Preoperative predictors of obesity recurrence after laparoscopic gastrectomy

V.A. Vetoshkin

St. Petersburg City Hospital No. 40 of the Kurortny Administrative District

ORCID: 0000-0001-5346-9257

D.V. Gladyshev

St. Petersburg City Hospital No. 40 of the Kurortny Administrative District

ORCID: 0000-0001-5318-2619

M.E. Moiseev

St. Petersburg City Hospital No. 40 of the Kurortny Administrative District

ORCID: 0000-0002-6180-6695

A.D. Gladyshev

Kirov Military Medical Academy

ORCID: 0009-0006-6562-5871

S.A. Kovalenko

St. Petersburg City Hospital No. 40 of the Kurortny Administrative District

ORCID: 0000-0002-5850-0599

R.G. Askerkhanov

Moscow Clinical Scientific Practical Center

ORCID: 0000-0002-6266-5855

Preoperative predictors of obesity recurrence after laparoscopic gastrectomy

Authors:

V.A. Vetoshkin, D.V. Gladyshev, M.E. Moiseev, A.D. Gladyshev, S.A. Kovalenko, R.G. Askerkhanov

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Journal: Pirogov Russian Journal of Surgery. 2023;(9): 40‑44

DOI: 10.17116/hirurgia202309140

Downloaded: 3

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To cite this article:

Vetoshkin VA, Gladyshev DV, Moiseev ME, Gladyshev AD, Kovalenko SA, Askerkhanov RG. Preoperative predictors of obesity recurrence after laparoscopic gastrectomy. Pirogov Russian Journal of Surgery. 2023;(9):40‑44. (In Russ.)
https://doi.org/10.17116/hirurgia202309140

Доказательная гастроэнтерология: pro et contra

Актуальные вопросы педиатрической практики

Использование инфографики авторами научных работ

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OBJECTIVE

To find the preoperative predictors of obesity recurrence.

MATERIAL AND METHODS

We analyzed 81 patients with obesity who underwent laparoscopic sleeve gastrectomy. Patients were followed-up for 5 years and divided into 2 groups (64 (79.0%) patients were in the persistent weight loss group and 17 (21.0%) ones were in the obesity recurrence group).

RESULTS

We tried to make a mathematical model for predicting obesity recurrence after bariatric surgery based on various parameters (age, height, weight, hemoglobin A1C, lipoprotein A, T3, T4, triglycerides, TSH, cholesterol, arterial hypertension, diabetes, metabolic syndrome, percentage of fat mass). We trained the following classification models: logistic regression, naive Bayes classifier, decision tree. None classifier provided sufficient prediction quality. This may indicate that these data do not allow predicting of obesity recurrence after sleeve gastrectomy.

CONCLUSION

We failed to construct a mathematical model based on preoperative data of patients with obesity predicting recurrence in long-term period after sleeve gastrectomy.

Keywords:

bariatric surgery

sleeve gastrectomy

recurrence

obesity

predictors

Authors:

V.A. Vetoshkin

St. Petersburg City Hospital No. 40 of the Kurortny Administrative District

ORCID: 0000-0001-5346-9257

D.V. Gladyshev

St. Petersburg City Hospital No. 40 of the Kurortny Administrative District

ORCID: 0000-0001-5318-2619

M.E. Moiseev

St. Petersburg City Hospital No. 40 of the Kurortny Administrative District

ORCID: 0000-0002-6180-6695

A.D. Gladyshev

Kirov Military Medical Academy

ORCID: 0009-0006-6562-5871

S.A. Kovalenko

St. Petersburg City Hospital No. 40 of the Kurortny Administrative District

ORCID: 0000-0002-5850-0599

R.G. Askerkhanov

Moscow Clinical Scientific Practical Center

ORCID: 0000-0002-6266-5855

Received:

31.05.2023

Accepted:

10.06.2023

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