ReviewFrontiers in nutrition2026
Nutrition-related clinical laboratory indicators in perioperative management of geriatric hip fractures: a narrative review from risk stratification to precision intervention.
Review in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
Geriatric hip fracture represents a major global public health crisis that extends far beyond acute skeletal trauma, reflecting and accelerating systemic physiological decline in older adults. Malnutrition, affecting up to 46% of these patients depending on diagnostic criteria, has been established as a pivotal modifiable determinant of adverse postoperative outcomes including complications, functional decline, and mortality. Against this backdrop, nutrition-related clinical laboratory indicators have gained increasing recognition as objective, quantifiable, and readily accessible tools with potential dual utility in prognostic risk stratification and therapeutic monitoring, yet a comprehensive synthesis of their comparative performance and clinical translation remains lacking. This narrative review therefore aims to systematically synthesize current evidence on the spectrum of nutrition-related laboratory biomarkers ranging from classical protein markers (serum albumin and prealbumin), through inflammatory-nutritional composite indices (Prognostic Nutritional Index, Controlling Nutritional Status score, C-reactive protein/albumin ratio, glucose/albumin ratio, and systemic immune-inflammation index), to emerging proteomic and bone turnover biomarkers, and to critically appraise their predictive value for postoperative complications, functional recovery trajectories, and short- to long-term mortality. We further examine the pathophysiological nexus linking malnutrition, sarcopenia, and osteoporosis, and evaluate evidence-based perioperative nutritional interventions including oral nutritional supplements, enhanced recovery protocols, and multidisciplinary care models. Finally, we delineate future directions encompassing machine learning-driven predictive models, emerging diagnostic frameworks such as the Global Leadership Initiative on Malnutrition criteria, digital nutritional monitoring tools, and the integration of laboratory biomarkers into standardized clinical decision pathways. This review provides a comprehensive framework for clinicians and researchers to advance precision perioperative nutritional management in this vulnerable population.
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