Key result
The proposed automatic algorithm estimated pulse pressure variation from arterial blood pressure signals during spontaneous breathing in agreement with manual gold standard measurements within ±4% accuracy.
Why the study?
Does the proposed automatic algorithm accurately estimate pulse pressure variation compared to manual annotations in spontaneously breathing subjects?
Does the proposed automatic algorithm accurately estimate pulse pressure variation compared to manual annotations in spontaneously breathing subjects?
The proposed automatic algorithm provides reliable estimations of pulse pressure variation from arterial blood pressure signals during spontaneous breathing, matching manual annotations within ±4% accuracy.
Supports automated PPV monitoring during spontaneous breathing; leaves open prospective validation before clinical adoption.
BACKGROUND: We describe the first automatic algorithm designed to estimate the pulse pressure variation ([Formula: see text]) from arterial blood pressure (ABP) signals under spontaneous breathing conditions. While currently there are a few publicly available algorithms to automatically estimate [Formula: see text] accurately and reliably in mechanically ventilated subjects, at the moment there is no automatic algorithm for estimating [Formula: see text] on spontaneously breathing subjects. The algorithm utilizes our recently developed sequential Monte Carlo method (SMCM), which is called a maximum a-posteriori adaptive marginalized particle filter (MAM-PF). We report the performance assessment results of the proposed algorithm on real ABP signals from spontaneously breathing subjects. RESULTS: Our assessment results indicate good agreement between the automatically estimated [Formula: see text] and the gold standard [Formula: see text] obtained with manual annotations. All of the automatically estimated [Formula: see text] index measurements ([Formula: see text]) were in agreement with manual gold standard measurements ([Formula: see text]) within ±4 % accuracy. CONCLUSION: The proposed automatic algorithm is able to give reliable estimations of [Formula: see text] given ABP signals alone during spontaneous breathing.
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Noor et al. (2016) studied Spontaneous breathing in critical care (n=11). Automatic PPV estimation algorithm (Dual MAM-PF) vs. Manual PPV annotations was evaluated on Agreement between automatically estimated PPV and manual gold standard PPV (within ±4% accuracy). The proposed automatic algorithm estimated pulse pressure variation from arterial blood pressure signals during spontaneous breathing in agreement with manual gold standard measurements within ±4% accuracy.
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