Influence of head-over-body and body-over-head posture on craniospinal, vascular, and abdominal pressures in an acute ovine in-vivo model

头对身和身对头姿势对急性绵羊体内模型中颅脊压、血管压和腹压的影响

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Abstract

INTRODUCTION: Optimal shunt-based hydrocephalus treatments are heavily influenced by dynamic pressure behaviors between proximal and distal ends of shunt catheters. Posture-dependent craniospinal, arterial, venous, and abdominal dynamics thereby play an essential role. METHODS: An in-vivo ovine trial (n = 6) was conducted to evaluate communication between craniospinal, arterial, venous, and abdominal dynamics. Tilt-testing was performed between -13° and + 13° at 10-min intervals starting and ending at 0° prone position. Mean pressure, pulse pressure, and Pearson correlation (r) to the respective angle were calculated. Correlations are defined as strong: |r|≥ 0.7, mild: 0.3 <|r|< 0.7, and weak: |r|≤ 0.3. Transfer functions (TFs) between the arterial and adjacent compartments were derived. RESULTS: Strong correlations were observed between posture and: mean carotid/femoral arterial (r = - 0.97, r = - 0.87), intracranial, intrathecal (r = - 0.98, r = 0.94), jugular (r = - 0.95), abdominal cranial, dorsal, caudal, and intravesical pressure (r = - 0.83, r = 0.84, r = - 0.73, r = 0.99) while mildly positive correlation exists between tilt and central venous pressure (r = 0.65). Only dorsal abdominal pulse pressure yielded a significant correlation to tilt (r = 0.21). TFs followed general lowpass behaviors with resonant peaks at 4.2 ± 0.4 and 11.5 ± 1.5 Hz followed by a mean roll-off of - 15.9 ± 6.0 dB/decade. CONCLUSIONS: Tilt-tests with multi-compartmental recordings help elucidate craniospinal, arterial, venous, and abdominal dynamics, which is essential to optimize shunt-based therapy. Results motivate hydrostatic influences on mean pressure, with all pressures correlating to posture, with little influence on pulse pressure. TF results quantify the craniospinal, arterial, venous, and abdominal compartments as compliant systems and help pave the road for better quantitative models of the interaction between the craniospinal and adjacent spaces.

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