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Medicina
Special Issues
Advanced Clinical Approaches in Perioperative Pain Management
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Advanced Clinical Approaches in Perioperative Pain Management

A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Intensive Care/ Anesthesiology".

Deadline for manuscript submissions: 30 May 2026 | Viewed by 1265

Special Issue Editor

Prof. Dr. Mark Ulrich Gerbershagen

E-Mail Website
Guest Editor
Department of Anesthesiology, Hospital Cologne-Holweide, University Witten-Herdecke, Neufelder Strasse 32, 51067 Cologne, Germany
Interests: anesthesia; intensive care medicine; malignant hyperthermia; thoracic anesthesia; regional anesthesia; airway management; obstetric anesthesia; pain management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The management of pain during the perioperative period continues to represent a significant challenge in contemporary surgical practice, with direct implications for patient recovery, the prevention of chronic pain, and long-term outcomes. The field is undergoing a rapid transformation, with multimodal and precision-based strategies redefining standards of care. Recent developments in the field include the following: firstly, the integration of enhanced recovery protocols that align analgesic strategies with holistic perioperative care; secondly, the innovative application of regional anesthesia; and thirdly, the optimized use of non-opioid adjuvants. Conversely, digital health tools and personalized risk assessment models are transforming the way clinicians monitor, predict, and adapt pain interventions in real time.

In order to further advance this dynamic area of research, we welcome submissions that explore novel clinical, technological, and translational approaches in perioperative pain management, as well as original research, systematic reviews, clinical trials, and thought-provoking perspectives that address a range of topics; this includes, but is not limited to, the following: ultrasound-guided nerve blocks, opioid-sparing pharmacology, patient-centered care models, and digital innovations in monitoring and assessment. Contributions that span the interface between clinical practice and scientific discovery, or that emphasize multidisciplinary and global perspectives, are particularly encouraged.

Prof. Dr. Mark Ulrich Gerbershagen
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 250 words) can be sent to the Editorial Office for assessment.

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. Medicina is an international peer-reviewed open access monthly 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 2200 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

  • anesthesiology
  • regional anesthesia
  • acute pain
  • chronic pain
  • perioperative pain management

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Published Papers (2 papers)

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Research

12 pages, 2281 KB  
Article
Machine Learning Methods for the Prediction of Intraoperative Hypotension with Biosignal Waveforms
by Jae-Geum Shim, Wonhyuck Yoon, Sang Jun Lee, Se-Hyun Chang, So-Ra Jung and Jun Young Chung
Medicina 2025, 61(11), 2039; https://doi.org/10.3390/medicina61112039 - 14 Nov 2025
Viewed by 539
Abstract
Background and Objectives: Intraoperative hypotension (IOH) is of great importance in preventing diseases such as postoperative myocardial infarction, acute kidney injury, and mortality. This study aimed to develop and validate machine learning and deep learning models that predict IOH using both biosignals [...] Read more.
Background and Objectives: Intraoperative hypotension (IOH) is of great importance in preventing diseases such as postoperative myocardial infarction, acute kidney injury, and mortality. This study aimed to develop and validate machine learning and deep learning models that predict IOH using both biosignals and personalized clinical information for each patient. Materials and Methods: In this retrospective observational study, we used the VitalDB open dataset, which included intraoperative biosignals and clinical information from 6388 patients who underwent non-cardiac surgery between June 2016 and August 2017 at Seoul National University Hospital, Seoul, South Korea. The predictive performances of models trained with four waveforms (arterial blood pressure, electrocardiography, photoplethysmography, and capnography) and clinical information were evaluated and compared at time points at 5 min before the hypotensive event. To predict hypotensive events during surgery, we developed two predictive models: machine learning and deep learning. In total, 2611 patients were enrolled in this retrospective study. Machine and deep learning algorithms were developed and validated using raw waveforms and clinical information as inputs. Results: Gradient boosting machine showed predicted IOH with an AUROC and accuracy of 0.94 (0.93–0.95) and 0.88 (0.86–0.89). A hybrid CNN-RNN model also showed similar performance with an AUROC and accuracy of 0.94 (0.93–0.95) and 0.88 (0.87–0.89). Conclusions: This study developed and validated machine and deep learning models to predict IOH using waveform data and covariate values. In the future, we anticipate that the results of our study will contribute to predicting IOH in real time in the operating room and reducing the occurrence of IOH. Full article
(This article belongs to the Special Issue Advanced Clinical Approaches in Perioperative Pain Management)
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15 pages, 5188 KB  
Article
Ultrasound-Guided Regional Anesthesia as Primary Analgesic Management in the Orthopedic-Surgical Emergency Department of an Affiliated Hospital: A Retrospective Analysis over a 6-Year Period
by Eckehart Schöll, Mark Ulrich Gerbershagen, Andreas Marc Müller and Rainer Jürgen Litz
Medicina 2025, 61(11), 2006; https://doi.org/10.3390/medicina61112006 - 10 Nov 2025
Viewed by 573
Abstract
Background and Objectives: Ultrasound (US)-guided peripheral regional anesthesia (pRA) is gaining increasing importance in emergency medicine as an effective, low-ridsk alternative to general anesthesia (GA), procedural sedation (PS), or opioid therapy. By enabling rapid, direct pain management in the emergency department (ED), [...] Read more.
Background and Objectives: Ultrasound (US)-guided peripheral regional anesthesia (pRA) is gaining increasing importance in emergency medicine as an effective, low-ridsk alternative to general anesthesia (GA), procedural sedation (PS), or opioid therapy. By enabling rapid, direct pain management in the emergency department (ED), pRA can help preserve scarce surgical and anesthetic resources and, in some cases, avoid inpatient admissions. The aim of this study was to analyze the indications, techniques, and clinical impact of pRA in the orthopedic-focused ED of an affiliated hospital. Materials and Methods: All pRA and PS procedures performed over a six-year period were retrospectively reviewed among 35,443 orthopedic-trauma emergency patients. pRA was carried out under US guidance with standardized monitoring. Diagnoses, block techniques, effectiveness, and complications were analyzed descriptively. Results: A total of 1292 patients (3.7%) underwent either pRA (n = 1117; 3.2%) or PS (n = 175; 0.5%). pRA was performed in 22% of cases for interventions such as reductions or extensive wound management. In 78%, pRA was applied for analgesia, for example, in the diagnostic work-up and treatment of non-immediately operable fractures, lumbago, or arthralgia. The most common pRA techniques were brachial plexus blocks (54%) and femoral nerve blocks (25%). Fascial plane blocks (6.1%) and paravertebral blocks (1.5%) were rarely used. PS was performed in 175 of 1292 patients (13%), although pRA would have been feasible in 159 of these cases. No complications of pRA were observed, and GA could routinely be avoided. Conclusions: US-guided pRA proved to be an effective and safe alternative to PS, GA, or systemic analgesia for selected indications, allowing immediate treatment without the need for operative capacities. To ensure safe application, these techniques should be an integral part of the training curriculum for ED personnel. Full article
(This article belongs to the Special Issue Advanced Clinical Approaches in Perioperative Pain Management)
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