPF. Based on significant factors, a nomogram is plotted to predict the risk of POPF. The C-index of this nomogram to assess prediction accuracy was 0.916 (P < 0.001) indicating good prediction performance.

Conclusion

Hypertension, non-diabetes, no history of abdominal surgery, antecolic gastrojejunostomy and soft pancreas were independent risk factors of POPF. Meanwhile, a nomogram for predicting POPF with good test performance and discriminatory capacity was constituted.

Surgeon vs Pathologist for Prediction of Pancreatic Fistula: Results from the Randomized Multicenter RECOPANC Study

BACKGROUND

Surgically assessed pancreatic texture has been identified as the strongest predictor of postoperative pancreatic fistula. However, texture is a subjective parameter with no proven reliability or validity. Therefore, a more objective parameter is needed. In this study, we evaluated the fibrosis level at the pancreatic neck resection margin and correlated fibrosis and all clinico-pathologic parameters collected over the course of the Pancreatogastrostomy vs Pancreatojejunostomy for RECOnstruction (RECOPANC) study.

STUDY DESIGN

The RECOPANC trial was a multicenter randomized prospective trial of patients undergoing pancreatoduodenectomy. There were 261 hematoxylin and eosin-stained slides allocated for histopathologic analyses. Pancreatic fibrosis was scored from 0 to III (no fibrosis up to severe fibrosis) by 2 blinded independent pathologists. All variables possibly associated with POPF were entered into a generalized linear model for multivariable analysis.

RESULTS

The fibrosis grade and pancreatic texture were scored in all 261 patients. In POPF B/C (postoperative pancreatic fistula grade B or C) patients, 71% had a soft pancreas, and fibrosis grades were distributed as follows: 48% with score 0, 28% with score I, 20% with score II, and 7% with score III, respectively. Fibrosis grading showed substantial inter-rater reliability (kappa = 0.74) and correlated positively with hard pancreatic texture (p < 0.05). In univariable analysis, area under the curve (AUC) for POPF B/C prediction was higher for fibrosis grade than for pancreatic texture (0.71 vs 0.59). In multivariate analysis, the following predictors were selected: sex, surgeon volume, pancreatic texture, and fibrosis grade. However, the addition of pancreatic texture only led to an incremental improvement (AUC 0.794 vs 0.819).

CONCLUSIONS

Histologically evaluated pancreatic fibrosis is an easily applicable and highly reproducible POPF predictor and superior to surgically evaluated pancreatic texture. Future studies might use fibrosis grade for risk stratification in pancreatoduodenectomy.

The comparation of short-term outcome between laparoscopic and open pancreaticoduodenectomy: a propensity score matching analysis

Pancreaticoduodenectomy (PD) is one of the most complex and delicate operations in abdominal surgery. With the development of laparoscopic techniques, more and more pancreatic experts have become skilled in laparoscopic pancreaticoduodenectomy (LPD). However, the short-term efficacy of LPD compared to open pancreaticoduodenectomy (OPD) remains unclear. Here, we performed a propensity score matching study aiming to compare the short outcomes of patients who underwent LPD or OPD after the learning curve and established a risk model of pancreatic fistula. The data of 346 patients who had OPD or LPD from July 2015 to January 2020 were retrieved. After a 1:1 matching, 224 patients remained. The operation time was significantly longer (P = 0.001) but the amount of bleeding was significantly lower (P = 0.001) in the LPD group than in the OPD group. Patients in LPD group had fewer blood transfusions (P = 0.002) than those in OPD group. More lymph nodes (P < 0.001) were dissected in LPD group. The rate of grade B/C pancreatic fistula was significantly higher in the LPD group than in the OPD group (16.1% vs. 6.3%, P = 0.002). By multi variate Logistic regression analysis, we identified pancreatic tumor, malignancy and low body mass index were risk factors of Grade B/C pancreatic fistula after PD operation. Then, we developed a Grade B/C pancreatic fistula nomogram with the risk factors. The C-index of the nomogram was 0.836 (95% CI 0.762-0.910). In conclusion, LPD could be technically feasible, get less trauma and achieve similar short-term outcome as compared with OPD.

Risk prediction platform for pancreatic fistula after pancreatoduodenectomy using artificial intelligence

BACKGROUND

Despite advancements in operative technique and improvements in postoperative managements, postoperative pancreatic fistula (POPF) is a life-threatening complication following pancreatoduodenectomy (PD). There are some reports to predict POPF preoperatively or intraoperatively, but the accuracy of those is questionable. Artificial intelligence (AI) technology is being actively used in the medical field, but few studies have reported applying it to outcomes after PD.

AIM

To develop a risk prediction platform for POPF using an AI model.

METHODS

Medical records were reviewed from 1769 patients at Samsung Medical Center who underwent PD from 2007 to 2016. A total of 38 variables were inserted into AI-driven algorithms. The algorithms tested to make the risk prediction platform were random forest (RF) and a neural network (NN) with or without recursive feature elimination (RFE). The median imputation method was used for missing values. The area under the curve (AUC) was calculated to examine the discriminative power of algorithm for POPF prediction.

RESULTS

The number of POPFs was 221 (12.5%) according to the International Study Group of Pancreatic Fistula definition 2016. After median imputation, AUCs using 38 variables were 0.68 ± 0.02 with RF and 0.71 ± 0.02 with NN. The maximal AUC using NN with RFE was 0.74. Sixteen risk factors for POPF were identified by AI algorithm: Pancreatic duct diameter, body mass index, preoperative serum albumin, lipase level, amount of intraoperative fluid infusion, age, platelet count, extrapancreatic location of tumor, combined venous resection, co-existing pancreatitis, neoadjuvant radiotherapy, American Society of Anesthesiologists’ score, sex, soft texture of the pancreas, underlying heart disease, and preoperative endoscopic biliary decompression. We developed a web-based POPF prediction platform, and this application is freely available at http://popfrisk.smchbp.org.

CONCLUSION

This study is the first to predict POPF with multiple risk factors using AI. This platform is reliable (AUC 0.74), so it could be used to select patients who need especially intense therapy and to preoperatively establish an effective treatment strategy.