Surgeries

Prehabilitation represents a proactive, multimodal strategy to enhance patient resilience prior to plastic and reconstructive surgery, building on the success of Enhanced Recovery After Surgery (ERAS) pathways. This narrative review synthesizes the conceptual framework of prehabilitation—encompassing exercise training, nutritional optimization, risk factor modification, and psychological preparation—and examines its current application within plastic surgery. While evidence from selected randomized trials and systematic reviews in orthopedic and colorectal surgery suggests potential reductions in complications (often in the range of 20–40% in higher-risk populations), the results remain heterogeneous and context-dependent. To date, there have been no randomized controlled trials on plastic surgery, despite unique patient populations facing modifiable risks, including smoking, obesity, and malnutrition. This review proposes a risk-stratified prehabilitation framework tailored to key plastic surgery domains: breast reconstruction, head-and-neck microsurgery, post-bariatric body contouring, and major esthetic procedures. Practical implementation strategies address timelines, multidisciplinary teams, and digital delivery tools. By positioning prehabilitation as a structured preoperative component within ERAS pathways, plastic surgeons may support better perioperative readiness, potentially influencing complications, recovery, and patient experience. This review proposes conceptual frameworks intended to guide structured evaluation and future clinical research in plastic surgery.

Background/Objectives: Intraoperative neuromonitoring (IONM) has improved safety in thyroid and parathyroid surgery, yet intermittent IONM (I-IONM) may miss traction injuries developing between stimulations. We evaluated the feasibility and clinical utility of a trend-based intermittent monitoring mode (NIM Vital NerveTrend®) that records closely spaced stimulations and plots amplitude and latency over time. Methods: We conducted a prospective observational study at a high-volume endocrine surgery unit (January–September 2025). Forty-four consecutive patients undergoing thyroidectomy and/or parathyroidectomy with NerveTrend® were enrolled. Electromyography (EMG) responses were categorized as Green (amplitude > 50% of baseline and latency < 110%), Yellow (amplitude < 50% or latency > 110%), Red (amplitude < 50% and latency > 110%), and Loss of Signal (LOS: amplitude <100 µV). Primary outcomes included LOS prevalence and the association between stimulation frequency and the appearance of Yellow trends. Ethical approval: AVEN protocol 486/2024/OSS/AOUPR; informed consent obtained. Results: Of 71 nerves at risk (NAR), 55 had a valid baseline and were analyzed; LOS occurred in 3/55 NAR (5.5%). The mean number of stimulations per NAR was 4.5 (range 1–9). Cases with both Green and Yellow points had a significantly higher mean number of stimulations than cases with only Green points (5.1 vs. 3.8; Student’s t-test p = 0.0059). One Red measurement occurred in a case that progressed to LOS. Conclusions: NerveTrend® provided near real-time functional feedback while maintaining the simplicity of I-IONM. Increased stimulation frequency was associated with early Yellow trend alerts, potentially signaling traction stress and enabling timely surgical adjustments. Larger multicenter studies and protocol standardization are warranted.

Background: Lip aging is a heterogeneous and visually complex process, yet a standardized morphological classification applicable to clinical practice is still lacking. Current approaches mainly focus on volumetric loss or perioral rhytids, while the geometric features of the lips, including borders, projection, and eversion, remain poorly codified. Methods: Fifty anonymized lip images acquired under standardized conditions using digital facial imaging were independently evaluated by five physicians experienced in esthetic medicine. Images were classified according to three predefined morphotypes representing distinct patterns of lip aging. Inter-rater reliability was assessed using Fleiss’s kappa statistic. Results: Three recurrent morphotypes were consistently identified: devolumized lips, central lips, and chapped lips. Overall, 87% of images were assigned to one of the three morphotypes by at least four of five evaluators, while 13% were classified as undefined due to mixed features. Inter-rater agreement was substantial (κ = 0.89; 95% CI 0.79–0.99), confirming high reproducibility of the proposed classification. Conclusions: This study proposes a simple and reproducible image-based morphotypic classification of lip aging that captures recurrent visual patterns within this cohort. The framework may facilitate standardized clinical communication, support personalized rejuvenation strategies, and provide a foundation for future quantitative imaging studies and AI-based phenotype recognition in esthetic and reconstructive practice.