Podder Dhruba, Stala Olivia, Hirani Rahim, Karp Adam M, Etienne Mill
School of Medicine, New York Medical College, Valhalla, NY 10595, USA.
Department of Neurology, New York Medical College, Valhalla, NY 10595, USA.
Neurol Int. 2025 Jun 18;17(6):94. doi: 10.3390/neurolint17060094.
Effective postoperative pain management remains a major clinical challenge in spinal surgery, with poorly controlled pain affecting up to 50% of patients and contributing to delayed mobilization, prolonged hospitalization, and risk of chronic postsurgical pain. This review synthesizes current and emerging strategies in postoperative spinal pain management, tracing the evolution from opioid-centric paradigms to individualized, multimodal approaches. Multimodal analgesia (MMA) has become the cornerstone of contemporary care, combining pharmacologic agents, such as non-steroidal anti-inflammatory drugs (NSAIDs), acetaminophen, and gabapentinoids, with regional anesthesia techniques, including erector spinae plane blocks and liposomal bupivacaine. Adjunctive nonpharmacologic modalities like early mobilization, cognitive behavioral therapy, and mindfulness-based interventions further optimize recovery and address the biopsychosocial dimensions of pain. For patients with refractory pain, neuromodulation techniques such as spinal cord and peripheral nerve stimulation offer promising results. Advances in artificial intelligence (AI), biomarker discovery, and nanotechnology are poised to enhance personalized pain protocols through predictive modeling and targeted drug delivery. Enhanced recovery after surgery protocols, which integrate many of these strategies, have been shown to reduce opioid use, hospital length of stay, and complication rates. Nevertheless, variability in implementation and the need for individualized protocols remain key challenges. Future directions include AI-guided analytics, regenerative therapies, and expanded research on long-term functional outcomes. This review provides an evidence-based framework for pain control following spinal surgery, emphasizing integration of multimodal and innovative approaches tailored to diverse patient populations.
有效的术后疼痛管理仍然是脊柱手术中的一项重大临床挑战，疼痛控制不佳影响高达50%的患者，并导致活动延迟、住院时间延长和慢性术后疼痛风险增加。本综述综合了术后脊柱疼痛管理的当前和新兴策略，追溯了从以阿片类药物为中心的模式到个性化多模式方法的演变。多模式镇痛（MMA）已成为当代护理的基石；它将非甾体抗炎药（NSAIDs）、对乙酰氨基酚和加巴喷丁类药物等药物与竖脊肌平面阻滞和脂质体布比卡因等区域麻醉技术相结合。早期活动、认知行为疗法和正念干预等辅助非药物模式进一步优化恢复，并解决疼痛的生物心理社会层面问题。对于难治性疼痛患者，脊髓和周围神经刺激等神经调节技术提供了有希望的结果。人工智能（AI）、生物标志物发现和纳米技术的进步有望通过预测建模和靶向药物递送增强个性化疼痛方案。整合了许多这些策略的术后加速康复方案已被证明可减少阿片类药物使用、住院时间和并发症发生率。然而，实施的可变性和个性化方案的需求仍然是关键挑战。未来的方向包括人工智能引导的分析、再生疗法以及对长期功能结果的扩展研究。本综述为脊柱手术后的疼痛控制提供了一个基于证据的框架，强调整合针对不同患者群体量身定制的多模式和创新方法。
