Risk factors of pancreatic fistula after distal pancreas resections: an observational retrospective study

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Abstract

BACKGROUND: The main complication of surgical pancreas interventions is the pancreatic fistula (PF) abnormal secretion of pancreatic secretions into the abdominal cavity, which can lead to more severe complications. At the same time, some predictors of PF remain poorly understood.

AIM: To investigate the risk factors for the development of PF after distal pancreatic resection.

MATERIALS AND METHODS: The study included 40 patients who underwent distal resection. The influence of various clinical parameters on the development of PF after surgery was evaluated. Methods of mathematical modeling and correlation analysis were used. Mathematical modeling was carried out using the Random forest machine learning algorithm, and the indicator of the relative importance of the “importance” parameters was evaluated.

RESULTS: According to the Random forest model, on day 1 after surgery, the most significant predictors of the development of PF were: the volume of neoplasm, age and stage of the oncological process, for which “importance” was 53.2, 13.7 and 12.5 (AUC ROC=62%); on day 3–5, “importance” was 61.7, 11.5 and 5.2 (AUC ROC=79%). An increase in the concentration of pancreatic amylase in blood plasma for 2–3 and 3–5 days correlated with its increase in the drainage discharge for 5-7 days after the intervention (r=0.48 and 0.76; p <0.05). A correlation was found between the level of amylase in the drainage discharge on 3–5 days after the intervention and the level of leukocytes according to the general blood test (r=0.62, p <0.05).

CONCLUSION: An increase in plasma amylase levels is the main risk factor for the development of PF. An increase in the concentration of amylase in the drainage discharge can be considered as a potential risk factor for the development of pancreatic fistulas with clinical manifestations in the following days. The stage of the oncological process, the size of the neoplasm and the age of the patient are also risk factors.

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About the authors

Ruslan I. Moshurov

National Medical Research Radiological Center

Email: ruslan4ic93@mail.ru
ORCID iD: 0000-0002-5676-4224
SPIN-code: 2134-1092

MD, Cand. Sci. (Medicine)

Russian Federation, 4 Koroleva street, 249031 Obninsk

Mikhail B. Potievskiy

National Medical Research Radiological Center

Author for correspondence.
Email: mikhailpotievsky@yandex.ru
ORCID iD: 0000-0002-8514-8295
SPIN-code: 8127-1917

MD

Russian Federation, 4 Koroleva street, 249031 Obninsk

Vladimir S. Trifanov

National Medical Research Radiological Center

Email: trifan1975@yandex.ru
ORCID iD: 0000-0003-1879-6978
SPIN-code: 3710-8052

MD, Dr. Sci. (Medicine), Associate Professor

Russian Federation, 4 Koroleva street, 249031 Obninsk

Nikolai A. Grishin

National Medical Research Radiological Center

Email: grishinlap@mail.ru
ORCID iD: 0000-0003-1703-9115
SPIN-code: 4707-7941

MD, Cand. Sci. (Medicine)

Russian Federation, 4 Koroleva street, 249031 Obninsk

Leonid O. Petrov

National Medical Research Radiological Center

Email: leonid_petrov@mail.ru
ORCID iD: 0000-0001-6272-9647
SPIN-code: 4559-3613

MD, Cand. Sci. (Medicine)

Russian Federation, 4 Koroleva street, 249031 Obninsk

Pavel V. Sokolov

National Medical Research Radiological Center

Email: sokolov-p-v@yandex.ru
ORCID iD: 0000-0002-5050-7868
SPIN-code: 8527-6278

MD

Russian Federation, 4 Koroleva street, 249031 Obninsk

Sergei A. Ivanov

National Medical Research Radiological Center

Email: oncourolog@gmail.com
ORCID iD: 0000-0001-7689-6032
SPIN-code: 4264-5167

MD, Dr. Sci. (Medicine), Professor, corresponding member of the Russian Academy of Sciences

Russian Federation, 4 Koroleva street, 249031 Obninsk

Petr V. Shegai

National Medical Research Radiological Center

Email: dr.shegai@mail.ru
ORCID iD: 0000-0001-9755-1164
SPIN-code: 6849-3221

MD, Cand. Sci. (Medicine)

Russian Federation, 4 Koroleva street, 249031 Obninsk

Andrei D. Kaprin

National Medical Research Radiological Center

Email: kaprin@mail.ru
ORCID iD: 0000-0001-8784-8415
SPIN-code: 1759-8101

MD, Dr. Sci. (Medicine), Professor, academician of the Russian Academy of Sciences

Russian Federation, 4 Koroleva street, 249031 Obninsk

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Supplementary files

Supplementary Files
Action
1. JATS XML
2. Fig. 1. Quality of Random forest model. The model is based on clinical data, obtained on different days after the surgery: a — 1st day, AUC ROC=62%, b — 3–5 days, AUC ROC=79%, c — 10–15 days, AUC ROC=80%. The probability of a false positive result (FPR — false positive rate) is indicated along the abscissa axis, and the probability of a true positive result (TPR — true positive rate) is indicated along the ordinate axis. The figure shows the AUC ROC data, which is a metric of model accuracy. The FPR values are obtained as a result of cross validation, and the TPR values are taken from the original dataset.

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