Evaluation, Management, and Outcomes in Perioperative Medicine

A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Surgery".

Deadline for manuscript submissions: 15 February 2026 | Viewed by 1748

Special Issue Editors


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Guest Editor
Department of Medicine, Autonomous University of Madrid, 29040 Madrid, Spain
Interests: point-of-care ultrasound; lung ultrasound; venous thromboembolic disease; systemic venous congestion; body composition

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Guest Editor Assistant
Medical Department, Faculty of Medicine, University Complutense of Madrid, 28040 Madrid, Spain
Interests: surgical prehabilitation; sarcopenia; disease related malnutrition; perioperative medicine

Special Issue Information

Dear Colleagues,

Perioperative medicine has undergone significant transformations in recent decades, evolving from a purely surgical and anesthetic focus to a holistic, multidisciplinary approach encompassing medical optimization, risk stratification, and post-operative recovery. Advances in anesthesiology, enhanced recovery pathways, and individualized patient care have contributed to improved outcomes. Nonetheless, the increasing complexity of surgical patients—often elderly, frail, or with multiple comorbidities—demands the further refinement of perioperative strategies. Recent attention has focused on prehabilitation, nutritional status, cognitive evaluation, and cardiovascular risk management, all of which play a pivotal role in perioperative success. However, there remains a need for high-quality evidence to guide clinicians in this evolving field.

This Special Issue aims to explore the comprehensive landscape of perioperative medicine, emphasizing the integration of evaluation protocols, patient-centered management strategies, and the impact on both short- and long-term surgical outcomes. We welcome contributions that advance our understanding of the physiological, psychological, and functional trajectories of surgical patients before, during, and after major procedures. By bringing together diverse perspectives—from anesthesiology and surgery to geriatrics, internal medicine, and rehabilitation—this Special Issue will foster interdisciplinary dialog and innovation.

We are particularly interested in manuscripts presenting novel findings or approaches in various areas, such as the following:

  • Perioperative risk stratification and optimization;
  • Implementation and efficacy of prehabilitation programs;
  • Biomarkers and predictive models for surgical outcomes;
  • Personalized anesthesia and intraoperative management;
  • Postoperative complications: prevention, detection, and management;
  • Role of artificial intelligence and machine learning in perioperative care;
  • Functional recovery and quality of life post-surgery;
  • Innovations in patient blood management, nutritional support, and frailty assessment.

We invite original research articles, systematic reviews, narrative reviews, meta-analyses, and clinical trials that contribute to the advancement of perioperative medicine. Multidisciplinary studies, translational research, and papers highlighting the real-world implementation of perioperative strategies are especially welcome. Submissions should provide robust methodology, clinically relevant insights, and practical implications for healthcare professionals involved in perioperative care.

Dr. Yale Tung-Chen
Guest Editor

Dr. Francisco Javier García Sánchez
Guest Editor Assistant

Manuscript Submission Information

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Keywords

  • perioperative medicine
  • surgical outcomes
  • prehabilitation
  • risk stratification
  • patient optimization
  • enhanced recovery
  • multimorbidity
  • postoperative complications
  • functional recovery
  • patient-centered care

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Published Papers (2 papers)

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Research

13 pages, 283 KB  
Article
Optimization of Postoperative Antimicrobial Therapy in Surgical Patients Using a Clinical Decision Support System: Use Patterns and Clinical Outcomes
by Miguel Ángel Amor García, Irene Orozco Cifuentes, Raquel Moreno Díaz, José Antonio Martínez Consuegra and Carmen de Cáceres Velasco
Medicina 2025, 61(11), 2043; https://doi.org/10.3390/medicina61112043 - 15 Nov 2025
Viewed by 527
Abstract
Background and Objectives: Antimicrobial stewardship plays a key role in the surgical setting by reducing the incidence of healthcare-associated infections and limiting the emergence of antimicrobial resistance. Clinical Decision Support Systems (CDSSs), when integrated into routine practice, are valuable tools for optimizing [...] Read more.
Background and Objectives: Antimicrobial stewardship plays a key role in the surgical setting by reducing the incidence of healthcare-associated infections and limiting the emergence of antimicrobial resistance. Clinical Decision Support Systems (CDSSs), when integrated into routine practice, are valuable tools for optimizing antimicrobial prescribing. However, evidence regarding their impact on surgical patients, particularly across different specialties, remains limited. Materials and Methods: We conducted a quasi-experimental time series study in surgical patients at a primary-level hospital, evaluating the effect of a CDSS on postoperative antimicrobial therapy. The pre-intervention period included patients admitted from April 2017 to September 2020, and the post-intervention period included those admitted from October 2020 to March 2024. Antimicrobial consumption and expenditures were measured as defined daily doses (DDDs) per 1000 patient-days and euros (€) per 1000 patient-days, respectively. Subgroup analyses were performed by the surgical service. Clinical outcomes included mortality and length of stay (LOS). Results: Following CDSS implementation, overall antimicrobial consumption decreased by 4.4%. Significant reductions were observed in aminoglycosides (−52.0%), macrolides, lincosamides and streptogramins (−40.6%), and fluoroquinolones (−32.3%). Reductions were heterogeneous across surgical services, with significant reductions in Traumatology (−21.3%) and Urology (−14.3%). Expenditures decreased from 3185.4 to 2733.9€/1000 patient-days (−14.2%; p = 0.17). Mortality remained stable, whereas significant reductions in LOS were observed in Urology (5 to 4 days, p = 0.03) and traumatology (16 to 8.5 days, p < 0.01). During the post-intervention period, 476 stewardship recommendations were issued for 330 patients, with an acceptance rate of 76.1%. The most frequent interventions were discontinuation of antimicrobials (25.8%), transition to oral therapy (21.0%), and de-escalation (18.7%). Conclusions: Implementation of a CDSS in the surgical setting was associated with reduced antimicrobial consumption, a downward trend in expenditures, and high acceptance of stewardship recommendations. Mortality remained unchanged, while reductions in LOS in selected services support the safety and potential efficiency of this approach. Full article
(This article belongs to the Special Issue Evaluation, Management, and Outcomes in Perioperative Medicine)
13 pages, 777 KB  
Article
Nomogram Development and Feature Selection Strategy Comparison for Predicting Surgical Site Infection After Lower Extremity Fracture Surgery
by Humam Baki and Atilla Sancar Parmaksızoğlu
Medicina 2025, 61(8), 1378; https://doi.org/10.3390/medicina61081378 - 30 Jul 2025
Viewed by 789
Abstract
Background and Objectives: Surgical site infections (SSIs) are a frequent complication after lower extremity fracture surgery, yet tools for individualized risk prediction remain limited. This study aimed to develop and internally validate a nomogram for individualized SSI risk prediction based on perioperative [...] Read more.
Background and Objectives: Surgical site infections (SSIs) are a frequent complication after lower extremity fracture surgery, yet tools for individualized risk prediction remain limited. This study aimed to develop and internally validate a nomogram for individualized SSI risk prediction based on perioperative clinical parameters. Materials and Methods: This retrospective cohort study included adults who underwent lower extremity fracture surgery between 2022 and 2025 at a tertiary care center. Thirty candidate predictors were evaluated. Feature selection was performed using six strategies, and the final model was developed with logistic regression based on bootstrap inclusion frequency. Model performance was assessed by area under the curve, calibration slope, Brier score, sensitivity, and specificity. Results: Among 638 patients undergoing lower extremity fracture surgery, 76 (11.9%) developed SSIs. Of six feature selection strategies compared, bootstrap inclusion frequency identified seven predictors: red blood cell count, preoperative C-reactive protein, chronic kidney disease, operative time, chronic obstructive pulmonary disease, body mass index, and blood transfusion. The final model demonstrated an AUROC of 0.924 (95% CI, 0.876–0.973), a calibration slope of 1.03, and a Brier score of 0.0602. Sensitivity was 86.2% (95% CI, 69.4–94.5) and specificity was 89.5% (95% CI, 83.8–93.3). Chronic kidney disease (OR, 88.75; 95% CI, 5.51–1428.80) and blood transfusion (OR, 85.07; 95% CI, 11.69–619.09) were the strongest predictors of infection. Conclusions: The developed nomogram demonstrates strong predictive performance and may support personalized SSI risk assessment in patients undergoing lower extremity fracture surgery. Full article
(This article belongs to the Special Issue Evaluation, Management, and Outcomes in Perioperative Medicine)
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