Fluid responsiveness in patients under mechanical ventilation and low tidal volume ventilation through the pulse pressure variation after tidal volume challenge in the post-operative cardiac surgery

Background It is known that in the immediate postoperative period of cardiac surgery, strict control of hemodynamic variables and blood volume is necessary, since there is an imbalance between oxygen supply and consumption. Thus, the present study seeks to validate methods previously used in different clinical situations to predict fluid responsiveness, in the current scenario of the immediate postoperative period of cardiac surgery. Purpose To evaluate the influence of “tidal volume challenge” from 6 ml / kg to 8 ml / kg of the predicted body weight (PBW) in conjunction with the end expiratory occlusion test (EEOT) in the variation of pulse pressure to predict fluid responsiveness in the immediate postoperative period of cardiac surgery. Methodology This prospective study included 30 patients after cardiac surgery. Hemodynamic and ventilatory parameters were initially recorded in mechanical ventilation at 6 ml/kg and after tidial volume challenge and with the EEOT at 8 ml/kg of predicted body weight (PBW). After recorded the intervention data, there was a return to ventilation at 6 ml/kg and a saline infusion of 500 ml was performed for 15 minutes. Fluid responsiveness was defined for patients who had an increase of 10% or more in velocity time integral (VTI) by echocardiogram after volume expansion compared to baseline value. Multivariate analysis was used to identify independent predictors of fluid response status. Sensitivity and specificity analyzes were performed to determine the predictive precision of each parameter. Results The main result of our study is that, when the tidal volume is increased from 6 to 8 ml/kg of PBW, the relative increase in pulse pressure variation (%ΔPPV6–8) predicts with excellent accuracy responsiveness to fluids with cut-off values of 18.3%, with sensitivity of 92.9% and specificity of 84% (P=0.019). Although changing PPV6, EEOT6 and EEOT8 are not reliable in predicting fluid responsiveness, they still require additional calculations. PPV8 also discriminates between responders and non-responders; however, with sensitivity (78.6%) and specificity (66.6%) when the value found in the PPV8 is up 8.5, but without statistical significance (figure). Conclusion The challenge of tidal volume and its influence on the ΔPP variation has excellent accuracy to predict fluid responsiveness in the immediate postoperative period of cardiac surgery. EEOT did not present good accuracy to predict fluid responsiveness in patients in the immediate postoperative period of cardiac surgery. FUNDunding Acknowledgement Type of funding sources: None.

Assessment of Fluid Responsiveness After Tidal Volume Challenge During Pressure-Controlled Ventilation Volume Guaranteed: An observational study

Background: The reliability of pulse pressure variation (PPV) and stroke volume variation (SVV) to predict fluid responsiveness have not previously been established when using pressure-controlled ventilation-volume guaranteed (PCV-VG) mode. We hypothesized that with a transient increase in tidal volume from 6 to 8 mL/kg of predicted body weight (PBW), which we reference as the “tidal volume challenge (TVC)”, the changes to PPV and SVV will be an indicator of fluid responsiveness.Methods: The patients were first ventilated with a tidal volume of (Vt) 6 mL/kg of predicted body weight (PBW) using PCV-VG. Following intravenous anesthesia induction, PPV6 and SVV6 were recorded, then the TVC was performed, which increased Vt from 6 mL/kg to 8 mL/kg PBW for 1 minute and PPV8 and SVV8 were recorded again. The changes in value of PPV and SVV (ΔPPV6-8 and ΔSVV6-8) were calculated after TVC. Following the minute of TVC, the tidal volume was returned to 6 ml/kg PBW for the fluid challenge (FC), a colloid infusion of 6ml/kg PBW for 20 minutes. Patients were classified as responders if there was an increase in cardiac index (CI) of more than 15% after FC, otherwise the patients were identified as non-responders. Eligible patients were divided into groups of responders or non-responders.Results: 37 patients were classified as responders and 44 were non-responders. PPV6 and SVV6 could not predict the fluid responsiveness, while PPV8 and SVV8 could predict the fluid responsiveness when using PCV-VG mode. The changes in value of PPV and SVV after TVC (ΔPPV6-8 and ΔSVV6-8) identified true fluid responders with the highest sensitivity and specificity in the above variables, which predicted fluid responsiveness with the area under the receiver operating characteristic curves (AUCs) (95% CIs) being 0.96 (0.93-1.00) and 0.98 (0.96-1.00), respectively. No significant difference was found when comparing the AUCs of ΔPPV6-8 and ΔSVV6-8 (P > 0.05). Linear correlation was represented between the change value of CI after FC and the change value of SVV or PPV after TVC (r = 0.68; P < 0.0001 and r = 0.77; P < 0.0001, respectively).Conclusions: A transient increase in tidal volume, which we reference as the “tidal volume challenge (TVC)” could enhance the predictive value of PPV and SVV for the evaluation of fluid responsiveness in patients under ventilation with PCV-VG.Trial registration: Chinese Clinical Trial Registry (ChiCTR2000028995). Prospectively registered on 11 January 2020. http://www.medresman.org.

Prediction of Volume Responsiveness by Stroke Volume Variation vs. Central Venous Pressure in Children Undergoing Fontan Operation

Background: Fontan operation is a palliative medical procedure performed on children with single-ventricle defects. As postoperative success of the procedure largely depends on the preload volume, it is necessary to ensure the effective volume of systemic circulation by maintaining an appropriate pressure gradient between the systemic vein and the left atrium. However, there is a lack of effective indexes to evaluate volume responsiveness in Fontan patients. Stroke volume variation (SVV) is a dynamic hemodynamic parameter based on cardiopulmonary interaction in mechanical ventilation. This study is to validate the sensitivity and specificity of SVV vs. central venous pressure (CVP) in assessing volume responsiveness of Fontan patients.Method: 64 children were included in this prospective study with single-ventricle who underwent modified Fontan operation between May 2018 and January 2020. Patients were given 10ml·kg− 1 albumin for volume challenge within 10 min after CPB. Before and after volume challenge, the invasive arterial pressure module was connected to Mostcare™ equipment to collect SBP, MBP, DBP, SVV, CI and SVRI dynamically in a time window of 30 s at a frequency of 1000 Hz. According to the range of CI change, patients with ΔCI ≥ 15% were classified into response (R) group and patients with ΔCI < 15% into non-response (NR) group. Using SVV and CVP as indicators, the ROC of the patients was established, and the AUC, diagnostic threshold, sensitivity and specificity were calculated.Results: The 64 pediatric patients included with a mean age of 4.85 ± 1.20 years, a mean height of 98.00 ± 16.74 cm and a mean weight of 15.65 ± 5.37 kg. The SVV value was 17.15 ± 3.97% and 13.45 ± 2.45% before and after fluid challenge treatment vs. 18.60 ± 1.83 mmHg and 20.20 ± 2.39 mmHg for CVP in responders. The AUC of SVV was 0.74 (95% confidence interval [CI] 0.54–0.94, P < 0.05) and the cutoff value was 16%, offering a sensitivity of 50% and a specificity of 91.7% vs.0.70 (95% CI 0.50–0.92, P > 0.05), 19.5 mmHg, 58% and 76% for CVP.Conclusion: SVV exhibited a good predictive value for volume responsiveness in pediatric Fontan patients. Appropriate volume therapy according to SVV could improve the cardiac function of such patients.Trial registration: This research was registered in Chinese Clinical Trail Registry on Jan 26, 2018. Registration number is ChiCTR1800014654.Registry URL is http://www.chictr.org.cn/showproj.aspx?proj=25019. This observational prospective study was approved by the Local Ethics Committee of Shanghai Children’s Medical Center affiliated to Shanghai Jiao Tong University (SCMCIRB-K2017035)

Analytics Optimized Geoscience Data Store with STARE-based Packaging

&lt;p&gt;The only effective strategy to address the volume challenge of Big Data is &amp;#8220;parallel processing&amp;#8221;, e.g. employing a cluster of computers (nodes), in which a large volume of data is partitioned and distributed to the cluster nodes. Each of the cluster nodes processes a small portion of the whole volume. The nodes, working in tandem, can therefore collectively process the entire volume within a much-reduced period of time. In the presence of data variety, however, it is no longer as straightforward, because na&amp;#239;ve partition and distribution of diverse geo-datasets (packaged with existing practice) inevitably results in misalignment of data for the analysis. Expensive cross-node communication, which is also a form of data movement, thus becomes necessary to bring the data in alignment first before analysis may commence.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Geoscience analysis predominantly requires spatiotemporal alignment of diverse data. For example, we often need to compare observations acquired by different means &amp; platforms and compare model output with observations. Such comparisons are meaningful only if data values for the same space and time are compared. With the existing practice of packaging data using the conventional array data structure, it is nearly impossible to spatiotemporally align diverse data. Because, while array indices are generally used for partition and distribution, for different datasets (even data granules) the same indices most-often-than-not refer to different spatiotemporal neighborhoods. Partition and distribution using conventional array indices thus often results in data of the same spatiotemporal neighborhoods (from different datasets) reside on different nodes. Comparison thus cannot be performed until they are brought together to the same node.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Therefore, we need indices that tie directly and consistently to spatiotemporal neighborhoods to be used for partition and distribution. SpatioTemporal Adaptive-Resolution Encoding (STARE) provides exactly such indices, which can replace floating-point encoding of longitude-latitude and time as a more analytics-optimized alternative. Moreover, data packaging can base on STARE indices. Due to its hierarchical nature, geo-spatiotemporal data packaged based on STARE hierarchy offers essentially a reusable partition for distribution adaptable to various computing-and-storage architectures, through which spatiotemporal alignment of geo-data from diverse sources can be readily and scalably achieved to optimize parallel analytic operations.&lt;/p&gt;

Stroke Volume Variation and Stroke Volume Index Can Predict Fluid Responsiveness after Mini-Volume Challenge Test in Patients Undergoing Laparoscopic Cholecystectomy

Background and Objectives: For using appropriate goal-directed fluid therapy during the surgical conditions of pneumoperitoneum in the reverse Trendelenburg position, we investigated the predictability of various hemodynamic parameters for fluid responsiveness by using a mini-volume challenge test. Materials and Methods: 42 adult patients scheduled for laparoscopic cholecystectomy were enrolled. After general anesthesia was induced, CO2 pneumoperitoneum was applied and the patient was placed in the reverse Trendelenburg position. The mini-volume challenge test was carried out with crystalloid 4 mL/kg over 10 min. Hemodynamic parameters, including stroke volume variation (SVV), cardiac index (CI), stroke volume index (SVI), mean arterial pressure (MAP), and heart rate (HR), were measured before and after the mini-volume challenge test. The positive fluid responsiveness was defined as an increase in stroke volume index ≥10% after the mini-volume challenge. For statistical analysis, a Shapiro–Wilk test was used to test the normality of the data. Continuous variables were compared using an unpaired t-test or the Mann–Whitney rank-sum test. Categorical data were compared using the chi-square test. A receiver operating characteristic curve analysis was used to assess the predictability of fluid responsiveness after the mini-volume challenge. Results: 31 patients were fluid responders. Compared with the MAP and HR, the SVV, CI, and SVI showed good predictability for fluid responsiveness after the mini-volume challenge test (area under the curve was 0.900, 0.833, and 0.909, respectively; all p-values were <0.0001). Conclusions: SVV and SVI effectively predicted fluid responsiveness after the mini-volume challenge test in patients placed under pneumoperitoneum and in the reverse Trendelenburg position.

Predicting Fluid Responsiveness Using Pulse Pressure Variation after Tidal Volume Challenge in Postoperative Patients Receiving Lung Protective Ventilation: A Clinical Trial

Background: Lung protective ventilation with low tidal volume is beneficial in patients with intermediate to high risk of postoperative pulmonary complications. However, during low tidal volume ventilation, pulse pressure variation (PPV) and stroke volume variation (SVV) do not predict fluid responsiveness. We aimed to determine whether changes in PPV and SVV after transient increases in tidal volume can predict fluid responsiveness in these patients. Methods: We recorded 22 measurements from 15 patients who experienced postoperative acute circulatory failure. We performed a tidal volume challenge by transiently increasing tidal volume (VT) from 6 to 8 mL/kg (VT6–8), 8 to 10 mL/kg (VT8–10), and 6 to 10 mL/kg (VT6–10) of patients' predicted body weight. The change in PPV (∆PPV) at VT6–8 (∆PPV6–8), VT8–10 (∆PPV8–10), VT6–10 (∆PPV6–10) and the change in SVV (∆SVV) at VT6–8 (∆SVV6–8), VT8–10 (∆SVV8–10), and VT6–10 (∆SVV6–10) were recorded. Patients were classified as fluid responders if there was an increase in stroke volume of more than 10% after a fluid bolus. Results: Following the tidal volume challenge, ∆PPV and ∆SVV failed to predict fluid responsiveness, with areas under the receiver operating characteristic curves (with 95% confidence intervals) of 0.49 (0.23–0.74), 0.54 (0.29–0.79), 0.52 (0.28–0.77) for ∆PPV6–8, ∆PPV8–10, and ∆PPV6–10, and 0.55 (0.30–0.80), 0.55 (0.31–0.80), and 0.59 (0.34–0.84) for ∆SVV6–8, ∆SVV8–10, and ∆SVV6–10, respectively. Conclusions: Changes in PPV and SVV after the tidal volume challenge did not predict fluid responsiveness in postoperative patients with low tidal volume ventilation. Trial registration: This trial was registered with Clinicaltrials.in.th, TCTR20190808003.