Ability of an Arterial Waveform Analysis-Derived Hypotension Prediction Index to Predict Future Hypotensive Events in Surgical Patients

BACKGROUND: Intraoperative hypotension is associated with worse perioperative outcomes for patients undergoing major noncardiac surgery. The Hypotension Prediction Index is a unitless number that is derived from an arterial pressure waveform trace, and as the number increases, the risk of hypotension occurring in the near future increases. We investigated the diagnostic ability of the Hypotension Prediction Index in predicting impending intraoperative hypotension in comparison to other commonly collected perioperative hemodynamic variables. METHODS: This is a 2-center retrospective analysis of patients undergoing major surgery. Data were downloaded and analyzed from the Edwards Lifesciences EV1000 platform. Receiver operating characteristic curves were constructed for the Hypotension Prediction Index and other hemodynamic variables as well as event rates and time to event. RESULTS: Two hundred fifty-five patients undergoing major surgery were included in the analysis yielding 292,025 data points. The Hypotension Prediction Index predicted hypotension with a sensitivity and specificity of 85.8% (95% CI, 85.8%-85.9%) and 85.8% (95% CI, 85.8%-85.9%) 5 minutes before a hypotensive event (area under the curve, 0.926 [95% CI, 0.925-0.926]); 81.7% (95% CI, 81.6%-81.8%) and 81.7% (95% CI, 81.6%-81.8%) 10 minutes before a hypotensive event (area under the curve, 0.895 [95% CI, 0.894-0.895]); and 80.6% (95% CI, 80.5%-80.7%) and 80.6% (95% CI, 80.5%-80.7%) 15 minutes before a hypotensive event (area under the curve, 0.879 [95% CI, 0.879-0.880]). The Hypotension Prediction Index performed superior to all other measured hemodynamic variables including mean arterial pressure and change in mean arterial pressure over a 3-minute window. CONCLUSIONS: The Hypotension Prediction Index provides an accurate real time and continuous prediction of impending intraoperative hypotension before its occurrence and has superior predictive ability than the commonly measured perioperative hemodynamic variables

Relationship between intraventricular mechanical dyssynchrony and left ventricular systolic and diastolic performance: An in vivo experimental study

Abstract Left ventricular mechanical dyssynchrony (LVMD) refers to the nonuniformity in mechanical contraction and relaxation timing in different ventricular segments. We aimed to determine the relationship between LVMD and LV performance, as assessed by ventriculo‐arterial coupling (VAC), LV mechanical efficiency (LVeff), left ventricular ejection fraction (LVEF), and diastolic function during sequential experimental changes in loading and contractile conditions. Thirteen Yorkshire pigs submitted to three consecutive stages with two opposite interventions each: changes in afterload (phenylephrine/nitroprusside), preload (bleeding/reinfusion and fluid bolus), and contractility (esmolol/dobutamine). LV pressure–volume data were obtained with a conductance catheter. Segmental mechanical dyssynchrony was assessed by global, systolic, and diastolic dyssynchrony (DYS) and internal flow fraction (IFF). Late systolic LVMD was related to an impaired VAC, LVeff, and LVEF, whereas diastolic LVMD was associated with delayed LV relaxation (logistic tau), decreased LV peak filling rate, and increased atrial contribution to LV filling. The hemodynamic factors related to LVMD were contractility, afterload, and heart rate. However, the relationship between these factors differed throughout the cardiac cycle. LVMD plays a significant role in LV systolic and diastolic performance and is associated with hemodynamic factors and intraventricular conduction

Performance comparison of ventricular and arterial dP/dtmax for assessing left ventricular systolic function during different experimental loading and contractile conditions

Abstract Background Maximal left ventricular (LV) pressure rise (LV dP/dtmax), a classical marker of LV systolic function, requires LV catheterization, thus surrogate arterial pressure waveform measures have been proposed. We compared LV and arterial (femoral and radial) dP/dtmax to the slope of the LV end-systolic pressure-volume relationship (Ees), a load-independent measure of LV contractility, to determine the interactions between dP/dtmax and Ees as loading and LV contractility varied. Methods We measured LV pressure-volume data using a conductance catheter and femoral and radial arterial pressures using a fluid-filled catheter in 10 anesthetized pigs. Ees was calculated as the slope of the end-systolic pressure-volume relationship during a transient inferior vena cava occlusion. Afterload was assessed by the effective arterial elastance. The experimental protocol consisted of sequentially changing afterload (phenylephrine/nitroprusside), preload (bleeding/fluid bolus), and contractility (esmolol/dobutamine). A linear-mixed analysis was used to assess the contribution of cardiac (Ees, end-diastolic volume, effective arterial elastance, heart rate, preload-dependency) and arterial factors (total vascular resistance and arterial compliance) to LV and arterial dP/dtmax. Results Both LV and arterial dP/dtmax allowed the tracking of Ees changes, especially during afterload and contractility changes, although arterial dP/dtmax was lower compared to LV dP/dtmax (bias 732 ± 539 mmHg⋅s− 1 for femoral dP/dtmax, and 625 ± 501 mmHg⋅s− 1 for radial dP/dtmax). Changes in cardiac contractility (Ees) were the main determinant of LV and arterial dP/dtmax changes. Conclusion Although arterial dP/dtmax is a complex function of central and peripheral arterial factors, radial and particularly femoral dP/dtmax allowed reasonably good tracking of LV contractility changes as loading and inotropic conditions varied

Peripheral vascular decoupling in porcine endotoxic shock

Cardiac output measurement from arterial pressure waveforms presumes a defined relationship between the arterial pulse pressure (PP), vascular compliance (C), and resistance (R). Cardiac output estimates degrade if these assumptions are incorrect. We hypothesized that sepsis would differentially alter central and peripheral vasomotor tone, decoupling the usual pressure wave propagation from central to peripheral sites. We assessed arterial input impedance (Z), C, and R from central and peripheral arterial pressures, and aortic blood flow in an anesthetized porcine model (n = 19) of fluid resuscitated endotoxic shock induced by endotoxin infusion (7 μg·kg -1·h -1 increased to 14 and 20 μg·kg -1·h -1 every 10 min and stopped when mean arterial pressure <40 mmHg or Sv O2 < 45%). Aortic, femoral, and radial artery pressures and aortic and radial artery flows were measured. Z was calculated by FFT of flow and pressure data. R and C were derived using a two-element Windkessel model. Arterial PP increased from aortic to femoral and radial sites. During stable endotoxemia with fluid resuscitation, aortic and radial blood flows returned to or exceeded baseline while mean arterial pressure remained similarly decreased at all three sites. However, aortic PP exceeded both femoral and radial arterial PP. Although Z, R, and C derived from aortic and radial pressure and aortic flow were similar during baseline, Z increases and C decreases when derived from aortic pressure whereas Z decreases and C increases when derived from radial pressure, while R decreased similarly with both pressure signals. This central-to-peripheral vascular tone decoupling, as quantified by the difference in calculated Z and C from aortic and radial artery pressure, may explain the decreasing precision of peripheral arterial pressure profile algorithms in assessing cardiac output in septic shock patients and suggests that different algorithms taking this vascular decoupling into account may be necessary to improve their precision in this patient population. © 2011 the American Physiological Society

Comparison of differences in cohort (forwards) and case control (backwards) methodological approaches for validation of the Hypotension Prediction Index.

BackgroundThe Hypotension Prediction Index (the index) software is a machine learning algorithm that detects physiological changes that may lead to hypotension. The original validation used a case control (backwards) analysis that has been suggested to be biased. We therefore conducted a cohort (forwards) analysis and compared this to the original validation technique.MethodsWe conducted a retrospective analysis of data from previously reported studies. All data were analysed identically with 2 different methodologies and receiver operating characteristic curves (ROC) constructed. Both backwards and forwards analyses were performed to examine differences in area under the ROC for HPI and other haemodynamic variables to predict a MAP &lt; 65mmHg for at least 1 minute 5, 10 and 15 minutes in advance.ResultsTwo thousand and twenty-two patients were included in the analysis, yielding 4,152,124 measurements taken at 20 second intervals. The area-under-the-curve for the index predicting hypotension analysed by backward and forward methodologies respectively was 0.957 (95% CI, 0.947-0.964) vs 0.923 (95% CI, 0.912-0.933) 5 minutes in advance, 0.933 (95% CI, 0.924-0.942) vs 0.923 (95% CI, 0.911-0.933) 10 minutes in advance , and 0.929 (95% CI, 0.918-0.938) vs. 0.926 (95% CI, 0.914-0.937) 15 minutes in advance. No other variable had an area-under-the-curve &gt; 0.7 except for MAP. Area-under-the-curve using forward analysis for MAP predicting hypotension 5, 10, and 15 minutes in advance was 0.932 (95% CI, 0.920-0.940), 0.929 (95% CI, 0.918-0.938), and 0.932 (95% CI, 0.921-0.940). The R 2 for the variation in the index due to MAP was 0.77.ConclusionUsing an updated methodology, we found the utility of the HPI index to predict future hypotensive events is high, with an area under the receiver-operating-characteristics curve similar to that of the original validation method