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PubMed · 1769140

Uremic autonomic dysfunction evaluated by pattern recognition analysis.

G Vita·P Princi·V Savica·G Bellinghieri·R M Puglisi·L Marabello·C Messina
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Abstract

A pattern recognition analysis of six cardiovascular reflex tests was performed with the aim to increase their diagnostic efficiency. A normal model was defined by SIMCA method using log-transformed values of 85 healthy subjects. The model was tested with data from 60 patients with chronic renal failure. Specificity resulted 94% and sensitivity 96%. 55% of the uremics were recognized affected by autonomic damage. The method allowed a better definition of autonomic function in those patients defined as "borderline" on conventional evaluation of the tests. Pattern recognition analysis of autonomic tests provides a global assessment of all the tests performed. Its use should be encouraged as a diagnostic tool.

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Autonomic Nervous System DiseasesComputer SimulationDiagnosis, Computer-AssistedFemaleHumansMaleMiddle AgedPattern Recognition, AutomatedReflexSensitivity and SpecificityUremiaJournal Article

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G Vita, P Princi, V Savica, G Bellinghieri, R M Puglisi, L Marabello, C Messina. 1991. Uremic autonomic dysfunction evaluated by pattern recognition analysis.. https://pubmed.ncbi.nlm.nih.gov/1769140/

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PubMed1992

Comparison of different methods for assessing sympathovagal balance in chronic congestive heart failure secondary to coronary artery disease.

Twenty-five patients (aged 62 +/- 2 years) with stable, moderate to severe ischemic congestive heart failure (CHF) (New York Heart Association class II/III: 15/10; ejection fraction 21.6 +/- 2%; and peak oxygen uptake 13.6 +/- 0.7 ml/kg/min) were studied to evaluate the ability of different methods to characterize autonomic tone in chronic CHF. Sympathovagal balance was assessed by: (1) heart rate variability in the time domain, assessed by the SD of RR intervals; (2) heart rate variability in the frequency domain, assessed by low- (0.03 to 0.14 Hz) and high- (0.18 to 0.40 Hz) frequency components of heart rate variability by autoregressive power spectral analysis; (3) 24-hour, daytime and nighttime heart rate; (4) submaximal heart rate during upright bicycle exercise, with respiratory gas analysis to obtain peak oxygen uptake; and (5) radiolabeled norepinephrine spillover. These methods did not correlate, with the exception of day and nighttime heart rate (r = 0.74; p < 0.001) and the expected inverse correlation between low and high frequency (r = -0.92; p < 0.001). No method correlated significantly with peak oxygen uptake, exercise tolerance or ejection fraction. After 8 weeks of physical training at home, all methods showed improvement in autonomic balance: increases in SD of RR intervals (+21%; p < 0.02) and high frequency (+41%; p < 0.007), and decreases in low frequency (-19%; p < 0.002), low-/high-frequency ratio (-48%; p < 0.03), norepinephrine spillover (-28.9%; p < 0.03), 24-hour heart rate (-2.7%; p < 0.005) and submaximal heart rate (-10.8%; p < 0.01).(ABSTRACT TRUNCATED AT 250 WORDS)

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