2022
DOI: 10.7759/cureus.23079
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Predictive Analytics for Inpatient Postoperative Opioid Use in Patients Undergoing Mastectomy

Abstract: Introduction: The use of opioids in mastectomy patients is a particular challenge, having to balance the management of acute pain while minimizing risks of continuous opioid use postoperatively. Despite attempts to decrease postmastectomy opioid use, including regional anesthetics, gabapentinoids, topical anesthetics, and nonopioid anesthesia, prolonged opioid use remains clinically significant among these patients. The goal of this study is to identify risk factors and develop machine-learning-based models to… Show more

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Cited by 3 publications
(6 citation statements)
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“…Development of postoperative complications: Most studies focused on the prediction of postoperative acute complications 26–28,42,44–49,59,99,110,112,113,118,123 such as pain and opioid use, 53–57 postoperative atrial fibrillation (new-onset atrial fibrillation), 82 postoperative risk of stroke or myocardial infarction, 50,71,77 and delirium or cognitive decline. 65–70 Other models focused on the risk of developing pneumonia or respiratory failure, 83,85,125 acute kidney injury, 43,52,58,60–63,120–122 liver failure 117 or development of sepsis or surgical site infection.…”
Section: Resultsmentioning
confidence: 99%
“…Development of postoperative complications: Most studies focused on the prediction of postoperative acute complications 26–28,42,44–49,59,99,110,112,113,118,123 such as pain and opioid use, 53–57 postoperative atrial fibrillation (new-onset atrial fibrillation), 82 postoperative risk of stroke or myocardial infarction, 50,71,77 and delirium or cognitive decline. 65–70 Other models focused on the risk of developing pneumonia or respiratory failure, 83,85,125 acute kidney injury, 43,52,58,60–63,120–122 liver failure 117 or development of sepsis or surgical site infection.…”
Section: Resultsmentioning
confidence: 99%
“…We compared our predictive models with prior reports and are presented in Table 5. 9,27,30,35,40 Tsuboi et al 35 developed a multivariable linear regression model for predicting the outcome of 24-hour postoperative fentanyl consumption (R-squared 5 0.302) in patients with inflammatory bowel disease. Yoshida et al 40 developed multivariable linear regression models to predict 24hour postoperative fentanyl requirement (R-squared 5 0.145) and perioperative fentanyl requirement (R-squared 5 0.185) in patients undergoing orthognathic surgery.…”
Section: Discussionmentioning
confidence: 99%
“…Similar to our study, these 2 studies developed models to predict postoperative fentanyl requirement directly; however, the performance of our predictive model was higher (R-squared 5 0.313) than the abovementioned studies. Dolendo et al 9 and Nair et al 27 developed multiple statistical models to predict and classify patients based on the postoperative opioid requirement in patients undergoing mastectomy and ambulatory surgeries, respectively. Pan et al 30 developed a multivariable linear regression model for predicting perioperative analgesic requirement in patients undergoing Caesarean section using physical and psychological tests.…”
Section: Discussionmentioning
confidence: 99%
“…Generalized linear mixed models (GLMMs), least absolute shrinkage and selection operator (Lasso), Linear regression (LR), Logistic regression (LR), Bayesian regression [42], [32], [43], [33], [34], [35], [27], [44], [45], [46], [39], [41], [31] Model that estimates the relationship between one dependent variable and one or more independent variables using a line.…”
Section: Regressionmentioning
confidence: 99%
“…The study found that the ANN outperformed the LR model in predicting treatment response. Dolendo et al (2022) [45] analyzed 148 cancer patients who underwent mastectomy, utilizing LR to assess factors affecting postoperative opioid use. The study suggested that these models, if implemented, could significantly impact preoperative counseling and patient satisfaction by aiding in the prediction of postoperative pain.…”
Section: Ai/ml Models Used For Cancer Pain Management Prediction and ...mentioning
confidence: 99%