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. 2024 Dec 30;14(1):31808.
doi: 10.1038/s41598-024-83038-7.

Predictive value of trendelenburg position and carotid ultrasound for fluid responsiveness in patients on VV-ECMO with acute respiratory distress syndrome in the prone position

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Predictive value of trendelenburg position and carotid ultrasound for fluid responsiveness in patients on VV-ECMO with acute respiratory distress syndrome in the prone position

Junjie Zhao et al. Sci Rep. .

Abstract

Fluid administration is widely used to treat hypotension in patients undergoing veno-venous extracorporeal membrane oxygenation (VV-ECMO). However, excessive fluid administration may lead to fluid overload can aggravate acute respiratory distress syndrome (ARDS) and increase patient mortality, predicting fluid responsiveness is of great significance for VV-ECMO patients. This prospective single-center study was conducted in a medical intensive care unit (ICU) and finally included 51 VV-ECMO patients with ARDS in the prone position (PP). Stroke volume index variation (ΔSVI), pulse pressure variation (PPV), stroke volume variation (SVV), baseline carotid corrected flow time (FTcBaseline), and respirophasic variation in carotid artery blood flow peak velocity (ΔVpeakCA) were taken before and after the Trendelenburg position or volume expansion. Fluid responsiveness was defined as a 15% or more increase in stroke volume index as assessed by transthoracic echocardiography after the volume expansion (VE). In our study, 33 patients (64.7%) were identified as fluid responders. Stroke volume index variation induced by the Trendelenburg position (ΔSVITrend), FTcBaseline, and ΔVpeakCA demonstrated superior predictive performance of fluid responsiveness. ΔSVITrend had an AUC of 0.89 (95% CI, 0.80-0.98) with an optimal threshold of 14.5% (95% CI, 12.5-21.5%), with the sensitivity and specificity were 82% (95% CI, 66-91%) and 83% (95% CI, 61-94%). FTcBaseline had an AUC of 0.87 (95% CI, 0.76-0.98) with an optimal threshold of 332ms (95% CI, 318-335ms), the sensitivity and specificity were 85% (95% CI, 69-93%) and 83% (95% CI, 61-94%), respectively. ΔVpeakCA showed an AUC of 0.83 (95% CI, 72-95), with a 10% optimal threshold (95% CI, 9-13%), sensitivity was 82% (95% CI, 66-91%) and specificity 78% (95% CI, 55-91%). ΔSVITrend, FTcBaseline and ΔVpeakCA could effectively predict fluid responsiveness in VV-ECMO patients with ARDS in the PP. Compared to ΔSVITrend and ΔVpeakCA, FTcBaseline is easier and more direct to acquire, and it does not require Trendelenburg position or VE, making it a more accessible and efficient option for assessing fluid responsiveness.

Keywords: Carotid ultrasound; Fluid responsiveness; Trendelenburg position; VV-ECMO.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests. Ethics approval and consent to participate: This prospective, single-center study was conducted in the ICU between May 2022 and February 2024. It was approved by the Institutional Review Board of Quzhou People’s Hospital (Quzhou, China: Number B 2022-083) and performed in accordance with the Declaration of Helsinki. All research was performed in accordance with relevant guidelines/regulations. Informed consent was obtained from all participants and/or their legal guardians. Consent for publication: Not applicable.

Figures

Fig. 1
Fig. 1
The study flowchart.
Fig. 2
Fig. 2
The study protocols. (a) An outline of each step; (b) a clinical scenery of VV-ECMO patient in the prone position; (c) the 15° upward bed angulation for measurements at baselines and volume expansion test; (d) The 15° downward bed angulation for measurements in the Trendelenburg position.
Fig. 3
Fig. 3
Individual values from five parameters to detect fluid responsiveness in fluid responders and non-responders. Black dotted line displays optimal thresholds for each diagnostic test computed by ROC curve analysis. (a) ΔSVITrend, Stroke volume index variation induced by the Trendelenburg position; (b) FTcBaseline, baseline carotid artery corrected flow time; (c) ΔVpeakCA, respirophasic variation in carotid artery blood flow peak velocity; (d) PPV, pulse pressure variation; (e) SVV, stroke volume variation.
Fig. 4
Fig. 4
The relationship between ΔSVIVE and the five parameters.The grey line is the regression line. The gray dotted line area is the 95% confidence interval of the regression line. (a) ΔSVITrend, Stroke volume index variation induced by the Trendelenburg position; (b) FTcBaseline, baseline carotid artery corrected flow time; (c) ΔVpeakCA, respirophasic variation in carotid artery blood flow peak velocity; (d) PPV, pulse pressure variation; (e) SVV, stroke volume variation.
Fig. 5
Fig. 5
Receiver operating characteristics curves from five diagnostics tests to detect fluid responsiveness. (a) ΔSVITrend, Stroke volume index variation induced by the Trendelenburg position; (b) FTcBaseline, baseline carotid artery corrected flow time; (c) ΔVpeakCA, respirophasic variation in carotid artery blood flow peak velocity; (d) PPV, pulse pressure variation; (e) SVV, stroke volume variation.
Fig. 6
Fig. 6
Grey zone analysis. (a) ΔSVITrend, Stroke volume index variation induced by the Trendelenburg position; (b) FTcBaseline, baseline carotid artery corrected flow time; (c) ΔVpeakCA, respirophasic variation in carotid artery blood flow peak velocity; (d) PPV, pulse pressure variation; (e) SVV, stroke volume variation.

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