Abstract
Research Advances and Precision Prospects of Biofeedback Combined with Baliao Acupoint Acupuncture for Rectal Atonic Constipation Based on Networked Brain-Gut Axis Modulation and Three-Tier Synergistic Intervention
DOI:
En KeyWords: rectal atonic constipation  brain-gut axis network  biofeedback  Baliao acupoints  three-tier synergistic intervention  neural plasticity  precision therapy
Fund Project:湖北省中医药管理局立项课题:"基于''肠-脑轴互动异常''理论对生物反馈联合八髎穴针刺治疗直肠无力型便秘的疗效评价研究"(ZY2025L161)
Author:xucheng
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En Abstract:
      Rectal atonic constipation (RAC), a highly disabling and refractory subtype of functional defecation disorders, has been increasingly redefined from a mere motility disorder to a systemic homeostatic imbalance across the neuro-endocrine-immune-microbiome multidimensional interaction network of the brain-gut axis. Departing from conventional unidimensional or parallel dual-target narratives, this review systematically integrates and critically examines the molecular mechanisms, neuroelectrophysiological foundations, and translational value of biofeedback combined with Baliao acupoint acupuncture from the perspective of networked brain-gut axis regulation. We propose a "central perceptual reshaping – sacral segmental facilitation – colonic motor activation" three-tier synergistic intervention framework, incorporating quantitative biomarkers such as neuroimaging structure-function coupling, gut metagenomic and metabolomic profiles, and autonomic balance parameters to elucidate the potential synergistic pathways through which combined therapy may overcome the limitations of monotherapies. Addressing the clinical neglect of individual brain-gut state fluctuations in current fixed protocols, we further advance a dynamic state-dependent precision adaptation strategy, advocating a shift from fixed courses to closed-loop adaptive interventions integrated with real-time physiological monitoring. This review aims to provide a theoretically grounded and practically relevant framework for multi-target mechanistic dissection, clinical decision-making optimization, and future AI-assisted personalized management of RAC.
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