Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 2 appraisals
Oral and maxillofacial surgery
Preservation rhinoplasty versus conventional structural reduction: a systematic review of aesthetic, functional, and patient-reported outcomes
BACKGROUND: Dorsal preservation rhinoplasty aims to maintain the native dorsal roof while achieving aesthetic and functional goals comparable to structural dorsal hump reduction. This systematic review evaluates comparative outcomes, patient-reported measures, and complication patterns across techniques. METHODS: A systematic search of PubMed, Embase, Scopus, Web of Science, and Cochrane CENTRAL was performed from inception to November 1, 2025. Eligible studies included randomized trials, comparative cohorts, and case series with ≥ 10 patients and ≥ 6 months of follow-up. Two reviewers independently screened studies, extracted data, and assessed risk of bias using RoB 2 and ROBINS-I. Outcomes included validated PROs, objective airway metrics, aesthetic assessments, and complications. RESULTS: From 487 records identified, 20 studies met inclusion criteria. Across randomized and nonrandomized comparative studies, dorsal preservation demonstrated aesthetic and functional results equivalent to structural dorsal hump reduction at 6-12 months. Patient-reported improvement (ROE, NOSE, SCHNOS) was consistently favorable in both groups. The only comparative objective airway study showed no significant differences in cross-sectional area or nasal volume. Complication and revision rates were low overall, with pooled recurrence and revision typically between 2-4%. CONCLUSION: Current evidence indicates that dorsal preservation rhinoplasty provides outcomes comparable to structural reduction in appropriately selected patients. Standardized reporting and more objective physiologic evaluations are needed.
10 May 2026
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Artificial Intelligence in Facial Plastic Procedures
OBJECTIVES: We reviewed the prospects of Artificial Intelligence (AI) and its usage in facial plastic surgery. METHODS: Literature search was performed using PubMed, Medline, Google and Google Scholar search engines between 2000 and 2025 years. RESULTS: AI is poised to impact the threefold missions of patient care, education and research. It plays a role in aiding clinician decision-making, serving as virtual conversational agents for patient engagement, and forecasting surgical outcomes. Primary areas of AI exploration in the medical field include machine learning (ML), neural networks (NN) and natural language processing (NLP). ML models have demonstrated the ability to detect facial features such as larger nasofrontal and nasolabial angles, correlating with increased attractiveness post-cosmetic rhinoplasty. Efficient resource allocation can be achieved through ML models guiding the analysis of post-operative free flap viability in facial skin cancer reconstruction. During online patient consultations, AI virtual assistants (AIVA) utilising NLP comprehend human speech intent, responding through dialogue. Unsupervised ML in facial analysis software is currently employed for correctly diagnosing rare diseases by recognising dysmorphic craniofacial features in two-dimensional photographs. AI also finds application in assessing post-operative outcomes, as well as in surgical training and research. CONCLUSION: The use of AI in healthcare is on the rise, contributing to advancements in pre-operative assessments, predicting prognoses, managing patients and monitoring postoperative progress. Surgeons are encouraged to explore collaboration with data scientists to shape the evolution of AI, aiming to enhance surgical efficiency, improve patient outcomes and potentially alleviate the workload associated with repetitive administrative duties.
1 Jan 2026
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