Kinetics of postoperative drain fluid amylase values after pancreatoduodenectomy: New insights to dynamic, data-driven drain management

Diagnostic Accuracy of Lipase as Early Predictor of Postoperative Pancreatic Fistula: Results from the LIPADRAIN study

Objective

To evaluate the diagnostic accuracy of drain fluid lipase as an early predictor of postoperative pancreatic fistula and establish the most appropriate day for their measure.

Background

Clinically relevant postoperative pancreatic fistula remains a potentially life-threatening complication after pancreatic surgery. Early detection strategies remain key to reduce both the incidence and the burden of pancreatic fistula.

Methods

The LIPAse DRAIN (LIPADRAIN) study is a multicenter, prospective diagnostic study conducted in 7 tertiary university hospitals. Drain fluid values to detect clinically relevant postoperative pancreatic fistula from postoperative day 1 to postoperative day 6 were evaluated using receiver operating characteristic curve analysis. A biomarker was considered to be relevant for clinical use if its area under the curve (AUC) was greater than 0.75.

Results

Of the 625 patients included in the analysis, clinically relevant postoperative pancreatic fistula occurred in 203 (32%) patients. On postoperative days 3 and 4, drain fluid lipase was a reliable biomarker to detect clinically relevant postoperative pancreatic fistula (AUC: 0.761; 95% confidence interval [CI]: 0.761-0.799 and AUC: 0.784; 95% CI: 0.743-0.821, respectively). On postoperative day 3, with a threshold of 299 units/L, drain fluid lipase yielded a negative predictive value of 51%, sensitivity of 78%, and specificity of 63% for the detection of clinically relevant postoperative pancreatic fistula.

Conclusions

In this multicenter prospective study, drain fluid lipase is a reliable biomarker at postoperative days 3 and 4 for the diagnosis of clinically relevant postoperative pancreatic fistula after pancreatic surgery and should be systematically measured on postoperative day 3.

Drain fluid volume combined with amylase level predicts clinically relevant postoperative pancreatic fistula after pancreaticoduodenectomy: A retrospective clinical study

BACKGROUND AND AIM

Several indicators are recognized in the development of clinically relevant postoperative pancreatic fistula (CR-POPF) after pancreaticoduodenectomy (PD). However, drain fluid volume (DFV) remains poorly studied. We aimed to discover the predictive effects of DFV and guide clinical management.

METHODS

We retrospectively reviewed the clinical data of patients that received PD between January 2015 and December 2019 in a high-volume center. DFV was analyzed as a potential risk factor and postoperative short-term outcomes as well as drain removal time were compared stratified by different DFV levels. Receiver operating characteristic curves and area under curves (AUC) were compared for DFV alone and DFV combined with drain fluid amylase (DFA). Subgroup analysis of DFV stratified by DFA evaluated the predictability of CR-POPF.

RESULTS

CR-POPF occurred in 19.7% of 841 patients. Hypertension, postoperative day 3 (POD3) DFA ≥ 300 U/L, and POD3 DFV ≥ 30 mL were independent risk factors, while pancreatic main duct diameter ≥ 3 mm was a protective factor. POD3 DFV ≥ 30 mL increased the overall occurrences of CR-POPF and major complications (P = 0.017; P = 0.029). POD3 DFV alone presented a low predictive value (AUC 0.602), while POD3 DFV combined with DFA had a high predictive value (AUC 0.759) for CR-POPF. Subgroup analysis showed that the combination of POD3 DFV ≥ 30 mL and DFA ≥ 300 U/L led to higher incidences of CR-POPF (P = 0.003).

CONCLUSION

CR-POPF is common after PD, and high DFV combined with DFA may predict its occurrence and facilitate appropriate management.

The risk of clinically-relevant pancreatic fistula after pancreaticoduodenectomy is better predicted by a postoperative trend in drain fluid amylase compared to day 1 values in isolation

BACKGROUND

Recent studies support early drain removal after pancreaticoduodenectomy in patients with a drain fluid amylase on postoperative day 1 (DFA1) level of ≤5,000. The use of DFA1 to guide drain management is increasingly common among pancreatic surgeons; however, the benefit of checking additional drain fluid amylases beyond DFA1 is less known. We sought to determine whether a change in drain fluid amylase (ΔDFA) is a more reliable predictor of clinically relevant postoperative fistula than DFA1 alone.

METHODS

Using the American College of Surgeons National Surgical Quality Improvement Plan, pancreaticoduodenectomy patients with intraoperative drain placement, known DFA1, highest recorded drain fluid amylase value on postoperative day 2 to 5 (DFA2nd), day of drain removal, and clinically relevant postoperative fistula status were reviewed. Logistic models compared the predictive performance of DFA1 alone versus DFA1 + ΔDFA.

RESULTS

A total of 2,417 patients with an overall clinically relevant postoperative fistula rate of 12.6% were analyzed. On multivariable regression, clinical predictors for clinically relevant postoperative fistula included body mass index, steroid use, operative time, and gland texture. These variables were used to develop model 1 (DFA1 alone) and model 2 (DFA1 + ΔDFA). Model 2 outperformed model 1 in predicting the risk of clinically relevant postoperative fistula. According to model 2 predictions, the risk of clinically relevant postoperative fistula increased with any rise in drain fluid amylase, regardless of whether the DFA1 was above or below 5,000 U/L. The risk of clinically relevant postoperative fistula significantly decreased with any drop in drain fluid amylase, with an odds reduction of approximately 50% corresponding with a 70% decrease in drain fluid amylase (P < .001). A risk calculator was developed using DFA1 and a secondary DFA value in conjunction with other clinical predictors for clinically relevant postoperative fistula.

CONCLUSION

Clinically relevant postoperative fistula after pancreaticoduodenectomy is more accurately predicted by DFA1 and ΔDFA versus DFA1 in isolation. We developed a novel risk calculator to provide an individualized approach to drain management after pancreaticoduodenectomy.

Postoperative Serum Hyperamylasemia Adds Sequential Value to the Fistula Risk Score in Predicting Pancreatic Fistula after Pancreatoduodenectomy

OBJECTIVE

To evaluate whether postoperative serum hyperamylasemia (POH), with drain fluid amylase (DFA) and C-reactive protein (CRP), improves the Fistula Risk Score (FRS) accuracy in assessing the risk of a postoperative pancreatic fistula (POPF).

SUMMARY BACKGROUND DATA

The FRS predicts POPF occurrence using intraoperative predictors with good accuracy but intrinsic limits.

METHODS

Outcomes of patients who underwent pancreaticoduodenectomies between 2016 and 2021 were evaluated across FRS-risk zones and POH occurrence. POH consists of serum amylase activity greater than the upper limit of normal (52 U/l), persisting within the first 48 hours postoperatively (postoperative day -POD- 1 and 2).

RESULTS

Out of 905 pancreaticoduodenectomies, some FRS elements, namely soft pancreatic texture (odds ratio (OR) 11.6), pancreatic duct diameter (OR 0.80), high-risk pathologic diagnosis (OR 1.54), but not higher blood loss (OR 0.99), were associated with POH. POH was an independent predictor of POPF, which occurred in 46.8% of POH cases ( P <0.001). Once POH occurs, POPF incidence rises from 3.8% to 42.9%, 22.9% to 41.7%, and 48.9% to 59.2% in patients intraoperatively classified at low, moderate and high FRS risk, respectively. The predictive ability of multivariable models adding POD 1 drain fluid amylase, POD 1-2 POH and POD 3 C-reactive protein to the FRS showed progressively and significantly higher accuracy (AUC FRS=0.82, AUC FRS-DFA=0.85, AUC FRS-DFA-POH=0.87, AUC FRS-DFA-POH-CRP=0.90, DeLong always P <0.05).

CONCLUSIONS

POPF risk assessment should follow a dynamic process. The stepwise retrieval of early, postoperative biological markers improves clinical risk stratification by increasing the granularity of POPF risk estimates and affords a possible therapeutic window before the actual morbidity of POPF occurs.

Current Perioperative Care in Pancreatoduodenectomy: A Step-by-Step Surgical Roadmap from First Visit to Discharge

Pancreaticoduodenectomy (PD) is a mainstay in the management of periampullary tumors. Treatment algorithms increasingly employ a multimodal strategy, which includes neoadjuvant and adjuvant therapies. However, the successful treatment of a patient is contingent on the execution of a complex operation, whereby minimizing postoperative complications and optimizing a fast and complete recovery are crucial to the overall success. In this setting, risk reduction and benchmarking the quality of care are essential frameworks through which modern perioperative PD care must be delivered. The postoperative course is primarily influenced by pancreatic fistulas, but other patient- and hospital-associated factors, such as frailty and the ability to rescue from complications, also affect the outcomes. A comprehensive understanding of the factors influencing surgical outcomes allows the clinician to risk stratify the patient, thereby facilitating a frank discussion of the morbidity and mortality of PD. Further, such an understanding allows the clinician to practice based on the most up-to-date evidence. This review intends to provide clinicians with a roadmap to the perioperative PD pathway. We review key considerations in the pre-, intra-, and post-operative periods.

Machine learning algorithms as early diagnostic tools for pancreatic fistula following pancreaticoduodenectomy and guide drain removal: A retrospective cohort study

OBJECTIVE

Clinically relevant postoperative pancreatic fistula (CR-POPF) remains the major cause of morbidity following pancreaticoduodenectomy (PD). Several model score systems such as the Fistula Risk Score (FRS) have been developed to predict CR-POPF using preoperative and intraoperative data. Machine learning (ML) algorithms are increasingly applied in the medical field and they could be used to assess the risk of CR-POPF, identify clinically meaningful data and guide drain removal.

METHODS

Data from consecutive patients who underwent PD between January 1, 2010 and March 31, 2021 at a single high-volume center was collected retrospectively in this study. Demographics, clinical features, intraoperative parameters, and laboratory values were used to conduct the ML model. Four different ML algorithms (CatBoost, lightGBM, XGBoost and Random Forest) were used to train this model with cross-validation.

RESULTS

A total of 2421 patients with 62 clinical parameters were enrolled in this ML model. The majority of patients (76.3%) underwent open PD while others underwent robot-assisted PD. CR-POPF occurred in 424 (17.5%) patients. The CatBoost algorithm outperformed other algorithms with a mean area under the receiver operating characteristic curve (AUC) of 0.81 (95% confidence interval: 0.80-0.82) from the 5-fold cross-validation procedure. In the test dataset, the CatBoost algorithm also achieved the best mean-AUC of 0.83. The most important value was mean drain fluid amylase (DFA) in the first seven postoperative days (POD). The performance of models that used only preoperative data and intraoperative data was marginally lower than that of models that used combined data.

CONCLUSION

Our ML algorithms could be applied as early diagnostic tools for CR-POPF in patients who underwent PD. Such real-time clinical decision support tools can identify patients with a high risk of CR-POPF, help in developing the perioperative management plan and guide the optimal timing of drain removal.