The Predictive Value of Trendelenburg Position and Neck Ultrasound for Fluid Responsiveness in Prone ARDS Patients with VV-ECMO

doi:10.21203/rs.3.rs-4841829/v1

Background

In clinical practice, fluid administration is widely used to treat hypotension in patients undergoing veno-venous extracorporeal membrane oxygenation (VV-ECMO). However, volume expansion (VE) may aggravate acute respiratory distress syndrome (ARDS) and increase patient mortality, predicting fluid responsiveness is of great significance in the treatment of hypotension in patients undergoing VV-ECMO.

Methods

This prospective single-center study was conducted in a medical intensive care unit and included 51 VV-ECMO patients with ARDS in the prone position who required volume expansion due to hypotension. Stroke volume index variation (△SVI), carotid artery corrected flow time (FT_c), and artery peak velocity variation (ΔV_peak) were taken before and during the Trendelenburg position or Volume expason is given. Fluid responsiveness was defined as a volume expansion-induced increase in ΔSVI of ≥ 15%.

Results

33 patients (64.7%) were identified as fluid responders. The area under the receiver operating characteristic curve (ROC) for FT_c and ΔV_peak induced by the Trendelenburg position to predict fluid responsiveness were 0.866 (95% confidence interval [CI] 0.755–0.977) and 0.833 (95% CI 0.716–0.949), respectively. The sensitivity at the optimal threshold of 331.5 ms for FTc was 84.85% (95% CI 69.1–93.4%), with a specificity of 83.33% (95% CI 60.8–94.2%). For ΔV_peak, the sensitivity at the optimal threshold of 10.1% was 81.82% (95% CI 65.9–91.4%), with a specificity of 77.78% (95% CI 54.9–91.0%). The grey zone for FT_c and ΔV_peak included 29% and 45% of patients, respectively.

Conclusions

Changes in FT_c and ΔV_peak, monitored through neck ultrasound and induced by the Trendelenburg position, are reliable indicators for predicting fluid responsiveness in VV-ECMO patients with ARDS in the prone position. Furthermore, FT_c demonstrates superior predictive value compared to ΔV_peak.

Health sciences/Medical research/Biomarkers/Predictive markers

Health sciences/Medical research

Fluid responsiveness

Trendelenburg position

VV-ECMO

Neck ultrasound

Veno-Venous Extracorporeal Membrane Oxygenation (VV-ECMO) serves as a potent tool for severe acute respiratory distress syndrome (ARDS) patients with poor response to conventional mechanical ventilation[1–5]. VV-ECMO serves as an artificial lung, facilitating extracorporeal gas exchange to sustain sufficient oxygenation and carbon dioxide elimination, with the objective of mitigating ventilator-induced lung injury and providing a window for primary disease treatment. Clinicians often utilize intravenous fluid infusion during VV-ECMO support to bolster cardiac output (CO), thereby addressing hypotension and enhancing oxygen delivery[6, 7]. Nevertheless, due to alterations in alveolar capillary membrane permeability, fluid overload can predispose patients to complications such as pulmonary edema, thereby exacerbating the underlying condition[8, 9]. Hence, the ability to predict fluid responsiveness is crucial for VV-ECMO patients with ARDS, as it informs fluid management strategies and mitigates the risk of exacerbating the condition[10].

Commonly utilized methods for assessing volume responsiveness in critically ill patients include static indicators such as central venous pressure (CVP) and inferior vena cava (IVC), as well as dynamic indicators like stroke volume variation (SVV) or pulse pressure variation (PPV)[11–14]. CVP has historically been used to guide fluid therapy, but recent studies have shown that CVP cannot predict fluid responsiveness[15]. Additionally, in VV-ECMO patients, the placement of the venous drainage cannula limits the applicability of IVC assessment. Moreover, SVV and PPV, commonly used to assess volume responsiveness, necessitate mechanical ventilation with a tidal volume greater than 8 ml/kg[16, 17]. V-V ECMO patients typically undergo lung-protective ventilation with small tidal volumes, making them less suitable for assessing volume responsiveness in this patient population[18]. Passive leg raising (PLR) test transiently increases venous return by postural maneuver[19]. Unfortunately, prone positioning is commonly adopted for ARDS patients receiving ECMO support to improve ventilation, but limitations related to positioning as well as the risks of cannula distortion or displacement hinder the application of this maneuver in such patients. In conclusion, the specificity and complexity of VV-ECMO patients limits the applicability of traditional methods for assessing fluid responsiveness.

The Trendelenburg position is considered a "self" preload challenge[20], similar in principle to PLR, and can be applied to patients in the prone position. Studies have demonstrated its good accuracy in predicting reactivity in patients with ARDS[21]and surgical patients[22]. It can be applied to the majority of veno-arterial extracorporeal membrane oxygenation (VA-ECMO) patients. Neck ultrasound measurements, such as carotid artery corrected flow time (FT_c), and carotid artery peak velocity variation (△V_peak), have recently been recognized as reliable indicators of stroke volume[23–25]. These measurements offer advantages such as rapidity, non-invasiveness, and simplicity. However, it is noteworthy that the subjects in the aforementioned studies were not VV-ECMO patients. The efficacy of FT_c, and ΔV_peak in assessing fluid responsiveness in VV-ECMO patients remains unclear at present.

Building upon this, our study employed a non-invasive ultrasound hemodynamic assessment method to monitor, carotid artery corrected flow time, and carotid artery peak velocity variation before and after the Trendelenburg position. The objective was to investigate the predictive value of these parameters for fluid responsiveness in VV-ECMO patients.

Study design

This study is a prospective single-center study, performed between May 2021 and February 2024 in ICU and approved by the Institutional Review Board (Quzhou People's Hospital, Quzhou, China: Number B 2022-083). Informed consent from the patients’ closest relatives was required for inclusion.

Patients

V-V ECMO patients admitted to ICU were recruited in this study. The Inclusion criteria including [25] 1) adults (≥ 18 years) diagnosed with ARDS; 2) received prone ventilation therapy during VV-ECMO.

Exclusion criteria were patients with contraindications for volume expansion test, severe arrhythmias, age less than 18 years old, carotid artery stenosis > 50% or occluded carotid arteries, a poor ultrasonographic window for carotid doppler measurements, any contraindications to Trendelenburg position (head injury or intracranial hypertension, intraabdominal hypertension).

Each patient undergoes invasive hemodynamic monitoring based on the clinical needs. According to the continuous monitoring of ΔSVI before and after Trendelenburg position, patients are categorized into two groups: fluid responder group (33 cases, ΔSVI ≥ 15%), and fluid non-responder group (18 cases, ΔSVI < 15%).

Protocol

Throughout the study, patients were sedated with a combination of remifentanil and midazolam, with the aim of achieving a Ramsay score of 6[27], this protocol included four sequential steps(Fig. 1):

(1)Baseline-1: patient in a prone position, with a 15° upward bed angulation; (2)Trendelenburg position: 15° downward bed angulation[28].

(3)Baseline-2: recover to the same position as baseline-1;

(4)Volume expansion test: administration of 500 ml crystalloids over 15 min without postural change.

After each step is completed and stabilized for 1 minute, record patient parameters including ΔSVI, FT_c, ΔV_peak, HR, MAP, etc. For enhanced accuracy of the acquired data, measurements were taken three times for each patient, and the average was calculated to determine the final parameters.

Measurements

ΔVpeak-CA &FTc: Using a portable color Doppler ultrasound (Vivid i, GE Company, Israel), a variable-frequency linear array transducer with a range of 6-13MHz was longitudinally positioned on the right side of the neck, with the transducer marker oriented towards the patient's head. In the short-axis plane below the thyroid cartilage, the right carotid artery was located, and real-time B-mode images of the long axis of the right carotid artery were obtained. The ultrasound beam angle with the direction of blood flow was maintained below 60°. Pulse wave (PW) mode was selected, and after displaying the pulse Doppler spectrum, the optimal sampling volume and angle were adjusted to obtain a satisfactory spectral freeze-frame image. Measurements of carotid blood flow, including FTc (flow time corrected) and Vpeak-CA (peak velocity of the carotid artery), were taken. ΔVpeak-CA was calculated using the formula: ΔVpeak = (Max peak - Min peak) / [(Max peak + Min peak) / 2] × 100%. The cycle time (flow time, FT) from the onset of systole to the dual rotation trace was measured, and FTc was calculated using the Bazett formula[29]: FTc = FT + [1.29 × (HR − 60)], where FT represents the cycle time from the onset of systole to the dual rotation trace, and heart rate (HR) is obtained by measuring the heartbeat interval at the onset of Doppler blood flow.

Data collection

Upon patient inclusion, demographic information, APACHE II scores, and etiology of ARDS etc., were collected. Supportive treatments included VV-ECMO, mechanical ventilation (MV). We documented all data related to these parameters. Follow-up was conducted for all study patients until discharge or death, recording clinical outcomes such as the duration of MV, ECMO duration, ICU length of stay, and in-hospital mortality rate.

Statistical analysis

SPSS 26.0 (version26; SPSS, Inc., Chicago, IL, USA) was used to analyse the data. Values are mean ± SD, median (interquartile range) or n (%). For the comparison of variables between these two groups, t-tests were used for continuous variables that follows a normal distribution, while Mann-Whitney U-test were used for continuous variables that does not follows a normal distribution. For categorical variables, Chi-squared test was used. Linear regression analysis was used to demonstrate relationships between change of ΔVTI and FTc induced by the Trendelenburg position, and volume expansion test. Receiver operating characteristic (ROC) curves were plotted to analyse the predictive value of the Trendelenburg position combined with neck ultrasound for fluid responsiveness in VV-ECMO patients. Sensitivity, specificity, positive and negative predictive values (PPV and NPV), and associated 95% confidence intervals (CI) were calculated based on the cutoff value as determined by the Youden Index (specificity + sensitivity − 1). To evaluate the variation of best threshold, we conducted a gray-zone analysis, as described by Joël Coste[30]. A value of P < 0.05 was considered statistically significant.

Patient characteristics

From May 2021 to February 2024, we enrolled 71 VV-ECMO patients with ARDS in the prone position to our study, ultimately 51 patients met the inclusion criteria. The study flowchart is illustrated in Figure 2. Detailed characteristics, comorbidities, reasons for intensive care unit (ICU) admission, and clinical outcomes of the patients are presented in Table 1. In this study, the primary etiologies for ARDS admission were pulmonary infection (69.70%), sepsis (39.39%), and gas poisoning, (27.27%). The median duration of VV-ECMO support was [6(4.5-8) vs. 6(4.75-8.25), P=0.796] days, with [12(36.36%) vs. 8(44.44%), P=0.572] patients successfully weaned from VV-ECMO. The median duration of mechanical ventilation (MV) was [10(7-12) vs. 8(6-10), P=0.142] days, and patients underwent tracheotomy [10(30.30%) vs. 5(27.78%), P=0.014]. The median length of ICU stay was [12(9-17) vs. 11(9-13), P=0.275] days, during which [14(42.42%) vs. 8(44.44%), P=0.890] individuals succumbed to their conditions.

Table 1. Characteristics and clinical outcomes of included population

Variables	Fluid responder group （n=33）	Fluid non-responder group (n=18）	P-value
Demographic information
Age, year	55.52±4.42	56.22±6.19	0.638
BMI, kg/m²	23.44±1.55	22.93±3.27	0.086
Gender, n(%)			0.945
Male	18(54.55)	10(55.56)
Female	15(45.45)	8(44.44)
Etiology of ARDS
Pulmonary infection, n(%)	23(69.70)	12(66.67)	0.407
Gas poisoning, n(%)	9(27.27)	5(27.78)	0.969
Trauma, n(%)	6(18.18)	6(33.33)	0.223
Sepsis, n(%)	13(39.39)	7(38.89)	0.407
Others, n(%)	7(21.21)	8(44.44)	0.082
Comorbidities
Hypertension, n(%)	18(54.55)	9(50.00)	0.756
Diabetes, n(%)	14(42.42)	10(55.56)	0.369
Coronary heart disease, n(%)	4(12.12)	3(16.67)	0.652
Chronic renal failure, n(%)	6(18.18)	2(11.11)	0.057
COPD, n(%)	9(27.27)	4(22.22)	0.692
Postoperative critical ill status
APACHE II score	22(19-26)	21(19-24)	0.354
Clinical outcomes
Length of ECMO, day	6(4.5-8)	6(4.75-8.25)	0.796
Weaning from ECMO, n (%)	12(36.36)	8(44.44)	0.572
Length of MV, day	10(7-12)	8(6-10)	0.142
Tracheotomy, n (%)	10(30.30)	5(27.78)	0.140
Length of ICU stay, day	12(9-17)	11(9-13)	0.275
Hospital mortality, n (%)	14(42.42)	8(44.44)	0.890

Effect of volume expansion on haemodynamic variables

In this study, we found 33 patients (64.7%) were fluid responders. Hemodynamic parameters from each step are shown (Table 2). At baseline-2, SVI and FT_c were lower and ΔV_peak higher in fluid responders compared with fluid non-responders. Volume expansion test increased SVI, FT_c and decreased ΔV_peak in both groups. However, the decrease in ΔV_peak was significantly higher in fluid responders than in fluid non-responders (Table 2).

Effect of Trendelenburg position on haemodynamic variables

At baseline-1, SVI and FT_c indices were higher, and V_peak was significantly lower for the Trendelenburg position compared to their corresponding baseline values. In the fluid responders group, the Trendelenburg position resulted in a mean decrease of V_peak to 12.07±3.60%, and an increase in SVI and FT_c to mean values of 44.39±4.42 ml m−2 and 349.09±9.49 ms, respectively (Table 2).

Table 2. Hemodynamic parameters at baselines, at the Trendelenburg position and after volume expansion test. The data are reported as mean ± SD

Variables	Baseline-1	Trendelenburg position	Baseline-2	Volume expansion test
SVI, (ml m ⁻²)
Responder group	36.12±4.23	44.39±4.42^*	37.21±3.73	45.97±5.19^*
Non-responder group	37.78±5.87	41.94±5.72	38.89±3.88	43.61±4.41^*
FT_c, ms
Responder group	317.97±11.94	349.09±9.49^*	319.64±11.65^#	348.52±9.92^*#
Non-responder group	337.89±11.38	352.11±10.96^*	338.44±10.35	353.50±8.70^*#
ΔV_peak, n(%)
Responder group	15.26±3.26	12.07±3.60^*	15.65±4.13	12.63±3.47^*
Non-responder group	8.96±2.98	8.05±3.37^*	9.08±3.22	7.90±3.99^*
HR (beat/min)
Responder group	75.85±11.43	77.39±9.64^*	79.45±12.20	79.42±12.67^*
Non-responder group	73.11±11.50	74.78±12.61^*	81.78±11.32	79.22±12.77^*
MAP (mmHg)
Responder group	77.48±6.66	82.94±4.59^*	81.52±3.45	88.67±5.83^*
Non-responder group	78.83±5.39	80.78±4.41^*	82.67±3.77	86.61±5.00^*

^*p < 0.05, comparison between responders (n = 33) and non-responders (n = 18)

^#p < 0.05, comparison between Trendelenburg position and baseline-1 or volume expansion test and baseline-2.

Prediction of fluid responsiveness of Trendelenburg position

Data on fluid responsiveness predictions are shown (Table 3). The AUROC of ΔV_peak induced by Trendelenburg position to predict fluid responsiveness was (0.833[95% CI, 0.716-0.949]), with a sensitivity of 81.82%, and specificity of 77.78%, at a best threshold of 10.1%. The corresponding gray-zone was 8.95-13.20%, covering 45% of patients. The FT_c, displayed higher predictive accuracies (AUROCs: 0.866[95% CI, 0.755-0.977], with a sensitivity of 84.85%, and specificity of 83.33%, the optimal threshold is 331.5ms. The gray-zone was 317.5-335ms, covering 29% of patients, whereas narrower ranges of gray-zone than ΔV_peak (Figure 3).

Table 3. Predictive parameters of ROC curves induced by Trendelenburg position.

Variables	FTc	ΔV_peak
AUROC [95% CI]	0.866[0.755-0.977]	0.833[0.716-0.949]
P-value	<0.05	<0.05
Optimal cut-off value	<331.5ms	>10.1%
Grey zone	317.5-335ms	8.95-13.20%
Patients in grey zone (%)	15(29%)	23(45%)
Sensitivity (%) (95% CI)	84.85[0.691-0.934]	81.82[0.656-0.914]
Specificity (%)(95% CI)	83.33[0.608-0.942]	77.78[0.548-0.910]
PPV (%) (95%CI)	0.90[0.731-0.975]	0.82[0.639-0.924]
NPV (%) (95%CI)	0.75[0.506-0.904]	0.78[0.519-0.926]
Youden index	0.681	0.590

Our study evaluated the utility of Trendelenburg position combined with carotid ultrasound in predicting fluid responsiveness in VV-ECMO patients with ARDS in the prone position. The results showed that the optimal threshold for FTc induced by Trendelenburg position was 331.5ms, with a sensitivity of 84.85% and specificity of 83.33%, the AUC of the ROC curve was 0.866, the grey zone encompassed 29% of patients (15/51), indicating high diagnostic accuracy. The optimal threshold for △Vpeak was 10.1%, with sensitivity and specificity of 81.82% and 77.78% respectively, AUC was 0.833, grey zone encompassed 45% of patients (23/51), it`s diagnostic accuracy slightly lower than FTc. This study enables clinicians to predict fluid responsiveness in such patients non-invasively, facilitating the development of appropriate fluid management strategies without increasing the risk of fluid overload.

VV-ECMO is a valuable therapeutic option for severe acute respiratory distress syndrome (ARDS) with suboptimal response to protective lung ventilation[31, 32]. During this support, clinicians typically administer appropriate fluid infusion to stabilize ECMO flow and correct hypotension, thereby increasing oxygen delivery[33]. However, Positive fluid balance is associated with a higher risk of death in ECMO patients[34], Fluid overload can cause pulmonary edema and heart failure, exacerbating the condition of ARDS patients and ultimately leading to increased mortality[35].Therefore, fluid management in VV-ECMO patients is closely intertwined with their condition. Accurate prediction of fluid responsiveness is crucial to reduce fluid overload for such patients.

Fluid responsiveness refers to the physiological response of patients to fluid loading[12]. The evaluation of fluid responsiveness has always been a hot and challenging area of research. Clinical indicators are diverse, ranging from static parameters such as CVP and IVC to dynamic parameters such as stroke volume variation (SVV) and Pulse pressure variation (PPV). Evaluation indicators have undergone a transition from static to dynamic and from invasive to non-invasive. The purpose of our study of volume responsiveness was to improve organ tissue ischemia and hypoxia while avoiding volume overload, increasing mortality and hospitalization time.

Early CVP measurement can assess fluid responsiveness and improve the survival rates of critically ill patients with or at risk for ARDS [36]. CVP, serving as a pressure indicator, can reflect preload depending on cardiac compliance. However, various factors such as heart failure, volume expansion, the use of vasopressors, mechanical ventilation, or PEEP application can alter cardiac compliance, leading to inaccuracies in preload assessment via CVP [37]. Since our study population predominantly used a protective ventilation strategy with low tidal volume and high PEEP, CVP is not suitable for predicting fluid responsiveness in such patients.

PPV and SVV are dynamic parameters widely used to estimate cardiac preload and predict hemodynamic fluid responsiveness[38]. Nowadays, optimization strategies for fluid management are often based on these parameters, which can be easily obtained through monitoring devices such as non-invasive ultrasound, offering the advantages of safety, repeatability, real-time monitoring, and efficiency. However, some studies suggest that factors such as tidal volume (Vt) may influence the performance of PPV and SVV, especially in patients undergoing thoracoabdominal closure or positioned in the prone position[39, 40]. During the treatment of ARDS patients, mechanical ventilation can induce ventilator-induced lung injury (VILI) through various mechanisms, including volutrauma, barotrauma, and atelectrauma[41]. Therefore, guidelines from the Extracorporeal Life Support Organization (ELSO) recommend limiting tidal volume to less than 6 ml/kg to reduce the occurrence of VILI[42], and supplementing with prone positioning ventilation during ECMO to treat moderate to severe ARDS [43]. Multiple studies[44, 45] have demonstrated that prone positioning during ECMO is feasible, safe, and can enhance ECMO weaning and significantly improve outcomes. Constrained by the lung-protective ventilation strategy with low tidal volume(≤ 6 ml/kg), PPV and SVV are not suitable for predicting fluid responsiveness in such patients.

In contrast, the application of FT_c and ΔV_peak derived from neck ultrasound has multiple advantages. Firstly, this technique is entirely non-invasive, allowing for easy assessment of a patient's hemodynamic status through carotid artery ultrasound. Secondly, these parameters are applicable to patients with low tidal volume(≤ 6ml/kg) and cardiac arrhythmias[39], unlike other dynamic markers such as PPV and SVV, which require higher tidal volumes and regular heart rhythms. Additionally, the measurement of FTc and ΔVpeak is not affected by changes in intrathoracic pressure during respiration[46].

Trendelenburg position or PLR are used either as a diagnostic tool to assess fluid responsiveness[19, 20]. The physiological mechanisms of both methods are similar, involving changes in body position or elevation of the lower limbs to promote blood flow toward the heart, resulting in "autotransfusion," increasing venous return to the heart, enhancing CO, and ultimately increasing organ perfusion. However, PLR requires the patient to maintain a supine position, VV-ECMO patients often undergo prone positioning ventilation. Therefore, our study ultimately chose the Trendelenburg position.

Limitations

Our study had several limitations. Firstly, it was conducted in a single center, which may limit its generalizability across different clinical settings. Secondly, all patients in this study were under deep sedation; therefore, the application of Trendelenburg position combined with carotid artery ultrasound in predicting fluid responsiveness needs further validation in non-sedated states. Finally, This study solely involved VV-ECMO patients, thus the predictive capability for other types of ECMO patients remains unclear. In the future, we will further explore combining FTc and ΔVpeak with other predictive tools to enhance the accuracy of fluid responsiveness assessment.

Our study provides robust evidence supporting the high diagnostic accuracy of FT_c and ΔVpeak measured through neck ultrasound induced by the Trendelenburg position for predicting fluid responsiveness in VV-ECMO patients with ARDS in the prone position.

Ethics approval and consent to participate

This research has been approved by the ethics committee of Quzhou People's Hospital (Quzhou People's Hospital, Quzhou, China: Number B 2022-083). The study has undergone a thorough ethical review to ensure that it complies with all relevant ethical standards and guidelines for research involving human participants. This study has obtained informed consent from all participants and/or their legal guardian(s).

Consent for publication

Not applicable.

Availability of data and materials

The datasets generated and/or analysed during the current study are not publicly available due [the datasets contain sensitive information that, if publicly released, could compromise the privacy and confidentiality of the study participants] but are available from the corresponding author on reasonable request.

Competing interests

The authors declare that the study was conducted without any commercial or financial relationships that could be construed as potential conflicts of interest.

Funding

This work was supported in part by grants from Medical and Health Research Program of Zhejiang Province (No. 2023KY1296, HL Fang;).

Authors' contributions

Conceptualization, Honglong Fang, Junjie Zhao.; methodology, Honglong Fang and Junjie Zhao; software, Honglong Fang and Junjie Zhao; validation, Honglong Fang and Junjie Zhao ; formal analysis, Honglong Fang and Junjie Zhao; investigation, Honglong Fang and Junjie Zhao; resources, Honglong Fang, Yong Sun; data curation, Yong Sun, Jing Tang and Kai guo.; writing-original draft preparation, Honglong Fang and Junjie Zhao; writing-review and editing, Honglong Fang, Jiancheng Zhuge and Junjie Zhao; supervision, Honglong Fang, and Jiancheng Zhuge.

Acknowledgements

Not applicable.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work the author(s) used [chatgpt] in order to [polish English language editing]. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

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No competing interests reported.

The Predictive Value of Trendelenburg Position and Neck Ultrasound for Fluid Responsiveness in Prone ARDS Patients with VV-ECMO

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Abstract

Background

Methods

Results

Conclusions

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Background

Methods

Study design

Patients

Protocol

Measurements

Data collection

Statistical analysis

Results

Discussion

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Conclusions

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References

Additional Declarations

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Version 1