Z. Dang, J. Dan, W. Su, G. Ren, Z. Wang, Y. Ma, S. Li, D. Ji, L. Li, J. Gao
Background: ERAS protocols reduce hospital stay by 1.88 days and complications by 29% globally, but their one-size-fits-all paradigm, validated at sea level, may fail at high altitude where chronic hypoxia and population-specific genetic adaptations remodel baseline physiology. No study has quantified ERAS effect weight shifts at high altitude or proposed a theoretical model to explain the gap. Objectives: To evaluate three dimensions of plateau ERAS remodeling: (i) risk factor weight shift, (ii) traditional marker failure, (iii) genetic background modification, and propose the PAERS (Plateau Adaptation-ERAS Remodeling Syndrome) risk stratification model tailored to altitude. Methods: Retrospective cohort of 612 adults undergoing elective laparoscopic cholecystectomy (2018-2023) at Qinghai Red Cross Hospital (2260 m). Three analytical tiers: (1) multivariable regression comparing risk factor coefficients against plain-altitude benchmarks; (2) restricted cubic spline and interaction modeling for Hb, SpO2, and LOS; (3) inferential genetic modifier analysis using population-level EPAS1 carrier rates. Primary outcomes: LOS and complication rate. Results: Three-dimensional shift was observed: (1) Weight Remodeling: BMI replaced sex as primary risk factor (OR = 1.86, P < .001), surgeon variability amplified (F = 6.33 vs plain benchmark 2-4, an ~58% increase in F-statistic ratio, P < .001); (2) Marker Failure: Hb showed J-type relationship with LOS (Hb x SpO2 interaction beta = -0.0095, P = .009), with effect reversal across SpO2 strata (Plateau Hemoglobin Paradox); (3) Genetic Modification (population-level inference): ~70% EPAS1 carrier rate (range 57-85% across studies) suggests HIF-2alpha pathway is a baseline modifier that must be accounted for. Three falsifiable predictions were proposed. Conclusions: High-altitude ERAS faces three challenges: effect weight remodeling, biomarker failure, and genetic background calibration. The PAERS hypothesis proposes an integrated risk stratification model, shifting from one-size-fits-all to altitude-aware, patient-specific protocols.