Objective: To analyze the accuracy and specificity of recent studies to compare the ability of predicting fluid responsiveness with Passive Leg Raising (PLR) by using invasive or non-invasive techniques during passive leg raising. Data Sources: MEDLINE, EMBASE and the Cochrane Database of Systematic Reviews were systematically searched. Study Selection: Clinical trials that reported the sensitivity, specificity and area under the receiver operating characteristic curve (AUC) between the responder and non-responder induced by passive leg raising and Volume Expansion (VE) in critical ill patients were selected. 246 studies were screened, 14 studies were included for data extraction, which met our inclusion criteria. Data Extraction: Data were abstracted on study characteristics, patient population, type and amount of VE, time of VE, definition of responders, position, techniques used for measuring hemodynamic change, number and percentage of responders, the correlation coefficient, sensitivity, specificity, best threshold and area under the ROC curve (AUC). Meta-analytic techniques were used to summarize the data. Data Synthesis: A total of 524 critical ill patients from 14 studies were analyzed. Data are reported as point estimate (95% confidence intervals). The pooled sensitivity and specificity of invasive techniques were 80% (73% - 85%) and 89% (84% - 93%) respectively with the area under the sROC of 0.94. While, the pooled sensitivity and specificity of non-invasive techniques were 88% (84% - 92%) and 91% (86% - 94%) respectively with the area under the sROC of 0.95. The pooled DOR of invasive techniques was 32.2 (13.6 - 76.8), which was much lower than that of non-invasive techniques with the value of 64.3 (33.9 - 121.7). Conclusions: The hemodynamic indexes changes induced by PLR could reliably predict fluid responsiveness. Non-invasive hemodynamic techniques with their accuracy and safety can benefit the daily work in ICUs. Because the number of patients included in the present trials was small, further studies should be undertaken to confirm these findings.
Fluid therapy is an essential part in Intensive Care Unit (ICU) to survive patients with hypovolemia. In fact, that’s not easy. Studies have shown that about 50% of critically ill patients do not exhibit the desired effect [
Passive Leg Raising (PLR) is a reversible maneuver that mimics rapid Volume Expansion (VE) by shifting venous blood from the lower limbs toward the intrathoracic compartment [
There are a lot of “fast-response devices” and all of them can be divided into 2 categories: invasive and non-invasive. Invasive hemodynamic techniques such as transpulmonarythermodilution (PiCCO), Vigileo, arterial BP transducer, pulmonary artery catheter are widely used in intensive units. Over the past few years, new techniques assessed for rapid and non-invasive prediction of fluid responsiveness have been introduced in clinical practice. Transthoracic echocardiography (TTE), transesophageal echocardiography (TEE), transthoracic Doppler ultrasonography (USCOM), Bioreactance technology-based system (NICOM), Continuous Non-invasive Arterial Pressure (CNAP) have been developed to predict fluid responsiveness.
Evidence shows that various studies have confirmed the ability of predicting fluid responsiveness by these techniques, but the predictive value of the hemodynamic response after PLR as a dynamic index of fluid responsiveness between invasive and non- invasive techniques has not been compared yet. The aim of this systematic review is to answer the question: can non-invasive techniques be better than invasive ones to be used as a tool for predicting volume responsiveness in critically ill during PLR maneuver and VE?
Data reporting conformed to the Standards for Reporting of Diagnostic Accuracy (STARD) [
Two authors independently performed a search in MEDLINE (using PubMed as the search engine, from 1947), EMBASE (from 1974) and the Cochrane Database of Systematic Reviews for prospective studies in January 2014 with the following key words: “Passive leg raising” AND (fluid therapy OR fluid responsiveness OR fluid expansion OR fluid load* OR volume therapy OR volume responsiveness OR volume expansion).
Only full-text articles in indexed journals were included. Reviews, chapter, case reports, reference network and studies published in abstract form were excluded. No language restriction was imposed. We included only studies with patients admitted in intensive care unit (ICU). Children and pregnant women would be excluded. Articles were collected by one reviewer and crosschecked by another reviewer and references of included papers were examined to identify other studies of interest.
We included full-text studies with the following criteria: 1. PLR was performed and followed with VE; 2. the number of patients and boluses had been counted; 3. the reference standard of predicting fluid responsiveness had been described; 4. the number of responsive patients and non-responsive patients had been counted; 5. sensitivity, specificity and the threshold of the index in identifying those patients who subsequently responded to VE (responders) had been calculated.
Data were extracted using a structured data collection sheet including the following items: authors, year of publication, study setting, population, age of patients, number of patients included, ventilation mode, cardiac rhythm (sinus vs. arrhythmias), type and amount of VE, time of VE, definition of responders, position, assessments used for measuring hemodynamic change, number of VE administered, number and percentage of responders, sensitivity, specificity, best threshold and area under the ROC curve (AUC). We use QUADAS-2 (quality assessment of diagnostic accuracy-2) [
We used RevMan 5.2 (Cochrane Collaboration, Oxford, UK) to make the QUADAS-2 scale to assess quality of studies on diagnostic accuracy to be included in systematic reviews. To calculate pooled values of sensitivity, specificity, diagnostic odds ratio (DOR) and area under summary receiver operating characteristic (sROC) curve we used MetaDiSC 1.4 (Unit of Clinical Biostatisticsteam of the Ramon y Cajal Hospital, Madrid, Spain). P-values of less than 0.05 were considered statistically significant. Publication bias was performed by STATA statistical software 12.0 (StataCorp, College Station, TX).
We used the Cochran Q statistic [
For each study, sensitivity, specificity, positive likelihood ratio (+LR), negative likelihood ratio (−LR), and DOR were calculated after constructing a 2 × 2 contingency table. Pooled estimates with 95% confidence intervals (CIs) were calculated using a random-effects model. A summary receiver operating characteristic (sROC) curve was drawn according to the regression model proposed by Moses et al. [
The initial search yielded 246 articles after the first query in the three databases. Among them, 86 were excluded for not directly concerning item of interest. In the 160 full-articles, 103 were excluded because they were reviews, chapters or abstracts. 16 were excluded because they didn’t perform PLR and another 14 were excluded because they didn’t use VE. 13 were excluded because they didn’t satisfy our inclusion criteria. Therefore, 14 studies [
The clinical characteristics of the 14 included studies were summarized in
Authors | Year | No. | Ventilation | Rhythm | VE | Position | Responder | Index | Techniques |
---|---|---|---|---|---|---|---|---|---|
Lafanechère [ | 2006 | 22 | MV | sinus | 500cc saline | supine position | ΔABF≥15% | cABF-TEE cPP | TEE arterial BP transducer |
Monnet [ | 2006 | 71 | MV | sinus/arr | 500cc saline | semi-recumbent | ΔABF≥15% | cPP cABF-TEE | arterial BP transducer TEE |
Lamia [ | 2007 | 24 | MV/SB | sinus/AF | 500cc saline | semi-recumbent | ΔSVI≥15% | cVTIAo-TTE cCO-TTE | TTE TTE |
Maizel [ | 2007 | 34 | SB | sinus | 500cc saline | supine position | ΔCO-TTE≥12% | cCO-TTE cSV-TTE | TTE TTE |
Thiel [ | 2009 | 89 | MV/SB | sinus/arr | 500cc saline, Ringer’s lactate, HES | semi-recumbent | ΔSV≥15% | cSV-TTE | TTE(USCOM) |
Monnet [ | 2009 | 34 | MV | sinus/arr | 500cc saline | semi-recumbent | ΔCI≥15% | cCI cPP | PiCCO arterial BP transducer |
Biais [ | 2009 | 30 | MV/SB | sinus | 500cc saline | semi-recumbent | ΔSV-TTE≥15% | cSV cSV-TTE | Vigileo TTE |
Préau [ | 2010 | 34 | SB | sinus | 500cc HES | semi-recumbent | ΔSV≥15% | cSV-TTE cPP | TTE arterial BP transducer |
Guinot [ | 2011 | 17 | MV | sinus/arr | 500cc saline | semi-recumbent | ΔSV-TTE>15% | cSV-TTE cCO-TTE | TTE TTE |
Liu [ | 2011 | 20 | MV | sinus/arr | 250cc saline | semi-recumbent | ΔSV≥10% | cSV | PiCCO |
Wang [ | 2011 | 33 | MV/SB | sinus/arr | 500cc saline | semi-recumbent | ΔSV-TTE≥15% | cSV-TTE cSV-USCOM | TTE USCOM |
Monnet [ | 2012 | 39 | MV | sinus | 500cc saline | semi-recumbent | ΔCI≥15% | cPPV cPPV-CNAP | PiCCO CNAP |
García [ | 2012 | 37 | MV | sinus/arr | 500cc HES | semi-recumbent | ΔCO≥15% | cCO-TEE cPP | TEE arterial BP transducer |
Monnet [ | 2013 | 40 | MV | sinus/arr | 500cc saline | semi-recumbent | ΔCI≥15% | cCI | PiCCO |
MV: mechanical ventilation, arr: arrhythmia, AF: atrial fibrillation, VE: volume expansion, min minutes, BP: blood pressure, Δ: variation; c: PLR-induced changes, TTE: transthoracic echocardiography, TEE: transesophageal echocardiography, CI: cardiac index, CO: cardiac output, SV: stroke volume, PP: pulse pressure, PPV: pulse pressure variation, ABF: aortic blood flow, VTIAo: aortic velocity-time integral, USCOM: transthoracic Doppler ultrasonography, CNAP: continuous non- invasive arterial pressure.
Authors | Index | Boluses | TP | FP | FN | TN | AUC | Best Threshold | Sens. | Spec. | DOR | +LR | −LR |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Lafanechère [ | cPP | 22 | 7 | 1 | 3 | 11 | 0.78 | 12 | 70 | 92 | 25.7 | 8.4 | 0.3 |
Monnet [ | cPP | 71 | 22 | 5 | 15 | 29 | 0.96 | 12 | 60 | 85 | 8.5 | 4 | 0.5 |
Monnet [ | cCI | 34 | 21 | 0 | 2 | 11 | 0.94 | 10 | 91 | 100 | 197.8 | 21.5 | 0.1 |
Biais [ | cSV | 30 | 20 | 2 | 0 | 8 | 0.96 | 13 | 100 | 80 | 139.4 | 4.3 | 0 |
Préau [ | cPP | 34 | 11 | 3 | 3 | 17 | 0.86 | 9 | 79 | 85 | 20.8 | 5.2 | 0.3 |
Liu [ | cSV | 46 | 12 | 2 | 3 | 29 | 0.85 | 12.5 | 80 | 93.5 | 58 | 12.4 | 0.2 |
Monnet [ | cPPV | 39 | 15 | 2 | 2 | 20 | 0.89 | 10 | 88 | 91 | 75 | 9.7 | 0.1 |
García [ | cPP | 37 | 14 | 3 | 7 | 13 | 0.73 | 11 | 67 | 81 | 8.7 | 3.6 | 0.4 |
Monnet [ | cCI | 40 | 20 | 1 | 1 | 18 | 0.98 | 15 | 95 | 95 | 360 | 18.1 | 0.1 |
Overall (95% CIs) | 353 | 80 | 89 | 32.2 | 5.8 | 0.2 | |||||||
(73 - 85) | (84 - 93) | (13.5 - 76.8) | (3.8 - 8.8) | (0.1 - 0.4) |
TP: true-positive, FP: false-positive, FN: false-negative, TN: true-negative, AUC: area under the receiver operating characteristics curve, 95% CIs: 95% confidence intervals, Sens: sensitivity, Spec: specificity, DOR: diagnostic odds ratio, +LR: positive likelihood ratio, -LR: negative likelihood ratio, CI: cardiac index, SV: stroke volume, PP: pulse pressure, PPV: pulse pressure variation.
Authors | Index | boluses | TP | FP | FN | TN | AUC | Best Threshold | Sens. | Spec. | DOR | +LR | −LR |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Lafanechère [ | cABF-TEE | 22 | 9 | 2 | 1 | 10 | 0.95 | 8 | 90 | 83 | 45 | 5.4 | 0.1 |
Monnet [ | cABF-TEE | 71 | 36 | 2 | 1 | 32 | 0.75 | 10 | 97 | 94 | 576 | 16.5 | 0 |
Lamia [ | cVTIAo-TTE | 24 | 10 | 0 | 3 | 11 | 0.96 | 12.5 | 77 | 100 | 69 | 18 | 0.3 |
Maizel [ | cSV-TTE | 34 | 15 | 3 | 2 | 14 | 0.9 | 8 | 88 | 83 | 35 | 5 | 0.1 |
Thiel [ | cSV-TTE | 102 | 38 | 4 | 9 | 51 | 0.89 | 15 | 81 | 93 | 53.8 | 11.1 | 0.2 |
Biais [ | cSV-TTE | 30 | 17 | 1 | 3 | 9 | 0.92 | 16 | 85 | 90 | 51 | 8.5 | 0.2 |
Préau [ | cSV-TTE | 34 | 12 | 2 | 2 | 18 | 0.94 | 10 | 86 | 90 | 54 | 8.6 | 0.2 |
Guinot [ | cCO-TTE | 25 | 11 | 2 | 2 | 10 | 0.87 | 5 | 85 | 83 | 27.5 | 5.1 | 0.2 |
Wang [ | cSV-TTE | 36 | 24 | 2 | 0 | 10 | 0.95 | 15 | 100 | 83.3 | 205.8 | 5.1 | 0 |
Monnet [ | cPPV-CNAP | 39 | 14 | 2 | 3 | 20 | 0.89 | 11 | 82 | 91 | 46.7 | 9.1 | 0.2 |
García [ | cCO-TEE | 37 | 20 | 1 | 1 | 15 | 0.97 | 12 | 95 | 94 | 300 | 15.2 | 0.1 |
Overall (95%CIs) | 454 | 88 | 91 | 64.3 | 7.8 | 0.17 | |||||||
(84 - 92) | (86 - 94) | (33.9 - 121.7) | (5.3 - 11.6) | (0.12 - 0.24) |
TP: true-positive, FP: false-positive, FN: false-negative, TN: true-negative, AUC: area under the receiver operating characteristics curve, 95% CIs: 95% confidence intervals, Sens: sensitivity, Spec: specificity, DOR: diagnostic odds ratio, SV: stroke volume, ABF: aortic blood flow, VTIAo: aortic velocity-time integral, TTE: transthoracic echocardiography, TEE: transesophageal echocardiography, CNAP: continuous non-invasive arterial pressure.
A total of 524 patients were enrolled (range 17 - 89 for single paper) and a total of 574 VE were administered. The mean responder rate was 52.8%.
All studies were conducted in intensive care units (ICU) on patients with hypovolemia, whose attending physician decided to perform a fluid challenge. 2 study [
We first divided the 14 studies into 2 groups: invasive group [
There were 9 papers (327 patients, 353 boluses) in the invasive group. The results I2 = 39.6% (<50%) and p = 0.1037 (>0.05) showed that heterogeneity was not significant among the trials. Forest plots of the pooled sensitivity and specificity were shown in
After excluded the threshold effect with spearman correlation coefficient = 0.233 and p = 0.546 (>0.05), we used Moses-Shapiro-Littenberg method to draw the symmetrical summary ROC curve (SROC) with AUC of 0.94.
There were 11 papers (430 patients, 454 boluses) in the non-invasive group. The results
I2 = 0.0% (<50%) and p = 0.809 (>0.05) showed that heterogeneity was not significant. Forest plots of the pooled sensitivity and specificity were shown in
After excluded the threshold effect with spearman correlation coefficient = 0.361 and p = 0.276 (>0.05), we drew the symmetrical summary ROC curve (SROC) (
The result of Egger test and Begg test showed that the potential publication bias was significant (P > 0.05), which indicated a potential for publication bias.
The main finding of our systematic review are as follows: (1) The result of pooled sensi-
tivity and specificity between invasive and non-invasive techniques are 80% (73% - 85%) vs. 88% (84% - 92%) and 89% (84% - 93%) vs. 91% (86% - 94%), which cannot conclude inferior or superior; (2) The results of pooled DOR between invasive and non-invasive is 32.2 (13.6 - 76.8) vs. 64.3 (33.9 - 121.7), which indicate using non-inva- sive techniques have better discriminatory test performance with higher DOR values [
Knowing that dynamic indexes such as CO, CI, SV, ABF, SVV, PPV make use of provoked cardiac reaction assessed with fluid bolus and postural change can predict fluid responsiveness. A recent analysis by Vallee F shows that increase in thermodilution CO following a fluid bolus can predict fluid responsiveness [
The strengths of our meta-analysis lie in the methods adhering to recent guidelines for diagnostic reviews [
Limitations still exist in our meta-analysis. First, the pooling of diagnostic accuracy data inevitably contributed to sources of bias [
The hemodynamic indexes induced by PLR can well discriminate between fluid responders and non-responders regardless of arrhythmia and ventilation mode. Non-in- vasive hemodynamic techniques with their accuracy and safety can benefit the daily work in ICUs.
Si, X., Cao, D.Y., Wu, J.F., Chen, J., Liu, Z.M., Chen, M.Y., Bin, O.Y. and Guan, X.D. (2016) Meta-Analysis of Invasive versus Non-Invasive Techniques to Predict Fluid Responsiveness by Passive Leg Raising in the Critically Ill. International Journal of Clinical Medicine, 7, 736-747 http://dx.doi.org/10.4236/ijcm.2016.711080