Optimizing liposomal bupivacaine in thoracoscopic enhanced recovery: precision stratification, protocol standardization, and equitable access: A Letter to the Editor about “Effect of liposomal bupivacaine for preoperative erector spinae plane block o

Dear Editor, We commend Shan et al[1] for their multicenter randomized trial demonstrating that erector spinae plane block (ESPB) with liposomal bupivacaine (LB) significantly reduces 72-hour cumulative pain scores and opioid requirements following video-assisted thoracoscopic lung resection. This methodologically rigorous trial meaningfully advances perioperative analgesia by addressing the clinical need for prolonged regional anesthesia within enhanced recovery after surgery (ERAS) pathways. While the investigation appropriately highlights LB’s pharmacokinetic advantages and cost-effectiveness, we identify three underexplored dimensions that could substantially amplify its translational impact. We have been assured that the article complies with TITAN Guidelines 2025 – governing declaration and use of AI[2]. Enhancing precision through biomarker stratification The trial identified statistically significant pain reduction with LB at 24–48 hours but noted that clinical significance (minimal clinically important difference, MCID) was only achieved at discrete timepoints (24/32 h). This temporal heterogeneity underscores the substantial interindividual variability in treatment response, driven by uncharacterized biological determinants. Genetic polymorphisms in drug metabolism pathways – particularly OPRM1 A118G variants altering µ-opioid receptor affinity and CYP3A4 variants affecting local anesthetic clearance – may critically modulate LB efficacy[3]. Concurrently, preoperative inflammatory states quantified by elevated interleukin-6 or C-reactive protein correlate with heightened pain sensitivity through central glial activation, potentially antagonizing LB’s peripheral effects[4]. Shan et al excluded patients with psychiatric comorbidities or chronic pain, yet psychological resilience modulates postoperative pain perception and LB efficacy. Future trials should incorporate preoperative biomarker profiling (genetic, inflammatory, and psychometric) to stratify patients most likely to derive clinically meaningful benefits from LB. For example, machine learning algorithms trained on multi-omic data could identify high responders, optimizing resource allocation in resource-constrained settings. Standardizing ERAS implementation to isolate intervention effects Critical protocol deviations were observed in ERAS implementation despite formal adherence: 20% of LB recipients deviated from patient-controlled analgesia (PCA) protocols, while rescue analgesic regimens (e.g., tramadol vs oxycodone) varied across centers. These inconsistencies introduce major confounding in opioid consumption metrics and obscure LB’s true pharmacodynamic profile. Such heterogeneity reflects pervasive real-world ERAS execution challenges, including variable staff training, equipment access disparities, and inconsistent adherence auditing. Given LB’s peak efficacy coincides with the critical 24–48-hour mobilization phase, its synergy with ERAS components requires evaluation using standardized implementation frameworks. The RE-AIM model (Reach, Effectiveness, Adoption, Implementation, Maintenance) offers a validated approach to quantify delivery fidelity through metrics like “dose-adjusted compliance rates” and implementation barriers analysis[5]. Incorporation of ERAS Compliance Scores would enable risk-adjusted outcome interpretation – particularly crucial for translating findings to low-resource settings with substantial protocol delivery variance. Addressing Population Heterogeneity in Pharmacokinetic Optimization The trial’s homogeneous cohort (mean BMI 23.5 kg/m2, exclusion of high-BMI patients) overlooks the escalating global obesity epidemic and its impact on regional anesthesia efficacy. Adipose tissue fundamentally alters LB’s pharmacokinetics: excessive adipose tissue cause that diffusion barriers reduce fascial plane spread volume, while increased volume of distribution prolongs time to effective therapeutic concentration[6]. These changes necessitate adipose-adjusted dosing strategies such as weight-tiered regimens or concentration optimization. Furthermore, neglecting this subpopulation perpetuates treatment disparities: obese patients exhibit significantly higher postoperative opioid requirements and greater chronic pain risk compared to non-obese patients. The economic implications are substantial, particularly in low- and middle-income countries where LB costs substantially more than traditional bupivacaine, rendering universal adoption unsustainable without precision allocation. Future research must prioritize pharmacokinetic–pharmacodynamic modeling across diverse somatotypes to ensure equitable therapeutic access. We commend Shan et al’s methodologically robust trial establishing LB as valuable for thoracoscopic enhanced recovery. Building on this foundation, three enhancements could maximize impact: First, implement preoperative biomarker stratification to target LB responders. Second, standardize ERAS delivery via RE-AIM frameworks to optimize synergy during LB’s 24–48 h efficacy peak. Third, address obesity through adipose-adjusted pharmacokinetic modeling for equitable global access. These refinements – spanning precision allocation, standardized protocols, and inclusive pharmacokinetics – will transform the authors’ pivotal work into a model of precision analgesia accessible across diverse populations, advancing thoracic recovery toward greater efficacy, equity, and sustainability.