4.6 Article

A noninvasive estimation of cerebral perfusion pressure using critical closing pressure

期刊

JOURNAL OF NEUROSURGERY
卷 123, 期 3, 页码 638-648

出版社

AMER ASSOC NEUROLOGICAL SURGEONS
DOI: 10.3171/2014.10.JNS14613

关键词

cerebral perfusion pressure; critical closing pressure; noninvasive model; transcranial Doppler ultrasonography; vascular disorders

资金

  1. A. G. Leventis Foundation Scholarship
  2. Charter Studentship from St. Edmund's College, Cambridge
  3. Royal College of Surgeons of England Research Fellowship
  4. National Institute for Health Research (NIHR) Academic Clinical Fellowship
  5. Raymond and Beverly Sackler Studentship
  6. Codman
  7. NIHR Research Professorship
  8. NIHR Cambridge Biomedical Research Centre
  9. NIHR Senior Investigator Award
  10. Medical Research Council [G9439390, G0600986, G0001237, G0601025] Funding Source: researchfish
  11. National Institute for Health Research [NIHR-RP-R3-12-013, NF-SI-0508-10327] Funding Source: researchfish
  12. MRC [G0601025, G0600986, G0001237, G9439390] Funding Source: UKRI

向作者/读者索取更多资源

OBJECT Cerebral blood flow is associated with cerebral perfusion pressure (CPP), which is clinically monitored through arterial blood pressure (ABP) and invasive measurements of intracranial pressure (ICP). Based on critical closing pressure (CrCP), the authors introduce a novel method for a noninvasive estimator of CPP (eCPP). METHODS Data from 280 head-injured patients with ABP, ICP, and transcranial Doppler ultrasonography measurements were retrospectively examined. CrCP was calculated with a noninvasive version of the cerebrovascular impedance method. The eCPP was refined with a predictive regression model of CrCP-based estimation of ICP from known ICP using data from 232 patients, and validated with data from the remaining 48 patients. RESULTS Cohort analysis showed eCPP to be correlated with measured CPP (R = 0.851, p < 0.001), with a mean SD difference of 4.02 +/- 6.01 mm Hg, and 83.3% of the cases with an estimation error below 10 mm Hg. eCPP accurately predicted low CPP (< 70 mm Hg) with an area under the curve of 0.913 (95% CI 0.883-0.944). When each recording session of a patient was assessed individually, eCPP could predict CPP with a 95% Cl of the SD for estimating CPP between multiple recording sessions of 1.89-5.01 mm Hg. CONCLUSIONS Overall, CrCP-based eCPP was strongly correlated with invasive CPP, with sensitivity and specificity for detection of low CPP that show promise for clinical use.

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