Define Fluid Responsiveness Research Articles

The effects of respiratory rate and tidal volume on pulse pressure variation in healthy lungs–a generalized additive model approach may help overcome limitations

Pulse pressure variation (PPV) is a well-established method for predicting fluid responsiveness in mechanically ventilated patients. The predictive accuracy is, however, disputed for ventilation with low tidal volume (VT) or low heart-rate-to-respiratory-rate ratio (HR/RR). We investigated the effects of VT and RR on PPV and on PPV’s ability to predict fluid responsiveness. We included patients scheduled for open abdominal surgery. Prior to a 250 ml fluid bolus, we ventilated patients with combinations of VT from 4 to 10 ml kg−1 and RR from 10 to 31 min−1. For each of 10 RR-VT combinations, PPV was derived using both a classic approach and a generalized additive model (GAM) approach. The stroke volume (SV) response to fluid was evaluated using uncalibrated pulse contour analysis. An SV increase > 10% defined fluid responsiveness. Fifty of 52 included patients received a fluid bolus. Ten were fluid responders. For all ventilator settings, fluid responsiveness prediction with PPV was inconclusive with point estimates for the area under the receiver operating characteristics curve between 0.62 and 0.82. Both PPV measures were nearly proportional to VT. Higher RR was associated with lower PPV. Classically derived PPV was affected more by RR than GAM-derived PPV. Correcting PPV for VT could improve PPV’s predictive utility. Low HR/RR has limited effect on GAM-derived PPV, indicating that the low HR/RR limitation is related to how PPV is calculated. We did not demonstrate any benefit of GAM-derived PPV in predicting fluid responsiveness.Trial registration: ClinicalTrials.gov, reg. March 6, 2020, NCT04298931.

Passive leg raising test induced changes in plethysmographic variability index to assess fluid responsiveness in critically ill mechanically ventilated patients with acute circulatory failure

BackgroundPassive leg raising (PLR) reliably predicts fluid responsiveness but requires a real-time cardiac index (CI) measurement or the presence of an invasive arterial line to achieve this effect. The plethysmographic variability index (PVI), an automatic measurement of the respiratory variation of the perfusion index, is non-invasive and continuously displayed on the pulse oximeter device. We tested whether PLR-induced changes in PVI (ΔPVIPLR) could accurately predict fluid responsiveness in mechanically ventilated patients with acute circulatory failure. MethodsThis was a secondary analysis of an observational prospective study. We included 29 mechanically ventilated patients with acute circulatory failure in this study. We measured PVI (Radical-7 device; Masimo Corp., Irvine, CA) and CI (Echocardiography) before and during a PLR test and before and after volume expansion of 500 mL of crystalloid solution. A volume expansion-induced increase in CI of >15% defined fluid responsiveness. To investigate whether ΔPVIPLR can predict fluid responsiveness, we determined areas under the receiver operating characteristic curves (AUROCs) and gray zones for ΔPVIPLR. ResultsOf the 29 patients, 27 (93.1%) received norepinephrine. The median tidal volume was 7.0 [IQR: 6.6–7.6] mL/kg ideal body weight. Nineteen patients (65.5%) were classified as fluid responders (increase in CI > 15% after volume expansion). Relative ΔPVIPLR accurately predicted fluid responsiveness with an AUROC of 0.89 (95%CI: 0.72–0.98, p < 0.001). A decrease in PVI ≤ −24.1% induced by PLR detected fluid responsiveness with a sensitivity of 95% (95%CI: 74–100%) and a specificity of 80% (95%CI: 44–97%). Gray zone was acceptable, including 13.8% of patients. The correlations between the relative ΔPVIPLR and changes in CI induced by PLR and by volume expansion were significant (r = −0.58, p < 0.001, and r = −0.65, p < 0.001; respectively). ConclusionsIn sedated and mechanically ventilated ICU patients with acute circulatory failure, PLR-induced changes in PVI accurately predict fluid responsiveness with an acceptable gray zone. Trial registrationClinicalTrials.govNCT03225378.

PASSIVE LEG RAISING-INDUCED CHANGES IN PEAK VELOCITY VARIATION OF LEFT VENTRICULAR OUTFLOW TRACT TO PREDICT FLUID RESPONSIVENESS IN POSTOPERATIVE CRITICALLY ILL ELDERLY PATIENTS.

Background : Accurate prediction of fluid responsiveness is important for postoperative critically ill elderly patients. The objective of this study was to evaluate the predictive values of peak velocity variation (ΔVpeak) and passive leg raising (PLR)-induced changes in ΔVpeak (ΔVpeak PLR ) of the left ventricular outflow tract to predict fluid responsiveness in postoperative critically ill elderly patients. Method : Seventy-two postoperative elderly patients with acute circulatory failure who were mechanically ventilated with sinus rhythm were enrolled in our study. Pulse pressure variation (PPV), ΔVpeak, and stroke volume were collected at baseline and after PLR. An increase of >10% in stroke volume after PLR defined fluid responsiveness. Receiver operating characteristic curves and gray zones were constructed to assess the ability of ΔVpeak and ΔVpeak PLR to predict fluid responsiveness. Results : Thirty-two patients were fluid responders. The area under the receiver operating characteristic curves (AUC) for baseline PPV and ΔVpeak to predict fluid responsiveness was 0.768 (95% confidence interval [CI], 0.653-0.859; P < 0.001) and 0.899 (95% CI, 0.805-0.958; P < 0.001) with gray zones of 7.63% to 12.66% that included 41 patients (56.9%) and 9.92% to 13.46% that included 28 patients (38.9%). ΔPPV PLR predicted fluid responsiveness with an AUC of 0.909 (95% CI, 0.818-0.964; P < 0.001), and the gray zone was 1.49% to 2.93% and included 20 patients (27.8%). ΔVpeak PLR predicted fluid responsiveness with an AUC of 0.944 (95% CI, 0.863-0.984; P < 0.001), and the gray zone was 1.48% to 2.46% and included six patients (8.3%). Conclusions : Passive leg raising-induced changes in peak velocity variation of blood flow in the left ventricular outflow tract accurately predicted fluid responsiveness with a small gray zone in postoperative critically ill elderly patients.

Reliability of stroke volume or pulse pressure variation as dynamic predictors of fluid responsiveness in laparoscopic surgery: a systematic review.

The reliability of stroke volume variation (SVV) and pulse pressure variation (PPV) in predicting fluid responsiveness during laparoscopic surgery remains unclear. We conducted the present systematic review to summarize the current evidence.We reviewed studies that investigated the reliability of SVV and PPV in laparoscopic surgery.Seven studies were included in the final analysis. Two studies demonstrated that the area under the receiver operating characteristic curve (AUROC) for SVV was less than 0.8, and five studies reported that the AUROC was > 0.8. The pooled AUROC for SVV and PPV was more than 0.8 with high heterogeneities between the included studies.Most individual studies have suggested that SVV and PPV are sufficiently reliable for predicting fluid responsiveness during laparoscopic surgery. However, the limited number of patients, varied apparatus used to define fluid responsiveness, diverse definitions of fluid responsiveness, and different fluids used to perform fluid challenges in the included studies render firm conclusions about SVV's and PPV's reliability impossible.

Passive leg raising-induced changes in pulse pressure variation to assess fluid responsiveness in mechanically ventilated patients: a multicentre prospective observational study

BackgroundPassive leg raising-induced changes in cardiac index can be used to predict fluid responsiveness. We investigated whether passive leg raising-induced changes in pulse pressure variation (ΔPPVPLR) can also predict fluid responsiveness in mechanically ventilated patients. MethodsIn this multicentre prospective observational study, we included 270 critically ill patients on mechanical ventilation in whom volume expansion was indicated because of acute circulatory failure. We did not include patients with cardiac arrythmias. Cardiac index and PPV were measured before/during a passive leg raising test and before/after volume expansion. A volume expansion-induced increase in cardiac index of >15% defined fluid responsiveness. To investigate whether ΔPPVPLR can predict fluid responsiveness, we determined areas under the receiver operating characteristic curves (AUROCs) and grey zones for relative and absolute ΔPPVPLR. ResultsOf the 270 patients, 238 (88%) were on controlled mechanical ventilation with no spontaneous breathing activity and 32 (12%) were on pressure support ventilation. The median tidal volume was 7.1 (inter-quartile range [IQR], 6.6–7.6) ml kg−1 ideal body weight. One hundred sixty-four patients (61%) were fluid responders. Relative and absolute ΔPPVPLR predicted fluid responsiveness with an AUROC of 0.92 (95% confidence interval [95% CI], 0.88–0.95; P<0.001) each. The grey zone for relative and absolute ΔPPVPLR included 4.8% and 22.6% of patients, respectively. These results were not affected by ventilatory mode and baseline characteristics (type of shock, centre, vasoactive treatment). ConclusionsPassive leg raising-induced changes in pulse pressure variation accurately predict fluid responsiveness with a small grey zone in critically ill patients on mechanical ventilation. Clinical trial registrationNCT 03225378.

Accuracy of pulse pressure variations for fluid responsiveness prediction in mechanically ventilated patients with biphasic positive airway pressure mode.

The accuracy of pulse pressure variation (PPV) to predict fluid responsiveness using pressure-controlled (PC) instead of volume-controlled modes is under debate. To specifically address this issue, we designed a study to evaluate the accuracy of PPV to predict fluid responsiveness in severe septic patients who were mechanically ventilated with biphasic positive airway pressure (BIPAP) PC-ventilation mode. 45 patients with sepsis or septic shock and who were mechanically ventilated with BIPAP mode and a target tidal volume of 7-8ml/kg were included. PPV was automatically assessed at baseline and after a standard fluid challenge (Ringer's lactate 500ml). A 15% increase in stroke volume (SV) defined fluid responsiveness. The predictive value of PPV was evaluated through a receiver operating characteristic (ROC) curve analysis and "gray zone" statistical approach. 20 (44%) patients were considered fluid responders. We identified a significant relationship between PPV decrease after volume expansion and SV increase (spearman ρ = -0.5, p < 0.001). The area under ROC curve for PPV was 0.71 (95%CI 0.56-0.87, p = 0.007). The best cut-off (based on Youden's index) was 8%, with a sensitivity of 80% and specificity of 60%. Using a gray zone approach, we identified that PPV values comprised between 5 and 15% do not allow a reliable fluid responsiveness prediction. In critically ill septic patients ventilated under BIPAP mode, PPV appears to be an accurate method for fluid responsiveness prediction. However, PPV values comprised between 5 and 15% constitute a gray zone that does not allow a reliable fluid responsiveness prediction.

Central venous-to-arterial PCO2 difference as a marker to identify fluid responsiveness in septic shock

Defining the hemodynamic response to volume therapy is integral to managing critically ill patients with acute circulatory failure, especially in the absence of cardiac index (CI) measurement. This study aimed at investigating whether changes in central venous-to-arterial CO2 difference (Δ-ΔPCO2) and central venous oxygen saturation (ΔScvO2) induced by volume expansion (VE) are reliable parameters to define fluid responsiveness in sedated and mechanically ventilated septic patients. We prospectively studied 49 critically ill septic patients in whom VE was indicated because of circulatory failure and clinical indices. CI, ΔPCO2, ScvO2, and oxygen consumption (VO2) were measured before and after VE. Responders were defined as patients with a > 10% increase in CI (transpulmonary thermodilution) after VE. We calculated areas under the receiver operating characteristic curves (AUCs) for Δ-ΔPCO2, ΔScvO2, and changes in CI (ΔCI) after VE in the whole population and in the subgroup of patients with an increase in VO2 (ΔVO2) ≤ 10% after VE (oxygen-supply independency). Twenty-five patients were fluid responders. In the whole population, Δ-ΔPCO2 and ΔScvO2 were significantly correlated with ΔCI after VE (r = − 0.30, p = 0.03 and r = 0.42, p = 0.003, respectively). The AUCs for Δ-ΔPCO2 and ΔScvO2 to define fluid responsiveness (increase in CI > 10% after VE) were 0.76 (p < 0.001) and 0.68 (p = 0.02), respectively. In patients with ΔVO2 ≤ 10% (n = 36) after VE, the correlation between ΔScvO2 and ΔCI was 0.62 (p < 0.001), and between Δ-ΔPCO2 and ΔCI was − 0.47 (p = 0.004). The AUCs for Δ-ΔPCO2 and ΔScvO2 were 0.83 (p < 0.001) and 0.73 (p = 0.006), respectively. In these patients, Δ-ΔPCO2 ≤ -37.5% after VE allowed the categorization between responders and non-responders with a positive predictive value of 100% and a negative predictive value of 60%. In sedated and mechanically ventilated septic patients with no signs of tissue hypoxia (oxygen-supply independency), Δ-ΔPCO2 is a reliable parameter to define fluid responsiveness.

Machine learning methods to improve bedside fluid responsiveness prediction in severe sepsis or septic shock: an observational study

BackgroundPassive leg raising (PLR) predicts fluid responsiveness in critical illness, although restrictions in mobilising patients often preclude this haemodynamic challenge being used. We investigated whether machine learning applied on transthoracic echocardiography (TTE) data might be used as a tool for predicting fluid responsiveness in critically ill patients. MethodsWe studied, 100 critically ill patients (mean age: 62 yr [standard deviation: 14]) with severe sepsis or septic shock prospectively over 24 months. Transthoracic echocardiography measurements were performed at baseline, after PLR, and before and after a standardised fluid challenge in learning and test populations (n=50 patients each). A 15% increase in stroke volume defined fluid responsiveness. The machine learning methods used were classification and regression tree (CART), partial least-squares regression (PLS), neural network (NNET), and linear discriminant analysis (LDA). Each method was applied offline to determine whether fluid responsiveness may be predicted from left and right cardiac ventricular physiological changes detected by cardiac ultrasound. Predictive values for fluid responsiveness were compared by receiver operating characteristics (area under the curve [AUC]; mean [95% confidence intervals]). ResultsIn the learning sample, the AUC values were PLR 0.76 (0.62–0.89), CART 0.83 (0.73–0.94), PLS 0.97 (0.93–1), NNET 0.93 (0.85–1), and LDA 0.90 (0.81–0.98). In the test sample, the AUC values were PLR 0.77 (0.64–0.91), CART 0.68 (0.54–0.81), PLS 0.83 (0.71–0.96), NNET 0.83 (0.71–0.94), and LDA 0.85 (0.74–0.96) respectively. The PLS model identified inferior vena cava collapsibility, velocity–time integral, S-wave, E/Ea ratio, and E-wave as key echocardiographic parameters. ConclusionsMachine learning generated several models for predicting fluid responsiveness that were comparable with the haemodynamic response to PLR.

Choice of assessment time after fluid challenge in patients with septic shock

To explore the short-term hemodynamic change of fluid challenge (FC) with crystalloid or colloid and define fluid responsiveness at the optimal time in patients with septic shock. A prospective observational study was conducted. Septic shock patients monitored with pulmonary catheters admitted to medical intensive care unit (ICU) of the Peking Union Medical College Hospital from July 2016 to December 2018 were enrolled. All included patients received FC and were divided into two groups according to the type of fluid used, i.e. crystalloid group (normal saline for 500 mL) and colloid group (4% succinyl gelatin for 500 mL). The choice of fluid type was decided by the attending physician. Hemodynamic variables were measured at baseline, and 0 (immediately), 10, 30, 45, 60, 90, 120 minutes after FC, included cardiac index (CI), heart rate (HR), mean artery pressure (MAP), central venous pressure (CVP) and pulmonary arterial wedge pressure (PAWP). Fluid responsiveness was defined as CI increased by more than 10% after FC. The data were analyzed by repeated measurements of variance between the two groups as well as responders and nonresponders. Forty patients were included, 20 cases each in colloid group and crystalloid group; of whom 26 were fluid responders with 12 of colloid group and 14 of crystalloid group. Of the 14 nonresponders, 8 were of colloid group and 6 of crystalloid group. (1) Compared with before FC, CI (mL×s-1×m-2) was significantly increased in crystalloid and colloid groups after FC (71.7±16.7 vs. 65.0±16.7, 68.3±25.0 vs. 63.3±23.3, both P < 0.05). In the colloid group, volume expansion increased the CI to maximum (76.7±18.3) at 30 minutes after FC, at 120 minutes after FC, a significantly higher CI (70.0±16.7) was also observed (P < 0.05), an increased in CI ≥ 10% was observed at 60 minutes after FC. In the crystalloid group, CI was increased to maximum at 10 minutes (73.3±28.3) and decreased to baseline at 60 minutes, an increased in CI ≥ 10% was also observed at 10 minutes after FC. In addition, there was no significant difference in CI changes between colloidal group and crystalloid group at different time points after FC. (2) CI did not change over time in nonresponders groups, whereas in responders CI increased parallelly to that in both crystalloid and colloid groups over time. However, an increased in CI ≥ 10% was observed through the 120 minutes after FC in responders of colloid group compared with that of at 30 minutes after FC in crystalloid group. There was significant difference in CI changes between colloidal group and crystalloid group at 30, 45, 60, 90 minutes after FC (mL×s-1×m-2: 18.3±3.3 vs. 8.3±1.7, 18.3±3.3 vs. 5.0±1.7, 13.3±1.7 vs. 3.3±1.7, 11.7±3.3 vs. 3.3±1.7, all P < 0.05). (3) The maximal values of CVP and PAWP were observed at the end of FC. In colloid group, both the two variables were notably higher than that before FC over 120 minutes compared with that of only at 10 minutes in crystalloid group. The MAP in colloid increased to maximum immediately at the end of FC and decreased to baseline at 45 minutes, however, the MAP in crystalloid group and HR of both groups showed no differences over 120 minutes. Hemodynamic changes were significantly different between crystalloid and colloid after FC in patients with septic shock. Therefore, the timing of fluid responsiveness assessment should be different individually. The assessment time of colloid group may be prolonged to 30 minutes after FC while that of crystal group can be at 10 minute after FC.

The predictability of dynamic preload indices depends on the volume of fluid challenge

This study was designed to assess the association between volume of fluid challenge (FC) and predictability of respiratory variation of stroke volume (ΔrespSV) in the operating theater.Patients undergoing intermediate/high-risk surgery and monitored by esophageal Doppler monitoring (EDM) were prospectively included. All patients were under general anesthesia and mechanically ventilated. Exclusion criteria were frequent ectopic beats or preoperative arrhythmia, right ventricular failure, and spontaneous breathing. Hemodynamic parameters and esophageal Doppler indices (SV, cardiac output, ΔrespSV) were collected before, after infusion of 250 mL, and after infusion of 500 mL of crystalloid solution. Responders were defined by a >15% increase of stroke volume after FC at each step.After infusion of a 250 mL FC, 41 patients (32%) were classified as fluid responders (R250). After infusion of a 500 mL FC, 80 patients (63%) were classified as fluid responders (R500). The predictability of ΔrespSV was fair with an area under the curve (AUC) of 0.79 (95% CI 0.71–0.86, P < .001) to predict fluid responsiveness with a 250 mL FC. With an AUC of 0.94 (95% CI 0.88–0.97, P < .0001), ΔrespSV presented an excellent ability to predict fluid responsiveness with a 500-mL FC.Predictability of ΔrespSV changed with the volume of fluid infused to assess fluid responsiveness. The accuracy of ΔrespSV was higher with 500 mL than with 250 mL. Bedside studies evaluating the predictability of dynamic preload indices should define fluid responsiveness as a >15% increase of SV in response to a 500-mL FC.

Predictive value of central venous-to-arterial carbon dioxide partial pressure difference for fluid responsiveness in septic shock patients: a prospective clinical study

To evaluate the accuracy of central venous-to-arterial carbon dioxide partial pressure difference (Pcv-aCO2) before and after rapid rehydration test (fluid challenge) in predicting the fluid responsiveness in patients with septic shock. A prospective observation was conducted. Forty septic shock patients admitted to medical intensive care unit (ICU) of Peking Union Medical College Hospital from October 2015 to June 2017 were enrolled. All of the patients received fluid challenge in the presence of invasive hemodynamic monitoring. Heart rate (HR), blood pressure, cardiac index (CI), Pcv-aCO2 and other physiological variables were recorded at 10 minutes before and immediately after fluid challenge. Fluid responsiveness was defined as an increase in CI greater than 10% after fluid challenge, whereas fluid non-responsiveness was defined as no increase or increase in CI less than 10%. The correlation between Pcv-aCO2 and CI was explored by Pearson correlation analysis. Receiver operating characteristic (ROC) curves were established to evaluate the discriminatory abilities of baseline and the changes after fluid challenge in Pcv-aCO2 and other physiological variables to define the fluid responsiveness. The patients were separated into two groups according to the initial value of Pcv-aCO2. The cut-off value of 6 mmHg (1 mmHg = 0.133 kPa) was chosen according to previous studies. The discriminatory abilities of baseline and the change in Pcv-aCO2 (ΔPcv-aCO2) were assessed in each group. A total of 40 patients were finally included in this study. Twenty-two patients responded to the fluid challenge (responders). Eighteen patients were fluid non-responders. There was no significant difference in baseline physiological variable between the two groups. Fluid challenge could increase CI and blood pressure significantly, decrease HR notably and had no effect on Pcv-aCO2 in fluid responders. In non-responders, blood pressure was increased significantly and CI, HR, Pcv-aCO2 showed no change after fluid challenge. Pcv-aCO2 was comparable in responders and non-responders. In 40 patients, CI and Pcv-aCO2 was inversely correlated before fluid challenge (r = -0.391, P = 0.012) and the correlation between them weakened after fluid challenge (r = -0.301, P = 0.059). There was no significant correlation between the changes in CI and Pcv-aCO2 after fluid challenge (r = -0.164, P = 0.312). The baseline Pcv-aCO2 and ΔPcv-aCO2 could not discriminate between responders and non-responders, with the area under ROC curve (AUC) of 0.50 [95% confidence interval (95%CI) = 0.32-0.69] and 0.51 (95%CI = 0.33-0.70), respectively. HR and blood pressure before fluid challenge and their changes after fluid challenge showed very poor discriminative performances. Before fluid challenge, 16 patients had a Pcv-aCO2 > 6 mmHg. Their mean CI was significantly lower and Pcv-aCO2 was significantly higher than that in 24 patients whose Pcv-aCO2 ≤ 6 mmHg [n = 24; CI (mL×s-1×m-2): 48.3±11.7 vs. 65.0±18.3, P < 0.01; Pcv-aCO2 (mmHg): 8.4±1.9 vs. 2.9±2.8, P < 0.01]. Pcv-aCO2 was decreased significantly after fluid challenge in patients with an initial Pcv-aCO2 > 6 mmHg and their ΔPcv-aCO2 was notably different as compared with the patients whose baseline Pcv-aCO2 ≤ 6 mmHg (mmHg: -3.8±3.4 vs. 0.9±2.9, P < 0.01). 68.8% (11/16) patients responded to the fluid challenge in patients with an initial Pcv-aCO2 > 6 mmHg. The AUC of the baseline Pcv-aCO2 and ΔPcv-aCO2 to define fluid responsiveness was 0.85 (95%CI = 0.66-1.00) and 0.84 (95%CI = 0.63-1.00), respectively, and the positive predictive value was 1 when the cut-off value was 8.0 mmHg and -4.2 mmHg, respectively. 45.8% (11/24) patients responded to the fluid challenge in patients whose baseline Pcv-aCO2 ≤ 6 mmHg. There was no predictive value of baseline Pcv-aCO2 and ΔPcv-aCO2 on fluid responsiveness. Pcv-aCO2 and its change cannot serve as a surrogate of the change in cardiac output to define the response to fluid challenge in septic shock patients whose baseline Pcv-aCO2 ≤ 6 mmHg, while the predictive values of baseline Pcv-aCO2 and the change in Pcv-aCO2 are presented in patients with the initial value of Pcv-aCO2 > 6 mmHg. Clinical Trials, NCT01941472.

Changes of central venous oxygen saturation define fluid responsiveness in patients with septic shock: A prospective observational study

PurposeTo evaluate whether the changes of central venous oxygen saturation (Scvo2) after fluid challenge can define fluid responsiveness in patients with septic shock. MethodsIn this prospective observational study, septic shock patients with invasive cardiac output monitoring requiring fluid challenge were included. Cardiac index (CI) and Scvo2 were measured before and after fluid challenges. The changes of CI (ΔCI) and the changes of Scvo2 (ΔScvo2) were calculated and analyzed using Pearson correlation. Receiver operating characteristics curve (ROC) analysis was used to classify fluid responders and nonresponders. Area under ROC was calculated. ResultsForty patients were included and 18 patients (45%) were fluid responders. In the responders, CI increased from 3.4±1.1 to 4.4±1.0 L min−1 m−2 and Scvo2 from 69.6%±9.8% to 77.1%±8.9% (both P<.001) after fluid challenge. In the nonresponders, neither CI nor Scvo2 changed (4.1±1.3 vs 4.1±1.3 L min−1 m−2, 71.0%±13.8% vs 70.6%±14.1%, both P>.05). The correlation between ΔScvo2 and ΔCI was significant (r=0.702, P<.001). The area under ROC of ΔScvo2 to define fluid responsiveness was 0.88 (95% confidence interval [95% CI], 0.76-0.99). A ΔScvo2 threshold value of 5.0% discriminated responders from nonresponders with sensitivity of 0.78 (95% CI, 0.52-0.93) and specificity of 0.95 (95% CI, 0.75-1.00). ConclusionsThe changes of Scvo2 correlate with the changes of CI, and the changes of Scvo2 define fluid responsiveness in patients with septic shock.

Using extra systoles to predict fluid responsiveness in cardiothoracic critical care patients.

Fluid responsiveness prediction is an unsettled matter for most critical care patients and new methods relying only on the continuous basic monitoring are desired. It was hypothesized that the post-ectopic beat, which is associated with increased preload, could be analyzed in relation to preceding sinus beats and that the change in cardiac performance (e.g. systolic blood pressure) at the post-ectopic beat could predict fluid responsiveness. Cardiothoracic critical care patients scheduled for a 500ml volume expansion were observed. In the 30min prior to volume expansion, the ECG was analyzed for occurrence of extra systoles preceded by at least 10 sinus beats. Classification variables, were defined as the change in a variable (e.g. systolic blood pressure or pre-ejection period) from the median of 10 preceding sinus beats to extra systolic post-ectopic beat. A stroke volume increase >15% following volume expansion defined fluid responsiveness. Thirty patients were included. The change in systolic blood pressure predicted fluid responsiveness in 24 patients correctly with 83% specificity and 75% sensitivity (optimal threshold: 5% systolic blood pressure increase), receiver operating characteristic (ROC) area: 0.81 (CI [0.64;0.98]). The change in pre-ejection period predicted fluid responsiveness in 22 patients correctly with 67% specificity and 83% sensitivity (optimal threshold: 19ms pre-ejection period decrease), ROC area: 0.81 (CI [0.66;0.96]). Pulse pressure variation had ROC area of 0.57 (CI [0.39;0.75]). Based on standard critical care monitoring, analysis of the extra systolic post-ectopic beat predicts fluid responsiveness in cardiothoracic critical care patients with good accuracy.

Fluid responsiveness predicted by elevation of PEEP in patients with septic shock

The assessment of whether a patient is fluid responsive can be difficult in clinical practice. Invasive filling pressures are inadequate indicators of preload and fluid responsiveness in critically ill patients. Dynamic indices may be unreliable in clinical practice because of arrhythmias or spontaneous breathing efforts. Elevation of positive end-expiratory pressure (PEEP) causes cardiorespiratory interactions, which may produce signs of hypovolaemia. Our aim was to assess whether haemodynamic changes during a short elevation of PEEP would predict fluid responsiveness in patients with septic shock. We performed a prospective observational study in 20 patients with septic shock on mechanical ventilation. We assessed the following changes in haemodynamic variables during a temporary elevation of PEEP from 10 cm H2O to 20 cm H2O during an end-expiratory pause: mean arterial pressure (MAP), systolic arterial pressure, pulse pressure, central venous pressure, pulmonary artery occlusion pressure, left ventricular end diastolic area and aortic velocity-time integral. We defined fluid responsiveness as an increase in cardiac output of 15% to a subsequent fluid challenge. Decrease in MAP related to elevation of PEEP predicted fluid responsiveness (P = 0.003). The best cut-off value of ΔMAP for clinical use was -8%, with a negative predictive value for fluid responsiveness of 100%. In patients with septic shock, the absence of decrease in MAP during an elevation of PEEP may be used to identify patients who will not increase their cardiac output in response to fluid challenge.

Noninvasively derived stroke volume variation by finger volume clamping can reliably predict fluid responsiveness

Background and Goal of Study: Dynamic preload variables derived from the arterial pressure waveform have been shown to accurately predict fluid responsiveness in mechanically ventilated patients. One of these variables, stroke volume variation (SVV), can also be obtained noninvasively by the finger volume clamp method using the Nexfin® device (Edwards Lifesciences BMYE, Amsterdam, Netherlands). In patients undergoing general surgery, we explored the ability of noninvasive SVV to predict fluid responsiveness defined at multiple thresholds. We also studied the limits of the so-called grey zone, indicating the area of doubt.1 Materials and Methods: After local IRB approval, 81 patients undergoing general surgery were included. SVV and stroke volume index (SVI) were measured using the noninvasive volume clamp method (Nexfin®). All patients received a 500 ml colloid bolus for routine clinical care and the attendinganaesthetist was blinded for Nexfin®- derived variables. A minimal increase in Stroke Volume Index (↑SVI) was used to define fluid responsiveness with thresholds of 10, 15, and 20%. Areas under the ROC curve (AUROC) were calculated to assess the ability of SVV to predict fluid responsiveness and to calculate the grey zone limits (i.e. values for which sensitivity and specificity are < 90%). Results and Discussion: Mean (SD) SVI increased from 40 (11) to 45 (10) ml/m². For all thresholds, the number of fluid responders / non-responders, AUROC’s and the associated limits of the grey zone are shown in table 1. Sensitivities and specificities are shown in figure 1. Conclusion: Advanced noninvasive haemodynamic monitoring using the volume clamp method to measure SVV can adequately predict fluid responsiveness in patients undergoing general surgery. Its ability to assess fluid responsiveness is dependent on the intended increase in SVI and improves for higher ↑SVI thresholds. Reference: 1. Cannesson M, et al. Anesthesiology 2011; 115: 231-41

ScvO2 As a Marker to Define Fluid Responsiveness

Definition of the hemodynamic response to volume expansion (VE) could be useful in shocked critically ill patients in absence of cardiac index (CI) measurements. The aim of this study is to evaluate whether central venous oxygen saturation variations (ΔScvO(2)) after VE could be an alternative to classify responders (R) and nonresponders (NR) to volume therapy. A total of 30 patients requiring VE were included in this prospective cohort study, all equipped with radial arterial line and pulmonary artery catheters. CI, mixed venous oxygen saturation (SvO(2)) and ScvO(2) were measured before and after VE. CI, SvO(2), and ScvO(2) changes after volume were analyzed using linear regression. Receiver operating characteristics curve analysis was used to test their ability to distinguish R and NR. ΔScvO(2) and SvO(2) variations after VE (ΔSvO(2)) were significantly correlated with CI changes (ΔCI) after VE (r = 0.67 and r = 0.49, p < 0.001, respectively). A ΔScvO(2) threshold value of 4% allowed the definition of R and NR patients with 86% sensitivity (95%CI; 57-98%) and 81% specificity (95%CI; 54-96%). ScvO2 variations after VE was able to categorize VE efficiently and could be suggested as an alternative marker to define fluid responsiveness in absence of invasive CI measurement.

Response to Letter to the Editor Entitled Central Venous-Arterial Carbon Dioxide Tension Gradient: Another Marker to Define Fluid Responsiveness

The Journal of Trauma: Injury, Infection, and Critical Care 70(4):p 1015-1016, April 2011. | DOI: 10.1097/TA.0b013e31821179cc