Articles: operative.
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Curr Opin Anaesthesiol · Oct 2024
ReviewHarnessing artificial intelligence for predicting and managing postoperative pain: a narrative literature review.
This review examines recent research on artificial intelligence focusing on machine learning (ML) models for predicting postoperative pain outcomes. We also identify technical, ethical, and practical hurdles that demand continued investigation and research. ⋯ Artificial intelligence (AI) has the potential to enhance perioperative pain management by providing more accurate predictive models and personalized interventions. By leveraging ML algorithms, clinicians can better identify at-risk patients and tailor treatment strategies accordingly. However, successful implementation needs to address challenges in data quality, algorithmic complexity, and ethical and practical considerations. Future research should focus on validating AI-driven interventions in clinical practice and fostering interdisciplinary collaboration to advance perioperative care.
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Chronic postsurgical pain (CPSP) is a highly prevalent condition. To improve CPSP management, we aimed to develop and internally validate generalizable point-of-care risk tools for preoperative and postoperative prediction of CPSP 3 months after surgery. A multicentre, prospective, cohort study in adult patients undergoing elective surgery was conducted between May 2021 and May 2023. ⋯ These models demonstrated good calibration and clinical utility. The primary CPSP model demonstrated fair predictive performance including 2 significant predictors. Derivation of a generalizable risk tool with point-of-care predictors was possible for the threshold-based CPSP models but requires independent validation.
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Chronic postoperative pain is present in approximately 20% of patients undergoing total knee arthroplasty. Studies indicate that pain mechanisms are associated with development and maintenance of chronic postoperative pain. The current study assessed pain sensitivity, inflammation, microRNAs, and psychological factors and combined these in a network to describe chronic postoperative pain. ⋯ The reduction of the number of parameters stabilized the models and reduced the explanatory value to 69% and 51%. This is the first study to use the DIABLO model for chronic postoperative pain and to demonstrate how different pain mechanisms form a pain mechanistic network. The complex model explained 81% of the variability of clinical pain intensity, whereas the less complex model explained 51% of the variability of clinical pain intensity.
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Anesthesia and analgesia · Sep 2024
Risk of Venous Thromboembolism After Total Knee Arthroplasty in Patients with Obstructive Sleep Apnea: Results from a National Cohort.
Obstructive sleep apnea (OSA) is a prevalent condition associated with many comorbidities. However, establishing the independent impact of OSA on specific health outcomes can be challenging without access to a substantial patient cohort. This study aimed to investigate whether a diagnosis of OSA was independently associated with venous thromboembolism (VTE) after total knee arthroplasty (TKA). ⋯ In this study encompassing a nationally representative sample of TKA patients, OSA was associated with increased incidence of VTE at 1 month postoperatively, an association that persisted after the generation of matched cohorts. While limitations related to the lack of patient-level data, disease severity, and therapy adherence should be acknowledged, our large sample size enabled us to factor many baseline characteristics into our analysis, reinforcing the association of these findings. Prospective work is needed on the impact of modulating factors such as anticoagulation regimen and positive airway pressure therapy on these outcomes.