Assessment of Fluid Responsiveness After Tidal Volume Challenge During Pressure-Controlled Ventilation Volume Guaranteed: An observational study

doi:10.21203/rs.3.rs-45075/v1

Download PDF

Research article

Assessment of Fluid Responsiveness After Tidal Volume Challenge During Pressure-Controlled Ventilation Volume Guaranteed: An observational study

https://doi.org/10.21203/rs.3.rs-45075/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background: The reliability of pulse pressure variation (PPV) and stroke volume variation (SVV) to predict fluid responsiveness have not previously been established when using pressure-controlled ventilation-volume guaranteed (PCV-VG) mode. We hypothesized that with a transient increase in tidal volume from 6 to 8 mL/kg of predicted body weight (PBW), which we reference as the “tidal volume challenge (TVC)”, the changes to PPV and SVV will be an indicator of fluid responsiveness.

Methods: The patients were first ventilated with a tidal volume of (V_t) 6 mL/kg of predicted body weight (PBW) using PCV-VG. Following intravenous anesthesia induction, PPV₆and SVV₆ were recorded, then the TVC was performed, which increased V_t from 6 mL/kg to 8 mL/kg PBW for 1 minute and PPV₈ and SVV₈ were recorded again. The changes in value of PPV and SVV (ΔPPV_6-8 and ΔSVV_6-8) were calculated after TVC. Following the minute of TVC, the tidal volume was returned to 6 ml/kg PBW for the fluid challenge (FC), a colloid infusion of 6ml/kg PBW for 20 minutes. Patients were classified as responders if there was an increase in cardiac index (CI) of more than 15% after FC, otherwise the patients were identified as non-responders. Eligible patients were divided into groups of responders or non-responders.

Results: 37 patients were classified as responders and 44 were non-responders. PPV₆ and SVV₆ could not predict the fluid responsiveness, while PPV₈ and SVV₈ could predict the fluid responsiveness when using PCV-VG mode. The changes in value of PPV and SVV after TVC (ΔPPV_6-8 and ΔSVV_6-8) identified true fluid responders with the highest sensitivity and specificity in the above variables, which predicted fluid responsiveness with the area under the receiver operating characteristic curves (AUCs) (95% CIs) being 0.96 (0.93-1.00) and 0.98 (0.96-1.00), respectively. No significant difference was found when comparing the AUCs of ΔPPV_6-8 and ΔSVV_6-8 (P > 0.05). Linear correlation was represented between the change value of CI after FC and the change value of SVV or PPV after TVC (r = 0.68; P < 0.0001 and r = 0.77; P < 0.0001, respectively).

Conclusions: A transient increase in tidal volume, which we reference as the “tidal volume challenge (TVC)” could enhance the predictive value of PPV and SVV for the evaluation of fluid responsiveness in patients under ventilation with PCV-VG.

Trial registration: Chinese Clinical Trial Registry (ChiCTR2000028995). Prospectively registered on 11 January 2020. http://www.medresman.org.

Anesthesiology & Pain Medicine

Pressure-controlled ventilation-volume guaranteed

Pulse pressure variability

Stroke volume variability

Cardiac index

Fluid therapy is cornerstone of the hemodynamic management of patients undergoing major surgery. Goal-directed fluid therapy (GDFT) attempts to avoid the occurrence of excessive fluid load and hypovolemia, shorten the length of hospital stays, reduce mortality and minimize the complications caused by fluid imbalance during surgery [1, 2].To better implement GDFT, we need to find appropriate indicators that can accurately predict fluid responsiveness.

Studies have shown that dynamic indicators, such as pulse pressure variability (PPV) and stroke volume variability (SVV), are superior to static indices to predict fluid responsiveness [2–4]. However, accuracy and thresholds are affected by many factors, such as changes in the mode of ventilation or tidal volume [5, 6]. In surgeries involving general anesthesia, the application of volume-controlled ventilation (VCV) when attempting to ensure adequate respiration often leads to excessive airway pressure. Pressure-controlled ventilation (PCV) often fails to provide adequate ventilation volume under the condition of ensuring proper airway pressure [7, 8]. Recently, a new type of intelligent ventilation mode, PCV-VG, has emerged, it combines the advantages of both VCV and PCV which utilizes a decelerating flow and constant pressure to offer the pre-set V_t without increasing airway pressures [9]. In addition, application of PCV-VG combined with low tide volume (V_t) (6–8 ml/kg PBW) had been advocated as a lung protective ventilation strategy, which can effectively reduce airway pressure, avoid the occurrence of pulmonary barotrauma, stabilize hemodynamics and reduce pulmonary complications [10, 11]. When the gas was delivered with decelerating flow rate in the ventilation with PCV-VG, the variability of intrathoracic pressure may decrease, which affects the accuracy of the prediction produced for fluid responsiveness [8, 12]. Additionally, previous studies reported that ventilation with the V_t below 8 ml/kg PBW is not enough to cause significant changes in intrathoracic pressure, and this may blunt the accuracy of PPV and SVV to predict the fluid responsiveness [13, 14]. Therefore, it is not clear whether PPV and SVV could accurately predict patients' fluid responsiveness during ventilation with PCV-VG combined with a lung protective ventilation strategy achieved by low V_t (6–8 ml/kg PBW).

We have failed to identify any previous studies exploring fluid responsiveness during ventilation with PCV-VG. This study was conducted to assess the reliability of PPV and SVV in predicting fluid responsiveness of patients ventilated using PCV-VG with low V_t (6–8 ml/kg PBW) and also to determine whether the TVC could enhance the predictive value of PPV and SVV in this lung protective ventilation strategy.

2.1 General information

This prospective study was conducted between January 2020 and March 2020 in accordance with the Declaration of Helsinki principles. The study was registered in the Chinese Clinical Trial Registry (ChiCTR2000028995) and was approved by the Ethics Committee for Clinical Trials of the Second Hospital of Anhui Medical University, Hefei, China [approval no: PJ-YX2019-037]. Written informed consent was obtained from the participants or guardians before surgery. Included in this study were eighty-one patients with American Society of Anesthesiologists (ASA) physical status of I-II, aged 18 to 65 years, scheduled for laparoscopy-assisted radical gastrectomy under general anesthesia. Patients were excluded according to the following criteria: kidney dysfunction; cardiac arrhythmias and valvular heart disease; chronic obstructive pulmonary disease; right ventricular failure; intracranial hypertension; severe obesity difficulty (BMI > 30 kg/m²); airway asthma or a long history of smoking. FC was performed to identify fluid responders if there was an increase in CI ≥ 15%, otherwise the patients were identified as non-responders. The patients were separated into two groups, responder and non-responder.

2.2 Perioperative management

Intravenous and arterial access were established for monitoring of continuous invasive blood pressure and central venous pressure (CVP) after arrival to the operating room and before the induction of anesthesia. Drager monitor (model: A7, Hefei unity medical co.) was used for monitoring the non-invasive blood pressure, invasive radial arterial blood pressure, pulse oximetry, heart rate (HR), ratio of the HR and respiratory rate (HR/RR), electrocardiogram, peak airway pressure, plateau pressure (P_pl), driving pressure (P_pl-positive end-expiratory pressure [PEEP]) and partial pressure of carbon dioxide in end expiratory gas (P_ETCO2). The vital variables, such as pulse pressure variability (PPV); stroke volume variability (SVV) and cardiac index (CI) were recorded by a continuous non-invasive arterial pressure monitor (CNAP) (model: CANP™ Monitor 500, Guangzhou Xinju Science and Trade Co.). All patients received fluid of Ringer's solution at a rate of 5 ~ 7 ml/kg/h. And bispectral index (BIS) (the America, Covidien IIc Co.) and the arterial blood gas analysisis of patients were monitored perioperatively.

General anesthesia was induced by intravenous (i.v.) midazolam (0.03 mg/kg), sufentanil (0.5 µg/kg), rocuronium (0.6 mg/kg) and etomidate (0.2 mg/kg) after mask oxygen inhalation for two minutes. Tracheal intubation was performed after reaching BIS between 40 and 60 and appropriate muscle relaxation was achieved, the Mindray anesthesia machine (model: A5, Shenzhen Mindray biomedical electronics co LTD) was connected for mechanical ventilation with PCV-VG mode and followed the setting: V_t of 6 ml/kg PBW; P_ETCO₂ remained in the 35–45 mmHg range with an inspired oxygen fraction 0.5 and a fresh gas flow 2 L/min of oxygen and air; PEEP was kept between 3–5 cmH₂O and SpO₂ was maintained at more than 95%. Maintenance of anesthesia was conducted by propofol (4 ~ 8 mg/kg/h), remifentanil (0.1 ~ 0.3 µg/kg/min), cisatracurium (0.1 ~ 0.2 mg/kg/h) and sevoflurane (1%~2%). Anesthetic depth was maintained at a BIS of 40–60 throughout the surgical procedure by adjusting the end-tidal concentration of sevoflurane. Simultaneously, the appropriate application of vasoactive drugs (atropine and noradrenaline) was for the maintenance of HR and mean arterial pressure (MAP) at around 20% of the base value.

2.3. Hemodynamic and Respiratory monitoring and Study Protocol

The PPV, SVV, MAP, HR, CVP, peak airway pressure, P_pl, driving pressure, central venous oxygen saturation, oxygenation index and compliance of the respiratory system (C_rs) were recorded after intravenous anesthesia induction. The depth of the anesthesia was ensured by the monitoring of BIS. Before the start of the surgery and administration of any vasopressor, with the patient supine, the study protocol (Fig. 1) was started as follows: (1) Patients were ventilated by PCV-VG with V_t 6 mL/kg PBW, maximum airway pressure of 30 mmH₂O, and PEEP 3 ~ 5 cmH₂O for 1 minute, baseline measurements including the PPV (PPV₆) and SVV (SVV₆) were recorded (T₀). (2) The TVC was performed by a transiently increasing Vt (from 6 up to 8 mL/kg PBW for 1 minute), and another set of measurements including the PPV (PPV₈) and SVV (SVV₈) was recorded after 1 minute (T₁). Additionally, the changes in value of PPV and SVV (ΔPPV_6 − 8 = PPV₈ – PPV₆ and ΔSVV_6 − 8 = SVV₈ – SVV₆) were calculated. (3) The V_t was reduced back to 6 ml/kg PBW with the completion of TVC. Measurements including the CI (CI_T2), PPV (PPV_T2) and SVV (SVV_T2) were recorded after an additional 1 minute (T₂). (4) The FC was achieved by infusion of 6 ml/kg PBW of hydroxyethyl starch over 20 minutes, simultaneously, a set of measurement including the CI (CI_T2), PPV (PPV_T3) and SVV (SVV_T3) were also recorded at the end of FC (T₃), and the change in PPV, SVV and CI after FC (ΔPPV_fc = PPV_T3 – PPV_T2, ΔSVV_fc = SVV_T3 – SVV_T2 and ΔCI = CI_T3 – CI_T2) were also calculated.

2.4. Sample size and statistical analyses

TVC has not previously been studied in patients ventilated with the ventilation of PCV-VG mode, the expected areas under the curves of PPV₆ and ΔPPV_6 − 8 were respectively 0.65 and 0.90, which was used to calculate the sample size requirement for comparing two ROC curves by statstodo, a statistical analytics tool. A sample size of 60 patients, was sufficient to detect a significant difference (α = 5%) with a statistical power (β-value) of 90%, however it was increased to 81 patients for considering a 15% failure rate.

The continuous variables were presented as mean (standard deviation) or median (interquartile range) depending on the normal distribution tested by the D’Agostino-Pearson. Categorical variables presented as proportions (percentage), such as ASA physical status and gender, were analyzed using the χ² test. Continuous variables normally distributed were analyzed using independent-sample t-test while Mann-Whitney U or Wilcoxon signed-rank tests was used to compare abnormal distributions between two groups (responders and non-responders). A one-way analysis of variance (ANOVA) for repeated measurements has been performed for analysis of the hemodynamic values from T₀ to T₃. The Tukey test was used for post hoc pairwise multiple comparisons analysis. Moreover, the predictive value of SVV, PPV, TVC and FC were evaluated by receiver operating characteristic (ROC) curve (95% confidence interval). The DeLong test was used to compare the statistically significant ROC curves [15]. Statistical analyses and graphics were conducted using GraphPad PRISM V7 (GraphPad Software Inc, San Diego, CA). We considered a P values less than 0.05 to be significant for all comparisons.

100 patients scheduled for laparoscopy - assisted radical gastrectomy under general anesthesia were screened and 90 considered eligible in the enrollment period. Totally 9 patients were excluded with following reasons: 8 patients were not accordant with the inclusion criteria and 1 suddenly decided to give up the operation before arrival to the operating room). 81 patients were eventually included, 37 were responders and 44 patients were non-responders, grouped based on the administration of FC. (Fig. 2)

3.1. Preoperative characteristics

As shown in Table 1, there was no statistically significant difference between the two groups in the baseline characteristics (gender, age, BMI, ASA, and preoperative complications), respiratory characteristics (peak airway pressure, driving pressure, oxygenation index, P_pl and C_rs) and hemodynamic characteristics (MAP, central venous oxygen saturation and the parameters of arterial blood gas analysis ) (P > 0.05).

Table 1

Baseline Hemodynamic and Respiratory Characteristics
	R (n = 37)	NR (n = 44)	P Value
General characteristics
ASA physical status (n)
Ⅰ	29 (78)	33 (75)	0.721
Ⅱ	8 (22)	11 (25)	0.721
Male (n)	19 (51)	24 (55)	0.774
Age (year)	53 (48–63)	58 (50–64)	0.159
BMI (kg/m²)	22.4 (21.4–23.7)	23.3 (20.9–24.0)	0.663
MAP (cmH₂O)	81 (13)	80 (12)	0.854
Central venous oxygen saturation (%) AAssSsssaturation	74.9 (1.4)	75.4 (1.4)	0.123
PH	7.41 (0.04)	7.39 (0.03)	0.059
Lactate (mmol/L)	0.8 (0.7–1.1)	0.9 (0.8–1.2)	0.147
Chronic preoperative disease (n)
Diabetes	8 (21.6)	11 (25.0)	0.721
Hypertension	8 (21.6)	10 (22.7)	0.905
Respiratory characteristics
Ppeak (cmH₂O)	18.5 (2.2)	18.3 (1.8)	0.670
Pplat (cmH₂O)	11 (10–12)	11 (10–13)	0.627
Pplat-PEEP (cmH₂O)	8.0 (1.4)	8.5 (1.3)	0.084
C_rs (ml/cmH₂O)	60 (4)	59 (3)	0.215
PaO₂/FiO₂ (mmHg)	445 (27)	451 (26)	0.332
Values are reported as frequency (percentage), mean (standard deviation) and median (interquartile range), as appropriate. ASA, American Society of Anesthesiologists Classification; NR, non-responders; R, responders; MAP, mean arterial pressure; PEEP, Positive end-expiratory pressure; BMI, body mass index; Pplat, plateau pressure; Ppeak, peak airway pressure; PaO₂/FiO₂, arterial partial pressure of oxygen/fraction of inspired oxygen; C_rs, compliance of the respiratory system.

3.2. Effect of TVC and FC administration

The TVC significantly increased PPV (from 7.5–11.2%, P < 0.001) and SVV (from 8.6–13.4%, P < 0.001) in responders, but didn't affect PPV and SVV in non-responders (T₁ vs T₀). PPV and SVV in the responder's group were significantly higher than those in the non-responder's group at T₁ (Table 2).

Table 2

Hemodynamic Characteristics of Fluid Responders and Non-responders in Study Period
	T₀	T₁	T₂	T₃	P Value (T₀ vs T₁)	P Value (T₂ vs T₃)	P Value T₁ (R vs NR)	ANONA (P)
MAP (cmH₂O)
R (n = 37)	78 (10)	79 (9)	80 (9)	78 (10)	0.940	0.913	0.245	0.857
NR (n = 44)	76 (9)	78 (11)	79 (10)	81 (12)	0.809	0.809	0.245	0.150
CVP (cmH₂O)
R (n = 37)	5.2 (1.9)	5.6 (1.5)	5.9 (1.5)	10.6 (1.6)	0.710	༜0.001	0.006	༜0.001
NR (n = 44)	6.3 (1.8)	6.6 (1.7)	7.0 (1.3)	6.6 (1.2)	0.763	0.763	0.006	0.225
HR (beats/min)
R (n = 37)	63 (10)	61 (9)	62 (9)	60 (8)	0.767	0.889	0.221	0.467
NR (n = 44)	61 (9)	59 (8)	60 (8)	59 (7)	0.497	0.906	0.221	0.483
CI (L/min/m²)
R (n = 37)	3.05 (0.14)	3.02 (0.11)	2.99 (0.11)	3.73 (0.17)	0.730	༜0.001	0.003	༜0.001
NR (n = 44)	3.12 (0.16)	3.11 (0.15)	3.11 (0.13)	3.15 (0.08)	0.962	0.671	0.003	0.577
PPV (%)
R (n = 37)	7.5 (1.6)	11.2 (1.9)	12.0 (1.9)	5.5 (1.4)	༜0.001	༜0.001	༜0.001	༜0.001
NR (n = 44)	7.9 (2.1)	7.8 (2.2)	6.9 (1.3)	6.7 (1.4)	0.998	0.965	༜0.001	༜0.001
SVV (%)
R (n = 37)	8.6 (1.6)	13.4 (2.0)	14.3 (2.6)	6.5 (1.5)	༜0.001	༜0.001	༜0.001	༜0.001
NR (n = 44)	9.7 (2.7)	9.8 (2.6)	8.0 (1.3)	7.4 (1.4)	0.997	0.588	༜0.001	༜0.001
Values are reported as mean (standard deviation); SVV, stroke volume variation; MAP, mean arterial pressure; R, responders; NR, non-responders; PPV, pulse pressure variation; CVP, central venous pressure; CI, cardiac index; HR, heart rate.

Following FC administration, there were significant decrease in PPV (from 12.0–5.5%, P < 0.001) and SVV (from 14.3–6.5%, P < 0.001) only in responders. And FC also significantly increased CVP only in responders. However, the all recorded variables in non-responders, as shown in Table 2, haven’t been changed by the administration of FC.

3.3. Prediction of Fluid Responsiveness

As shown in Table 3, the PPV₆ and SVV₆ did not correlate to fluid responsiveness while ΔPPV_6 − 8, ΔSVV_6 − 8, PPV₈ and SVV₈ could predict the fluid responsiveness. The best cutoff value of ΔSVV_6 − 8 was 1.5% with a sensitivity of 95.2% and a specificity of 94.7%. Similarly, the best cutoff value of ΔPPV_6 − 8 was also 1.5% showing a sensitivity of 89% and a specificity of 93%. The AUCs of the ΔPPV_6 − 8 and ΔSVV_6 − 8 were 0.96 (95% CI, 0.93-1.00) and 0.98 (95% CI, 0.96-1.00), respectively. ΔPPV_fc and ΔSVV_fc, the change value of PPV and SVV after FC, discriminated responders from non-responders, which similarly have very high predictive value with AUCs (with 95% CIs) being 0.99 (0.98–1.01) and 0.98 (0.96–1.01), respectively (Table 3). The AUCs of ΔPPV_6 − 8 and ΔSVV_6 − 8 were all significantly greater than the AUCs of PPV₈ and SVV₈. And the AUCs for ΔPPV_6 − 8, ΔSVV_6 − 8, ΔPPV_fc and ΔSVV_fc were not significantly different (Table 4).

Table 3

Diagnostic Ability of Various Variables in Predicting Fluid Responsivenes
Variables	Area Under the Receiver-Operaing Characteristic Curve (95% CI)	P Value	Youden Index	Best cutoff Value (%)	Sensitivity (%)	Specificity (%)	Positive Predictive Value (95% CI)	Negative Predictive Value (95% CI)
PPV₆	0.54 (0.41–0.66)	0.589		-	-	-
SVV₆	0.62 (0.50–0.74)	0.069		-	-	-
PPV₈	0.87 (0.80–0.95)	< 0.001	0.63	8.5	97	66	71(61–78)	97(81–100)
SVV₈	0.85 (0.78–0.93)	< 0.001	0.53	10.5	89	64	67(58–76)	88(73–95)
ΔPPV_6 − 8	0.96 (0.93-1.00)	< 0.001	0.82	1.5	89	93	92(79–97)	91(80–96)
ΔSVV_6 − 8	0.98 (0.95–1.01)	< 0.001	0.88	1.5	95	93	92(80–97)	95(84–99)
ΔPPV_fc	0.99 (0.98–1.01)	< 0.001	0.97	2.5	97	100	100(89–100)	98(86–100)
ΔSVV_fc	0.98 (0.96–1.01)	< 0.001	0.90	3.5	92	98	97(83–100)	94(83–98)
PPV₆, PPV at V_t 6 mL/kg PBW; SVV₆, SVV at V_t 6 mL/kg PBW; PPV₈, PPV at V_t 8 mL/kg PBW; SVV_8, SVV at V_t 8 mL/kg PBW; ΔPPV_6 − 8, change value of PPV after TVC; ΔSVV_6 − 8, change value of SVV after TVC; ΔPPV_fc, change value of PPV after fluid challenge; ΔSVV_fc, change value of SVV after fluid challenge; SVV, stroke volume variation; PPV, pulse pressure variation; TVC, tidal volume challenge; PBW, predicted body weight; V_t, tidal volume; Dashes indicate variable was not measured.

Table 4

**Comparisons of Area under Receiver Operating Characteristic Curves**
Tests	P Value
AUC PPV₈ vs AUC ΔPPV_6 − 8	0.013
AUC SVV₈ vs AUC ΔSVV_6 − 8	0.002
AUC ΔPPV_6 − 8 vs AUC ΔPPV_fc	0.094
AUC ΔSVV_6 − 8 vs AUC ΔSVV_fc	0.886
AUC ΔPPV_6 − 8 vs AUC ΔSVV_6 − 8	0.237
AUC ΔPPV_fc vs AUC ΔSVV_fc	0.165
De Long test was used for comparation of ROC curves. AUC, area under the receiver operating characteristic curve; PPV₈, PPV at V_t 8 mL/kg PBW; SVV_8, SVV at V_t 8 mL/kg PBW; ΔPPV_6 − 8, change value of PPV after TVC; ΔSVV_6 − 8, change value of SVV after TVC; ΔPPV_fc, change value of PPV after fluid challenge; ΔSVV_fc, change value of SVV after fluid challenge; TVC, tidal volume challenge; PBW, predicted body weight; V_t, tidal volume.

The box and whisker plots have been performed to compare these variables (ΔPPV_6 − 8, ΔSVV_6 − 8, ΔPPV_fc and ΔSVV_fc) among two groups (responders and non-responders) and there was a significant (P < 0.05) difference (Fig. 4). The ROC curves of above variables were shown in Fig. 3.

3.4. Linear Correlation

A linear correlation between ΔCI after FC administration and ΔPPV_6 − 8 (r = 0.68; P < 0.001) and ΔSVV_6 − 8 (r = 0.77; P < 0.001) was observed (Fig. 5).

The accuracy of predicting fluid responsiveness in patients is the key to guiding perioperative fluid management [16]. Therefore, it is necessary to identify the most accurate measures of fluid responsiveness with the objective of minimizing incidents of fluid overload and hypovolemia. The PPV could show predictive value with a Vt at least 8 mL/kg PBW as shown in the study of De Backer D et al [14]. Several studies have indicated that the SVV and PPV may signify a nonresponsive status even in responders during low Vt ventilation. The reason is that the Vt might be insufficient to produce a significant change in the intrathoracic pressure [17–19]. Meanwhile, previous studies show that ventilation using PCV-VG combined with low Vt (6–8 ml/kg PBW) has been effective as a lung protective ventilation strategy [10, 11]. It is not clear whether PPV and SVV can accurately assess patients' fluid responsiveness during mechanical ventilation using PCV-VG combined with low Vt (6–8 ml/kg PBW). In recent years, the assessment of fluid responsiveness performed via dynamic evaluation of hemodynamic parameters in response to certain interventions, known as functional hemodynamic tests, such as mini fluid challenge test (MFT), tidal volume challenge (TVC) and end-expiratory occlusion test (EEOT), have been considered reliable and effective methods in guiding perioperative fluid management [20–22].

This study initially explored the reliability of functional hemodynamic tests in predicting fluid responsiveness in patients ventilated using PCV-VG. The main finding showed that ΔPPV_6 − 8 and ΔSVV_6 − 8 are remarkable predictors of fluid responsiveness in patients undergoing laparoscopy-assisted radical gastrectomy with cutoff values of both 1.5%. The change in PPV and SVV after a fluid challenge (ΔPPV_fc and ΔSVV_fc) also accurately predicts fluid responsiveness with very high sensitivity and specificity. And yet, it requires a fluid bolus to discriminate responders from non-responders seen in the change of cardiac index and may increase the risk of fluid overload in the non-responder corhort. PVV and SVV at Vt 8 mL/kg PBW also identifies responders with the area under receiver-operating characteristic curve (AUC) (0.87 and 0.85, respectively), which are lower than those of ΔPPV_6 − 8 and ΔSVV_6 − 8 (Table 4). Therefore, TVC should be a good strategy to enhance the predictive value of PPV and SVV for the evaluation of fluid responsiveness in patients undergoing protective ventilation with small tidal volume.

Meanwhile, many studies have shown that using PCV-VG can reduce lung injury caused by mechanical ventilation as well as reduce expiratory pressure and improve arterial oxygenation. This is assumed to be a beneficial effect of the decelerating flow rate on the airway and the decelerating waveform on intrapulmonary distribution by PCV-VG [23–25]. Therefore, we suspected that the decelerating flow rate may influence the change of patients’ intrathoracic pressure and the cardiopulmonary interactions weakly, thus affecting the accuracy of the dynamic indicators. The TVC (an increase of V_t from 6 to 8 mL/kg PBW) can reduce the influence of the decelerating flow rate on the change and conduction of intrathoracic pressure. As a result, ΔPPV_6 − 8 and ΔSVV_6 − 8 accurately predicted fluid responsiveness depending on the increased fluctuation of intrathoracic pressure, as well as greater dynamic compliance and cardiopulmonary interaction, during the implementation of TVC. This was confirmed in this study: In line with the findings of previous studies conducted in patients ventilated with the VCV mode, this study showed that the fluid responsiveness of patients predicted by the PPV₆ and SVV₆ under ventilation of PCV-VG mode were also not valuable. But the AUCs of PPV₆, SVV₆ in this study is lower than those in previous studies. Moreover, the AUCs of PPV₈ and SVV₈ are also lower than those in studies conducted in patients ventilated with the VCV mode. Nevertheless, it has been showed that the AUCs of ΔPPV_6 − 8 and ΔSVV_6 − 8 in this study were not significantly different with those in previous studies [26–28]. Simultaneously, the correlation between the ΔPPV_6 − 8 and ΔSVV_6 − 8 after the TVC application and ΔCI after FC administration (Fig. 5) suggests that the using PCV-VG with low tide volume in surgical subjects with normal respiratory compliance may not alter the interaction between volume status, the transmission of the intrathoracic pressure to the heart and the final effect on PPV and SVV, ensuring the application of TVC suitable for the setting of PCV-VG mode. The results shown above could support our hypothesis and confirm that the absolute changes in PPV and SVV (ΔPPV_6 − 8 and ΔSVV_6 − 8) after TVC could also be a reliably functional hemodynamic test for predicting fluid responsiveness when using PCV-VG combined with low V_t (6–8 ml/kg PBW).

Our research showed that the TVC significantly increased PPV and SVV in responders but didn't affect PPV and SVV in non-responders, which is consistent with previous reports about TVC. The threshold of ΔPPV_6 − 8 and ΔSVV_6 − 8 were lower than those initially reported by Myatra et al [6]. This finding may be explained by two factors. On the one hand, compared with VCV mode used in Myatra’s study, the decelerating flow rate of PCV-VG may weaken the transmission of intrathoracic pressure to pleural and atrial pressure and influence cardiopulmonary interaction and lead to a decrease of threshold of these variables. On the other hand, different from the patients with ASA physical status I-II and normal lung compliance we selected, the patients in Myatra’s trail were critically ill patients with acute circulatory failure, 30% of whom were affected with a reduced chest wall compliance, which may enhance the transmission of applied airway pressure to the pericardium and the vena cava [28, 29]. In other words, there were varying degrees of influence of TVC application in elective surgical and critically ill patients on account of the distinction of cardiopulmonary interactions [30].

Some limitations of this study should be discussed. First, the time frame takes place after the induction of anesthesia and before the intervention of surgery, because the aim was to evaluate whether the TVC could enhance the predictive value of PPV and SVV in patients under the ventilation of PCV-VG. Therefore, it is impossible to predict the influence of different surgical types and operations on the results, which still needs further study; Secondly, this study only explored the reliability of PPV and SVV in predicting fluid responsiveness under ventilation of PCV-VG, but the reliability of other functional hemodynamic tests, such as EEOT and MFT, are not clear and also need further study. Finally, the other limitations in application of PPV and SVV in ventilation of PCV-VG, such as cardiac arrhythmias, the presence of spontaneous breathing and right ventricular dysfunction, could not be avoidable.

A transient increase in tidal volume, which we reference as the “tidal volume challenge (TVC)” could enhance the predictive value of PPV and SVV for the evaluation of fluid responsiveness in patients under ventilation with PCV-VG.

PPV：Pulse pressure variation

SVV：Stroke volume variation

PCV-VG：Pressure-controlled ventilation-volume guaranteed

PBW: Predicted body weight

TVC: Tidal volume challenge

FC: Fluid challenge

CI: Cardiac index

ROC: The receiver operating characteristic curve

AUC: The area under the receiver operating characteristic curve

GDFT: Goal-directed fluid therapy

PCV: Pressure-controlled ventilation

VCV: Volume-controlled ventilation

V_t: Tide volume

ASA: American Society of Anesthesiologists

BMI: Body mass index

CVP: Central venous pressure

HR: Heart rate

P_pl: Plateau pressure

PEEP: Positive end-expiratory pressure

P_ETCO2: Partial pressure of carbon dioxide in end expiratory gas

BIS: Bispectral index

SpO₂: Oxygen saturation

MAP: Mean arterial pressure

C_rs: Compliance of the respiratory system

MFT: Mini fluid challenge test

EEOT: End-expiratory occlusion test

Ethics approval and consent to participate

The study was registered in the Chinese Clinical Trial Registry (ChiCTR2000028995) and was approved by the Ethics Committee for Clinical Trials of the Second Hospital of Anhui Medical University, Hefei, China [approval no: PJ-YX2019-037].

Written informed consent was obtained from the all participants or guardians before surgery.

Consent for publication

Not applicable.

Availability of data and materials

The datasets generated and / or analyzed during the current study will be available from the corresponding author on reasonable request.

Conflict of interest

The author declares that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Funding

This work was supported by the funding of Anhui province science and technology project (grant numbers: 1704a0802165).

Contributions

Y J and LL J is Co-First Author, participated in Conceptualization, Writing - Original Draft, Methodology, Formal analysis, Visualization, Investigation, Data curation and Project administration. J H did the statistical analysis and reviewed the manuscript Y Z participated in Conceptualization, Supervision, Methodology, Resources, Data curation, Validation, Writing - review & editing, Project administration and Funding acquisition. All authors read and approved the final manuscript.

Acknowledgment

We acknowledge Can Wang, for his valuable contribution and encouragement, Peng Zhu and ChunXia Huang for their excellent help with the statistical analyses.

Kendrick JB, Kaye AD, Tong Y, Belani K, Urman RD, Hoffman C, Liu H: Goal-directed fluid therapy in the perioperative setting. J Anaesthesiol Clin Pharmacol 2019, 35(Suppl 1):S29-S34.
Weinberg L, Mackley L, Ho A, Mcguigan S, Ianno D, Yii M, Banting J, Muralidharan V, Tan CO, Nikfarjam M et al: Impact of a goal directed fluid therapy algorithm on postoperative morbidity in patients undergoing open right hepatectomy: a single centre retrospective observational study. BMC ANESTHESIOL 2019, 19(1):135.
Hong JQ, He HF, Chen ZY, Du ZS, Liu WF, Weng PQ, Huang HB: Comparison of stroke volume variation with pulse pressure variation as a diagnostic indicator of fluid responsiveness in mechanically ventilated critically ill patients. SAUDI MED J 2014, 35(3):261-268.
Hasanin A, Zanata T, Osman S, Abdelwahab Y, Samer R, Mahmoud M, Elsherbiny M, Elshafaei K, Morsy F, Omran A: Pulse Pressure Variation-Guided Fluid Therapy during Supratentorial Brain Tumour Excision: A Randomized Controlled Trial. Open Access Maced J Med Sci 2019, 7(15):2474-2479.
Messina A, Colombo D, Cammarota G, De Lucia M, Cecconi M, Antonelli M, Corte FD, Navalesi P: Patient-ventilator asynchrony affects pulse pressure variation prediction of fluid responsiveness. J CRIT CARE 2015, 30(5):1067-1071.
Myatra SN, Prabu NR, Divatia JV, Monnet X, Kulkarni AP, Teboul JL: The Changes in Pulse Pressure Variation or Stroke Volume Variation After a "Tidal Volume Challenge" Reliably Predict Fluid Responsiveness During Low Tidal Volume Ventilation. CRIT CARE MED 2017, 45(3):415-421.
Kothari A, Baskaran D: Pressure-controlled Volume Guaranteed Mode Improves Respiratory Dynamics during Laparoscopic Cholecystectomy: A Comparison with Conventional Modes. Anesth Essays Res 2018, 12(1):206-212.
Assad OM, El SA, Khalil MA: Comparison of volume-controlled ventilation and pressure-controlled ventilation volume guaranteed during laparoscopic surgery in Trendelenburg position. J CLIN ANESTH 2016, 34:55-61.
Lee JM, Lee SK, Kim KM, Kim YJ, Park EY: Comparison of volume-controlled ventilation mode and pressure-controlled ventilation with volume-guaranteed mode in the prone position during lumbar spine surgery. BMC ANESTHESIOL 2019, 19(1):133.
Byun SH, Lee SY, Jung JY: Effects of small tidal volume and positive end-expiratory pressure on oxygenation in pressure-controlled ventilation-volume guaranteed mode during one-lung ventilation. Yeungnam Univ J Med 2018, 35(2):165-170.
Guay J, Ochroch EA, Kopp S: Intraoperative use of low volume ventilation to decrease postoperative mortality, mechanical ventilation, lengths of stay and lung injury in adults without acute lung injury. Cochrane Database Syst Rev 2018, 7:D11151.
Kim YS, Won YJ, Lee DK, Lim BG, Kim H, Lee IO, Yun JH, Kong MH: Lung ultrasound score-based perioperative assessment of pressure-controlled ventilation-volume guaranteed or volume-controlled ventilation in geriatrics: a prospective randomized controlled trial. CLIN INTERV AGING 2019, 14:1319-1329.
Lansdorp B, Lemson J, van Putten MJ, de Keijzer A, van der Hoeven JG, Pickkers P: Dynamic indices do not predict volume responsiveness in routine clinical practice. Br J Anaesth 2012, 108(3):395-401.
De Backer D, Heenen S, Piagnerelli M, Koch M, Vincent JL: Pulse pressure variations to predict fluid responsiveness: influence of tidal volume. Intensive Care Med 2005, 31(4):517-523.
DeLong ER, DeLong DM, Clarke-Pearson DL: Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. BIOMETRICS 1988, 44(3):837-845.
Zhu AC, Agarwala A, Bao X: Perioperative Fluid Management in the Enhanced Recovery after Surgery (ERAS) Pathway. Clin Colon Rectal Surg 2019, 32(2):114-120.
Yang X, Du B: Does pulse pressure variation predict fluid responsiveness in critically ill patients? A systematic review and meta-analysis. CRIT CARE 2014, 18(6):650.
Teboul JL, Monnet X: Pulse pressure variation and ARDS. MINERVA ANESTESIOL 2013, 79(4):398-407.
Pinsky MR: Using ventilation-induced aortic pressure and flow variation to diagnose preload responsiveness. Intensive Care Med 2004, 30(6):1008-1010.
Dou ZM, Lin QL, Cao YQ, Li B, Liu J. Effect of tidal volume challenge on fluid respo-nsivene-ss in septic patients with mechanical ventilation.Chin J Crit Care,2019,39(4):366-370.
Monnet X, Osman D, Ridel C, Lamia B, Richard C, Teboul JL: Predicting volume responsiveness by using the end-expiratory occlusion in mechanically ventilated intensive care unit patients. CRIT CARE MED 2009, 37(3):951-956.
Monnet X, Bleibtreu A, Ferre A, Dres M, Gharbi R, Richard C, Teboul JL: Passive leg-raising and end-expiratory occlusion tests perform better than pulse pressure variation in patients with low respiratory system compliance. CRIT CARE MED 2012, 40(1):152-157.
Yao W, Yang M, Cheng Q, Shan S, Yang B, Han Q, Ma J: Effect of Pressure-Controlled Ventilation-Volume Guaranteed on One-Lung Ventilation in Elderly Patients Undergoing Thoracotomy. Med Sci Monit 2020, 26:e921417.
Pu J, Liu Z, Yang L, Wang Y, Jiang J: Applications of pressure control ventilation volume guaranteed during one-lung ventilation in thoracic surgery. INT J CLIN EXP MED 2014, 7(4):1094-1098.
Song SY, Jung JY, Cho MS, Kim JH, Ryu TH, Kim BI: Volume-controlled versus pressure-controlled ventilation-volume guaranteed mode during one-lung ventilation. Korean J Anesthesiol 2014, 67(4):258-263.
Messina A, Montagnini C, Cammarota G, Giuliani F, Muratore L, Baggiani M, Bennett V, Della CF, Navalesi P, Cecconi M: Assessment of Fluid Responsiveness in Prone Neurosurgical Patients Undergoing Protective Ventilation: Role of Dynamic Indices, Tidal Volume Challenge, and End-Expiratory Occlusion Test. ANESTH ANALG 2020, 130(3):752-761.
Reuter DA, Bayerlein J, Goepfert MS, Weis FC, Kilger E, Lamm P, Goetz AE: Influence of tidal volume on left ventricular stroke volume variation measured by pulse contour analysis in mechanically ventilated patients. Intensive Care Med 2003, 29(3):476-480.
Charron C, Fessenmeyer C, Cosson C, Mazoit JX, Hebert JL, Benhamou D, Edouard AR: The influence of tidal volume on the dynamic variables of fluid responsiveness in critically ill patients. ANESTH ANALG 2006, 102(5):1511-1517.
Gattinoni L, Chiumello D, Carlesso E, Valenza F: Bench-to-bedside review: chest wall elastance in acute lung injury/acute respiratory distress syndrome patients. CRIT CARE 2004, 8(5):350-355.
Lansdorp B, Hofhuizen C, van Lavieren M, van Swieten H, Lemson J, van Putten MJ, van der Hoeven JG, Pickkers P: Mechanical ventilation-induced intrathoracic pressure distribution and heart-lung interactions*. CRIT CARE MED 2014, 42(9):1983-1990.

STROBEchecklist.docx

Download PDF

Version 1

posted

You are reading this latest preprint version

Assessment of Fluid Responsiveness After Tidal Volume Challenge During Pressure-Controlled Ventilation Volume Guaranteed: An observational study

Status:

Version 1

Abstract

Figures

1. Background

2. Methods

2.1 General information

2.2 Perioperative management

2.3. Hemodynamic and Respiratory monitoring and Study Protocol

2.4. Sample size and statistical analyses

3. Results

3.1. Preoperative characteristics

3.2. Effect of TVC and FC administration

3.3. Prediction of Fluid Responsiveness

3.4. Linear Correlation

4. Discussion

5. Conclusions

Abbreviations

Declarations

Ethics approval and consent to participate

Consent for publication

Availability of data and materials

Conflict of interest

Funding

Contributions

Acknowledgment

References

Supplementary Files

Status:

Version 1