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CN-121983335-A - Prediction model for acute pain after caesarean section operation

CN121983335ACN 121983335 ACN121983335 ACN 121983335ACN-121983335-A

Abstract

The invention screens a group of marker sets which can effectively predict acute pain of patients after caesarean section operation, wherein the marker sets comprise whether the patients have preoperative anxiety, gestational diabetes mellitus, the age of the patients, the Pittsburgh Sleep Quality Index (PSQI) of the patients, the gestational ages of the patients and the abdominal circumference. Based on the method, a visual and quantifiable nomogram prediction model is constructed, and the method can be used for evaluating the risk probability of acute pain of a cesarean patient after operation before clinical operation, and providing targeted and individual pain management for the patient subsequently so as to improve the pregnancy safety of the patient and relieve the physical and psychological pain of the patient after operation.

Inventors

  • YANG LUYAO
  • MENG FANQING
  • PANG YUNTING
  • LIU WEI
  • FANG YONG
  • ZHOU FENG
  • Guo Yaqiu
  • GAO ZHONGQUAN
  • BAO HAN

Assignees

  • 济南市妇幼保健院

Dates

Publication Date
20260505
Application Date
20260116

Claims (9)

  1. 1. The marker set for predicting the risk of acute pain after caesarean section comprises a combination of whether preoperative anxiety exists, whether gestational diabetes mellitus exists, whether the patient is age, pittsburgh Sleep Quality Index (PSQI), gestational age and abdominal circumference, wherein the marker set is judged by a probability P value of acute pain after caesarean section of the patient, and the P value is calculated according to the following formula: logit(P)= -16.817＋1.326X 1 ＋1.005X 2 －0.058X 3 ＋0.119X 4 ＋0.050X 5 ＋0.034X 6 , Wherein X 1 is whether there is preoperative anxiety, is a two-class variable, in the formula, X 1 =80 when there is preoperative anxiety in the patient, X 1 =0 when there is no preoperative anxiety in the patient; X 2 is gestational diabetes, which is a two-class variable, in the calculation formula, when a patient has gestational diabetes, X 2 =60, when the patient has no gestational diabetes before operation, X 2 =0; X 3 is age, which is a continuous variable, directly substituted into the actual age of the patient (unit: age); X 4 is PSQI, a continuous variable, a PSQI score taken directly into the patient; X 5 is gestational age, which is a continuous variable, and is directly taken into the actual gestational age (unit: day) of the patient; X 6 is the abdominal circumference, which is a continuous variable, directly taken into the actual abdominal circumference (units: cm) of the patient.
  2. 2. The marker set of claim 1, wherein the probability P-value is high when the patient P-value is greater than 0.5, the patient is at high risk of developing acute pain following caesarean section.
  3. 3. Use of a marker set according to claim 1 for the preparation of a reagent for predicting the occurrence of acute pain in a patient following caesarean section, said reagent being one which can detect an indicator of said marker.
  4. 4. The use according to claim 3, wherein the marker set is determined by the probability P of acute pain after caesarean section of the patient, and the P is calculated as follows: logit(P)= -16.817＋1.326X 1 ＋1.005X 2 －0.058X 3 ＋0.119X 4 ＋0.050X 5 ＋0.034X 6 , Wherein X 1 is whether there is preoperative anxiety, is a two-class variable, in the formula, X 1 =80 when there is preoperative anxiety in the patient, X 1 =0 when there is no preoperative anxiety in the patient; X 2 is gestational diabetes, which is a two-class variable, in the calculation formula, when a patient has gestational diabetes, X 2 =60, when the patient has no gestational diabetes before operation, X 2 =0; X 3 is age, which is a continuous variable, directly substituted into the actual age of the patient (unit: age); X 4 is PSQI, a continuous variable, a PSQI score taken directly into the patient; X 5 is gestational age, which is a continuous variable, and is directly taken into the actual gestational age (unit: day) of the patient; X 6 is the abdominal circumference, which is a continuous variable, directly taken into the actual abdominal circumference (units: cm) of the patient.
  5. 5. The use according to claim 3, wherein the probability P-value, when the P-value is greater than 0.5, is high for the risk of acute pain occurring after caesarean section of the patient.
  6. 6. A risk prediction system for acute pain after caesarean section operation, which comprises a data input module, a data processing module and a result output module; The data input module inputs data of whether the patient has preoperative anxiety, gestational diabetes, age, PSQI, gestational age and abdominal circumference; The data processing module is used for calculating the data input by the data input module to obtain the probability P value of the acute pain of the patient after the caesarean section operation, and the calculation formula of the P value is as follows: logit(P)= -16.817＋1.326X 1 ＋1.005X 2 －0.058X 3 ＋0.119X 4 ＋0.050X 5 ＋0.034X 6 ; The result output module is used for outputting the predicted result P value obtained in the data processing module.
  7. 7. The risk prediction system of claim 6, wherein the data processing module, X 1 , is a binary variable, wherein X 1 =80 when the patient has preoperative anxiety, and X 1 =0 when the patient has no preoperative anxiety; X 2 is gestational diabetes, which is a two-class variable, in the calculation formula, when a patient has gestational diabetes, X 2 =60, when the patient has no gestational diabetes before operation, X 2 =0; X 3 is age, which is a continuous variable, directly substituted into the actual age of the patient (unit: age); X 4 is PSQI, a continuous variable, a PSQI score taken directly into the patient; X 5 is gestational age, which is a continuous variable, and is directly taken into the actual gestational age (unit: day) of the patient; X 6 is the abdominal circumference, which is a continuous variable, directly taken into the actual abdominal circumference (units: cm) of the patient.
  8. 8. The risk prediction system of claim 6, wherein the probability P-value is high when the P-value is greater than 0.5, the patient is at high risk of developing acute pain after caesarean section.
  9. 9. A computer readable storage medium having stored thereon a computer program which when executed by a processor realizes the content in the system according to claim 6.

Description

Prediction model for acute pain after caesarean section operation Technical Field The invention belongs to the technical field of medical diagnosis, and particularly relates to construction and application of a prediction model. Background The postoperative acute pain refers to severe pain of the incision and the surrounding parts of the incision occurring within 48 hours after the end of the surgical operation. The postoperative pain of caesarean section is a common physiological reaction after puerperal operation and mainly comprises somatic pain and visceral pain, the somatic pain mainly originates from an operation incision of the abdomen, the somatic pain originates from mechanical nociceptors of skin and the abdominal wall, the mechanical nociceptors are transmitted into the dorsal horn of the spinal cord through A delta neurons and uploaded to the spinal cord thalamus bundle, and the A delta fiber nociceptors are spinal cord sensory neurons with small diameters, and have the advantages of high transmission speed, sharp pain feeling and clear positioning. Visceral pain is mainly caused by temporary pressure occlusion of blood vessels on the uterus, resulting in temporary hypoxia, ischemia of surrounding tissues, and is transmitted to the white transportation branch of the lumbar sympathetic nerve chain entering T 10-L1 through C fibers along the sympathetic nerve pathway to the pelvic cavity and the upper and lower celiac nerve plexus, and finally the rear roots of the nerves enter the spinal cord and are uploaded to the thalamus, and C fiber nociceptors are small-diameter myelofree sensory neurons which encode persistent pain but relatively vague localization. During pain signaling, there are several regulatory links that process the signal. Among them, the action of enhancing the nociceptive afferent signal is called "sensitization". The process is affected by various substances, cytokines, pathways and the like, so that the pain perception of different individuals is greatly different. In addition, different extrinsic factors can have a significant impact on the pain level. Currently, opioids are the main drugs for venous analgesia after caesarean section, and epidural block analgesia is considered to be the most suitable way for postoperative analgesia of puerperal sections of caesarean section. However, adverse reactions associated with opioids after administration have attracted considerable attention. Studies have shown that 1 person per 300 opioid-exposed patients is an ideal choice for treating acute pain after caesarean section by foreign researchers in the long-term opioid users （Posteromedial quadratus lumborum block versus wound infiltration after caesarean section: A randomised, double-blind, controlled study[J]. Eur J Anaesthesiol. 2021;38(Suppl 2):S138-S144.）. intrathecal morphine. However, related side effects such as nausea, vomiting, sedation and itching may affect the mother's own intimate relationship as well as the mother and infant. On the premise of ensuring the safety of the mother and the infant, the maximum analgesic effect obtained by the minimum medicine dosage is the optimal analgesic effect of the puerperal caesarean section operation. In order to better manage pain and make a targeted pain management plan, individualized assessment and prediction of pain after caesarean section is becoming more important. One widely used prediction method is to predict postoperative pain by preoperative experimental pain assessment, but there is a study showing no significant correlation between the preoperative pain threshold and the postoperative pain score of caesarean section （Postcesarean section pain prediction by preoperative experimental pain assessment[J].Anesthesiology. 2003;98(6):1422-1426.）.Hsu et al in the study with preoperative stress stimulation and anxiety questionnaires, the mean pain score of VAS immediately after surgery was significantly higher in patients with high anxiety than in patients with mild anxiety. However, at 24 hours post-surgery, there was no significant difference in the two average VAS pain scores, and there was no significant correlation （Predicting postoperative pain by preoperative pressure pain assessment[J]. Anesthesiology. 2005;103(3):613-618.）. between pre-surgery anxiety state and immediate post-surgery or 24 hour morphine consumption, an analytical study that comprehensively included multiple national data sources, showed that the occurrence of post-surgery severe pain could be predicted using 4 pre-operative risk factors, namely age, pre-surgery chronic pain, female and pre-surgery opioid intake, but the accuracy of the predictive model was low, and the AUC value was 0.607（Predicting poor postoperative acute pain outcome in adults: an international, multicentre database analysis of risk factors in 50,005 patients[J]. Pain Rep. 2020;5(4):e831.）. as demonstrated by the prior art. In a prospective study of 47 parturients with a preferred caesa