Comput. Biol. Med. - Prediction of pharmacologically induced baroreflex sensitivity from local time and frequency domain indices of R-R interval and systolic blood pressure signals obtained during deep breathing.

Tópicos

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Resumo

Pharmacological measurement of baroreflex sensitivity (BRS) is widely accepted and used in clinical practice. Following the introduction of pharmacologically induced BRS (p-BRS), alternative assessment methods eliminating the use of drugs were in the center of interest of the cardiovascular research community. In this study we investigated whether p-BRS using phenylephrine injection can be predicted from non-pharmacological time and frequency domain indices computed from electrocardiogram (ECG) and blood pressure (BP) data acquired during deep breathing. In this scheme, ECG and BP data were recorded from 16 subjects in a two-phase experiment. In the first phase the subjects performed irregular deep breaths and in the second phase the subjects received phenylephrine injection. From the first phase of the experiment, a large pool of predictors describing the local characteristic of beat-to-beat interval tachogram (RR) and systolic blood pressure (SBP) were extracted in time and frequency domains. A subset of these indices was selected using twelve subjects with an exhaustive search fused with a leave one subject out cross validation procedure. The selected indices were used to predict the p-BRS on the remaining four test subjects. A multivariate regression was used in all prediction steps. The algorithm achieved best prediction accuracy with only two features extracted from the deep breathing data, one from the frequency and the other from the time domain. The normalized L2-norm error was computed as 22.9% and the correlation coefficient was 0.97 (p=0.03). These results suggest that the p-BRS can be estimated from non-pharmacological indices computed from ECG and invasive BP data related to deep breathing.

Resumo Limpo

pharmacolog measur baroreflex sensit brs wide accept use clinic practic follow introduct pharmacolog induc brs pbrs altern assess method elimin use drug center interest cardiovascular research communiti studi investig whether pbrs use phenylephrin inject can predict nonpharmacolog time frequenc domain indic comput electrocardiogram ecg blood pressur bp data acquir deep breath scheme ecg bp data record subject twophas experi first phase subject perform irregular deep breath second phase subject receiv phenylephrin inject first phase experi larg pool predictor describ local characterist beattobeat interv tachogram rr systol blood pressur sbp extract time frequenc domain subset indic select use twelv subject exhaust search fuse leav one subject cross valid procedur select indic use predict pbrs remain four test subject multivari regress use predict step algorithm achiev best predict accuraci two featur extract deep breath data one frequenc time domain normal lnorm error comput correl coeffici p result suggest pbrs can estim nonpharmacolog indic comput ecg invas bp data relat deep breath

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