Cardiac cycle efficiency and dicrotic pressure variations: new parameters for fluid therapy An observational study

Reliability of pulse pressure and stroke volume variation in assessing fluid responsiveness in the operating room: a metanalysis and a metaregression

BACKGROUND

Pulse pressure and stroke volume variation (PPV and SVV) have been widely used in surgical patients as predictors of fluid challenge (FC) response. Several factors may affect the reliability of these indices in predicting fluid responsiveness, such as the position of the patient, the use of laparoscopy and the opening of the abdomen or the chest, combined FC characteristics, the tidal volume (Vt) and the type of anesthesia.

METHODS

Systematic review and metanalysis of PPV and SVV use in surgical adult patients. The QUADAS-2 scale was used to assess the risk of bias of included studies. We adopted a metanalysis pooling of aggregate data from 5 subgroups of studies with random effects models using the common-effect inverse variance model. The area under the curve (AUC) of pooled receiving operating characteristics (ROC) curves was reported. A metaregression was performed using FC type, volume, and rate as independent variables.

RESULTS

We selected 59 studies enrolling 2,947 patients, with a median of fluid responders of 55% (46-63). The pooled AUC for the PPV was 0.77 (0.73-0.80), with a mean threshold of 10.8 (10.6-11.0). The pooled AUC for the SVV was 0.76 (0.72-0.80), with a mean threshold of 12.1 (11.6-12.7); 19 studies (32.2%) reported the grey zone of PPV or SVV, with a median of 56% (40-62) and 57% (46-83) of patients included, respectively. In the different subgroups, the AUC and the best thresholds ranged from 0.69 and 0.81 and from 6.9 to 11.5% for the PPV, and from 0.73 to 0.79 and 9.9 to 10.8% for the SVV. A high Vt and the choice of colloids positively impacted on PPV performance, especially among patients with closed chest and abdomen, or in prone position.

CONCLUSION

The overall performance of PPV and SVV in operating room in predicting fluid responsiveness is moderate, ranging close to an AUC of 0.80 only some subgroups of surgical patients. The grey zone of these dynamic indices is wide and should be carefully considered during the assessment of fluid responsiveness. A high Vt and the choice of colloids for the FC are factors potentially influencing PPV reliability.

TRIAL REGISTRATION

PROSPERO (CRD42022379120), December 2022. https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=379120.

Novel parameters for predicting fluid responsiveness during the mini fluid challenge and ability of the cardiac power index: an observational cohort study

Background/aim

The percentage change in the stroke volume index (SVI) due to the mini fluid challenge (MFC) (MFC-ΔSVI%) is used commonly in daily practice. However, up to 20% of patients remain in the gray zone of this variable. Thus, it was aimed to compare the MFC-ΔSVI% and the percentage change in the cardiac power index (CPI) due to the MFC (MFC-ΔCPI%) with the baseline values of the pulse pressure variation (PPV) and stroke volume variation (SVV) in terms of their abilities to predict fluid responsiveness.

Materials and methods

The SVI, CPI, SVV, and PPV were recorded before 100 mL of isotonic saline was infused (MFC), after MFC was completed, and after an additional 400 mL of isotonic saline was infused to complete 500 mL of fluid loading (FL). Patients whose SVI increased more than 15% after the FL were defined as fluid responders.

Results

Sixty-seven patients completed the study and 35 (52%) of them were responders.The areas under the receiver operating characteristics curves for the MFC-ΔSVI% and MFC-ΔCPI% (0.94; 95% CI: 0.86-0.99 and 0.89; 95% CI: 0.79-0.95, respectively) were significantly higher than those for the SVV and PPV (0.63; 95% CI: 0.50-0.75 and 0.55; 95% CI: 0.42-0.67, respectively) (p < 0.001 for all of the comparisons). The gray zone analysis revealed that the MFC-ΔSVI% values of 12 patients were in the gray zone. Of the 12, the MFC-ΔCPI% values of 7 patients were outside of the gray zone.

Conclusion

Fluid responsiveness can be predicted more accurately using the MFC-ΔSVI% and MFC-ΔCPI% than using the SVV and PPV. Additionally, concomitant use of the MFC-ΔSVI% and MFC-ΔCPI% is recommended, as this approach diminishes the number of patients in the gray zone.

Variations in Microcirculatory and Hemodynamic Parameters during Oncological Demolitive-Reconstructive Head and Neck Surgery: A Protocol for an Observational Study

(1) Background: Oncological demolitive-reconstructive surgeries in the head and neck region cause significant stress on patients' biohumoural, cardiac, and vascular systems, leading to disturbances in macrocirculatory and microcirculatory parameters. Traditional monitoring addresses the symptoms, but not the underlying cause. Microcirculatory assessments complement macrocirculatory monitoring, and bladder-catheter-based technology offers a better representation of central microcirculation. Flap reconstruction surgeries involve demolitive and reconstructive phases, requiring optimal tissue perfusion. The literature lacks a consensus on macro-microcirculation coupling, and there is no agreement on the use of vasopressors during head and neck surgeries. Evidence-based guidelines are lacking, resulting in variations in vasopressor administration. (2) Methods: This is a 12-month observational, prospective study conducted in a single center. It aims to evaluate the impact of macro-microcirculation coupling on clinical complications in head and neck surgery. All consecutive patients undergoing oncologic surgery requiring flap reconstruction and meeting the inclusion criteria will be enrolled. The study will utilize standard hemodynamic monitoring and bladder catheterization for measuring urine output and temperature. (3) Conclusions: The study aims to evaluate the coupling of macro- and microcirculation in head and neck surgeries, assess hemodynamic parameters and microcirculatory changes, and investigate their association with postoperative complications. The results can enhance patient care and surgical outcomes.

Phenotypes of hemodynamic response to fluid challenge during anesthesia: a cluster analysis

BACKGROUND

The fluid challenge (FC) response is usually evaluated as binary, which may be inadequate to describe the complex interactions between heart function and vascular tone response after fluid administration. We applied a clustering approach to assess the different phenotypes of cardiovascular responses to FC administration, considering the associations of all the baseline variables potentially influencing pressure and flow response to a FC. Secondarily, we evaluated the reliability of baseline hemodynamic variables in discriminating fluid responsiveness, which is considered the standard approach at the bedside.

METHODS

Five merged datasets from elective surgical patients receiving a FC dose ≥4 mL/kg, infused over 10 minutes. In a principal component approach, hierarchical clustering was used to define hemodynamic phenotypes of response to FC administration. Hierarchical cluster analysis with Ward linkage was carried out to define similar patient groups using the Gower distance for the mixed combination of continuous and categorical variables. No a priori criteria of fluid responsiveness were applied. The area (AUC) under the pre-FC variables' receiver operating characteristic curves (ROC) was also built to predict fluid responsiveness, defined as SVI ≥10% after FC.

RESULTS

We analyzed 223 patients. The cluster analysis identified three hemodynamic clusters of patients: cluster 1 (98 patients, 44.0%) showed an average increase of mean arterial pressure (MAP) and Stroke Volume Index (SVI) of 17.3% (11.9-23.1) and 13.1% (0.5-23.4) at the end of FC, respectively. These patients showed baseline flow and pressure variables slightly below physiological ranges, with high pulse pressure variation (PPV). Cluster 2 (68 patients, 30.5%) showed no increase of MAP and SVI at the end of FC. These patients showed baseline flow and pressure variables within physiological ranges, with low hear rate (HR) and PPV. Cluster 3 (57 patients, 25.5%) showed no MAP increase and an SVI increase of 13.1 (2.1-19.6). These patients showed baseline pressure variables within physiological ranges, low flow variables associated to high HR and PPV. The pulse pressure variation (PPV) showed an AUC of 0.82 (0.03), with a grey zone ranging from 6% to 12%, including 86 (38.5%) patients.

CONCLUSIONS

Clustering analysis identified three hemodynamic clusters with different response phenotypes to FC. This promising approach may enhance the ability to detect fluid responsiveness at the bedside, by considering the specific association of parameters and not the presence of a single one, such as the PPV. In fact, in our cohort the reliability of the PPV was limited, showing high sensibility and specificity only above 12% and below 6%, respectively, and a grey zone including 38.5% of patients.

Prediction of fluid responsiveness by dynamic preload parameters in children undergoing thoracoscopic surgery with one-lung ventilation - A prospective observational study

Optimal perioperative fluid management is essential for reducing complications in children undergoing thoracoscopic surgery. The study aimed to assess the performance of 2 dynamic preload parameters - pulse pressure variation (PPV) and stroke volume variation (SVV)- either used alone or combined into a multivariable regression model for predicting fluid responsiveness in children undergoing video-assisted thoracoscopic surgery with one-lung ventilation. Children aged 1 to 6 years old undergoing video-assisted pulmonary segmentectomy or lobectomy were enrolled. Volume loading with 5 mL/kg of hydroxyethyl starch was administered over 15 minutes after establishment of artificial pneumothorax. PPV, SVV, cardiac index, cardiac cycle efficiency, and the difference between systolic blood pressure and dicrotic pressure were recorded using the pressure recording analytical method before and after volume loading. Patients with an elevation in cardiac index greater than 10% were defined as responders, and the remaining patients were nonresponders. Of 40 children, 36 were included in the final analysis, containing 13 responders and 23 nonresponders. SVV had an accuracy of 74% (95% confidence interval, 55-93%) for predicting fluid responsiveness, and a best cutoff of 22% showed a sensitivity of 62% and a specificity of 96%. PPV was incapable of discriminating responders from nonresponders. The multivariate regression model did not perform better than SVV alone. We found PPV failed to predict fluid responsiveness, while SVV predicted fluid responsiveness reasonably in the present context. There was no enhancement in predictivity accuracy with multivariable regression models. The accuracy of these approaches was limited, and more discriminative methods need to be found.

Pressure response to fluid challenge administration in hypotensive surgical patients: a post-hoc pharmacodynamic analysis of five datasets

In this study we evaluated the effect of fluid challenge (FC) administration in elective surgical patients with low or normal blood pressure. Secondarily, we appraised the pharmacodynamic effect of FC in normotensive and hypotensive patients. We assessed five merged datasets of patients with a baseline mean arterial pressure (MAP) above or below 65 mmHg and assessed the changes of systolic, diastolic, mean and dicrotic arterial pressures, dynamic indexes of fluid responsiveness and arterial elastance over a 10-min infusion. The hemodynamic effect was assessed by considering the net area under the curve (AUC), the maximal percentage difference from baseline (d_max), the time when the maximal value was observed (t_max) and change from baseline at 5-min (d₅) after FC end. A stroke volume index increase > 10% with respect to the baseline value after FC administration indicated fluid response. Two hundred-seventeen patients were analysed [102 (47.0%) fluid responders]. On average, FC restored a MAP [Formula: see text] 65 mmHg after 5 min. The AUCs and the d_max of pressure variables and arterial elastance of hypotensive patients were all significantly greater than normotensive patients. Pressure variables and arterial elastance changes in the hypotensive group were all significantly higher at d₅ as compared to the normotensive group. In hypotensive patients, FC restores a MAP [Formula: see text] 65 mmHg after 5 min from infusion start. The hemodynamic profile of FC in hypotensive and normotensive patients is different; both the magnitude of pressure augmentation and duration is greater in the hypotensive group.

Multivariable haemodynamic approach to predict the fluid challenge response: A multicentre cohort study

BACKGROUND

Beat-to-beat stroke volume (SV) results from the interplay between left ventricular function and arterial load. Fluid challenge induces time-dependent responses in cardiac performance and peripheral vascular and capillary characteristics.

OBJECTIVE

To assess whether analysis of the determinants of the haemodynamic response during fluid challenge can predict the final response at 10 and 30 min.

DESIGN

Observational multicentric cohort study.

SETTING

Three university ICUs.

PATIENTS

85 ICU patients with acute circulatory failure diagnosed within the first 48 h of admission.

INTERVENTION(S)

The fluid challenge consisted of 500 ml of Ringer's solution infused over 10 min. A SV index increase at least 10% indicated fluid responsiveness.

MAIN OUTCOME MEASURES

The SV, pulse pressure variation (PPV), arterial elastance, the systolic-dicrotic pressure difference (SAP-Pdic) and cardiac cycle efficiency (CCE) were measured at baseline, 1, 2, 3, 4, 5, 10, 15 and 30 min after the start of the fluid challenge. All haemodynamic data were submitted to a univariable logistic regression model and a multivariable analysis was then performed using the significant variables given by univariable analysis.

RESULTS

The multivariable model including baseline PPV, and the changes of arterial elastance at 1 min and of the CCE and SAP-Pdic at 5 min when compared with their baseline values, correctly classified 80.5% of responders and 90.7% of nonresponders at 10 min. For the response 30 min after starting the fluid challenge, the model, including the changes of PPV, CCE, SAP-Pdic at 5 min and of arterial elastance at 10 min compared with their baseline values, correctly identified 93.3% of responders and 91.4% of nonresponders.

CONCLUSION

In a selection of mixed ICU patients, a statistical model based on a multivariable analysis of the changes of PPV, CCE, arterial elastance and SAP-Pdic, with respect to baseline values, reliably predicts both the early and the late response to a standardised fluid challenge.

TRIAL REGISTRATION

ACTRN12617000076370.

Accuracy of a multiparametric score based on pulse wave analysis for prediction of fluid responsiveness: ancillary analysis of an observational study

Purpose

The pressure recording analytical method (PRAM) monitor is a non-invasive pulse contour cardiac output (CO) device that cannot be considered interchangeable with the gold standard for CO estimation. It, however, generates additional hemodynamic indices that need to be evaluated. Our objective was to investigate the performance of a multiparametric predictive score based on a combination of several parameters generated by the PRAM monitor to predict fluid responsiveness.

Methods

Secondary analysis of a prospective observational study from April 2016 to December 2017 in two French teaching hospitals. We included critically ill patients who were monitored by esophageal Doppler monitoring and an invasive arterial line, and received a 250–500 mL crystalloid fluid challenge. The main outcome measure was the predictive score discrimination evaluated by the area under the receiver operating characteristics curve.

Results

The three baseline PRAM-derived parameters associated with fluid responsiveness in univariate analysis were pulse pressure variation, cardiac cycle efficiency, and arterial elastance (P < 0.01, P = 0.03, and P < 0.01, respectively). The median [interquartile range] predictive score, calculated after discretization of these parameters according to their optimal threshold value was 3 [2–3] in fluid responders and 1 [1–2] in fluid non-responders, respectively (P < 0.001). The area under the curve of the predictive score was 0.807 (95% confidence interval, 0.662 to 0.909; P < 0.001).

Conclusion

A multiparametric score combining three parameters generated by the PRAM monitor can predict fluid responsiveness with good positive and negative predictive values in intensive care unit patients.

Electronic supplementary material

The online version of this article (10.1007/s12630-020-01736-y) contains supplementary material, which is available to authorized users.