Evaluation of stroke volume estimation during orthostatic stress: the utility of Modelflow.

IF 1.2 4区 医学 Q4 PERIPHERAL VASCULAR DISEASE Blood Pressure Monitoring Pub Date : 2023-12-01 Epub Date: 2023-08-24 DOI:10.1097/MBP.0000000000000671
Vera-Ellen M Lucci, Iain T Parsons, Brooke C D Hockin, Victoria E Claydon
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Abstract

Advanced blood pressure monitoring devices contain algorithms that permit estimation of stroke volume (SV). Modelflow (Finapres Medical Systems) is one common method to non-invasively estimate beat-to-beat SV. However, Modelflow accuracy during profound reductions in SV is unclear. We aimed to compare SV estimation by Modelflow and echocardiography, at rest and during orthostatic challenge. We tested 13 individuals (age 24 ± 2 years; 7 female) using combined head-up tilt and graded lower body negative pressure, continued until presyncope. SV was derived by both Modelflow and echocardiography on multiple occasions while supine, during orthostatic stress, and at presyncope. SV index (SVI) was determined by normalising SV for body surface area. Bias and limits of agreement were determined using Bland-Altman analyses. Two one-sided tests (TOST) examined equivalency. Across all timepoints, Modelflow estimates of SV (73.2 ± 1.6 ml) were strongly correlated with echocardiography estimates (66.1 ± 1.3 ml) (r = 0.56, P  < 0.001) with a bias of +7.1 ± 21.1 ml. Bias across all timepoints was further improved when SV was indexed (+3.6 ± 12.0 ml.m -2 ). Likewise, when assessing responses relative to baseline, Modelflow estimates of SV (-23.4 ± 1.4%) were strongly correlated with echocardiography estimates (-19.2 ± 1.3%) (r = 0.76, P  < 0.001), with minimal bias (-4.2 ± 13.1%). TOST testing revealed equivalency to within 15% of the clinical standard for SV and SVI, both expressed as absolute values and relative to baseline. Modelflow can be used to track changes in SV during profound orthostatic stress, with accuracy enhanced with correction relative to baseline values or body size. These data support the use of Modelflow estimates of SV for autonomic function testing.

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直立应力状态下卒中量估计的评估:Modelflow的实用性。
先进的血压监测设备包含允许估计中风量(SV)的算法。Modelflow(Finapres Medical Systems)是一种非侵入性估计逐搏SV的常用方法。然而,在SV大幅下降期间,Modelflow的准确性尚不清楚。我们的目的是比较静息状态和直立挑战期间通过Modelflow和超声心动图进行的SV估计。我们测试了13个人(年龄24岁) ± 2年;7名女性)使用组合的头向上倾斜和分级的下半身负压,持续到ynscope。在仰卧、直立应力和咽前的多次情况下,通过Modelflow和超声心动图得出SV。SV指数(SVI)是通过对体表面积的SV进行归一化来确定的。使用Bland-Altman分析确定了偏差和一致性限制。两个单侧测试(TOST)检查了等效性。在所有时间点,SV(73.2 ± 1.6 ml)与超声心动图估计值密切相关(66.1 ± 1.3 ml)(r = 0.56,P
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来源期刊
Blood Pressure Monitoring
Blood Pressure Monitoring 医学-外周血管病
CiteScore
2.00
自引率
7.70%
发文量
110
审稿时长
>12 weeks
期刊介绍: Blood Pressure Monitoring is devoted to original research in blood pressure measurement and blood pressure variability. It includes device technology, analytical methodology of blood pressure over time and its variability, clinical trials - including, but not limited to, pharmacology - involving blood pressure monitoring, blood pressure reactivity, patient evaluation, and outcomes and effectiveness research. This innovative journal contains papers dealing with all aspects of manual, automated, and ambulatory monitoring. Basic and clinical science papers are considered although the emphasis is on clinical medicine. Submitted articles undergo a preliminary review by the editor. Some articles may be returned to authors without further consideration. Those being considered for publication will undergo further assessment and peer-review by the editors and those invited to do so from a reviewer pool.
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