The increasing reliance on bibliometric indicators to define academic success has reshaped surgical training and evaluation worldwide. While research productivity plays a critical role in advancing medical knowledge, its growing dominance as a surrogate for professional excellence poses unique challenges in low-and middle-income countries. In these settings, surgeons shoulder a disproportionate burden of surgical disease, often managing high case volumes, advanced pathology, and limited resources. Despite this, academic recognition remains closely tied to publication metrics that inadequately capture operative skill, clinical judgement, and patient-centred outcomes. This editorial examines the misalignment between academic metrics and surgical competence in low-and middle-income countries, explores the influence of emerging technologies such as artificial intelligence on scholarly output, and argues for a more context-sensitive definition of surgical excellence. Reframing evaluation frameworks to balance scholarly contribution with clinical mastery is essential to preserving patient safety, training integrity, and the ethical foundations of surgical practice.
Talwar et al. (Tue,) studied this question.