https://scholars.lib.ntu.edu.tw/handle/123456789/611794
標題: | Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure-flow relation: The CARNet study | 作者: | Meel-van den Abeelen A.S.S. Simpson D.M. Wang L.J.Y. Slump C.H. Zhang R. Tarumi T. Rickards C.A. Payne S. Mitsis G.D. Kostoglou K. Marmarelis V. Shin D. Tzeng Y.-C. Ainslie P.N. Gommer E. M?ller M. Dorado A.C. Smielewski P. Yelicich B. Puppo C. Liu X. Czosnyka M. Wang C.-Y. Novak V. Panerai R.B. Claassen J.A.H.R. STEPHEN JOHN PAYNE |
關鍵字: | Blood pressure;Regression analysis;Signal processing;Standardization;Tissue;Cerebral autoregulation;Cerebral blood flow velocities;Logistic regressions;Method comparison;Optimal signal processing;Parameter setting;Spontaneous oscillations;Transfer function analysis;Transfer functions;area under the curve;article;autoregulation;blood flow velocity;blood pressure;brain blood flow;dynamic cerebral autoregulation;human;hypercapnia;logistic regression analysis;oscillation;priority journal;rank sum test;statistical analysis;transfer function analysis;biological model;brain circulation;clinical trial;homeostasis;multicenter study;pathophysiology;signal processing;statistical model;Blood Flow Velocity;Blood Pressure;Cerebrovascular Circulation;Homeostasis;Humans;Hypercapnia;Linear Models;Models, Biological;Signal Processing, Computer-Assisted | 公開日期: | 2014 | 卷: | 36 | 期: | 5 | 起(迄)頁: | 620-627 | 來源出版物: | Medical Engineering and Physics | 摘要: | Transfer function analysis (TFA) is a frequently used method to assess dynamic cerebral autoregulation (CA) using spontaneous oscillations in blood pressure (BP) and cerebral blood flow velocity (CBFV). However, controversies and variations exist in how research groups utilise TFA, causing high variability in interpretation. The objective of this study was to evaluate between-centre variability in TFA outcome metrics. 15 centres analysed the same 70 BP and CBFV datasets from healthy subjects (n= 50 rest; n= 20 during hypercapnia); 10 additional datasets were computer-generated. Each centre used their in-house TFA methods; however, certain parameters were specified to reduce a priori between-centre variability. Hypercapnia was used to assess discriminatory performance and synthetic data to evaluate effects of parameter settings. Results were analysed using the Mann-Whitney test and logistic regression. A large non-homogeneous variation was found in TFA outcome metrics between the centres. Logistic regression demonstrated that 11 centres were able to distinguish between normal and impaired CA with an AUC. >. 0.85. Further analysis identified TFA settings that are associated with large variation in outcome measures.These results indicate the need for standardisation of TFA settings in order to reduce between-centre variability and to allow accurate comparison between studies. Suggestions on optimal signal processing methods are proposed. ? 2014 IPEM. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84899642715&doi=10.1016%2fj.medengphy.2014.02.002&partnerID=40&md5=434ce78e2e572d19534dd3758e9b695a https://scholars.lib.ntu.edu.tw/handle/123456789/611794 |
DOI: | 10.1016/j.medengphy.2014.02.002 |
顯示於: | 應用力學研究所 |
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