Background: Fluid responsiveness prediction with continuously available monitoring is an unsettled matter for the vast majority of critically ill patients, and development of new and reliable methods is desired. We 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. Methods: Critically ill patients were observed when scheduled for a 500-ml volume expansion. The 30-min ECG prior to volume expansion was analyzed for the occurrence of extrasystoles. Classification variables were defined as the change in a variable (e.g., systolic blood pressure or pre-ejection period) from the median of ten preceding sinus beats to extrasystolic post-ectopic beat. A stroke volume increase > 10% following volume expansion defined fluid responsiveness. Results: Twenty-six patients were included. The change in systolic blood pressure predicted fluid responsiveness with receiver operating characteristic (ROC) area 0.79 (CI [0.52:1.00]), specificity 100%, sensitivity 67%, positive predictive value 100%, and negative predictive value 91% (threshold: 5%). The change in pre-ejection period predicted fluid responsiveness with ROC area 0.74 (CI [0.53:0.94]), specificity 78%, sensitivity 67%, positive predictive value 50%, and negative predictive value 88% (threshold 7.5 ms). Conclusions: Based on standard critical care monitoring, analysis of the extrasystolic post-ectopic beat predicts fluid responsiveness in critical care patients with good accuracy. The presented results are considered preliminary proof-of-concept results, and further validation is needed to confirm these preliminary findings.
Hemodynamic monitoring; Fluid responsiveness; Extrasystole; Ectopic beat; Stroke volume; Cardiac output
Electronic supplementary material The online version of this article (10.1186/s40560-018-0324-6) contains supplementary material, which is available to authorized users.
Fluid responsiveness prediction remains an unresolved issue for most ICU patients. Ventilator-induced dynamic variables, such as pulse pressure variation (PPV) or stroke volume variation (SVV), are only optimally reliable in 2–3% of admitted ICU patients [[
Recently, we suggested that an extrasystole could be considered as a preload varying mechanism [[
In a recent study, we showed that the post-ectopic change in the systolic blood pressure (SBP) and pre-ejection period (PEP) predicted fluid responsiveness with good accuracy in postoperative cardiac surgery patients [[
The Regional Ethics Committee, Central Region, Denmark, and the Danish Health and Medicines Authority considered the study design observational. The study was approved by the Danish Data Agency (
Critically ill patients aged 18 years or more admitted to our intensive care unit were observed if a volume expansion of 500 ml crystalloid was scheduled to be infused within 30 min or less on clinical reasons. Patients had been assessed with ultrasonography (Focus Assessed Transthoracic Echocardiography) as part of the clinical decision-making of prescribing a volume expansion (including crude assessment of left ventricular function by eyeballing). Patients with arrhythmia precluding the use of the extrasystoles method (i.e., atrial fibrillation, trigemini, or obscure pacing rhythm) were not observed. The study time frame was up to 30 min prior to volume expansion until 5 min after volume expansion. Any changes made in hemodynamically relevant treatments during this period excluded the observation, i.e., any changes in vasopressor, inotropic, analgesic or anesthetic infusion rates, changes in positive end-expiratory pressure (PEEP), and body position in the bed.
Sepsis was defined according to the previous criteria [[
The 30-min ECG and arterial pressure waveforms prior to volume expansion were extracted using Philips Research Data Export software. These waveforms were sampled at 125 Hz and subsequently upsampled to 1000 Hz as previously described [[
Detection of extrasystoles was done semi-automatically by custom-made R spike detection algorithms in Matlab (Version 2014a, Mathworks Inc., MA, USA). Potential extrasystoles were visually checked for eligibility defined by being preceded by ten sinus beats (representing baseline heartbeats) and the coupling interval being 80% or less than the preceding sinus beat (resulting in a relevant preload change [[
In case of more than one eligible extrasystole in the 30-min period before volume expansion, the derived variables for all extrasystoles were averaged (median) to represent a single number for an extrasystolic change in that variable per patient. The ten most recent extrasystoles prior to the volume expansion were used if there were more than ten extrasystoles in the 30-min period prior to the volume expansion.
Fluid responsiveness was initially defined as a 15% or more increase in SV, and results for this threshold is reported, but the limit was reduced to 10% upon data collection for statistical purposes due to only a few cases of fluid responsiveness to classify at the initial fluid response threshold of 15%.
Paired t test was used to compare hemodynamic variables prior to and after volume expansion. PPV was calculated for patients meeting the ventilator setting criteria for PPV. Central venous pressure is not standard monitoring in our ICU but was collected when available. We did not investigate additional variables for fluid responsiveness prediction since these were not readily available. All waveform data signal processing were done with Matlab. ROC area statistics are reported as “estimate [confidence interval]” along with optimal sensitivity and specificity measures according to the Youden index. The combined classification results from this and our previous clinical study in post-cardiac surgery patients are also reported. All statistical tests were performed with R (R studio, version 3.2.3 using package “pROC” for ROC statistics with the DeLong method used for ROC area confidence intervals). Spearman correlation is reported. Paired t test was used to compare the hemodynamic variables before and after fluid infusion. Student’s t test was used to compare the hemodynamic variables between responders and non-responders. Based on previous data, we calculated the sample size. Using a significance level of 0.05 and power of 0.8 and assuming equal numbers of fluid responders and non-responders, we needed 23 patients with extrasystoles to provide a ROC area significantly different from 0.5. Assuming that half of the patients had one or more extrasystoles in the observation window, we aimed at 46 patients.
Patient inclusion is shown in Fig. 1. Demographic and clinical data are presented in Table [
Demographic and clinical characteristics of patients
n = 26 Age, years 70.1 (11.2) Gender, male/female 9/17 Height, cm 168 (7.9) Weight, kg 65.7 (16.7) SOFA score 7.2 (3.2) Lactate 2.1 (1.5) Primary diagnosis -Severe sepsis 4 -GI origin 2 -Origin not confirmed 2 -Septic shock 14 -GI origin 5 -Pneumonia 5 -Origin not confirmed 4 -Severe hypotension after major orthopedic surgery 2 -Cerebral event 2 -GI bleeding 1 -Chronic pancreatitis 1 -Rhabdomyolysis 1 -Acute liver failure 1 Vasoactive/inotropic drugs -Norepinephrine 17 -Dobutamine 1 Hemodynamics Before fluids After fluids HR, min−1 90 (18) 88 (19) MAP, mmHg 73 (15) 82 (14)* SV, ml 72 (23) 71 (22)
GI gastro-intestinal, HR heart rate, MAP mean arterial pressure, SV stroke volume *p < 0.00001
In two cases, the post-ectopic change in PEP and PP could not be calculated for technical reasons (waveform “cut” near the diastolic pressure level), leaving 24 datasets for these variables.
Six (23%) patients responded to fluids with an increase in SV of at least 10%.
Classification characteristics of the four variables investigated during post-ectopic beats are shown in Table [
Classification characteristics of post-ectopic changes in variables
Prediction at 10% SV change threshold Prediction at 15% SV change threshold Variable ROC curve area Spec (%) Sens (%) Threshold ROC curve area Spec (%) Sens (%) Threshold SBPabs 0.78 [0.54; 1] 90 67 5.5 mmHg 0.66 [0.33; 0.99] 82 50 5.5 mmHg PEPabs 0.74 [0.53; 0.95] 78 67 7.5 ms 0.73 [0.47; 1] 75 75 7.5 ms PPabs 0.77 [0.52; 1] 78 83 8.46 mmHg 0.73 [0.36; 1] 75 75 8.46 mmHg dP/dtabs 0.76 [0.53; 0.99] 85 67 0.195 mmHg/s2 0.64 [0.33; 0.94] 32 100 0.030 mmHg/s2 SBPrel 0.79 [0.52; 1] 100 67 5% 0.66 [0.27; 1] 95 50 5.5% PEPrel 0.70 [0.50; 0.90] 65 83 2.5% 0.69 [0.44; 0.95] 68 75 3% PPrel 0.70 [0.48; 0.93] 67 83 15% 0.71 [0.41; 1] 80 75 15% dP/dtrel 0.68 [0.39; 98] 70 83 14% 0.68 [0.39; 0.98] 64 75 14%
SBP systolic blood pressure, PEP pre-ejection period, PP pulse pressure, dP/dt maximal systolic upstroke, SV stroke volume, ROC receiver operating characteristic, Spec specificity, Sens sensitivity, rel post-ectopic change calculated on relative scale, abs post-ectopic change calculated on absolute scale
Hemodynamic characteristics of sinus beats prior to ectopy and the post-ectopic beat for fluid non-responders and fluid responders
Non-responders Responders p value Baseline SBP (mmHg) 116 (21) 125 (35) 0.46 Post-ectopic SBP change (mmHg) − 0.1 (5.6) 5.9 (6.6) 0.04 Baseline PEP (ms) 212 (39) 212 (34) 0.99 Post-ectopic PEP change (ms) 4.0 (5.3) 7.5 (2.9) 0.14 Baseline PP (mmHg) 58 (21) 65 (22) 0.51 Post-ectopic PP change (mmHg) 4.0 (6.7) 10.6 (7.0) 0.05 Baseline dP/dt (ms) 0.88 (0.47) 0.94 (0.39) 0.77 Post-ectopic dP/dt change (mmHg/ms) 0.08 (0.11) 0.16 (0.08) 0.10
SBP systolic blood pressure, PEP pre-ejection period, PP pulse pressure
In the present study, we investigated the post-ectopic beat characteristics’ ability to predict fluid responsiveness in critically ill patients. Four out of six fluid responders (increasing SV by 10% or more) had a post-ectopic SBP
Extrasystoles were available in 63% of the observed non-atrial fibrillation patients in this study. In our previous clinical study in post-cardiac surgery patients, we found a similar incidence (61%). Still, both of these studies’ samples are considered convenience samples, but these figures are in alignment with a more detailed extrasystolic occurrence analysis (paper under review). The detection of extrasystoles was done semi-automatically in this study because the monitor’s automatic annotation of hearts beat was not available. Eventually, detection of extrasystoles should be automated by existing monitor software as well as the interbeat calculation of SPB, PP, etc. These detections are already done in existing monitoring, but not combined. The steady-state period of 30 min observation for extrasystoles is obviously not suggested as a waiting time for clinicians, rather the idea is that clinicians facing hemodynamically unstable patients could look back in time and supplement their intervention decision with the arterial waveform characteristics of recent extrasystoles (< 30 min). This is (as estimated) possible in more than half of non-atrial fibrillation patients. While not directly comparable, this stands in contrast to 2–3% of patients where PPV is reliable in the ICU. Still, there is a large group of patients (here, estimated 37%), where extrasystoles had not spontaneously occurred prior to volume expansion. In these cases, the extrasystole method is not applicable. It is up to the clinicians to decide whether the glass is half full or half empty with this extrasystolic occurrence. We think of it as half full because the information held in extrasystoles is, in principle, freely and readily available in half of the ICU patients monitored with ECG and invasive arterial pressure. Obviously, however, post-ectopic beat characteristics need to be calculated by monitors since eyeballing small changes in SBP is difficult and even impossible for PEP changes. For the method to work, these calculations have to be automated by monitors.
Our study is associated with some limitations that should be taken into account when interpreting the data. In this observational study, we included a heterogenic patient population. The study was small (n = 26), and we encountered few responders to classify with our method. Therefore, we have to pay discrete and meticulous caution for the data interpretation. The low number of responders leads to the choice of reducing the otherwise prospectively defined SV response threshold from 15 to 10%, which is a suboptimal modification to the registered study design. Still, combining the study results with previously reported clinical data (Additional file 1: Figure S1) is supporting the conclusion that the extrasystolic method is predicting fluid responsiveness in ICU patients with good accuracy. However, while Additional file 1: Figure S1 is summarizing the classification accuracy of the existing data for the extrasystoles method, it has to be kept in mind that the combined data originates from two different ICU patient populations, namely postoperative cardiac surgery patients [[
While not anticipating the low number of responders, we speculate that it could be related to the fact that most of the patients could be described as being in their “optimization/stabilization” phase, where a massive increase in stroke volume upon fluid loading is less likely as opposed to, for example, the early “rescue” hours in sepsis [[
There are fundamental differences between supraventricular and ventricular extrasystoles. Particularly, the compensatory pause is different (longer) for ventricular extrasystoles compared with supraventricular extrasystoles. However, in the clinical studies conducted so far, the post-ectopic changes encountered in, for example, SBP and PEP are not different when comparing the supraventricular and ventricular extrasystoles and they appear equally predictive of fluid responsiveness. This was the reason why we included both types of extrasystoles in the study. It has been hypothesized that both preload and contractility of the heart are altered during the ectopic activity, contributing to the compensatory mechanism of reduced stroke volume at the ectopic beat [[
Respiration, particularly mechanical ventilation, influences the beat-to-beat level of hemodynamic variables such as SBP. In our data analyses, we averaged out this effect as we calculated a median value from ten preceding heartbeats. However, the exact occurrence of an extrasystole within a respiratory cycle may influence the value of SBP at the post-ectopic beat.
In our study, we did not evaluate the exclusion of frequent arrhythmia (predominantly atrial fibrillation), but the overall occurrence of atrial fibrillation in medical and non-cardiac surgical adult intensive care unit patients is estimated at 10.5% [[
The magnitude of the post-ectopic PEP
This study’s data further supports the notion that extrasystoles may be useful for fluid responsiveness prediction, but we have not encountered excellent prediction with the extrasystoles method. Due to the limitations of our study along with the amount of available clinical data on extrasystoles’ ability to predict fluid responsiveness, we still consider the data at hand preliminary proof-of-concept results and we would be cautious and not yet recommend the method for clinical use before more validation studies point in the same direction as the currently available data, preferably carried out by other research groups. So far, however, a 5% post-ectopic increase in systolic blood pressure appears a consistent indicator of a positive fluid response, and this observation may be useful in situations where other reliable fluid responsiveness monitoring is not available.
STV contributed to the conception of the study, study design, data collection, data analysis, interpretation of data, and writing of the first draft of the paper and revising it critically for important intellectual content and gave final approval of the version to be published. MBK and TE contributed to the study design and data collection, revised the first draft critically for important intellectual content, and gave final approval of the version to be published. MFV contributed to the conception of study and study design, revised the first draft critically for important intellectual content, and gave final approval of the version to be published. TWLS contributed to the interpretation of data, revised the first draft critically for important intellectual content, and gave final approval of the version to be published. CS contributed to the study design and data collection, revised the first draft critically for important intellectual content, and gave final approval of the version to be published.
The extrasystoles method was previously protected by a patent application owned by Aarhus University (PCT/DK2014/050094; STV as sole inventor). The application did, however, not lead to the granting of a patent at priority expiry date.
TWLS is an associate editor of the Journal of Clinical Monitoring and Computing. TWLS received honoraria for consulting from Edwards Lifesciences and Masimo Corp. TWLS is currently the Chair of the Section Cardiovascular Dynamics of the European Society of Intensive Care Medicine as well as the Chair of the Scientific Subcommittee 14 (Monitoring, Ultrasound, and Equipment) of the European Society of Anaesthesiology.
Apart from this, all other authors declare that they have no competing interests.
This study was exclusively observational and approved as such by the Danish authorities.
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STV is financially supported by the Danish Medical Research Council (DFF – 4183-00540).
The dataset used and analyzed in the study is available from the corresponding author on request.
By Simon Tilma Vistisen; Martin Buhl Krog; Thomas Elkmann; Mikael Fink Vallentin; Thomas W. L. Scheeren and Christoffer Sølling