Testing preload responsiveness by the tidal volume challenge assessed by the plethysmographic perfusion index

Testing preload responsiveness by the tidal volume challenge assessed by the plethysmographic perfusion index | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Testing preload responsiveness by the tidal volume challenge assessed by the plethysmographic perfusion index Chiara BRUSCAGNIN, Rui SHI, Daniela ROSALBA, Gaelle FOUQUE, Julien HAGRY, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4575103/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Sep, 2024 Read the published version in Critical Care → Version 1 posted 11 You are reading this latest preprint version Abstract Background To detect preload responsiveness in patients ventilated with a tidal volume (Vt) at 6 mL/kg, the Vt challenge consists in increasing Vt from 6 to 8 mL/kg and measuring the induced increase in pulse pressure variation (PPV). However, this requires an arterial catheter. The perfusion index (PI), which reflects the amplitude of the plethysmographic signal, may reflect stroke volume and its respiratory variation (pleth variability index, PVI) may be a surrogate of PPV. We assessed whether changes in PVI or PI during a Vt challenge could be as reliable as changes in PPV for detecting preload responsiveness. Methods In critically ill patients mechanically ventilated with Vt = 6 mL/kg and no spontaneous breathing activity, monitored with a PiCCO2 system and a Masimo SET technique (sensor placed on the finger or the forehead), haemodynamic data were recorded during a Vt challenge and a passive leg raising (PLR) test. Preload responsiveness was defined by a PLR-induced increase in cardiac index ≥ 10%. Results Among 63 screened patients, 21 were excluded because of an unstable PI signal and/or atrial fibrillation. Among the 42 included patients, 16 were preload responders. During the Vt challenge in preload responders, PPV (absolute change), PI measured on the finger (percent change), PVI measured on the finger (absolute change), PI measured on the forehead (percent change) and PVI measured on the forehead (absolute change) changed by 4.4 ± 1.9%, -14.5 ± 10.7%, 1.9 ± 2.6%, -18.7 ± 10.9 and 1.0 ± 2.5, respectively. All these changes were significantly larger than in preload non-responders. Fluids fluid accumulation catecholamine systemic venous return vasodilatation Figures Figure 1 INTRODUCTION In patients with acute circulatory failure, after initial fluid resuscitation, fluid infusion increases cardiac output in only half of them [ 1 ]. As undue fluid infusion may contribute to fluid accumulation, the deleterious effect of which is clearly demonstrated [ 2 ], it is recommended to assess preload responsiveness before deciding to perform volume expansion [ 3 ]. For this purpose, pulse pressure variation (PPV), i.e., the change in arterial pulse pressure amplitude during mechanical ventilation which reflects the simultaneous change in stroke volume, is very reliable, but can be used in few patients because of strict conditions of use [ 4 , 5 ]. Among such conditions, tidal volume (Vt) must be ≥ 8 mL/kg of predicted body weight (PBW), as lower Vt values create false negatives [ 6 ]. To overcome this limitation, the Vt challenge has been described in mechanically ventilated patients [ 7 ]. It consists in transiently increasing Vt from 6 to 8 mL/kg PBW, and looking for a significant increase in PPV, reflecting that the slope of the cardiac function curve is steep. However, the Vt challenge has two limitations. First, although it has been validated by several studies, the diagnostic threshold they reported is variable [ 8 ]. Second, it requires an arterial pressure curve, which is usually plotted by using an arterial catheter. The plethysmography signal may be helpful in dispensing with the need for an arterial catheter. This signal is composed of a pulsatile portion and a non-pulsatile portion [ 9 ]. The ratio of the amplitude of the former to the latter, called the “perfusion index” (PI), has two determinants: the degree of vasoconstriction of the tissue in which the oxygen saturation of haemoglobin is measured, and stroke volume [ 9 ]. Thus, over short time periods, changes in PI may reflect changes in stroke volume, as shown during fluid loading [ 10 , 11 ], passive leg raising (PLR) [ 10 , 11 ], recruitment manoeuvres [ 12 ] and the end-expiratory occlusion test [ 11 ]. Also, the change in PI under mechanical ventilation, called “pleth variability index” (PVI), has been used to estimate PPV [ 13 ]. PVI has been shown to detect preload responsiveness [ 14 ], while opposite results have been recorded in critically ill patients receiving norepinephrine [ 15 ]. To overcome this vasoconstriction bias, it has been proposed to attach the plethysmography sensor to the forehead or the earlobe rather than to the finger [ 16 ]. It has not yet been tested whether the changes in PI or PVI could be used to assess the effects of the Vt challenge, with a larger increase in PI and a larger decrease in preload responders than non-responders. This would allow one to perform the test without any arterial catheter. Therefore, the primary goal of this study was to assess the ability of PI changes induced by a Vt challenge to diagnose preload responsiveness in critically ill adult patients. The secondary aims were (i) to test whether Vt-challenge-induced changes in PVI reliably diagnose preload responsiveness, (ii) to compare this diagnostic value of changes in PI and PVI according to the location of plethysmographic measurement (finger vs. forehead) and (iii) to compare the changes in PPV, PVI and PI during a PLR test and volume expansion. PATIENTS AND METHODS This prospective study was conducted in the 25-bed medical intensive care unit (ICU) of the Bicêtre hospital (Assistance publique-Hôpitaux de Paris). It was approved by the ethics committee of the French Intensive Care Society (SC016-18). All patients or their next of kin were informed about the study and agreed to participate. Patients Patients were included if they presented the following criteria: (i) age ≥ 18 y.o., (ii) hospitalization in the ICU, (iii) invasive mechanical ventilation in assist controlled mode with a Vt of 6 mL/kg PBW, (iv) monitoring already in place with a transpulmonary thermodilution PiCCO2 system (Pulsion Medical Systems, Getinge, Feldkirchen, Germany) and with a plethysmography Masimo SET device (Masimo Corporation, Irvine, CA) and (v) decision by the clinicians in charge to assess preload responsiveness through a Vt challenge and a PLR test. Patients were excluded if (i) they presented spontaneous breathing activity, as assessed by visual observation of the airway pressure curve, (ii) they presented atrial fibrillation, (iii) the PI signal on the fingertip was unstable, (iv) chest drainage was in place, (v) they were pregnant and (vi) they presented frequent extrasystoles. Patients were not included if the investigators were not available, and if they refused to participate in the study. Measurements All patients were equipped with an internal jugular venous catheter and a thermistor-tipped arterial catheter introduced through the femoral artery. Cardiac output was measured by pulse contour analysis and transpulmonary thermodilution [ 17 ]. For the latter, three injections of cold saline boluses were averaged [ 18 ]. Intra-abdominal pressure was measured through bladder pressure [ 19 ]. Arterial, central venous and airway pressures were continuously recorded by HEM3.2 software (Notocord, Croissy-sur-Seine, France). Data from the PiCCO2 device, including cardiac index (CI), arterial and central venous pressures and PPV were continuously recorded by PiCCOWin software (Pulsion Medical Systems, Getinge, Feldkirchen, Germany). A plethysmography sensor (Masimo Corporation, Irvine, CA) was placed on the index of either hand and another one on the forehead and connected to the Masimo SET device to measure pulse oxygen saturation (SpO 2 ), PI and PVI. Data were extracted a posteriori through a USB stick and analyzed on an Excel spreadsheet (Microsoft, Richmond, CA). PI values were averaged over a 25-sec moving period. Among ventilatory data, we collected Vt, respiratory rate, and plateau and positive end-expiratory pressures. Study design Once the patient was included in the study, demographic and ventilatory data were collected, the PICCO2 device was calibrated and a first set of haemodynamic and plethysmography data was recorded. A Vt challenge was then performed as previously described [ 7 ] by increasing Vt from 6 to 8 mL/kg PBW for one minute. At the end of the challenge, haemodynamic data (including pulse contour analysis-derived CI) and plethysmography data were recorded. After the Vt challenge, once CI had returned to its baseline value, a PLR test was performed as previously described [ 20 ]. When pulse contour analysis-derived CI was stable, i.e., over one minute, haemodynamic data (including pulse contour analysis-derived CI) and plethysmography data were collected. Immediately after PLR, transpulmonary thermodilution was performed again, and haemodynamic and plethysmography data were recorded. Finally, if the clinicians in charge decided to perform volume expansion, haemodynamic and plethysmography data were recorded, and immediately after, a 500-mL bolus of normal saline was infused over 15 min. Immediately after volume expansion, a final transpulmonary thermodilution measurement was performed, and all haemodynamic data (including thermodilution-derived CI) and plethysmography data were recorded. Statistical analysis Data distribution was assessed visually. Discrete numerical data were presented as numbers, continuous numerical data as median and interquartile range or mean ± SD, while categorical numbers were presented as number and percentage. The comparison between different study times was performed with a paired Student's t test or a Wilcoxon test. Comparisons between patient groups were performed by means of an unpaired Student's t test or a Mann-Whitney U test. Correlations were assessed using a Pearson test. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the ability of changes in PI, PPV, and CI induced by a Vt challenge to detect preload responsiveness, defined by a ≥ 10% increase in CI during PLR. The diagnostic threshold was selected as the threshold providing the best Youden index. Comparison of the areas under the ROC curves for multiple measurements (AUROCs) was carried out with the Hanley-McNeil test. Grey zones were calculated using the method defining three levels of response: positive, uncertain, and negative. Uncertain responses were defined using a two-step procedure. We first calculated the 95% CI of the Youden’s index resulting from a 1000 population bootstrap [ 21 ]. Then, we determined cut-off values for a sensitivity < 90% or a specificity < 90% (diagnosis tolerance of 10%). The largest interval from these two steps was used to determine the grey zone [ 21 ]. By estimating that the difference in PVI induced by the Vt challenge between preload responders and non-responders would be 4% [ 15 ], that the standard deviation of PVI in each of the groups would be 5% [ 15 ], considering an α risk of 5% and a β risk of 10%, we estimated that 42 patients should be included in the study. All tests were bilateral. A p value < 0.05 was considered significant. Statistical analysis was performed with MedCalc 20.218 software (MedCalc software Ltd., Mariakerke, Belgium). RESULTS Sixty-three patients were screened, of whom 14 were excluded because of an unstable PI signal on the fingertip and 7 because of atrial fibrillation. Their characteristics are shown in Supplemental table 1 . The baseline characteristics of the 42 included patients are summarized in Table 1 and Supplemental table 2. Table 1 Patient characteristics in preload responsive and non-responsive patients All patients Preload responders (n = 16) Preload non-responders (n = 26) p value Age (years) 62 ± 10 67 ± 10 59 ± 10 0.02 Sex (M/F) 32(76%)/10(23%) 10(63%)/6(37%) 22(85%)/4(15%) 0.11 SAPS II 55 ± 16 60 ± 15 51 ± 17 0.08 SOFA 15 ± 2 15 ± 2 14 ± 2 0.61 Lactate (mmol/L) 3.0 ± 2.2 3.4 ± 2.4 2.7 ± 2.0 0.33 LV ejection fraction (%) 40 ± 8 38 ± 7 41 ± 8 0.51 Origin of shock Septic 38 (91%) 16 (100%) 22(85%) 0.11 Hypovolaemic 1 (2.4%) 0 1 (4%) 0.42 Cardiogenic 1 (2.4%) 0 1 (4%) 0.42 Vasoplegic non-septic 2 (4.2%) 0 2 (7%) 0.29 Norepinephrine infusion 42 (100%) 16 (100%) 26 (100%) Dose of norepinephrine (µg/kg/min) 0.62 [1.00] 0.79 [1.39] 0.55 [0.80] 0.32 Vasopressin infusion 3 (7%) 2 (13%) 1 (4%) 0.29 ARDS 27 (64%) 9 (56%) 18 (69%) 0.40 Vt (mL/kg PBW) 375 ± 37 358 ± 33 385 ± 35 0.01 Respiratory rate (breaths/min) 25 ± 4 24 ± 4 26 ± 3 0.14 Plateau pressure (cmH 2 O) 20 ± 4 19 ± 4 21 ± 4 0.11 PEEP (cmH 2 O) 10 ± 2 10 ± 2 10 ± 2 0.52 PaO 2 /FiO 2 (mmHg) 205 ± 105 189 ± 98 214 ± 110 0.44 GEDVI (mL/m 2 ) 732 ± 168 716 ± 135 743 ± 188 0.62 EVLWI (mL/kg PBW) 11 ± 4 10 ± 3 12 ± 4 0.09 PVPI 2.0 ± 0.8 1.9 ± 0.6 2.3 ± 0.8 0.10 Values are expressed as n (%), mean ± SD or median [interquartile range]. ARDS: acute respiratory distress syndrome, EVLWI: extravascular lung water indexed for body weight, GEDVI: global end-diastolic volume indexed for body surface, ICU: intensive care unit, LV: left ventricle, PBW: predicted body weight, PEEP: positive end-expiratory pressure, PaO 2 /FiO 2 : oxygen arterial partial pressure over inspired fraction of oxygen, PVPI: pulmonary vascular permeability index, SAPS: simplified acute physiologic score, SOFA: sequential organ failure assessment, Vt: tidal volume. Effects of PLR and volume expansion Changes in haemodynamic variables are shown in Table 2 . In the 16 preload responders (38%), PLR increased CI by 17 ± 7%, while it did not change significantly during PLR in the 26 preload non-responders. Table 2 Haemodynamic and plethysmography variables at different study times in preload responsive and non-responsive patients. Baseline 1 Vt challenge Baseline 2 PLR Baseline 3 After volume expansion a Heart rate (beats/min) Preload responders (n = 16) 93 ± 15 93 ± 16 95 ± 17 93 ± 18* 87 ± 17 81 ± 1- Preload non-responders (n = 26) 86 ± 16 85 ± 16 84 ± 16* 82 ± 16 Systolic arterial pressure (mmHg) Preload responders (n = 16) 118 ± 22 117 ± 23 112 ± 16 124 ± 20* 118 ± 36 127 ± 37 Preload non-responders (n = 26) 126 ± 22 125 ± 24 130 ± 26# 134 ± 28* Mean arterial pressure (mmHg) Preload responders (n = 16) 77 ± 13 76 ± 14 71 ± 7 81 ± 9* 74 ± 22 84 ± 25* Preload non-responders (n = 26) 81 ± 20# 82 ± 21 85 ± 22# 83 ± 28* Diastolic arterial pressure (mmHg) Preload responders (n = 16) 57 ± 11 57 ± 11 55 ± 7 62 ± 10* 56 ± 14 62 ± 1* Preload non-responders (n = 26) 63 ± 11 63 ± 12 64 ± 10# 67 ± 10 Central venous pressure (mmHg) Preload responders (n = 16) 8 ± 5 9 ± 5 9 ± 5 12 ± 5* 7 ± 2 11 ± 6 Preload non-responders (n = 26) 11 ± 4 12 ± 4* 11 ± 3.62 13 ± 4.33* PPV (%) Preload responders (n = 16) 9 ± 7 13 ± 8* 12 ± 6 10 ± 8* 13 ± 9 10 ± 10* Preload non-responders (n = 26) 9 ± 7 10 ± 8* 6 ± 5# 6 ± 5 Cardiac index (L/min/m 2 ) Preload responders (n = 16) 2.54 ± 0.71 2.42 ± 0.70* 2.38 ± 0.75 2.77 ± 0.82* 2.12 ± 0.44 2.57 ± 0.54* Preload non-responders (n = 26) 2.98 ± 0.89 2.91 ± 0.89 * 3.08 ± 0.99# 3.14 ± 1.10 PI (%) Preload responders (n = 16) 0.44 ± 0.25 0.38 ± 0.23* 0.41 ± 0.21 0.49 ± 0.23* 0.47 ± 0.32 0.59 ± 0.41 Preload non-responders (n = 26) 1.47 ± 1.83# 1.45 ± 1.78# 1.84 ± 1.93# 1.81 ± 2.02*# PVI (%) Preload responders (n = 16) 16 ± 8 17 ± 8 20 ± 8 17 ± 6 18 ± 2 11 ± 5 Preload non-responders (n = 26) 15 ± 13 15 ± 12 16 ± 12 16 ± 11 Values are expressed as mean ± SD. For Baseline 3 and PLR in preload responders: n = 4. PI: perfusion index, PPV: pulse pressure variation, PVI: pleth variability index. a performed in 4 preload responders * p < 0.05 vs. Baseline # p < 0.05 vs. Preload responders. During PLR in preload responders, CI increased by 16.9 ± 6.5%. PPV expressed in absolute change (PPV before the Vt challenge – PPV during the Vt challenge) decreased by 3.5 ± 2.3%. Considering plethysmographic measurements performed on the finger, PI increased by 25.8 ± 21.6%, PVI expressed as absolute change decreased by 0.3 ± 1.4%. Results from measurements performed on the forehead are shown in Table 2 . All these changes except changes in PVI were larger than those observed during the PLR test in preload non-responders. Volume expansion was performed in four of the preload responsive patients. It increased CI by 21 ± 5%. In all these patients, the PLR test had increased CI changes by ≥ 10%. The changes in other haemodynamic variables during volume expansion are shown in Table 2 . Ability of PI changes to reflect CI changes, and of PVI to reflect PPV absolute values Taking all the changes measured between different study times (n = 88), the coefficient of correlation between PI measured on the forehead and CI relative changes was 0.58 (p < 0.001) (Supplementary Fig. 1). Taking all the measurements performed at different study times (n = 214), the coefficient of correlation between PVI measured on the forehead and PPV absolute values was 0.60 (p < 0.001) (Supplementary Fig. 2). Effects of the Vt challenge During the Vt challenge, CI decreased by 4.8 ± 2.8% in preload responders and by 2.3 ± 2.6% in preload non-responders (p < 0.001) (Table 2 ). Simultaneously, in preload responders, PPV (in absolute change), PI measured on the finger (in percent change), PVI measured on the finger (in absolute change), PI measured on the forehead (in percent change), PVI measured on the forehead (in absolute change) changed by 4.4 ± 1.9%, -14.5 ± 10.7%, 1.9 ± 2.6%, -18.7 ± 10.9 and 1.0 ± 2.5, respectively. All these changes were significantly larger than in preload non-responders. The changes in other variables are shown in Table 2 . Detection of preload responsiveness The ability of the changes in the variables investigated during PLR and the Vt challenge to detect preload responsiveness defined by a PLR-induced increase in CI ≥ 10% is described in Table 3 and Fig. 1 . The AUROCs generated by the Vt-challenge-induced changes in PI measured on the forehead were significantly larger than the Vt-challenge-induced changes in PI measured on the finger. Compared to the AUROCs generated by the Vt-challenge-induced changes in PPV and in PI measured on the forehead, the AUROCs generated by the PLR-induced changes in PVI (finger and forehead) were significantly smaller, while the other AUROCs were similar (Table 3 ). The grey zone for the Vt-challenge-induced changes in PI on the forehead to detect preload responsiveness ranged between − 3% and − 4%, in which 2 (5%) patients were situated (Supplementary Fig. 3). Table 3 Ability of tidal volume challenge-induced and passive leg raising-induced changes in haemodynamic variables to detect preload responsiveness. AUROC p value vs. 0.5 Diagnostic threshold Se Sp PPV NPV +LR -LR PLR-induced changes in PI (finger) (% change) 0.84 ± 0.08 0.001 > 18% 54.55 100.00 100.00 78.30 - 0.45 PLR-induced changes in PI (forehead) (% change) 0.95 ± 0.05 12% 90.00 94.12 90.00 94.10 15.30 0.11 PLR-induced changes in PPV (abs. change) 0.98 ± 0.02 < 0.001 ≤-2 points 90.91 100.00 100.00 95.20 - 0.09 PLR-induced changes in PVI (finger) (abs. change) 0.60 ± 0.12 0.41 <-2 points 0.00 100.00 - 66.70 - 1.00 PLR-induced changes in PVI (forehead) (abs. change) 0.53 ± 0.15 0.86 ≤-2 points 28.57 94.44 66.70 77.30 5.14 0.76 Vt-challenge-induced changes in CI (% change) 0.97 ± 0.02 < 0.001 ≤-3% 86.00 100.00 100.00 92.60 - 0.13 Vt-challenge-induced changes in PI (finger) (% change) 0.86 ± 0.06 < 0.001 ≤-7% 75.00 88.00 80.00 84.60 6.25 0.28 Vt-challenge-induced changes in PI (forehead) (% change) 0.98 ± 0.02 < 0.001 ≤-9% 86.67 95.83 92.90 92.00 20.80 0.14 Vt-challenge-induced changes in PPV (abs. change) 0.95 ± 0.04 2 points 87.50 96.15 93.30 92.60 22.75 0.13 Vt-challenge -induced changes in PVI (finger) (abs. change) 0.74 ± 0.08 0.007 > 1 point 53.33 91.67 80.00 75.90 6.40 0.51 Vt-challenge -induced changes in PVI (forehead) (abs. change) 0.62 ± 0.12 0.32 > 1 point 40.00 95.65 80.00 78.60 9.20 0.63 AUROC values are presented as value ± SE (standard error). +LR: positive likelihood ratio, -LR: negative likelihood ratio, AUROC: area under the receiver operating characteristic curve, CI: cardiac index, NPV: negative predictive value, PLR: passive leg raising, PPV: positive predictive value, PI: perfusion index, PVI: pleth variability index, Se: sensitivity, Sp: specificity, Vt: tidal volume DISCUSSION This study conducted in critically ill adult patients showed that the Vt challenge can detect preload responsiveness when performed by assessing the changes in PI. It is less reliable when assessing the changes in PVI. The study also confirms that preload responsiveness can be diagnosed by measuring the effects of PLR on PPV and PI. Conversely, the PLR-induced changes in PVI do not distinguish preload responsive from preload unresponsive patients. Placing the plethysmography sensor on the forehead improved the diagnostic ability of PI changes compared to placing the sensor placed on a finger. The Vt challenge has been described as a test that overcomes the limitation of PPV in patients ventilated with a Vt value at 6 mL/kg PBW, which generates false negatives for PPV as a marker of preload responsiveness [ 6 , 22 , 23 ]. A significant increase in PPV while Vt is transiently increased to 8 mL/kg reflects that the slope of the cardiac function curve is steep, predicting preload responsiveness. An advantage of the test is that it requires only a PPV measurement, i.e., it can be performed even if no direct cardiac output measurement is available. However, PPV requires an arterial catheter. As the ratio of the pulsatile and non-pulsatile portions of the plethysmography signal, PI has stroke volume as a determinant, among others. It has been shown to assess changes in CI induced by fluid loading [ 24 , 25 ] and various tests of preload responsiveness [ 11 , 12 ]. The present study shows that this is also the case for the Vt challenge. Vt-challenge-induced changes in PI detected preload responsiveness, defined by a positive PLR test, with a large AUROC and a narrow grey zone. This result was not obvious before the study, as the changes in CI induced by the Vt challenge are small, and the PI signal may have been unable to detect such small variations. This raises the possibility of performing the Vt challenge without any arterial pressure curve, for instance, before an arterial line is in place, in the operating setting in which no arterial catheter will be inserted, or in low-resource settings. Our study also shows for the first time that the Vt-challenge-induced decrease in CI measured by pulse contour analysis was excellent for detecting preload responsiveness. Importantly, a significant proportion of patients were excluded from analysis because of an unstable PI signal despite a 25-sec averaging period. This limitation was observed in previous studies performed in the ICU [ 11 ]. In contrast, it was absent in a study that tested PI changes to reflect changes in stroke volume during lung recruitment manoeuvres in the operating room setting, where the baseline value of PI was higher because of a lower degree of vasoconstriction [ 12 ]. Indeed, in the present study, the PI value of patients in whom PI was unstable was low, likely explaining a high noise-to-signal ratio. Also, we excluded patients with cardiac arrythmias, which are also responsible for PI instability [ 11 ]. Technical improvements may fix these instability problems, which limit the clinical applicability of our results in ICU patients. In line with this issue of vasoconstriction, the diagnostic ability of the Vt-challenge-induced changes in PI was better when measured on the forehead than on the fingertip. In the initial study describing the test, the haemodynamic effects of the Vt challenge were assessed not on stroke volume, but on PPV. This was based on the principle that if the 2 mL/kg-increase in Vt increases the degree of preload responsiveness, both ventricles are likely working in the steep part of the cardiac function curve. Based on the same principle, the decrease in PPV induced by a PLR test [ 26 – 28 ] or a PEEP test [ 28 ] also detects preload responsiveness. However, in the present study, changes in PVI induced by the Vt challenge or by PLR were unreliable in predicting preload responsiveness. We hypothesize that this is because PVI is unreliable in estimating PPV, as previously reported in critically ill patients [ 15 ]. The reliability of Vt-challenge-induced changes in PVI was not improved when the plethysmography sensor was placed on the forehead rather than on a finger. Our study has some limitations. First, we defined preload responsiveness using the effects on CI of PLR and not of fluid administration. We thought it was unethical to administer a fluid bolus even in the presence of preload responsiveness in critically ill patients - including some with ARDS - in whom an increased fluid balance is an independent risk factor of mortality [ 29 ]. Nevertheless, PLR has proven to be very reliable in predicting fluid responsiveness [ 30 ] and was used in previous studies to define preload responsiveness [ 11 , 28 , 31 , 32 ]. Accordingly, among the patients with a positive PLR test and who received fluid, all were fluid responsive. Second, our study included critically ill patients which, as stated above, may have decreased the ability of PVI to estimate PPV [ 15 ]. Third, we could not analyze the PVI signal, which was extracted directly from the Radical7 device, so that we cannot explain its poor reliability in estimating PPV. CONCLUSIONS We found that in mechanically ventilated patients without spontaneous breathing and atrial fibrillation, changes in PI but not changes in PVI during a Vt challenge accurately detected preload responsiveness. PI changes were more reliable when PI was measured on the forehead rather than on the finger. Abbreviations ARDS: acute respiratory distress syndrome AUROC: area under the ROC curve CI: cardiac index EVLWI: extravascular lung water indexed for body weight GEDVI: global end-diastolic volume indexed for body surface ICU: intensive care unit +LR: positive likelihood ratio -LR: negative likelihood ratio LV: left ventricle NPV: negative predictive value PaO 2 /FiO 2 : oxygen arterial partial pressure over inspired fraction of oxygen PBW: predicted body weight PEEP: positive end-expiratory pressure PI: perfusion index PLR: passive leg raising PPV: pulse pressure variation PVI: pleth variability index PVPI: pulmonary vascular permeability index SAPS: simplified acute physiologic score Se: sensitivity SOFA: sequential organ failure assessment Sp: specificity Vt: tidal volume Declarations Ethics approval and consent to participate ClinicalTrial.gov (NCT05428423). The trial protocol was approved by the ethics committee of the French Intensive Care Society (IDRCB: 2022-A01253-40). Informed consent was obtained from each patient or from the patient’s legally authorized representative if the patient was unable to provide consent. Alternatively, deferred informed consent was obtained from patients. The current study was performed in accordance with French law and the Declaration of Helsinki. Consent for publication Not applicable Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests X.M. is a member of the Medical Advisory Board of Pulsion Medical Systems (Getinge) and received honoraria for lectures from Pulsion Medical Systems (Getinge) and Baxter. J-L.T. is a member of the Medical Advisory Board of Pulsion Medical Systems (Getinge). The other authors have no conflict of interest to disclose. Funding None Authors’ contributions C.B. and C.L. had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: C.B. and X.M., with advice from all authors. Acquisition of data: C.B., R.S, D.R., G.F. and J.H. Analysis or interpretation of data: C.B., K.D. and X.M. Drafting of the manuscript: C.B. and X.M. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: C.B. and X.M. Administrative, technical, or material support: C.B., and X.M. Supervision: X.M. Acknowledgements None. References Messina A, Calabrò L, Pugliese L, Lulja A, Sopuch A, Rosalba D, Morenghi E, Hernandez G, Monnet X, Cecconi M. Fluid challenge in critically ill patients receiving haemodynamic monitoring: a systematic review and comparison of two decades. Crit Care. 2022 Jun 21;26(1):186. Malbrain MLNG, Van Regenmortel N, Saugel B, De Tavernier B, Van Gaal PJ, Joannes-Boyau O, Teboul JL, Rice TW, Mythen M, Monnet X. Principles of fluid management and stewardship in septic shock: it is time to consider the four D's and the four phases of fluid therapy. Ann Intensive Care. 2018 May 22;8(1):66. Evans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, Machado FR, Mcintyre L, Ostermann M, Prescott HC, Schorr C, Simpson S, Wiersinga WJ, Alshamsi F, Angus DC, Arabi Y, Azevedo L, Beale R, Beilman G, Belley-Cote E, Burry L, Cecconi M, Centofanti J, Coz Yataco A, De Waele J, Dellinger RP, Doi K, Du B, Estenssoro E, Ferrer R, Gomersall C, Hodgson C, Møller MH, Iwashyna T, Jacob S, Kleinpell R, Klompas M, Koh Y, Kumar A, Kwizera A, Lobo S, Masur H, McGloughlin S, Mehta S, Mehta Y, Mer M, Nunnally M, Oczkowski S, Osborn T, Papathanassoglou E, Perner A, Puskarich M, Roberts J, Schweickert W, Seckel M, Sevransky J, Sprung CL, Welte T, Zimmerman J, Levy M. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med. 2021 Nov;47(11):1181-1247. Teboul JL, Monnet X, Chemla D, Michard F. Arterial Pulse Pressure Variation with Mechanical Ventilation. Am J Respir Crit Care Med. 2019 Jan 1;199(1):22-31. Monnet X, Shi R, Teboul JL. Prediction of fluid responsiveness. What's new? Ann Intensive Care. 2022 May 28;12(1):46. De Backer D, Heenen S, Piagnerelli M, Koch M, Vincent JL. Pulse pressure variations to predict fluid responsiveness: influence of tidal volume. Intensive Care Med. 2005 Apr;31(4):517-23. Myatra SN, Prabu NR, Divatia JV, Monnet X, Kulkarni AP, Teboul JL. The Changes in Pulse Pressure Variation or Stroke Volume Variation After a "Tidal Volume Challenge" Reliably Predict Fluid Responsiveness During Low Tidal Volume Ventilation. Crit Care Med. 2017 Mar;45(3):415-421. Wang X, Liu S, Gao J, Zhang Y, Huang T. Does tidal volume challenge improve the feasibility of pulse pressure variation in patients mechanically ventilated at low tidal volumes? A systematic review and meta-analysis. Crit Care. 2023 Feb 2;27(1):45. Lima AP, Beelen P, Bakker J. Use of a peripheral perfusion index derived from the pulse oximetry signal as a noninvasive indicator of perfusion. Crit Care Med. 2002 Jun;30(6):1210-3. Beurton A, Teboul JL, Gavelli F, Gonzalez FA, Girotto V, Galarza L, Anguel N, Richard C, Monnet X. The effects of passive leg raising may be detected by the plethysmographic oxygen saturation signal in critically ill patients. Crit Care. 2019 Jan 18;23(1):19. Beurton A, Gavelli F, Teboul JL, De Vita N, Monnet X. Changes in the Plethysmographic Perfusion Index During an End-Expiratory Occlusion Detect a Positive Passive Leg Raising Test. Crit Care Med. 2021 Feb 1;49(2):e151-e160. de Courson H, Michard F, Chavignier C, Verchère E, Nouette-Gaulain K, Biais M. Do changes in perfusion index reflect changes in stroke volume during preload-modifying manoeuvres? J Clin Monit Comput. 2020 Dec;34(6):1193-1198. Cannesson M, Desebbe O, Rosamel P, Delannoy B, Robin J, Bastien O, Lehot JJ. Pleth variability index to monitor the respiratory variations in the pulse oximeter plethysmographic waveform amplitude and predict fluid responsiveness in the operating theatre. Br J Anaesth. 2008 Aug;101(2):200-6. Liu T, Xu C, Wang M, Niu Z, Qi D. Reliability of pleth variability index in predicting preload responsiveness of mechanically ventilated patients under various conditions: a systematic review and meta-analysis. BMC Anesthesiol. 2019 May 8;19(1):67. Monnet X, Guérin L, Jozwiak M, Bataille A, Julien F, Richard C, Teboul JL. Pleth variability index is a weak predictor of fluid responsiveness in patients receiving norepinephrine. Br J Anaesth. 2013 Feb;110(2):207-13. Fischer MO, Pellissier A, Saplacan V, Gérard JL, Hanouz JL, Fellahi JL. Cephalic versus digital plethysmographic variability index measurement: a comparative pilot study in cardiac surgery patients. J Cardiothorac Vasc Anesth. 2014 Dec;28(6):1510-5. Monnet X, Teboul JL. Transpulmonary thermodilution: advantages and limits. Crit Care. 2017 Jun 19;21(1):147. Monnet X, Persichini R, Ktari M, Jozwiak M, Richard C, Teboul JL. Precision of the transpulmonary thermodilution measurements. Crit Care. 2011 Aug 27;15(4):R204. Malbrain ML, Cheatham ML, Kirkpatrick A, Sugrue M, Parr M, De Waele J, Balogh Z, Leppäniemi A, Olvera C, Ivatury R, D'Amours S, Wendon J, Hillman K, Johansson K, Kolkman K, Wilmer A. Results from the International Conference of Experts on Intra-abdominal Hypertension and Abdominal Compartment Syndrome. I. Definitions. Intensive Care Med. 2006 Nov;32(11):1722-32. Monnet X, Teboul JL. Passive leg raising: five rules, not a drop of fluid! Crit Care. 2015 Jan 14;19(1):18. Cannesson M, Le Manach Y, Hofer CK, Goarin JP, Lehot JJ, Vallet B, Tavernier B. Assessing the diagnostic accuracy of pulse pressure variations for the prediction of fluid responsiveness: a "gray zone" approach. Anesthesiology. 2011 Aug;115(2):231-41. Monnet X, Malbrain MLNG, Pinsky MR. The prediction of fluid responsiveness. Intensive Care Med. 2023 Jan;49(1):83-86. De Backer D, Aissaoui N, Cecconi M, Chew MS, Denault A, Hajjar L, Hernandez G, Messina A, Myatra SN, Ostermann M, Pinsky MR, Teboul JL, Vignon P, Vincent JL, Monnet X. How can assessing hemodynamics help to assess volume status? Intensive Care Med. 2022 Oct;48(10):1482-1494. McGrath SP, Ryan KL, Wendelken SM, Rickards CA, Convertino VA. Pulse oximeter plethysmographic waveform changes in awake, spontaneously breathing, hypovolemic volunteers. Anesth Analg. 2011 Feb;112(2):368-74. Desgranges FP, Desebbe O, Ghazouani A, Gilbert K, Keller G, Chiari P, Robin J, Bastien O, Lehot JJ, Cannesson M. Influence of the site of measurement on the ability of plethysmographic variability index to predict fluid responsiveness. Br J Anaesth. 2011 Sep;107(3):329-35. Taccheri T, Gavelli F, Teboul JL, Shi R, Monnet X. Do changes in pulse pressure variation and inferior vena cava distensibility during passive leg raising and tidal volume challenge detect preload responsiveness in case of low tidal volume ventilation? Crit Care. 2021 Mar 18;25(1):110. Hamzaoui O, Shi R, Carelli S, Sztrymf B, Prat D, Jacobs F, Monnet X, Gouëzel C, Teboul JL. Changes in pulse pressure variation to assess preload responsiveness in mechanically ventilated patients with spontaneous breathing activity: an observational study. Br J Anaesth. 2021 Oct;127(4):532-538. Lai C, Shi R, Beurton A, Moretto F, Ayed S, Fage N, Gavelli F, Pavot A, Dres M, Teboul JL, Monnet X. The increase in cardiac output induced by a decrease in positive end-expiratory pressure reliably detects volume responsiveness: the PEEP-test study. Crit Care. 2023 Apr 9;27(1):136. Gavelli F, Shi R, Teboul JL, Azzolina D, Mercado P, Jozwiak M, Chew MS, Huber W, Kirov MY, Kuzkov VV, Lahmer T, Malbrain MLNG, Mallat J, Sakka SG, Tagami T, Pham T, Monnet X. Extravascular lung water levels are associated with mortality: a systematic review and meta-analysis. Crit Care. 2022 Jul 6;26(1):202. Monnet X, Marik P, Teboul JL. Passive leg raising for predicting fluid responsiveness: a systematic review and meta-analysis. Intensive Care Med. 2016 Dec;42(12):1935-1947. Gavelli F, Beurton A, Teboul JL, De Vita N, Azzolina D, Shi R, Pavot A, Monnet X. Bioreactance reliably detects preload responsiveness by the end-expiratory occlusion test when averaging and refresh times are shortened. Ann Intensive Care. 2021 Aug 28;11(1):133. Shi R, Moretto F, Prat D, et al. Dynamic changes of pulse pressure but not of pulse pressure variation during passive leg raising predict preload responsiveness in critically ill patients with spontaneous breathing activity. Journal of Critical Care. 2022 Dec;72:154141. Additional Declarations Competing interest reported. X.M. is a member of the Medical Advisory Board of Pulsion Medical Systems (Getinge) and received honoraria for lectures from Pulsion Medical Systems (Getinge) and Baxter. J-L.T. is a member of the Medical Advisory Board of Pulsion Medical Systems (Getinge). The other authors have no conflict of interest to disclose. 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SHI","email":"","orcid":"","institution":"AP-HP, Hôpital de Bicêtre, Inserm UMR S_999, FHU SEPSIS, CARMAS, Université Paris-Saclay","correspondingAuthor":false,"prefix":"","firstName":"Rui","middleName":"","lastName":"SHI","suffix":""},{"id":320568564,"identity":"4fdecd85-c607-43ef-8a84-5d878024abf8","order_by":2,"name":"Daniela ROSALBA","email":"","orcid":"","institution":"AP-HP, Hôpital de Bicêtre, Inserm UMR S_999, FHU SEPSIS, CARMAS, Université Paris-Saclay","correspondingAuthor":false,"prefix":"","firstName":"Daniela","middleName":"","lastName":"ROSALBA","suffix":""},{"id":320568565,"identity":"fbd465f0-ae10-4dee-a9d7-f2f64ccb8319","order_by":3,"name":"Gaelle FOUQUE","email":"","orcid":"","institution":"AP-HP, Hôpital de Bicêtre, Inserm UMR S_999, FHU SEPSIS, CARMAS, Université Paris-Saclay","correspondingAuthor":false,"prefix":"","firstName":"Gaelle","middleName":"","lastName":"FOUQUE","suffix":""},{"id":320568566,"identity":"1987fa12-c556-4a4b-9afd-332f1b876e04","order_by":4,"name":"Julien HAGRY","email":"","orcid":"","institution":"AP-HP, Hôpital de Bicêtre, Inserm UMR S_999, FHU SEPSIS, CARMAS, Université Paris-Saclay","correspondingAuthor":false,"prefix":"","firstName":"Julien","middleName":"","lastName":"HAGRY","suffix":""},{"id":320568567,"identity":"d6f5e989-cd0f-49d4-b3c2-8bd5a96f2823","order_by":5,"name":"Christopher LAI","email":"","orcid":"","institution":"AP-HP, Hôpital de Bicêtre, Inserm UMR S_999, FHU SEPSIS, CARMAS, Université Paris-Saclay","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"","lastName":"LAI","suffix":""},{"id":320568568,"identity":"63614b85-cf1c-4b1c-b7b6-092bbc0e9b03","order_by":6,"name":"Katia DONADELLO","email":"","orcid":"","institution":"Department of Anesthesia and Intensive Care B, Department of Surgery, Dentistry, Gynaecology and Pediatrics, University of Verona, AOUI-University Hospital Integrated Trust of Verona","correspondingAuthor":false,"prefix":"","firstName":"Katia","middleName":"","lastName":"DONADELLO","suffix":""},{"id":320568569,"identity":"e72cf999-ba39-45b4-952c-98f52ae6afb8","order_by":7,"name":"Jean-Louis TEBOUL","email":"","orcid":"","institution":"AP-HP, Hôpital de Bicêtre, Inserm UMR S_999, FHU SEPSIS, CARMAS, Université Paris-Saclay","correspondingAuthor":false,"prefix":"","firstName":"Jean-Louis","middleName":"","lastName":"TEBOUL","suffix":""},{"id":320568570,"identity":"c7735a18-fbec-45fd-a872-3f9e38d08d56","order_by":8,"name":"Xavier MONNET","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYJCCAwhmBQODAZD6QLyWA2fAWhhnEG/fwTYitBgcP2N44OMehmh+6d6Djz/Os8szl25gbK7Ao0WyJ8fg4IxnDLkz55xLNji4LbnYcs4BxsYzeLTwM6QlHOY5wJC74UaOmcTBbcyJG24ksD9swKOFjf9ZwuE/EC3mPw7OqQdpYWzEp4VfIvnAYQaoLQwHGw4T1iI54/GBgz0HJHJnzsgxljhz7HixwZ2DjXi1GJxPbP7w44BNbr9EjuGHiprqPIPbzQfxaoECCTgrgUGCkQgNyCABSfsoGAWjYBSMAjAAAPu4WtpYvhbAAAAAAElFTkSuQmCC","orcid":"","institution":"AP-HP, Hôpital de Bicêtre, Inserm UMR S_999, FHU SEPSIS, CARMAS, Université Paris-Saclay","correspondingAuthor":true,"prefix":"","firstName":"Xavier","middleName":"","lastName":"MONNET","suffix":""}],"badges":[],"createdAt":"2024-06-13 09:29:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4575103/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4575103/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13054-024-05085-w","type":"published","date":"2024-09-16T15:57:24+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60428670,"identity":"6544f416-cd14-4cf4-b9c6-42f2fa455f75","added_by":"auto","created_at":"2024-07-16 15:58:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":164926,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristics curves describing the ability to detect preload responsiveness of the tidal-volume-challenge-induced changes in pulse pressure variation (PPV, change in absolute value), in the pleth variability index measured on the finger (PVI, change in absolute value) and in the perfusion index measured on the finger (PI, change in percent).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4575103/v1/d4c76b05d121edc2f69f646a.png"},{"id":65103966,"identity":"4e577e2e-3626-47ad-87fc-04c45a7a9021","added_by":"auto","created_at":"2024-09-23 16:10:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1302350,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4575103/v1/22d69eb8-e5fb-489e-beb3-9e0d540e192f.pdf"},{"id":60428668,"identity":"0192de54-3eea-4e4b-bf31-962bd9c4d3c5","added_by":"auto","created_at":"2024-07-16 15:58:38","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":256842,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementTestingpreloadresponsivenessbythetidalvolumechallengeassessedbytheplethysmographicperfusionindex.docx","url":"https://assets-eu.researchsquare.com/files/rs-4575103/v1/c9df5d1167123ba71419e8b6.docx"}],"financialInterests":"Competing interest reported. X.M. is a member of the Medical Advisory Board of Pulsion Medical Systems (Getinge) and received honoraria for lectures from Pulsion Medical Systems (Getinge) and Baxter.\nJ-L.T. is a member of the Medical Advisory Board of Pulsion Medical Systems (Getinge).\nThe other authors have no conflict of interest to disclose.","formattedTitle":"Testing preload responsiveness by the tidal volume challenge assessed by the plethysmographic perfusion index","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eIn patients with acute circulatory failure, after initial fluid resuscitation, fluid infusion increases cardiac output in only half of them [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. As undue fluid infusion may contribute to fluid accumulation, the deleterious effect of which is clearly demonstrated [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], it is recommended to assess preload responsiveness before deciding to perform volume expansion [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. For this purpose, pulse pressure variation (PPV), i.e., the change in arterial pulse pressure amplitude during mechanical ventilation which reflects the simultaneous change in stroke volume, is very reliable, but can be used in few patients because of strict conditions of use [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Among such conditions, tidal volume (Vt) must be \u0026ge;\u0026thinsp;8 mL/kg of predicted body weight (PBW), as lower Vt values create false negatives [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo overcome this limitation, the Vt challenge has been described in mechanically ventilated patients [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. It consists in transiently increasing Vt from 6 to 8 mL/kg PBW, and looking for a significant increase in PPV, reflecting that the slope of the cardiac function curve is steep. However, the Vt challenge has two limitations. First, although it has been validated by several studies, the diagnostic threshold they reported is variable [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Second, it requires an arterial pressure curve, which is usually plotted by using an arterial catheter.\u003c/p\u003e \u003cp\u003eThe plethysmography signal may be helpful in dispensing with the need for an arterial catheter. This signal is composed of a pulsatile portion and a non-pulsatile portion [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The ratio of the amplitude of the former to the latter, called the \u0026ldquo;perfusion index\u0026rdquo; (PI), has two determinants: the degree of vasoconstriction of the tissue in which the oxygen saturation of haemoglobin is measured, and stroke volume [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Thus, over short time periods, changes in PI may reflect changes in stroke volume, as shown during fluid loading [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], passive leg raising (PLR) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], recruitment manoeuvres [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and the end-expiratory occlusion test [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Also, the change in PI under mechanical ventilation, called \u0026ldquo;pleth variability index\u0026rdquo; (PVI), has been used to estimate PPV [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. PVI has been shown to detect preload responsiveness [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], while opposite results have been recorded in critically ill patients receiving norepinephrine [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. To overcome this vasoconstriction bias, it has been proposed to attach the plethysmography sensor to the forehead or the earlobe rather than to the finger [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. It has not yet been tested whether the changes in PI or PVI could be used to assess the effects of the Vt challenge, with a larger increase in PI and a larger decrease in preload responders than non-responders. This would allow one to perform the test without any arterial catheter.\u003c/p\u003e \u003cp\u003eTherefore, the primary goal of this study was to assess the ability of PI changes induced by a Vt challenge to diagnose preload responsiveness in critically ill adult patients. The secondary aims were (i) to test whether Vt-challenge-induced changes in PVI reliably diagnose preload responsiveness, (ii) to compare this diagnostic value of changes in PI and PVI according to the location of plethysmographic measurement (finger vs. forehead) and (iii) to compare the changes in PPV, PVI and PI during a PLR test and volume expansion.\u003c/p\u003e"},{"header":"PATIENTS AND METHODS","content":"\u003cp\u003e This prospective study was conducted in the 25-bed medical intensive care unit (ICU) of the Bic\u0026ecirc;tre hospital (Assistance publique-H\u0026ocirc;pitaux de Paris). It was approved by the ethics committee of the French Intensive Care Society (SC016-18). All patients or their next of kin were informed about the study and agreed to participate.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003ePatients were included if they presented the following criteria: (i) age\u0026thinsp;\u0026ge;\u0026thinsp;18 y.o., (ii) hospitalization in the ICU, (iii) invasive mechanical ventilation in assist controlled mode with a Vt of 6 mL/kg PBW, (iv) monitoring already in place with a transpulmonary thermodilution PiCCO2 system (Pulsion Medical Systems, Getinge, Feldkirchen, Germany) and with a plethysmography Masimo SET device (Masimo Corporation, Irvine, CA) and (v) decision by the clinicians in charge to assess preload responsiveness through a Vt challenge and a PLR test.\u003c/p\u003e \u003cp\u003ePatients were excluded if (i) they presented spontaneous breathing activity, as assessed by visual observation of the airway pressure curve, (ii) they presented atrial fibrillation, (iii) the PI signal on the fingertip was unstable, (iv) chest drainage was in place, (v) they were pregnant and (vi) they presented frequent extrasystoles. Patients were not included if the investigators were not available, and if they refused to participate in the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMeasurements\u003c/h2\u003e \u003cp\u003eAll patients were equipped with an internal jugular venous catheter and a thermistor-tipped arterial catheter introduced through the femoral artery. Cardiac output was measured by pulse contour analysis and transpulmonary thermodilution [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. For the latter, three injections of cold saline boluses were averaged [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Intra-abdominal pressure was measured through bladder pressure [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Arterial, central venous and airway pressures were continuously recorded by HEM3.2 software (Notocord, Croissy-sur-Seine, France). Data from the PiCCO2 device, including cardiac index (CI), arterial and central venous pressures and PPV were continuously recorded by PiCCOWin software (Pulsion Medical Systems, Getinge, Feldkirchen, Germany).\u003c/p\u003e \u003cp\u003eA plethysmography sensor (Masimo Corporation, Irvine, CA) was placed on the index of either hand and another one on the forehead and connected to the Masimo SET device to measure pulse oxygen saturation (SpO\u003csub\u003e2\u003c/sub\u003e), PI and PVI. Data were extracted \u003cem\u003ea posteriori\u003c/em\u003e through a USB stick and analyzed on an Excel spreadsheet (Microsoft, Richmond, CA). PI values were averaged over a 25-sec moving period. Among ventilatory data, we collected Vt, respiratory rate, and plateau and positive end-expiratory pressures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eOnce the patient was included in the study, demographic and ventilatory data were collected, the PICCO2 device was calibrated and a first set of haemodynamic and plethysmography data was recorded. A Vt challenge was then performed as previously described [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] by increasing Vt from 6 to 8 mL/kg PBW for one minute. At the end of the challenge, haemodynamic data (including pulse contour analysis-derived CI) and plethysmography data were recorded.\u003c/p\u003e \u003cp\u003eAfter the Vt challenge, once CI had returned to its baseline value, a PLR test was performed as previously described [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. When pulse contour analysis-derived CI was stable, i.e., over one minute, haemodynamic data (including pulse contour analysis-derived CI) and plethysmography data were collected. Immediately after PLR, transpulmonary thermodilution was performed again, and haemodynamic and plethysmography data were recorded. Finally, if the clinicians in charge decided to perform volume expansion, haemodynamic and plethysmography data were recorded, and immediately after, a 500-mL bolus of normal saline was infused over 15 min. Immediately after volume expansion, a final transpulmonary thermodilution measurement was performed, and all haemodynamic data (including thermodilution-derived CI) and plethysmography data were recorded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData distribution was assessed visually. Discrete numerical data were presented as numbers, continuous numerical data as median and interquartile range or mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, while categorical numbers were presented as number and percentage.\u003c/p\u003e \u003cp\u003eThe comparison between different study times was performed with a paired Student's t test or a Wilcoxon test. Comparisons between patient groups were performed by means of an unpaired Student's t test or a Mann-Whitney U test. Correlations were assessed using a Pearson test. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the ability of changes in PI, PPV, and CI induced by a Vt challenge to detect preload responsiveness, defined by a\u0026thinsp;\u0026ge;\u0026thinsp;10% increase in CI during PLR. The diagnostic threshold was selected as the threshold providing the best Youden index. Comparison of the areas under the ROC curves for multiple measurements (AUROCs) was carried out with the Hanley-McNeil test. Grey zones were calculated using the method defining three levels of response: positive, uncertain, and negative. Uncertain responses were defined using a two-step procedure. We first calculated the 95% CI of the Youden\u0026rsquo;s index resulting from a 1000 population bootstrap [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Then, we determined cut-off values for a sensitivity\u0026thinsp;\u0026lt;\u0026thinsp;90% or a specificity\u0026thinsp;\u0026lt;\u0026thinsp;90% (diagnosis tolerance of 10%). The largest interval from these two steps was used to determine the grey zone [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBy estimating that the difference in PVI induced by the Vt challenge between preload responders and non-responders would be 4% [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], that the standard deviation of PVI in each of the groups would be 5% [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], considering an α risk of 5% and a β risk of 10%, we estimated that 42 patients should be included in the study. All tests were bilateral. A p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant. Statistical analysis was performed with MedCalc 20.218 software (MedCalc software Ltd., Mariakerke, Belgium).\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eSixty-three patients were screened, of whom 14 were excluded because of an unstable PI signal on the fingertip and 7 because of atrial fibrillation. Their characteristics are shown in Supplemental table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The baseline characteristics of the 42 included patients are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Supplemental table 2.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient characteristics in preload responsive and non-responsive patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAll patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePreload responders (n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePreload non-responders (n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex (M/F)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(76%)/10(23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(63%)/6(37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22(85%)/4(15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSAPS II\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSOFA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLactate (mmol/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLV ejection fraction (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOrigin of shock\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSeptic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22(85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHypovolaemic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCardiogenic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eVasoplegic non-septic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNorepinephrine infusion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDose of norepinephrine (\u0026micro;g/kg/min)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62 [1.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79 [1.39]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55 [0.80]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVasopressin infusion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eARDS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18 (69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVt (mL/kg PBW)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e375\u0026thinsp;\u0026plusmn;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e358\u0026thinsp;\u0026plusmn;\u0026thinsp;33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e385\u0026thinsp;\u0026plusmn;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRespiratory rate (breaths/min)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlateau pressure (cmH\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003cb\u003eO)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePEEP (cmH\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003cb\u003eO)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePaO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003cb\u003e/FiO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e205\u0026thinsp;\u0026plusmn;\u0026thinsp;105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e189\u0026thinsp;\u0026plusmn;\u0026thinsp;98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e214\u0026thinsp;\u0026plusmn;\u0026thinsp;110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGEDVI (mL/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e732\u0026thinsp;\u0026plusmn;\u0026thinsp;168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e716\u0026thinsp;\u0026plusmn;\u0026thinsp;135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e743\u0026thinsp;\u0026plusmn;\u0026thinsp;188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEVLWI (mL/kg PBW)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePVPI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eValues are expressed as n (%), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or median [interquartile range].\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eARDS: acute respiratory distress syndrome, EVLWI: extravascular lung water indexed for body weight, GEDVI: global end-diastolic volume indexed for body surface, ICU: intensive care unit, LV: left ventricle, PBW: predicted body weight, PEEP: positive end-expiratory pressure, PaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e: oxygen arterial partial pressure over inspired fraction of oxygen, PVPI: pulmonary vascular permeability index, SAPS: simplified acute physiologic score, SOFA: sequential organ failure assessment, Vt: tidal volume.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEffects of PLR and volume expansion\u003c/h2\u003e \u003cp\u003eChanges in haemodynamic variables are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In the 16 preload responders (38%), PLR increased CI by 17\u0026thinsp;\u0026plusmn;\u0026thinsp;7%, while it did not change significantly during PLR in the 26 preload non-responders.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHaemodynamic and plethysmography variables at different study times in preload responsive and non-responsive patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBaseline 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVt challenge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBaseline 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePLR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBaseline 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAfter volume expansion\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHeart rate (beats/min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload responders (n\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93\u0026thinsp;\u0026plusmn;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e93\u0026thinsp;\u0026plusmn;\u0026thinsp;18*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e87\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e81\u0026thinsp;\u0026plusmn;\u0026thinsp;1-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload non-responders (n\u0026thinsp;=\u0026thinsp;26)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84\u0026thinsp;\u0026plusmn;\u0026thinsp;16*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSystolic arterial pressure (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload responders (n\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118\u0026thinsp;\u0026plusmn;\u0026thinsp;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e117\u0026thinsp;\u0026plusmn;\u0026thinsp;23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e112\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e124\u0026thinsp;\u0026plusmn;\u0026thinsp;20*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e118\u0026thinsp;\u0026plusmn;\u0026thinsp;36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e127\u0026thinsp;\u0026plusmn;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload non-responders (n\u0026thinsp;=\u0026thinsp;26)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126\u0026thinsp;\u0026plusmn;\u0026thinsp;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125\u0026thinsp;\u0026plusmn;\u0026thinsp;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e130\u0026thinsp;\u0026plusmn;\u0026thinsp;26#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e134\u0026thinsp;\u0026plusmn;\u0026thinsp;28*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean arterial pressure (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload responders (n\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81\u0026thinsp;\u0026plusmn;\u0026thinsp;9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e74\u0026thinsp;\u0026plusmn;\u0026thinsp;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e84\u0026thinsp;\u0026plusmn;\u0026thinsp;25*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload non-responders (n\u0026thinsp;=\u0026thinsp;26)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81\u0026thinsp;\u0026plusmn;\u0026thinsp;20#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82\u0026thinsp;\u0026plusmn;\u0026thinsp;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85\u0026thinsp;\u0026plusmn;\u0026thinsp;22#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83\u0026thinsp;\u0026plusmn;\u0026thinsp;28*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiastolic arterial pressure (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload responders (n\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;10*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;1*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload non-responders (n\u0026thinsp;=\u0026thinsp;26)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64\u0026thinsp;\u0026plusmn;\u0026thinsp;10#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCentral venous pressure (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload responders (n\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;5*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload non-responders (n\u0026thinsp;=\u0026thinsp;26)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u0026thinsp;\u0026plusmn;\u0026thinsp;4.33*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePPV (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload responders (n\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u0026thinsp;\u0026plusmn;\u0026thinsp;8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;10*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload non-responders (n\u0026thinsp;=\u0026thinsp;26)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;5#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCardiac index (L/min/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload responders (n\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload non-responders (n\u0026thinsp;=\u0026thinsp;26)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89 *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePI (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload responders (n\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload non-responders (n\u0026thinsp;=\u0026thinsp;26)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.93#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.81\u0026thinsp;\u0026plusmn;\u0026thinsp;2.02*#\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePVI (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload responders (n\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePreload non-responders (n\u0026thinsp;=\u0026thinsp;26)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eValues are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. For Baseline 3 and PLR in preload responders: n\u0026thinsp;=\u0026thinsp;4.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003ePI: perfusion index, PPV: pulse pressure variation, PVI: pleth variability index.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003ea\u003c/sup\u003e performed in 4 preload responders\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 vs. Baseline\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e# p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 vs. Preload responders.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDuring PLR in preload responders, CI increased by 16.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5%. PPV expressed in absolute change (PPV before the Vt challenge \u0026ndash; PPV during the Vt challenge) decreased by 3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3%. Considering plethysmographic measurements performed on the finger, PI increased by 25.8\u0026thinsp;\u0026plusmn;\u0026thinsp;21.6%, PVI expressed as absolute change decreased by 0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4%. Results from measurements performed on the forehead are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. All these changes except changes in PVI were larger than those observed during the PLR test in preload non-responders.\u003c/p\u003e \u003cp\u003eVolume expansion was performed in four of the preload responsive patients. It increased CI by 21\u0026thinsp;\u0026plusmn;\u0026thinsp;5%. In all these patients, the PLR test had increased CI changes by \u0026ge;\u0026thinsp;10%. The changes in other haemodynamic variables during volume expansion are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eAbility of PI changes to reflect CI changes, and of PVI to reflect PPV absolute values\u003c/em\u003e \u003c/p\u003e \u003cp\u003eTaking all the changes measured between different study times (n\u0026thinsp;=\u0026thinsp;88), the coefficient of correlation between PI measured on the forehead and CI relative changes was 0.58 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Supplementary Fig.\u0026nbsp;1). Taking all the measurements performed at different study times (n\u0026thinsp;=\u0026thinsp;214), the coefficient of correlation between PVI measured on the forehead and PPV absolute values was 0.60 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Supplementary Fig.\u0026nbsp;2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003eEffects of the Vt challenge\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eDuring the Vt challenge, CI decreased by 4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8% in preload responders and by 2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6% in preload non-responders (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Simultaneously, in preload responders, PPV (in absolute change), PI measured on the finger (in percent change), PVI measured on the finger (in absolute change), PI measured on the forehead (in percent change), PVI measured on the forehead (in absolute change) changed by 4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9%, -14.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7%, 1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6%, -18.7\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9 and 1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5, respectively. All these changes were significantly larger than in preload non-responders. The changes in other variables are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDetection of preload responsiveness\u003c/h2\u003e \u003cp\u003eThe ability of the changes in the variables investigated during PLR and the Vt challenge to detect preload responsiveness defined by a PLR-induced increase in CI\u0026thinsp;\u0026ge;\u0026thinsp;10% is described in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The AUROCs generated by the Vt-challenge-induced changes in PI measured on the forehead were significantly larger than the Vt-challenge-induced changes in PI measured on the finger. Compared to the AUROCs generated by the Vt-challenge-induced changes in PPV and in PI measured on the forehead, the AUROCs generated by the PLR-induced changes in PVI (finger and forehead) were significantly smaller, while the other AUROCs were similar (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The grey zone for the Vt-challenge-induced changes in PI on the forehead to detect preload responsiveness ranged between \u0026minus;\u0026thinsp;3% and \u0026minus;\u0026thinsp;4%, in which 2 (5%) patients were situated (Supplementary Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAbility of tidal volume challenge-induced and passive leg raising-induced changes in haemodynamic variables to detect preload responsiveness.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUROC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep value vs. 0.5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDiagnostic threshold\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSp\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e+LR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-LR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePLR-induced changes in PI\u003c/b\u003e\u003csub\u003e\u003cb\u003e(finger)\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(% change)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e78.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePLR-induced changes in PI\u003c/b\u003e \u003csub\u003e\u003cb\u003e(forehead)\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(% change)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;12%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e94.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePLR-induced changes in PPV (abs. change)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026le;-2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePLR-induced changes in PVI\u003c/b\u003e\u003csub\u003e\u003cb\u003e(finger)\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(abs. change)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;-2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e66.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePLR-induced changes in PVI\u003c/b\u003e\u003csub\u003e\u003cb\u003e(forehead)\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(abs. change)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026le;-2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e77.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVt-challenge-induced changes in CI (% change)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026le;-3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e92.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVt-challenge-induced changes in PI\u003c/b\u003e\u003csub\u003e\u003cb\u003e(finger)\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(% change)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026le;-7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e84.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVt-challenge-induced changes in PI\u003c/b\u003e\u003csub\u003e\u003cb\u003e(forehead)\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(% change)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026le;-9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e92.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e92.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVt-challenge-induced changes in PPV (abs. change)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e92.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVt-challenge -induced changes in PVI\u003c/b\u003e\u003csub\u003e\u003cb\u003e(finger)\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(abs. change)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1 point\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e91.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e75.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVt-challenge -induced changes in PVI\u003c/b\u003e\u003csub\u003e\u003cb\u003e(forehead)\u003c/b\u003e\u003c/sub\u003e \u003cb\u003e(abs. change)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1 point\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e78.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eAUROC values are presented as value\u0026thinsp;\u0026plusmn;\u0026thinsp;SE (standard error).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e+LR: positive likelihood ratio, -LR: negative likelihood ratio, AUROC: area under the receiver operating characteristic curve, CI: cardiac index, NPV: negative predictive value, PLR: passive leg raising, PPV: positive predictive value, PI: perfusion index, PVI: pleth variability index, Se: sensitivity, Sp: specificity, Vt: tidal volume\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study conducted in critically ill adult patients showed that the Vt challenge can detect preload responsiveness when performed by assessing the changes in PI. It is less reliable when assessing the changes in PVI. The study also confirms that preload responsiveness can be diagnosed by measuring the effects of PLR on PPV and PI. Conversely, the PLR-induced changes in PVI do not distinguish preload responsive from preload unresponsive patients. Placing the plethysmography sensor on the forehead improved the diagnostic ability of PI changes compared to placing the sensor placed on a finger.\u003c/p\u003e \u003cp\u003eThe Vt challenge has been described as a test that overcomes the limitation of PPV in patients ventilated with a Vt value at 6 mL/kg PBW, which generates false negatives for PPV as a marker of preload responsiveness [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. A significant increase in PPV while Vt is transiently increased to 8 mL/kg reflects that the slope of the cardiac function curve is steep, predicting preload responsiveness. An advantage of the test is that it requires only a PPV measurement, i.e., it can be performed even if no direct cardiac output measurement is available. However, PPV requires an arterial catheter.\u003c/p\u003e \u003cp\u003eAs the ratio of the pulsatile and non-pulsatile portions of the plethysmography signal, PI has stroke volume as a determinant, among others. It has been shown to assess changes in CI induced by fluid loading [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and various tests of preload responsiveness [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The present study shows that this is also the case for the Vt challenge. Vt-challenge-induced changes in PI detected preload responsiveness, defined by a positive PLR test, with a large AUROC and a narrow grey zone. This result was not obvious before the study, as the changes in CI induced by the Vt challenge are small, and the PI signal may have been unable to detect such small variations. This raises the possibility of performing the Vt challenge without any arterial pressure curve, for instance, before an arterial line is in place, in the operating setting in which no arterial catheter will be inserted, or in low-resource settings. Our study also shows for the first time that the Vt-challenge-induced decrease in CI measured by pulse contour analysis was excellent for detecting preload responsiveness.\u003c/p\u003e \u003cp\u003eImportantly, a significant proportion of patients were excluded from analysis because of an unstable PI signal despite a 25-sec averaging period. This limitation was observed in previous studies performed in the ICU [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In contrast, it was absent in a study that tested PI changes to reflect changes in stroke volume during lung recruitment manoeuvres in the operating room setting, where the baseline value of PI was higher because of a lower degree of vasoconstriction [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Indeed, in the present study, the PI value of patients in whom PI was unstable was low, likely explaining a high noise-to-signal ratio. Also, we excluded patients with cardiac arrythmias, which are also responsible for PI instability [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Technical improvements may fix these instability problems, which limit the clinical applicability of our results in ICU patients. In line with this issue of vasoconstriction, the diagnostic ability of the Vt-challenge-induced changes in PI was better when measured on the forehead than on the fingertip.\u003c/p\u003e \u003cp\u003eIn the initial study describing the test, the haemodynamic effects of the Vt challenge were assessed not on stroke volume, but on PPV. This was based on the principle that if the 2 mL/kg-increase in Vt increases the degree of preload responsiveness, both ventricles are likely working in the steep part of the cardiac function curve. Based on the same principle, the decrease in PPV induced by a PLR test [\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] or a PEEP test [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] also detects preload responsiveness. However, in the present study, changes in PVI induced by the Vt challenge or by PLR were unreliable in predicting preload responsiveness. We hypothesize that this is because PVI is unreliable in estimating PPV, as previously reported in critically ill patients [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The reliability of Vt-challenge-induced changes in PVI was not improved when the plethysmography sensor was placed on the forehead rather than on a finger.\u003c/p\u003e \u003cp\u003eOur study has some limitations. First, we defined preload responsiveness using the effects on CI of PLR and not of fluid administration. We thought it was unethical to administer a fluid bolus even in the presence of preload responsiveness in critically ill patients - including some with ARDS - in whom an increased fluid balance is an independent risk factor of mortality [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Nevertheless, PLR has proven to be very reliable in predicting fluid responsiveness [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] and was used in previous studies to define preload responsiveness [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Accordingly, among the patients with a positive PLR test and who received fluid, all were fluid responsive. Second, our study included critically ill patients which, as stated above, may have decreased the ability of PVI to estimate PPV [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Third, we could not analyze the PVI signal, which was extracted directly from the Radical7 device, so that we cannot explain its poor reliability in estimating PPV.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eWe found that in mechanically ventilated patients without spontaneous breathing and atrial fibrillation, changes in PI but not changes in PVI during a Vt challenge accurately detected preload responsiveness. PI changes were more reliable when PI was measured on the forehead rather than on the finger.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eARDS: acute respiratory distress syndrome\u003c/p\u003e\n\u003cp\u003eAUROC:\u0026nbsp;area under the ROC curve\u003c/p\u003e\n\u003cp\u003eCI: cardiac index\u003c/p\u003e\n\u003cp\u003eEVLWI: extravascular lung water indexed for body weight\u003c/p\u003e\n\u003cp\u003eGEDVI: global end-diastolic volume indexed for body surface\u003c/p\u003e\n\u003cp\u003eICU: intensive care unit\u003c/p\u003e\n\u003cp\u003e+LR: positive likelihood ratio\u003c/p\u003e\n\u003cp\u003e-LR: negative likelihood ratio\u003c/p\u003e\n\u003cp\u003eLV: left ventricle\u003c/p\u003e\n\u003cp\u003eNPV: negative predictive value\u003c/p\u003e\n\u003cp\u003ePaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e: oxygen arterial partial pressure over inspired fraction of oxygen\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePBW: predicted body weight\u003c/p\u003e\n\u003cp\u003ePEEP: positive end-expiratory pressure\u003c/p\u003e\n\u003cp\u003ePI: perfusion index\u003c/p\u003e\n\u003cp\u003ePLR: passive leg raising\u003c/p\u003e\n\u003cp\u003ePPV: pulse pressure variation\u003c/p\u003e\n\u003cp\u003ePVI: pleth variability index\u003c/p\u003e\n\u003cp\u003ePVPI: pulmonary vascular permeability index\u003c/p\u003e\n\u003cp\u003eSAPS: simplified acute physiologic score\u003c/p\u003e\n\u003cp\u003eSe: sensitivity\u003c/p\u003e\n\u003cp\u003eSOFA: sequential organ failure assessment\u003c/p\u003e\n\u003cp\u003eSp: specificity\u003c/p\u003e\n\u003cp\u003eVt: tidal volume\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eClinicalTrial.gov (NCT05428423).\u003c/p\u003e\n\u003cp\u003eThe trial protocol was approved by the ethics committee of the French Intensive Care Society (IDRCB: 2022-A01253-40). Informed consent was obtained from each patient or from the patient\u0026rsquo;s legally authorized representative if the patient was unable to provide consent. Alternatively, deferred informed consent was obtained from patients. The current study was performed in accordance with French law and the Declaration of Helsinki.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eX.M. is a member of the Medical Advisory Board of Pulsion Medical Systems (Getinge) and received honoraria for lectures from Pulsion Medical Systems (Getinge) and Baxter.\u003c/p\u003e\n\u003cp\u003eJ-L.T. is a member of the Medical Advisory Board of Pulsion Medical Systems (Getinge).\u003c/p\u003e\n\u003cp\u003eThe other authors have no conflict of interest to disclose.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; contributions\u003c/h2\u003e\n\u003cp\u003eC.B. and C.L. had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: C.B. and X.M., with advice from all authors. Acquisition of data: C.B., R.S, D.R., G.F. and J.H. Analysis or interpretation of data: C.B., K.D. and X.M. Drafting of the manuscript: C.B. and X.M. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: C.B. and X.M. Administrative, technical, or material support: C.B., and X.M. Supervision: X.M.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eMessina A, Calabr\u0026ograve; L, Pugliese L, Lulja A, Sopuch A, Rosalba D, Morenghi E, Hernandez G, Monnet X, Cecconi M. Fluid challenge in critically ill patients receiving haemodynamic monitoring: a systematic review and comparison of two decades. Crit Care. 2022 Jun 21;26(1):186.\u003c/li\u003e\n \u003cli\u003eMalbrain MLNG, Van Regenmortel N, Saugel B, De Tavernier B, Van Gaal PJ, Joannes-Boyau O, Teboul JL, Rice TW, Mythen M, Monnet X. Principles of fluid management and stewardship in septic shock: it is time to consider the four D\u0026apos;s and the four phases of fluid therapy. Ann Intensive Care. 2018 May 22;8(1):66.\u003c/li\u003e\n \u003cli\u003eEvans L, Rhodes A, Alhazzani W, Antonelli M, Coopersmith CM, French C, Machado FR, Mcintyre L, Ostermann M, Prescott HC, Schorr C, Simpson S, Wiersinga WJ, Alshamsi F, Angus DC, Arabi Y, Azevedo L, Beale R, Beilman G, Belley-Cote E, Burry L, Cecconi M, Centofanti J, Coz Yataco A, De Waele J, Dellinger RP, Doi K, Du B, Estenssoro E, Ferrer R, Gomersall C, Hodgson C, M\u0026oslash;ller MH, Iwashyna T, Jacob S, Kleinpell R, Klompas M, Koh Y, Kumar A, Kwizera A, Lobo S, Masur H, McGloughlin S, Mehta S, Mehta Y, Mer M, Nunnally M, Oczkowski S, Osborn T, Papathanassoglou E, Perner A, Puskarich M, Roberts J, Schweickert W, Seckel M, Sevransky J, Sprung CL, Welte T, Zimmerman J, Levy M. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med. 2021 Nov;47(11):1181-1247.\u003c/li\u003e\n \u003cli\u003eTeboul JL, Monnet X, Chemla D, Michard F. Arterial Pulse Pressure Variation with Mechanical Ventilation. Am J Respir Crit Care Med. 2019 Jan 1;199(1):22-31.\u003c/li\u003e\n \u003cli\u003eMonnet X, Shi R, Teboul JL. Prediction of fluid responsiveness. What\u0026apos;s new? Ann Intensive Care. 2022 May 28;12(1):46. \u003c/li\u003e\n \u003cli\u003eDe Backer D, Heenen S, Piagnerelli M, Koch M, Vincent JL. Pulse pressure variations to predict fluid responsiveness: influence of tidal volume. Intensive Care Med. 2005 Apr;31(4):517-23.\u003c/li\u003e\n \u003cli\u003eMyatra SN, Prabu NR, Divatia JV, Monnet X, Kulkarni AP, Teboul JL. The Changes in Pulse Pressure Variation or Stroke Volume Variation After a \u0026quot;Tidal Volume Challenge\u0026quot; Reliably Predict Fluid Responsiveness During Low Tidal Volume Ventilation. Crit Care Med. 2017 Mar;45(3):415-421. \u003c/li\u003e\n \u003cli\u003eWang X, Liu S, Gao J, Zhang Y, Huang T. Does tidal volume challenge improve the feasibility of pulse pressure variation in patients mechanically ventilated at low tidal volumes? A systematic review and meta-analysis. Crit Care. 2023 Feb 2;27(1):45. \u003c/li\u003e\n \u003cli\u003eLima AP, Beelen P, Bakker J. Use of a peripheral perfusion index derived from the pulse oximetry signal as a noninvasive indicator of perfusion. Crit Care Med. 2002 Jun;30(6):1210-3. \u003c/li\u003e\n \u003cli\u003eBeurton A, Teboul JL, Gavelli F, Gonzalez FA, Girotto V, Galarza L, Anguel N, Richard C, Monnet X. The effects of passive leg raising may be detected by the plethysmographic oxygen saturation signal in critically ill patients. Crit Care. 2019 Jan 18;23(1):19.\u003c/li\u003e\n \u003cli\u003eBeurton A, Gavelli F, Teboul JL, De Vita N, Monnet X. Changes in the Plethysmographic Perfusion Index During an End-Expiratory Occlusion Detect a Positive Passive Leg Raising Test. Crit Care Med. 2021 Feb 1;49(2):e151-e160. \u003c/li\u003e\n \u003cli\u003ede Courson H, Michard F, Chavignier C, Verch\u0026egrave;re E, Nouette-Gaulain K, Biais M. Do changes in perfusion index reflect changes in stroke volume during preload-modifying manoeuvres? J Clin Monit Comput. 2020 Dec;34(6):1193-1198.\u003c/li\u003e\n \u003cli\u003eCannesson M, Desebbe O, Rosamel P, Delannoy B, Robin J, Bastien O, Lehot JJ. Pleth variability index to monitor the respiratory variations in the pulse oximeter plethysmographic waveform amplitude and predict fluid responsiveness in the operating theatre. Br J Anaesth. 2008 Aug;101(2):200-6. \u003c/li\u003e\n \u003cli\u003eLiu T, Xu C, Wang M, Niu Z, Qi D. Reliability of pleth variability index in predicting preload responsiveness of mechanically ventilated patients under various conditions: a systematic review and meta-analysis. BMC Anesthesiol. 2019 May 8;19(1):67. \u003c/li\u003e\n \u003cli\u003eMonnet X, Gu\u0026eacute;rin L, Jozwiak M, Bataille A, Julien F, Richard C, Teboul JL. Pleth variability index is a weak predictor of fluid responsiveness in patients receiving norepinephrine. Br J Anaesth. 2013 Feb;110(2):207-13. \u003c/li\u003e\n \u003cli\u003eFischer MO, Pellissier A, Saplacan V, G\u0026eacute;rard JL, Hanouz JL, Fellahi JL. Cephalic versus digital plethysmographic variability index measurement: a comparative pilot study in cardiac surgery patients. J Cardiothorac Vasc Anesth. 2014 Dec;28(6):1510-5.\u003c/li\u003e\n \u003cli\u003eMonnet X, Teboul JL. Transpulmonary thermodilution: advantages and limits. Crit Care. 2017 Jun 19;21(1):147. \u003c/li\u003e\n \u003cli\u003eMonnet X, Persichini R, Ktari M, Jozwiak M, Richard C, Teboul JL. Precision of the transpulmonary thermodilution measurements. Crit Care. 2011 Aug 27;15(4):R204. \u003c/li\u003e\n \u003cli\u003eMalbrain ML, Cheatham ML, Kirkpatrick A, Sugrue M, Parr M, De Waele J, Balogh Z, Lepp\u0026auml;niemi A, Olvera C, Ivatury R, D\u0026apos;Amours S, Wendon J, Hillman K, Johansson K, Kolkman K, Wilmer A. Results from the International Conference of Experts on Intra-abdominal Hypertension and Abdominal Compartment Syndrome. I. Definitions. Intensive Care Med. 2006 Nov;32(11):1722-32.\u003c/li\u003e\n \u003cli\u003eMonnet X, Teboul JL. Passive leg raising: five rules, not a drop of fluid! Crit Care. 2015 Jan 14;19(1):18.\u003c/li\u003e\n \u003cli\u003eCannesson M, Le Manach Y, Hofer CK, Goarin JP, Lehot JJ, Vallet B, Tavernier B. Assessing the diagnostic accuracy of pulse pressure variations for the prediction of fluid responsiveness: a \u0026quot;gray zone\u0026quot; approach. Anesthesiology. 2011 Aug;115(2):231-41.\u003c/li\u003e\n \u003cli\u003eMonnet X, Malbrain MLNG, Pinsky MR. The prediction of fluid responsiveness. Intensive Care Med. 2023 Jan;49(1):83-86. \u003c/li\u003e\n \u003cli\u003eDe Backer D, Aissaoui N, Cecconi M, Chew MS, Denault A, Hajjar L, Hernandez G, Messina A, Myatra SN, Ostermann M, Pinsky MR, Teboul JL, Vignon P, Vincent JL, Monnet X. How can assessing hemodynamics help to assess volume status? Intensive Care Med. 2022 Oct;48(10):1482-1494. \u003c/li\u003e\n \u003cli\u003eMcGrath SP, Ryan KL, Wendelken SM, Rickards CA, Convertino VA. Pulse oximeter plethysmographic waveform changes in awake, spontaneously breathing, hypovolemic volunteers. Anesth Analg. 2011 Feb;112(2):368-74. \u003c/li\u003e\n \u003cli\u003eDesgranges FP, Desebbe O, Ghazouani A, Gilbert K, Keller G, Chiari P, Robin J, Bastien O, Lehot JJ, Cannesson M. Influence of the site of measurement on the ability of plethysmographic variability index to predict fluid responsiveness. Br J Anaesth. 2011 Sep;107(3):329-35.\u003c/li\u003e\n \u003cli\u003eTaccheri T, Gavelli F, Teboul JL, Shi R, Monnet X. Do changes in pulse pressure variation and inferior vena cava distensibility during passive leg raising and tidal volume challenge detect preload responsiveness in case of low tidal volume ventilation? Crit Care. 2021 Mar 18;25(1):110.\u003c/li\u003e\n \u003cli\u003eHamzaoui O, Shi R, Carelli S, Sztrymf B, Prat D, Jacobs F, Monnet X, Gou\u0026euml;zel C, Teboul JL. Changes in pulse pressure variation to assess preload responsiveness in mechanically ventilated patients with spontaneous breathing activity: an observational study. Br J Anaesth. 2021 Oct;127(4):532-538.\u003c/li\u003e\n \u003cli\u003eLai C, Shi R, Beurton A, Moretto F, Ayed S, Fage N, Gavelli F, Pavot A, Dres M, Teboul JL, Monnet X. The increase in cardiac output induced by a decrease in positive end-expiratory pressure reliably detects volume responsiveness: the PEEP-test study. Crit Care. 2023 Apr 9;27(1):136. \u003c/li\u003e\n \u003cli\u003eGavelli F, Shi R, Teboul JL, Azzolina D, Mercado P, Jozwiak M, Chew MS, Huber W, Kirov MY, Kuzkov VV, Lahmer T, Malbrain MLNG, Mallat J, Sakka SG, Tagami T, Pham T, Monnet X. Extravascular lung water levels are associated with mortality: a systematic review and meta-analysis. Crit Care. 2022 Jul 6;26(1):202.\u003c/li\u003e\n \u003cli\u003eMonnet X, Marik P, Teboul JL. Passive leg raising for predicting fluid responsiveness: a systematic review and meta-analysis. Intensive Care Med. 2016 Dec;42(12):1935-1947.\u003c/li\u003e\n \u003cli\u003eGavelli F, Beurton A, Teboul JL, De Vita N, Azzolina D, Shi R, Pavot A, Monnet X. Bioreactance reliably detects preload responsiveness by the end-expiratory occlusion test when averaging and refresh times are shortened. Ann Intensive Care. 2021 Aug 28;11(1):133. \u003c/li\u003e\n \u003cli\u003eShi R, Moretto F, Prat D, et al. Dynamic changes of pulse pressure but not of pulse pressure variation during passive leg raising predict preload responsiveness in critically ill patients with spontaneous breathing activity. Journal of Critical Care. 2022 Dec;72:154141.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"critical-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cric","sideBox":"Learn more about [Critical Care](http://ccforum.biomedcentral.com/)","snPcode":"13054","submissionUrl":"https://submission.nature.com/new-submission/13054/3","title":"Critical Care","twitterHandle":"@Crit_Care","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Fluids, fluid accumulation, catecholamine, systemic venous return, vasodilatation","lastPublishedDoi":"10.21203/rs.3.rs-4575103/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4575103/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTo detect preload responsiveness in patients ventilated with a tidal volume (Vt) at 6 mL/kg, the Vt challenge consists in increasing Vt from 6 to 8 mL/kg and measuring the induced increase in pulse pressure variation (PPV). However, this requires an arterial catheter. The perfusion index (PI), which reflects the amplitude of the plethysmographic signal, may reflect stroke volume and its respiratory variation (pleth variability index, PVI) may be a surrogate of PPV. We assessed whether changes in PVI or PI during a Vt challenge could be as reliable as changes in PPV for detecting preload responsiveness.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn critically ill patients mechanically ventilated with Vt\u0026thinsp;=\u0026thinsp;6 mL/kg and no spontaneous breathing activity, monitored with a PiCCO2 system and a Masimo SET technique (sensor placed on the finger or the forehead), haemodynamic data were recorded during a Vt challenge and a passive leg raising (PLR) test. Preload responsiveness was defined by a PLR-induced increase in cardiac index\u0026thinsp;\u0026ge;\u0026thinsp;10%.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 63 screened patients, 21 were excluded because of an unstable PI signal and/or atrial fibrillation. Among the 42 included patients, 16 were preload responders. During the Vt challenge in preload responders, PPV (absolute change), PI measured on the finger (percent change), PVI measured on the finger (absolute change), PI measured on the forehead (percent change) and PVI measured on the forehead (absolute change) changed by 4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9%, -14.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7%, 1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6%, -18.7\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9 and 1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5, respectively. All these changes were significantly larger than in preload non-responders.\u003c/p\u003e","manuscriptTitle":"Testing preload responsiveness by the tidal volume challenge assessed by the plethysmographic perfusion index","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-16 15:58:32","doi":"10.21203/rs.3.rs-4575103/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-29T12:33:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-28T14:18:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-28T12:17:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"321775387431334352575390072840856966572","date":"2024-06-24T17:44:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"98644288121903347860275163634521454278","date":"2024-06-24T16:36:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-22T03:27:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"306581745638241044474468819746833042971","date":"2024-06-21T21:25:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-21T13:08:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-18T12:59:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-18T12:58:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"Critical Care","date":"2024-06-13T09:28:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"critical-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cric","sideBox":"Learn more about [Critical Care](http://ccforum.biomedcentral.com/)","snPcode":"13054","submissionUrl":"https://submission.nature.com/new-submission/13054/3","title":"Critical Care","twitterHandle":"@Crit_Care","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"01574212-b696-4b93-8e48-b15cec8ccd1c","owner":[],"postedDate":"July 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-23T16:01:44+00:00","versionOfRecord":{"articleIdentity":"rs-4575103","link":"https://doi.org/10.1186/s13054-024-05085-w","journal":{"identity":"critical-care","isVorOnly":false,"title":"Critical Care"},"publishedOn":"2024-09-16 15:57:24","publishedOnDateReadable":"September 16th, 2024"},"versionCreatedAt":"2024-07-16 15:58:32","video":"","vorDoi":"10.1186/s13054-024-05085-w","vorDoiUrl":"https://doi.org/10.1186/s13054-024-05085-w","workflowStages":[]},"version":"v1","identity":"rs-4575103","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4575103","identity":"rs-4575103","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}