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Pain Management: Current Challenges and Future Prospects
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Pain Management: Current Challenges and Future Prospects

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Anesthesiology".

Deadline for manuscript submissions: 30 August 2025 | Viewed by 1113

Special Issue Editor

Dr. Gian Marco Petroni

E-Mail Website
Guest Editor
Department of Emergency, Unit of Anesthesia and Pain management, Santa Maria Hospital, Terni, Italy
Interests: ESP block; chronic pain; chronic joint pain; radiofrequency ablation

Special Issue Information

Dear Colleagues,

Chronic pain is a complex and widespread phenomenon that occurs in the general population at a prevalence of 20%. Chronic pain causes a reduction in the quality of life, which is associated with increased morbidity and high costs for the healthcare system.

Every day, clinicians face great challenges related to chronic pain; these relate to topics ranging from invasive and minimally invasive techniques to regenerative medicine.

The aim of this Special Issue is to summarize the most recent evidence relating to pain medicine, with a focus on the radio frequency ablation of the articular branches to the large joints, as well as on the role of autologous regenerative therapy in chronic pain.

Research articles, reviews, technical communications, and case reports are welcome.

Dr. Gian Marco Petroni
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • chronic joint pain
  • radio frequency ablation
  • adipose-derived mesenchimal stem cells (ADMScs)
  • intrarticular injection
  • facet joint injection with ADMScs

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

11 pages, 930 KiB  
Article
Prediction of Postoperative Pain and Side Effects of Patient-Controlled Analgesia in Pediatric Orthopedic Patients Using Machine Learning: A Retrospective Study
by Young-Eun Joe, Nayoung Ha, Woojoo Lee and Hyo-Jin Byon
J. Clin. Med. 2025, 14(5), 1459; https://doi.org/10.3390/jcm14051459 - 21 Feb 2025
Viewed by 351
Abstract
Background/Objectives: Appropriate postoperative management, especially in pediatric patients, can be challenging for anesthesiologists. This retrospective study used machine learning to investigate the effects and complications of patient-controlled analgesia (PCA) in children undergoing orthopedic surgery. Methods: The medical records of children who [...] Read more.
Background/Objectives: Appropriate postoperative management, especially in pediatric patients, can be challenging for anesthesiologists. This retrospective study used machine learning to investigate the effects and complications of patient-controlled analgesia (PCA) in children undergoing orthopedic surgery. Methods: The medical records of children who underwent orthopedic surgery in a single tertiary hospital and received intravenous and epidural PCA were analyzed. Predictive models were developed using machine learning, and various demographic, anesthetic, and surgical factors were investigated to predict postoperative pain and complications associated with PCA. Results: Data from 1968 children were analyzed. Extreme gradient boosting effectively predicted moderate postoperative pain for the 6–24-h (area under curve (AUC): 0.85, accuracy (ACC): 0.79) and 24–48-h (AUC: 0.89, ACC: 0.87) periods after surgery. The factors that predicted moderate postoperative pain included the pain score immediately before the measurement period, the total amount of opioid infused, and age. For predicting side effects during the 6–24-h period after surgery, a least absolute shrinkage and selection operator model (AUC: 0.75, ACC: 0.64) was selected, while a random forest model (AUC: 0.91, ACC: 0.87) was chosen for the 24–48-h period post-surgery. The factors that predicted complications included the occurrence of side effects immediately before the measurement period, the total amount of opioid infused before the measurement period, and age. Conclusions: This retrospective study introduces machine-learning-based models and factors aimed at forecasting moderate postoperative pain and complications of PCA in children undergoing orthopedic surgery. This research has the potential to enhance postoperative pain management strategies for children. Full article
(This article belongs to the Special Issue Pain Management: Current Challenges and Future Prospects)
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14 pages, 913 KiB  
Article
Association of Opioid Prescription with Major Adverse Cardiovascular Events: Nationwide Cohort Study
by Tak-Kyu Oh, Hyoung-Won Cho and In-Ae Song
J. Clin. Med. 2025, 14(4), 1205; https://doi.org/10.3390/jcm14041205 - 12 Feb 2025
Viewed by 530
Abstract
Background: This study aimed to investigate the association between opioid use and the incidence of major adverse cardiovascular events (MACEs). Methods: This study included adult patients who had received oral or transdermal opioids in 2016. The control group comprised individuals who [...] Read more.
Background: This study aimed to investigate the association between opioid use and the incidence of major adverse cardiovascular events (MACEs). Methods: This study included adult patients who had received oral or transdermal opioids in 2016. The control group comprised individuals who did not receive opioids in 2016 and was selected using a 1:1 stratified random sampling procedure. A MACE was defined as the occurrence of acute myocardial infarction, stroke, heart failure, or cardiovascular mortality. The primary endpoints were new MACEs and cardiovascular mortality, as evaluated from 1 January 2017 to 31 December 2021. Results: The study included 4,179,130 participants, of whom 1,882,945 (45.1%) were opioid users. After propensity score matching, 1,811,732 individuals (905,866 in each group) were included. Cox regression analysis revealed that the opioid user group had a 24% higher incidence of MACEs than the non-user group (hazard ratio [HR]: 1.24; 95% confidence interval [CI]: 1.23, 1.24; p < 0.001). Additionally, the opioid user group showed a 30% higher risk of cardiovascular mortality than the non-user group (HR: 1.30; 95% CI: 1.26, 1.35; p < 0.001). Conclusions: Opioid use was associated with an increased incidence of MACE and higher risk of cardiovascular mortality. Full article
(This article belongs to the Special Issue Pain Management: Current Challenges and Future Prospects)
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