Background
Assessing preload dependence in critically ill patients is a challenge for intensive care unit (ICU) physicians [
1,
2]. During controlled mechanical ventilation, dynamic indexes can be applied in non-arrhythmic patients with sufficiently high tidal volume (V
T), i.e., > 8 mL/kg body weight and non-severely impaired lung compliance [
3‐
8]. The interplay between mechanical ventilation and hemodynamics is more complex in patients with spontaneous breathing activity, whose respiratory efforts affect intrathoracic pressure and venous return to the right ventricle (RV) [
9‐
12]. To overcome these limitations, functional hemodynamic assessment, consisting of maneuvers determining a sudden change in cardiac preload, such as passive leg raising (PLR) or end-expiratory occlusion test (EEOT), represents a valuable means of assessment of fluid responsiveness [
13‐
15].
Both PLR and EEOT have been successfully utilized for assessing fluid responsiveness, regardless of ventilatory assistance and mode of ventilation [
15,
16]. Unfortunately, however, some drawbacks limit the extensive use of these maneuvers in clinical practice. One the one hand, PLR cannot be applied in some clinical situations, such as trauma of the hip, legs or lumbar spine, deep venous thrombosis and intracranial or abdominal hypertension [
17‐
20]. Indeed, a recent large observational study showed PLR to be the most common form of assessment of fluid responsiveness, being used, nonetheless, in only 10.7% of the patients needing the assessment of fluid responsiveness [
2]. On the other hand, rates of EEOT failure as high as 22.5% have been reported, consequent to visible patient’s effort against the occluded airway [
15].
We propose here a new approach for assessing fluid responsiveness in patients undergoing partial ventilatory assistance. We hypothesized that the changes from baseline in systolic arterial pressure (SAP), pulse pressure (PP) and stroke volume index (SVI) in relationship to the airway pressure (Paw) generated during a “sigh” maneuver [
21] can predict fluid responsiveness in ICU patients undergoing pressure support ventilation (PSV).
Results
Forty-five adult patients were enrolled; however, only 40 patients were included in the data analysis. In fact, we excluded two patients because of arrhythmia after enrolment, and three because they had a persistent cough after sigh application. No patient was excluded from data analysis because of distorted arterial waveform signal.
Table
1 displays patients’ characteristics at enrolment, while Additional file
2: Table S1 in the supplementary material displays the hemodynamic measurements at each step of the protocol. A total of 27 patients (10 responders and 17 non-responders) did not receive any vasoactive drug. The median Richmond Agitation Sedation Scale (RASS) score was − 2 ± 0.5 in responders and − 2 ± 0.6 in non-responders (
p = 0.27). The hemodynamic effects of VE in responders and non-responders are separately reported in Table
2. The AUC for PP variation during the period of stable ventilatory pattern before sigh application was 0.51 (CI
95 0.34–0.67). The nadirs of SAP, SVI and PP occurred within the first 10 of the 20 beats analyzed after Sigh
25 in 15 of 16 (93.7%) responders and 19 of 24 (79.1%) non-responders (
p = 0.22), while after Sigh
35 in 13 of 16 (81.2%) responders and 17 of 24 (70.8%) non-responders (
p = 0.47). SAP, SVI and PP values at baseline
15, baseline
25 and baseline
35 did not differ (
p = 0.27, 0.28 and 0.12, respectively).
Table 1
Patient characteristics at enrolment
Age (years) | 72 [70–77] | 64 [54–75] | 0.34 |
Gender (male/female) | 14/2 | 14/10 | 0.07 |
Body mass index (kg/m2) | 24 [21–27] | 24 [23–26] | 0.85 |
SAPS II | 46 [44–49] | 45 [41–48] | 0.43 |
Temperature (°C) | 37.2 [36.8–37.4] | 36.9 [36.1–37.3] | 0.45 |
Ventilator settings (baseline) |
PEEP (cmH2O) | 5.0 [5.0–7.0] | 5.0 [5.0–6.3] | 0.77 |
Pressure support (cmH2O) | 10.0 [8.8–10.0] | 10.0 [10.0–10.0] | 0.82 |
VT (mL/kg ideal body weight) | 6.8 [5.9–7.4] | 7.0 [6.6–7.9] | 0.34 |
PaO2/FiO2 (ratio) | 310 [280–354] | 302 [274–330] | 0.65 |
RR (breaths/min) | 15 [13–18] | 13 [10–15] | 0.02 |
HR/RR ratio | 6.2 [5.0–6.5] | 5.9 [5.0–6.4] | 0.71 |
Vasoactive agents, n; (μg kg− 1 min− 1) |
Norepinephrine | 6; (0.2 [0.2–0.3]) | 7; (0.2 [0.1–0.2]) | 0.85 |
Dopamine | 2; (5.6 [4.8–5.9]) | 0 | 0.89 |
Acute circulatory failure origin, n; (%) |
Sepsis/septic shock | 6 (37.5) | 10 (41.7) | 0.99 |
Hypovolemia | 7 (43.8) | 8 (33.3) | 0.53 |
Trauma | 0 | 1 (4.1) | 0.99 |
Intracranial diseases | 3 (18.7) | 5 (20.9) | 0.99 |
Table 2
Effects of fluid administration on hemodynamic parameters in fluid responders and non-responders
CI (L/min/m2) |
Responders | 2.1 [2.0–2.2] | 2.8 [2.5–3.4] | 0.0006 | 0.0005 |
Non-responders | 2.8 [2.4–2.9] | 2.7 [2.4–2.9] | 0.24 |
SVI (mL/m2) |
Responders | 24 [21–26] | 38 [29–41] | 0.001 | 0.0006 |
Non-responders | 34 [28–40] | 35 [28–41] | 0.08 |
MAP (mmHg) |
Responders | 71 [64–76] | 88 [80–94] | 0.13 | 0.0005 |
Non-responders | 77 [69–86] | 81 [72–89] | 0.003 |
SAP (mmHg) |
Responders | 106 [98–124] | 132 [122–149] | 0.23 | < 0.0001 |
Non-responders | 115 [106–126] | 128 [113–140] | < 0.0001 |
HR (beats/min) |
Responders | 90 [83–92] | 85 [79–88] | 0.01 | 0.02 |
Non-responders | 73 [63–87] | 71 [64–82] | 0.14 |
PPV (%) |
Responders | 8.2 [5.6–14.8] | 7.0 [5.8–10.6] | 0.94 | 0.04 |
Non-responders | 9.8 [7.0–17.4] | 5.1 [4.3–7.7] | 0.007 |
Effects of sigh application (see Table 3)
The variations of SAP, SVI and PP changes after Sigh
15 were not different between responders and non-responders and, therefore, the ROC curves were not calculated.
Table 3
Variations in SAP, PP and SVI and slope following sigh application in responders and non-responders
Sigh15 |
Nadir of SAP (%) | −5.8 (− 12.3/−3.2) | −4.8 (−6.5/−2.5) | 0.19 | NA | NA | NA | NA |
Nadir of PP (%) | −10.7 (− 18.6/−6.0) | −6.3 (− 14.3/−4.1) | 0.10 | NA | NA | NA | NA |
Nadir of SVI (%) | −1.7 (−2.6/−0.9) | − 1.9 (−2.5/−1.0) | 0.91 | NA | NA | NA | NA |
Sigh25 |
Nadir of SAP (%) | − 18.0 (−8.6/− 21.8) | −13.8 (−7.3/−18.3) | 0.004 | 0.77 (0.61–0.93) | 50.0 (29.1–70.8) | 87.5 (61.5–98.4) | −17% |
Nadir of PP (%) | −23.8 (−15.3/−38.6) | −23.4 (− 12.3/−26.3) | 0.002 | 0.78 (0.63–0.93) | 70.8 (48.9–87.0) | 75.0 (47.6–92.0) | − 17% |
Nadir of SVI (%) | −1.0 (−9.8/8.2) | −8.7 (−3.2/−15.8) | 0.38 | 0.58 (0.40–0.77) | NA | NA | NA |
Sigh35 |
Nadir of SAP (%) | − 24.9 (−19.3/−31.0) | −13.8 (− 7.3/−18.3) | 0.0003 | 0.83 (0.70–0.95) | 62.5 (35.4–84.0) | 91.6 (73.0–98.0) | − 14% |
Nadir of PP (%) | −38.9 (− 35.1/−53.5) | −23.4 (− 12.3 / -26.3) | < 0.0001 | 0.91 (0.82–0.99) | 75 (47.6–92.7) | 91.6 (73.0–98.9) | −35% |
Nadir of SVI (%) | −22.8 (− 13.7/−27.5) | −8.7 (− 3.2/−15.8) | 0.0002 | 0.83 (0.71–0.95) | 68.7 (41.3–88.9) | 87.5 (67.4–97.0) | −21% |
Slope |
Slope of SAP | −10.4° (− 11.9/−8.6) | −1.5° (− 3.0/−0.20) | < 0.0001 | 0.99 (0.99–1.01) | 100.0 (79.4–100.0) | 95.8 (78.8–99.9) | −4.4° |
Slope of PP | − 7.6° (− 9.3/−6.4) | −3.7° (− 5.1/−2.1) | < 0.0001 | 0.91 (0.77–0.97) | 68.7 (41.3–88.9) | 95.8 (78.8–99.9) | −7.0° |
Slope of SVI | −3.3° (− 3.8/−2.2) | −1.5° (− 2.5/−0.9) | < 0.0001 | 0.83 (0.68–0.93) | 56.2 (29.8–80.2) | 91.6 (73.0–98.9) | −3.2° |
After Sigh25, the reductions in SAP and PP were statistically significant between responders and non-responders [(− 18.0% (− 8.6/− 21.8) vs. − 13.8% (− 7.3/− 18.3); p = 0.004 and − 23.8% (− 15.3/− 38.6) vs. − 23.4% (− 12.3/− 26.3); p = 0.002, respectively]), while the reduction in SVI was not (p = 0.38). After Sigh35, reductions in SAP, SVI and PP were all significantly different between responders and non-responders [(24.9% (− 19.3/− 31.0) vs. − 13.8% (− 7.3/− 18.3); p = 0.0003, − 22.8% (− 13.7/− 27.5) vs. − 8.7% (− 3.2/− 15.8); p = 0.0002 and − 38.9% (− 35.1/− 53.5) vs. − 23.4% (− 12.3/− 26.3); p < 0.0001, respectively)]. The AUCs of the ROC obtained after Sigh25 were not significantly different for any of the variables analyzed. The AUC for PP after Sigh35 [(0.91 (0.82–0.99); sensitivity 75% (47.6–92.7%) and specificity 91.6 (73.0–98.9%)] was significantly greater than the AUCs for SAP [(0.83 (0.70–0.95) and SVI 0.83 (0.71–0.95); p = 0.03 for both the comparisons)]. The PP nadir best threshold value of the ROC curve was − 35% from baseline.
The slopes of SAP, SVI and PP were all significantly different between responders and non-responders [(− 10.4°(− 11.9/− 8.6) vs. − 1.5°(− 3.0/− 0.20); − 3.3°(− 3.8/− 2.2) vs. − 1.5°(− 2.5/− 0.9) and 7.6° (− 9.3/− 6.4) vs. − 3.7°(− 5.1/− 2.1), respectively;
p < 0.0001 for all comparisons)]. The AUC of the slope for SAP [(0.99 (0.99–1.01); sensitivity 100.0% (79.4–100.0%) and specificity 95.8% (78.8–99.9%)] was significantly greater than the AUCs for PP [(0.91 (0.77–0.97)) and SVI (0.83 (0.68–0.93);
p = 0.04 and 0.009, respectively)]. The SAP slope best threshold value of the ROC curve was − 4.4° from baseline (Fig.
2).
The only parameter found to be independently associated with fluid responsiveness among those included in the logistic regression was the slope for SAP [(p = 0.009; odds ratio 0.27 (CI95 0.10–0.70)].
Discussion
Our study shows that the functional hemodynamic assessment of (1) the lowest SAP values obtained after the consecutive application of sighs at 15, 25 and 35 cmH2O and of (2) the lowest PP valued obtained after one sigh at and 35 cmH2O reliably predict fluid responsiveness in a selected ICU population undergoing PSV.
The rate of the dynamic indexes of fluid responsiveness being used in ICU patients to assess fluid responsiveness is rather small [
8]. Reliable tests are available for patients undergoing controlled mechanical ventilation such as PLR [
20], EEOT [
15,
27,
28] and, more recently, the “tidal volume challenge” [
29] and “mini-fluid challenge” [
30].
For the increasing number of ICU patients retaining, to some extent, a spontaneous breathing activity [
8,
31,
32], only PLR has been repeatedly demonstrated effective [
17‐
20], while the EEOT reliably predicted fluid responsiveness in those patients able to maintain a 15-s respiratory occlusion without triggering the ventilator [
33,
34] or with absence of spontaneous breathing efforts during the maneuver [
35]. Spontaneous breathing activity affects the reliability of the dynamic indexes of fluid responsiveness by influencing V
T magnitude [
7], increasing respiratory rate and, therefore, reducing heart rate/respiratory rate ratio
34 [
36] and causing asynchronies between patient and ventilator
11 [
12]. In fact, in the present study, the AUC was 0.51 for PP variation, which makes this index unsuitable for clinical use, confirming that fluid responsiveness should always be assessed by a functional test in patients with spontaneous breathing activity.
This is the first study demonstrating the feasibility of applying a transient increase in V
T by adding a sigh to predict fluid responsiveness in ICU patients with residual spontaneous breathing activity and undergoing PSV. In fact, a similar approach has been already successfully used in patients undergoing forms of controlled ventilation to enhance the reliability of stroke volume variation and PP variation. Freitas et al. increased the V
T from 6 to mL to 8 mL/kg body weight for 5 min [
37]; Reuter et al. randomly applied 5, 10, and 15 mL/kg of V
T [
38] and, more recently, Myatra et al. used a 1-min “V
T-challenge”, increasing the V
T from 6 up to 8 mL/kg [
39]. Finally, the analysis of the slope for SAP nadir has previously been successfully applied in small cohorts of postsurgical patients [
40‐
42].
In a similar manner, the application of a sigh is a test aimed at revealing fluid responsiveness by inducing increases in V
T and in intrathoracic pressure, which reduces the stroke volume by increasing RV afterload and, to some extent, by reducing RV preload. The RV is extremely sensitive to an acute increase in afterload and is unable to maintain the systolic function in this condition and reduces RV stroke volume through a beat-to-beat adaptive response [
43]. The complex interplay between sigh application and the transmission of the increased intrathoracic pressure to the RV would also cause false positive results in those patients affected by RV failure, by causing an amplified decrease in RV stroke volume.
After a few heartbeats, the reduced RV stroke volume affects left ventricle preload and SV, and, consequently, SAP and PP. The PP nadir occurred within the first 10 heartbeats after sigh application in 80% of our patients [
3,
4]. For instance, the decrease in both PP and SVI after a recruitment maneuver delivered with a positive airway pressure of 30 cm H
2O for 30 s has been recently successfully applied in patients undergoing general anesthesia, to predict fluid responsiveness [
44].
The hemodynamic variations induced by Sigh
15 on PP and SVI were negligible, while those induced by Sigh
25, though statistically significant, were small and overall were insufficient for clinical use (Table
3). After Sigh
35, the AUCs for SAP and SVI were almost identical, whereas the AUC for PP was larger AUC consequent to a higher specificity (91.6%). The variable transmission of the applied inspiratory pressure may explain the lack of reliability of Sigh
35 in some patients. Lansdorp et al. demonstrated that the amount of Paw distributed to the pericardium and vena cava is about one third of the overall applied pressure, with ± 17% and ± 11% variability for pericardium and vena cava, respectively [
45]. If, on the one hand, Sigh
35 identifies those patients who should not receive fluids to correct hemodynamic instability, i.e., displaying a drop in PP ≤ 35% during Sigh
35, on the other hand, it fails to recognize some responders, which makes an adjunctive form of functional hemodynamic assessment such as the PLR advisable before administering fluids.
The analysis of the slope for SAP variations after sigh application is a post-hoc mathematical elaboration, which predicts fluid responsiveness. The evaluation only of the nadir values avoids the inclusion of early inspiratory increases in the stroke volume, which are more prominent in patients with hypervolemia and congestive heart failure and not related to volume responsiveness [
11,
46]. The values of the slope angle are generated by the decrease in SAP during elevation of intrathoracic pressure after sigh application and are linked to the position of the ventricle on the Frank–Starling curve (the higher the value, the larger the preload dependence). However, Trepte et al. applied three consecutive pressure-controlled mechanical breaths of gradually increasing pressure up to 30 cmH
20, demonstrating moderate reliability of the nadir SAP analysis in predicting fluid responsiveness (AUC 0.77) [
42]. Though reliable overall, this analysis of the slope is limited by potential technical limitations. First, bedside clinical application of the slope analysis should be based on automatic computation of SAP changes, which is not presently available for routine use. However, in principle it would be possible to determine the SAP nadir during the first 20 beats after each sigh and obtain the slope measurement in a few minutes by means of a spreadsheet. Second, correct computation is affected by the occurrence of extrasystoles and by the precision of the measurement (the best cutoff value is − 4.4°) during the application of three consecutive pressure-controlled mechanical breaths. However, these technical limitations could be easily overcome by software integrating the signals obtained by the ventilator and the cardiac output monitoring device, making the sigh test easily applicable at the bedside.
Some may argue about the safety of raising Paw to 35 cmH
2O, though for a few seconds. In 13 ICU patients with early ARDS, Patroniti et al. increased Paw once a minute during PSV for 3–5 s at a minimum of 35 cm H
2O and observed an improvement in oxygenation without adverse effects [
21]. As confirmed, none of our patients had complications or side effects related to sigh application.
Our study has some limitations. First of all, our criteria for patient selection are very strict, as it is commonly the case for “proof of concept” studies, which often include relatively few and highly selected patients in order to control potential confounding factors, limiting the external validity of the study. The inclusion and exclusion criteria have been specifically requested by the local ethical committees to guarantee the safety of the study protocol application. Unfortunately, this led to a selection of less severely ill ICU patients. Second, the reliability of MOSTCARE™ is still debated. Despite the positive results of a large multicenter study performing a head-to-head comparison with transthoracic echocardiography along five consecutive heartbeats [
24], the ability of MOSTCARE™ in tracking CI variations during fluid infusion is still questioned [
47], Moreover, the MOSTCARE™ reliability is strictly dependent on the quality of the arterial pulse and on the ability of the operator to recognize artifacts of the signal and the centers involved are highly trained in the MOSTCARE™ use. Finally, we assessed the fluid responsiveness by infusing a VE of 500 mL over 10 min, in line with several previous ICU studies adopting the VE as gold standard [
48]. However, recently, Aya et al. tested different doses of VE and obtained different proportions of responders and non-responders [
49]. Since we did not adjust the VE on the body weight, some patients could be under or over-challenged, potentially affecting the rate of fluid responsiveness and, in turn, the ROC curve analysis.
For all these reasons, the promising results of this pilot investigation need to be confirmed in studies with less selective inclusion criteria.