Abstract 14095: Use of Femoral Arterial Doppler Velocity to Detect Perfusing Pulses During Cardiac Arrest

Introduction: Manual pulse detection is inaccurate in cardiac arrest(CA) and Doppler ultrasound may detect blood flow without an adequate perfusion blood pressure (pseudo-pulseless electrical activity). The purpose of this study is to assess whether maximum femoral arterial velocity during a pulse check is correlated with arterial line systolic blood pressure (SBP) and whether it can be used to accurately identify a SBP of ≥60mmHG. Methods: This is a prospective study of CA patients at a quaternary care Emergency Department. During a pulse check, a linear ultrasound was placed at the common femoral artery and the presence or absence of an arterial Doppler waveform, the associated maximum velocity value, and arterial line SBP were recorded simultaneously. The correlation between SBP and maximum waveform velocity was assessed. Arterial SBPs were dichotomized as <60mmHG or ≥60mmHg, as this was deemed as an adequate perfusion pressure, and a receiver operator characteristic curve analysis was performed to determine optimal cutoff value of maximum velocity associated with SBP ≥60mmHG. Sensitivity (Sn), specificity (Sp), and accuracy (Acc) of manual palpation and femoral artery pulse wave doppler for detection of SBP ≥60mmHg were calculated. Results: A total of 51 patients and 183 pulse checks were analyzed. There was a strong correlation between arterial line SBP and maximum waveform velocity (Spearman correlation coefficient: 0.92; p<0.001). The optimal cutoff value of waveform velocity associated with a SBP ≥60mmHG was 20 cm/second (Sn: 0.89; specificity: 0.94; area under the curve: 0.98) with an Acc of 0.92. To detect SBP ≥60mmHg, manual palpation had a Sn of 0.45, Sp of 0.82, and Acc of 0.67 McNemar's test showed that Sn (p<0.001), Sp (p=0.009), and Acc (p<0.001) was significantly higher for doppler ultrasound >=20cm/sec compared with manual palpation. Conclusion: In this study, during a pulse check, patients with a femoral arterial doppler waveform with a maximum velocity greater than 20cm/sec had a high probability of having a SBP ≥60mmHg, and improved Sn, Sp and Acc over manual palpation. The results demonstrate femoral arterial doppler maximum velocity is an accurate and objective tool to determine the presence of a pulse with adequate perfusion pressures.

Inter-rater Reliability of a 13-Category Arterial Doppler Waveform Classification and Practice of French Vascular Physicians

Background: Arterial Doppler Ultrasound waveform (DW) analysis allows the detection and evaluation of lower extremity peripheral artery disease. The high heterogeneity of the reported description of DW is reduced by the use of classification. However, the reliability of these classifications is either unknown or low to moderate and practices of vascular caregivers regarding the use of these classifications remain unknown.Aims: This study aims to assess the inter-observer reliability of the Saint-Bonnet classification, a 13-category DW classification. The secondary objective was to determine the utilization rate of the most common classifications and the ability of these classifications to describe DW.Methods: A national survey was conducted among all vascular physicians of French society of vascular medicine. They were invited by email to describe on a website 20 DW without and with the display of the Saint-Bonnet classification. The reliability of this classification was estimated by Fleiss' Kappa expressed with [95% confidence interval]. A semantic analysis allowed us to classify the physicians' responses according to the terms used. Finally we have evaluated for each classification the rate of misuse, i.e., the addition of a complementary term to the defined categories.Results: One hundred and ten physicians participated and only 5% of these were familiar with Saint-Bonnet classification. Fifty-four percent of vascular physicians used no classification at all. Vascular physicians used the Spronk (four-category), Descotes (five-category) and Saint-Bonnet (13-category) classifications for respectively, 31, 10, and 5%. Kappa coefficient of Fleiss (κ) was 0.546 [0.544–0.547] (p &lt; 0.001). Reliability by category ranges from κ of 0.075 to 0.864. In multivariate analysis, the use of a classification was associated with fewer years of experience and was dependent on geographic location. Misuse rate by classification was 88, 82, and 5% using Spronk, Descotes and Saint-Bonnet classifications respectively.Conclusion: The reliability of Saint-Bonnet classification is weak to moderate by vascular physicians who are not familiar with its use. However, unlike the other classifications, it seems to be sufficiently precise so that the user does not need to complete its description. There is a significant heterogeneity in the use of arterial Doppler classifications in France.

Arterial Doppler Waveforms Are Independently Associated With Maximal Walking Distance in Suspected Peripheral Artery Disease Patients

Objective: Arterial Doppler waveform recordings are commonly used to assess lower extremity arterial disease (LEAD) severity. However, little is known about the relationship between arterial Doppler waveform profiles and patients' walking capacity. The purpose of this study was to assess whether arterial Doppler waveforms are independently associated with maximal walking distance (MWD) in patients experiencing exertional limb symptoms.Materials and Methods: This cross-sectional study included suspected LEAD patients experiencing exertional limb symptoms. In both lower extremities, arterial Doppler waveforms and ankle-brachial index (ABI) values were obtained from the pedis and tibial posterior arteries. Each arterial flow measurement was ranked using the Saint-Bonnet classification system. Treadmill stress testing (3.2 km/h, 10% slope) coupled with exercise oximetry (Exercise-TcPO2) were used to determine MWD. Delta from rest oxygen pressure (DROP) was calculated. Following treadmill stress testing, post-exercise ABI values were recorded. Univariate and multivariate analyses were used to determine the clinical variables associated with MWD.Results: 186 patients experiencing exertional limb symptoms (62 ± 12 years and 26.8 ± 4.5 kg/m2) were included between May 2016 and June 2019. Median [25th; 75th] treadmill MWD was 235 [125;500]m. Better arterial Doppler waveforms were associated with better walking distance (p = 0.0012). Whereas, median MWD was 524 [185;525]m in the group that yielded the best Doppler waveforms, it was 182 [125,305]m in the group with the poorest Doppler waveforms (p = 0.0012). MWD was significantly better (p = 0.006) in the patients with the best ABIs. However, arterial Doppler waveforms alone were significantly associated with MWD (p = 0.0009) in the multivariate model. When exercise variables (post-exercise ABI or DROP) were incorporated into the multivariate model, these were the only variables to be associated with MWD.Conclusion: Of the various clinical parameters at rest, Doppler flow waveform profiles were associated with MWD in suspected LEAD patients. A stronger link was however found between exercise variables and MWD.

Comparison of the Use of Arterial Doppler Waveform Classifications in Clinical Routine to Describe Lower Limb Flow

Background: Characterisation of arterial Doppler waveforms is a persistent problem and a source of confusion in clinical practice. Classifications have been proposed to address the problem but their efficacy in clinical practice is unknown. The aim of the present study was to compare the efficacy of the categorisation rate of Descotes and Cathignol, Spronk et al. and the simplified Saint-Bonnet classifications. Methods: This is a multicentre prospective study where 130 patients attending a vascular arterial ultrasound were enrolled and Doppler waveform acquisition was performed at the common femoral, the popliteal, and the distal arteries at both sides. Experienced vascular specialists categorized these waveforms according to the three classifications. Results: of 1033 Doppler waveforms, 793 (76.8%), 943 (91.3%) and 1014 (98.2%) waveforms could be categorized using Descotes and Cathignol, Spronk et al. and the simplified Saint-Bonnet classifications, respectively. Differences in categorisation between classifications were significant (Chi squared test, p < 0.0001). Of 19 waveforms uncategorized using the simplified Saint-Bonnet classification, 58% and 84% were not categorized using the Spronk et al. and Descotes and Cathignol classifications, respectively. Conclusions: The results of the present study suggest that the simplified Saint-Bonnet classification provides a superior categorisation rate when compared with Spronk et al. and Descotes and Cathignol classifications.