PREDICTING THE INTENSITY OF POSTOPERATIVE PAIN IN PATIENTS UNDERGOING HYSTERECTOMY

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Abstract

Relevance. The problem of postoperative analgesia don’t lose it’s relevance despite the large implementation in practice the multimodal analgesia strategy. In prescribing the analgesia in the most cases don’t consider the predictors of intensive postoperative pain, which could to contribute the choice of ineffective postoperative analgesia. Purpose. The determination of predictors of intensive pain after hysterectomy. Materials and methods. We have observed women from 18 to 70 years old which have undergone a hysterectomy under general anesthesia. We have studied socio-demographic data, the presence of chronic abdominal pain before surgery, pain threshold and pain tolerance, type of surgical access and pain expectation. Results. A mathematical model was developed for predicting a moderate and severe (> 40 mm visual analogue scale) dynamic pain 2 hours after the operation with a 60% cut-off point, implemented as a calculator in MS Excel. As a set of predictors, the following signs were used: the presence of pain in the lower abdomen before the operation, tolerance to pain, the expected pain intensity and the type of surgical access. The predictive value of the positive model result was 79%, CI [69%, 86%]. Conclusion. Women who have a prediction of moderate and severe pain after the extirpation of the uterus are 60% or more likely to develop it, in order to achieve adequate analgesia, it may be recommended to use more intensive postoperative analgesia, including using regional techniques, which will improve the quality of postoperative analgesia.

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About the authors

Olga V. Smirnova

The Moscow Department of Health N.V. Sklifosovsky Federal Research Institute of Emergency Medicine

Email: smirnova.ov.doc@yandex.ru
researcher of anesthesiology department of N.V. Sklifosovsky Federal Research Institute of Emergency Medicine, 129090, Moscow, Russian Federation 129090, Moscow, Russian Federation

P. G Genov

The Moscow Department of Health N.V. Sklifosovsky Federal Research Institute of Emergency Medicine

129090, Moscow, Russian Federation

V. H Timerbaev

The Moscow Department of Health N.V. Sklifosovsky Federal Research Institute of Emergency Medicine

129090, Moscow, Russian Federation

T. F Tukibaev

The Moscow Department of Health N.V. Sklifosovsky Federal Research Institute of Emergency Medicine

129090, Moscow, Russian Federation

O. Yu Rebrova

Pirogov Russian National Research Medical University

117997, Moscow, Russian Federation

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