dc.contributorFaculdade de Medicina de São José do Rio Preto (FAMERP)
dc.contributorFaculdade de Medicina do ABC (FMABC)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:27:07Z
dc.date.accessioned2022-10-05T18:36:59Z
dc.date.available2014-05-27T11:27:07Z
dc.date.available2022-10-05T18:36:59Z
dc.date.created2014-05-27T11:27:07Z
dc.date.issued2012-10-31
dc.identifierInternational Archives of Medicine, v. 5, n. 1, 2012.
dc.identifier1755-7682
dc.identifierhttp://hdl.handle.net/11449/73692
dc.identifier10.1186/1755-7682-5-31
dc.identifier2-s2.0-84867896684
dc.identifier2-s2.0-84867896684.pdf
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3922676
dc.description.abstractBackground: Decreased heart rate variability (HRV) is related to higher morbidity and mortality. In this study we evaluated the linear and nonlinear indices of the HRV in stable angina patients submitted to coronary angiography. Methods. We studied 77 unselected patients for elective coronary angiography, which were divided into two groups: coronary artery disease (CAD) and non-CAD groups. For analysis of HRV indices, HRV was recorded beat by beat with the volunteers in the supine position for 40 minutes. We analyzed the linear indices in the time (SDNN [standard deviation of normal to normal], NN50 [total number of adjacent RR intervals with a difference of duration greater than 50ms] and RMSSD [root-mean square of differences]) and frequency domains ultra-low frequency (ULF) ≤ 0,003 Hz, very low frequency (VLF) 0,003 - 0,04 Hz, low frequency (LF) (0.04-0.15 Hz), and high frequency (HF) (0.15-0.40 Hz) as well as the ratio between LF and HF components (LF/HF). In relation to the nonlinear indices we evaluated SD1, SD2, SD1/SD2, approximate entropy (-ApEn), α1, α2, Lyapunov Exponent, Hurst Exponent, autocorrelation and dimension correlation. The definition of the cutoff point of the variables for predictive tests was obtained by the Receiver Operating Characteristic curve (ROC). The area under the ROC curve was calculated by the extended trapezoidal rule, assuming as relevant areas under the curve ≥ 0.650. Results: Coronary arterial disease patients presented reduced values of SDNN, RMSSD, NN50, HF, SD1, SD2 and -ApEn. HF ≤ 66 ms§ssup§2§esup§, RMSSD ≤ 23.9 ms, ApEn ≤-0.296 and NN50 ≤ 16 presented the best discriminatory power for the presence of significant coronary obstruction. Conclusion: We suggest the use of Heart Rate Variability Analysis in linear and nonlinear domains, for prognostic purposes in patients with stable angina pectoris, in view of their overall impairment. © 2012 Pivatelli et al.; licensee BioMed Central Ltd.
dc.languageeng
dc.relationInternational Archives of Medicine
dc.relation0,237
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectCardiovascular physiology
dc.subjectCoronary artery disease
dc.subjectHeart rate variability
dc.subjectNonlinear dynamics
dc.subjectStable angina
dc.subjectadult
dc.subjectangiocardiography
dc.subjectcoronary artery disease
dc.subjectcoronary artery obstruction
dc.subjectentropy
dc.subjectfemale
dc.subjectheart rate variability
dc.subjecthuman
dc.subjectmajor clinical study
dc.subjectmale
dc.subjectpredictive value
dc.subjectprognosis
dc.subjectsensitivity and specificity
dc.subjectstable angina pectoris
dc.subjectsupine position
dc.titleSensitivity, specificity and predictive values of linear and nonlinear indices of heart rate variability in stable angina patients
dc.typeArtigo


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