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Development of a nomogram for predicting acute pain among patients after abdominal surgery: A prospective observational study.
- Source :
- Journal of Clinical Nursing (John Wiley & Sons, Inc.); Aug2024, Vol. 33 Issue 9, p3586-3598, 13p
- Publication Year :
- 2024
-
Abstract
- Aims: To develop a nomogram to provide a screening tool for recognising patients at risk of post‐operative pain undergoing abdominal operations. Background: Risk prediction models for acute post‐operative pain can allow initiating prevention strategies, which are valuable for post‐operative pain management and recovery. Despite the increasing number of studies on risk factors, there were inconsistent findings across different studies. In addition, few studies have comprehensively explored predictors of post‐operative acute pain and built prediction models. Design: A prospective observational study. Methods: A total of 352 patients undergoing abdominal operations from June 2022 to December 2022 participated in this investigation. A nomogram was developed for predicting the probability of acute pain after abdominal surgery according to the results of binary logistic regression. The nomogram's predictive performance was assessed by discrimination and calibration. Internal validation was performed via Bootstrap with 1000 re‐samplings. Results: A total of 139 patients experienced acute post‐operative pain following abdominal surgery, with an incidence of 39.49%. Age <60, marital status (unmarried, divorced, or widowed), consumption of intraoperative remifentanil >2 mg, indwelling of drainage tubes, poor quality sleep, high pain catastrophizing, low pain self‐efficacy, and PCIA not used were predictors of inadequate pain control in patients after abdominal surgery. Using these variables, we developed a nomogram model. All tested indicators showed that the model has reliable discrimination and calibration. Conclusions: This study established an online dynamic predictive model that can offer an individualised risk assessment of acute pain after abdominal surgery. Our model had good differentiation and calibration and was verified internally as a useful tool for risk assessment. Relevance to Clinical Practice: The constructed nomogram model could be a practical tool for predicting the risk of experiencing acute post‐operative pain in patients undergoing abdominal operations, which would be helpful to realise personalised management and prevention strategies for post‐operative pain. Reporting Method: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines were adopted in this study. Patient or Public Contribution: Before the surgery, research group members visited the patients who met the inclusion criteria and explained the purpose and scope of the study to them. After informed consent, they completed the questionnaire. The patients' pain scores (VAS) were regularly assessed and documented by the bedside nurse for the first 3 days following surgery. Other information was obtained from medical records. [ABSTRACT FROM AUTHOR]
- Subjects :
- ABDOMINAL surgery
RISK assessment
PAIN measurement
GOODNESS-of-fit tests
PREDICTION models
T-test (Statistics)
RESEARCH funding
POSTOPERATIVE pain
SCIENTIFIC observation
LOGISTIC regression analysis
RESEARCH evaluation
QUESTIONNAIRES
DESCRIPTIVE statistics
CHI-squared test
MANN Whitney U Test
LONGITUDINAL method
PAIN management
MEDICAL screening
COMPARATIVE studies
DATA analysis software
DISEASE risk factors
Subjects
Details
- Language :
- English
- ISSN :
- 09621067
- Volume :
- 33
- Issue :
- 9
- Database :
- Complementary Index
- Journal :
- Journal of Clinical Nursing (John Wiley & Sons, Inc.)
- Publication Type :
- Academic Journal
- Accession number :
- 178882370
- Full Text :
- https://doi.org/10.1111/jocn.17031