The Dicrotic Notch: Mechanisms, Characteristics, and Clinical Correlations

Abushouk, Abdelrahman Ibrahim; Kansara, Tikal; Abdelfattah, Omar; Badwan, Osamah; Hariri, Essa; Chaudhury, Pulkit; Kapadia, Samir

doi:10.1007/s11886-023-01901-x

Cited by 7 publications

(4 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, as discussed in [9], ABP waveforms contain a range of information, including morphological features such as the position of the DN, which can provide valuable insights into overall hemodynamic status and may prove beneficial in managing complex hemodynamic situations. Furthermore, Abushouk et al [4] mentioned that changes in DN parameters often appear early in the progression of vascular disease, potentially aiding in its early recognition. He et al [41] noted that the DN in PPG waveforms may be useful for estimating blood pressure.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, Abushouk et. al [4] underscores the clinical significance of several DN parameters: (a) DN As mentioned in [7], pressure waveforms undergo shape changes as they propagate away from the heart due to variations in blood vessel properties and the influence of reflected waves. This can lead to the DN becoming less pronounced, sometimes visually undetectable, or just causing a slight inflexion in the curve [7].…”

Section: Introductionmentioning

confidence: 99%

“…It is a small, downward deviation observed on the descending portion of these waveforms (see Fig. 1), occurring immediately after the systolic peak [4,5]. It is the result of the reflection of a wave at the aortic valve, following valve closure during the cardiac cycle [6,7,8, 9,10].…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, Abushouk et. al [4] underscores the clinical significance of several DN parameters: (a) DN amplitude (DNa): Higher DNa is associated with elevated peripheral vascular resistance, increased diastolic blood pressure, and the potential for weakened aortic valve closure, (b) DN height (DNh): Higher DNh signifies greater elasticity in the large arteries and effective aortic valve closure, (c) DN time duration or systolic phase duration (SPD): Longer SPD indicates robust systolic function of the heart. These applications emphasize the critical significance of accurate DN detection for enhancing clinical outcomes.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

An algorithm to detect dicrotic notch in arterial blood pressure and photoplethysmography waveforms using the iterative envelope mean method

Pal,

Rudas,

Kim

et al. 2024

Preprint

View full text Add to dashboard Cite

Background and Objective: Detection of the dicrotic notch (DN) within a cardiac cycle is essential for assessment of cardiac output, calculation of pulse wave velocity, estimation of left ventricular ejection time, and supporting feature-based machine learning models for noninvasive blood pressure estimation, and hypotension, or hypertension prediction. In this study, we present a new algorithm based on the iterative envelope mean (IEM) method to detect automatically the DN in arterial blood pressure (ABP) and photoplethysmography (PPG) waveforms. Methods: The algorithm was evaluated on both ABP and PPG waveforms from a large perioperative dataset (MLORD dataset) comprising 17,327 patients. The analysis involved a total of 1,171,288 cardiac cycles for ABP waveforms and 3,424,975 cardiac cycles for PPG waveforms. To evaluate the algorithm's performance, the systolic phase duration (SPD) was employed, which represents the duration from the onset of the systolic phase to the DN in the cardiac cycle. Correlation plots and regression analysis were used to compare the algorithm with an established DN detection technique (second derivative). The marking of the DN temporal location was carried out by an experienced researcher using the help of the find_peaks function from the scipy PYTHON package, serving as a reference for the evaluation. The marking was visually validated by both an engineer and an anesthesiologist. The robustness of the algorithm was evaluated as the DN was made less visually distinct across signal-to-noise ratios (SNRs) ranging from -30 dB to -5 dB in both ABP and PPG waveforms. Results: The correlation between SPD estimated by the algorithm and that marked by the researcher is strong for both ABP (R2(87343) =.99, p<.001) and PPG (R2(86764) =.98, p<.001) waveforms. The algorithm had a lower mean error of dicrotic notch detection (s): 0.0047 (0.0029) for ABP waveforms and 0.0046 (0.0029) for PPG waveforms, compared to 0.0693 (0.0770) for ABP and 0.0968 (0.0909) for PPG waveforms for the established 2nd derivative method. The algorithm has high accuracy of DN detection for SNR of >= -9 dB for ABP waveforms and >= -12 dB for PPG waveforms indicating robust performance in detecting the DN when it is less visibly distinct. Conclusion: Our proposed IEM- based algorithm can detect DN in both ABP and PPG waveforms with low computational cost, even in cases where it is not distinctly defined within a cardiac cycle of the waveform (DN-less signals). The algorithm can potentially serve as a valuable, fast, and reliable tool for extracting features from ABP and PPG waveforms. It can be especially beneficial in medical applications where DN-based features, such as SPD, diastolic phase duration, and DN amplitude, play a significant role.

show abstract

Section: Discussionmentioning

confidence: 99%