Comparison of ventricular pressure relaxation assessments in human heart failure: quantitative influence on load and drug sensitivity analysis.

OBJECTIVES

We contrasted various methods for assessing ventricular pressure decay time constants to test whether sensitivity to slight data instability or disparities between model-assumed and real decay are systematically altered by cardiac failure. We hypothesized that such discrepancies could result in apparent increased relaxation sensitivity to load and drug stimulation.

BACKGROUND

Deviation of relaxation behavior from model-assumed waveforms may be worsened by failure, enhancing instability and apparent load and drug sensitivity of commonly used indexes.

METHODS

Pressure-volume relations were measured in patients with normal (n = 14), hypertrophic (hypertrophic cardiomyopathy [HCM], n = 15) and dilated-myopathic (dilated cardiomyopathy [DCM], n = 37) hearts before and during preload reduction or inotropic stimulation. Relaxation parameters (monoexponential [ME] model assuming zero-T(in) or non-zero-T(D), T(F) asymptote:, hybrid logistic-T(L), linear-T(LR), and pressure halftime-T(1/2)) were contrasted regarding sensitivity to slight data range manipulation and loading or drug changes.

RESULTS

In DCM, T(D) and T(F) prolonged 15% to 25% (p < 0.0001) by deletion of only 1-2 data points, whereas this had minimal effect on controls or HCM. This stemmed from systematic deviation of relaxation from an ME decay in DCM. T(1/2) and T(in) were highly sensitive to pure pressure offsets, whereas T(L) was most stable to both manipulations in all hearts. As a result, T(D) and T(F) appeared to be much more sensitive to systolic load in DCM than T(1/2) or T(L) and disproportionately sensitive to increased cyclic adenosine monophosphate (cAMP).

CONCLUSIONS

Relaxation consistently deviates from an ME decay in DCM resulting in instability and amplified relaxation systolic load or drug dependence of ME-based indexes in failing versus control (or HCM) hearts. The hybrid-logistic method improves quantitative analyses by providing more consistent data fits with all three heart types.