Arterial Blood Line Research Articles

Prognostic role of unmeasured anions determined by the Stewart approach in septic shock: A prospective cohort study

Background: Unlike standard methods for the analysis of acid-base disturbances, the Stewart approach allows for a precise quantification of unmeasured anions (strong ion gap, SIG). The prognostic value of these unmeasured anions has been reported in various clinical situations in the intensive care unit (ICU), but not specifically in septic shock. The aim of the present study was to assess whether or not the SIG could be a prognostic marker for 28-day mortality in critically ill patients admitted to the ICU for septic shock. Methods: This prospective cohort study was conducted from June 2016 to December 2017 in three ICUs of a French teaching hospital. All patients admitted to the ICU for septic shock and equipped with an arterial blood line were eligible. Oral consent was collected after delivering oral and written information to the patient or his/her family. The SIG was calculated from a complete blood sampling (blood electrolytes and arterial blood gas) collected immediately upon ICU admission. Receiver operating characteristics (ROC) curves were determined to assess the ability of SIG to predict 28-day mortality. Results: A total of 116 patients were analyzed. The 28-day mortality rate was 41.4%. Median (interquartile range [IQR]) SIG at admission was 7.1 (4.6-9.6) mEq/L for the 28-day survivors and 8.0 (6.1-10.3) mEq/L for non-survivors (P = 0.051). The area under ROC of SIG at admission for 28-day mortality prediction was 0.607 (95% confidence interval [CI] 0.504-0.710; P = 0.051). Conclusion: SIG is not a relevant prognostic marker for mortality in septic shock.

#828 Non-invasive determination of uric acid in blood during hemodialysis with an optical spent dialysate sensor

Abstract Background and Aims Kt/V urea is conventionally used hemodialysis (HD) adequacy marker, whereas many other uremic toxins with differing removal kinetics affect the mortality of end stage kidney disease (ESKD) patients. Among them, uric acid (UA) has been shown to cause cardiovascular mortality of ESKD patients. Recently, determination of UA concentration in blood with optical sensors during HD has been attempted by Lin et al in 2021 and Żyłka et al in 2023, but the accuracy has been relatively low. Moreover, Żyłka et al measured light absorption of spent dialysate at 573 nm to determine UA concentration, whereas previous research has shown that dialysate and UA have negligible light absorption in that region. The aim of this observational study was to predict concentration of UA with higher accuracy in ESKD patients’ blood during HD with various treatment settings by monitoring spent dialysate noninvasively with an optical sensor. Method Twenty-two ESKD patients on chronic HD were included into the study. Each patient received four 4 h long midweek HD sessions: one standard HD and three haemodiafiltration (HDF) sessions with different settings. Median (interquartile range) settings of the 1 HD session were: effective blood flow (Qb) = 199 (198-199) mL/min, dialysate flow (Qd) = 297 (297-298) mL/min, ultrafiltration rate (UF) = 13 (8-16) mL/min, dialyzer area 1.5 m2 and for the 3 HDF sessions: Qb = 298 (296-356) mL/min, Qd = 788 (489-792) mL/min, substitution fluid flow (Qsubs) = 96 (66-106) mL/min, UF = 11 (8-15) mL/min, dialyzer areas 1.8 m2 and 2.2 m2. Blood samples were collected before the start and at the end of each HD session from the arterial blood line and spent dialysate samples were collected 7, 60, 120, 180 and 240 min after the start from the outlet of the HD machine. Concentration of UA in spent dialysate and serum samples were determined with HPLC. An optical sensor (Optofluid Technologies OÜ, Tallinn, Estonia) was connected to the spent dialysate outlet of the HD machine and ultraviolet (UV) light absorption of spent dialysate was measured online in real time for each HD session. A linear interactions regression model was created using light absorbance at four different UV wavelengths to predict UA concentrations in collected spent dialysate samples. A curve of UA concentration for the whole HD session was determined based on the model and UV absorbance data measured with the optical sensor. Thereafter, UA concentration in spent dialysate at the start and at the end of each session (UAsensor hereinafter) was found from the concentration curve. The data of 88 HD sessions were equally divided into calibration and validation sets. Linear regression model was created using data of calibration set to predict concentration of UA (UApredicted) in blood as follows: UApredicted = a • UAsensor • $\frac{{{\rm{Qd}} + {\rm{\ Qsubs}} + {\rm{UF\ }}}}{{{\rm{Qb}}}}$, where “a” is the slope, UAsensor is the UA concentration in spent dialysate found from the concentration curve of the optical sensor, Qb is effective blood flow and Qd+Qsubs+UF is the total flow of spent dialysate. Subsequently, the accuracy of the model was evaluated on the calibration and validation data using Bland Altman analysis. Results UA concentrations in spent dialysate determined with HPLC and estimated with the optical sensor were strongly correlated (R2 = 0.992) and with comparable accuracy (BIAS±SE) (0.1 ± 3.84) µmol/L. Coefficient of determination 0.951 with the accuracy of 0.00 ± 31.43 µmol/L was achieved for calibration group, and coefficient of determination 0.962 with the accuracy of −7.64 ± 32.06 µmol/L was achieved for validation group between the UA concentration in blood determined with HPLC and corresponding values predicted by the optical sensor, respectively (Fig. 1). Conclusion Concentration of UA in dialysate and blood can be estimated noninvasively and accurately with the optical sensor in real time. This can be used to estimate removal efficiency and levels of UA during HD. In future, removal of other uremic toxins could be additionally monitored leading to a more personalized HD treatment.

Review of Blood Cultures Taken From Arterial Lines in James Cook University Hospital: Contamination Analysis And Comparison With Venous Samples

BACKGROUND: Blood cultures are crucial diagnostic tools for identifying and treating bloodstream infections. Traditionally, venous blood is the preferred source for sample acquisition, but arterial lines offer an alternative. However, concerns regarding contamination and diagnostic accuracy have been raised, questioning the reliability of arterial line blood cultures. This study aimed to evaluate the contamination rates of arterial line blood cultures at James-Cook University Hospital (JCUH), UK and compare them with venous samples to understand their clinical utility better. METHODS: A comprehensive retrospective review analysed 17,643 blood culture samples collected between September 2022 and March 2023 at JCUH. Among these, 109 arterial line blood cultures and 785 venous peripheral adult samples were included for data analysis. Contamination rates were calculated as the number of positive blood cultures with contaminants per total positive samples (arterial or venous). The incidence of contamination was defined as the number of total blood cultures reported with contaminants per total samples (arterial or venous). No discrimination was made based on the number of contaminants found. Clinical information accompanying the blood cultures, such as the specification of arterial lines as 'new' samples, was also considered. RESULTS: The overall contamination rate at JCUH was found to be 4.99%. Specifically, the contamination rate for venous samples was 49.26%, while arterial samples had a higher contamination rate of 56.52%. The incidence of contamination from arterial samples was 11.92%, significantly higher than the incidence rate for venous samples at 3.18%. Most arterial samples were requested from intensive care units (ICUs) and highly dependent wards (HDUs), indicating potential areas for targeted interventions to improve blood culture collection practices. CONCLUSION: Arterial blood cultures demonstrated higher contamination rates compared to venous samples, raising concerns about their reliability. Contamination in arterial samples, particularly when collected from critically ill patients in ICUs and HDUs, can lead to inappropriate use of antibiotics, delayed, or missed diagnosis, and suboptimal patient outcomes. The study recommends targeted interventions to improve arterial blood culture collection practices and further training for healthcare workers involved in arterial line care. Encouraging the use of only 'new' arterial lines and implementing standardized protocols can help reduce contamination rates. Furthermore, the study identified certain limitations, such as potential human errors in data analysis and the need for a larger dataset of arterial line cultures. Extending the analysis to compare different sample sources like CVCs, Hickman lines, and central lines could provide a more comprehensive understanding of contamination rates across various culture collection methods. In conclusion, venous samples showed higher clinical favourability with a lower contamination rate, providing increased dependability for accurate diagnosis and management. Although some studies have not shown clear superiority of arterial samples over venous samples, this analysis highlights considerable differences in contamination rates, suggesting a potential inferiority of arterial blood culture samples. While efforts can be made to optimize the consistency of arterial samples and reduce contamination rates, their use should be approached with caution. Implementing the recommended measures is essential for accurate diagnosis, improved patient outcomes, and effective antibiotic management in clinical practice.

Evaluation of partial pressure CO2 change in the dialyzer blood inlet during hemodialysis as a measure of vascular access recirculation.

Vascular access recirculation during hemodialysis is associated with reduced effectiveness and worse survival outcomes. To evaluate recirculation, an increase in pCO2 in the blood of the arterial line during hemodialysis (threshold of 4.5 mmHg) was proposed. The blood returning from the dialyzer in the venous line has significantly higher pCO2 , so in the presence of recirculation, pCO2 in the arterial blood line may increase (ΔpCO2 ) during hemodialysis sessions. The aim of our study was to evaluate ΔpCO2 as a diagnostic tool for vascular access recirculation in chronic hemodialysis patients. We evaluated vascular access recirculation with ΔpCO2 and compared it with the results of a urea recirculation test, which is the gold standard. ΔpCO2 was obtained from the difference in pCO2 in the arterial line at baseline (pCO2 T1) and after 5 min of hemodialysis (pCO2 T2). ∆pCO2 = pCO2 T2-pCO2 T1. In 70 hemodialysis patients (mean age: 70.52 ± 13.97 years; hemodialysis vintage of 41.36 ± 34.54, KT/V 1.4 ± 0.3), ∆pCO2 was 4 ± 4 mmHg, and urea recirculation was 7% ± 9%. Vascular access recirculation was identified using both methods in 17 of 70 patients, who showed a ∆pCO2 of 10 ± 5 mmHg and urea recirculation of 20% ± 9%; time in months of hemodialysis was the only difference between vascular access recirculation and non-vascular access recirculation patients (22 ± 19 vs. 46 ± 36, p: 0.05). In the non-vascular access recirculation group, the average ΔpCO2 was 1.9 ± 2 (p: 0.001), and the urea recirculation % was 2.8 ± 3 (p: 0.001). The ΔpCO2 correlated with the urea recirculation % (R: 0.728; p < 0.001). ΔpCO2 in the arterial blood line during hemodialysis is an effective and reliable diagnostic tool for identifying recirculation of the vascular access but not its magnitude. The ΔpCO2 test application is simple and economical and does not require special equipment.

#3367 NON-INVASIVE OPTICAL ESTIMATION OF INTRADIALYTIC CONCENTRATIONS OF UREMIC TOXINS IN BLOOD OF HEMODIALYSIS PATIENTS

Abstract Background and Aims Hemodialysis (HD) adequacy is generally estimated by the dialysis adequacy marker Kt/V urea that poorly describes removal of uremic toxins with different removal kinetics, such as protein bound or middle molecule uremic toxins, which have direct effect on morbidity and mortality of end stage kidney disease (ESKD) patients. We have recently shown the feasibility of estimating an alternative dialysis adequacy marker that can be applied to dialysis sessions with varying settings and different uremic toxins, intradialytic time average concentration (TAC) of uremic toxins, such as urea, uric acid (UA), indoxyl sulfate (IS) and beta-2-microglobulin in blood of ESKD patients, from spent dialysate concentrations determined by laboratory methods [1]. The aim of this retrospective observational study was to estimate intradialytic TAC of uremic toxins UA and IS non-invasively from spent dialysate concentrations determined by optical methods. Method Twenty-two ESKD patients on chronic HD were enrolled into the study. For each patient 4 midweek dialysis sessions with different treatment settings were included (1 HD: Qb = 200 mL/min, Qd = 300 mL/min, dialyzer 1,5m2; 3 HDF: median (interquartile range) Qb = 298 (296-356) mL/min, Qd = 795 (500–800) mL/min, Vsubst = 21.8 (15–24.5) L, dialyzers 1,8 m2 and 2,2 m2). During each dialysis session, blood samples were taken at 0 min (start) and 240 min after the start from the arterial blood line and dialysate samples were taken at 7 min and 240 min after the start from the outlet of the dialysis machine. Concentrations of UA and IS in serum and spent dialysate samples were determined with HPLC. In addition, UV absorbance and fluorescence of the spent dialysate samples were measured with spectrophotometer UV-3600 and spectrofluorometer RF-6000 (both from Shimadzu Corp., Japan), after which concentrations of UA and IS in spent dialysate samples were determined based on the optical properties of samples. Stability of HD treatment settings were monitored online and dialysis sessions with unstable blood and dialysate flow rates were excluded. TAC of UA and IS were calculated from serum concentrations and evaluated from laboratory and optically estimated logarithmic mean concentrations (Mln D) of spent dialysate. Results Mean intradialytic serum TAC values of UA and IS were 198.4±44.0 μmol/L and 69.5 ± 37.8 μmol/L and strongly correlated to those estimated from optically determined Mln D 198.0±38.9 μmol/L (R2 = 0.75) and 69.5 ± 37.8 μmol/L (R2 = 0.81), respectively. Mln D of UA and IS in spent dialysate based on laboratory methods were 102.2 ± 22.8 μmol/L and 5.9 ± 3.5 μmol/L and strongly correlated with the optically determined concentrations of 102.7 ± 23.1 μmol/L (R2 = 0.97) and 6.1 ± 3.4 μmol/L (R2 = 0.97), respectively. Conclusion Intradialytic serum TAC of UA and IS can be estimated non-invasively with optical methods from their concentration in spent dialysate independent of treatment modality. Optical online monitoring of spent dialysate in real-time could therefore provide additional information about treatment adequacy regarding the removal of uremic toxins’ other than urea. In future, TAC estimation models should be optimized for each uremic toxin to establish higher accuracy, considering real-time treatment settings, recirculation etc.

The optimized anticoagulation strategy in prolonged hemodialysis.

During extended (nocturnal) hemodialysis (ENHD), the dose of low-molecular-weight heparin (LMWH) can be administered as a single injection or as a divided dose over different time points. Our hypothesis was that a single injection might be sufficient to maintain dialyzer fiber patency. In addition, we investigated whether the biochemical clotting parameter anti-Xa accurately predicts fiber blocking. Our hypothesis was tested in 20 stable patients on ENHD in a random cross-over setting during two consecutive midweek sessions. The regular total dose of LMWH (i.e. enoxaparin, Clexane® 40-100 mg, Sanofi, Belgium) was either given (i) in a single injection at the dialysis start or (ii) divided over two injections, at the start and halfway the dialysis session. Blood samples were taken from the arterial blood line at different time points to determine plasma anti-Xa activity levels. Post-dialysis, the rinsed and dried hemodialyzers were scanned with a reference micro-computed tomography (µCT) scanning technique, and non-blocked fibers were counted in a central cross-section of the dialyzer outlet potting (ImageJ, NIH, USA). The percentage of open fibers in the dialyzers after a single injection of LMWH [91 (61-96)%] versus divided administration [94 (79-98)%] was not different. Time averaged anti-Xa activity levels were clinically not significantly different between both sessions. Anti-Xa activity levels correlated with the administered anticoagulation doses normalized for body weight, but not with the percentages open fibers in the dialyzers. Our results indicate that there is no need to administer enoxaparin over two injections for ENHD up to 8 h. The usefulness of monitoring anti-Xa levels to predict fiber patency, assessed by µCT, can be questioned, but further clinical trials are needed.

Optimized Arterial Line Artifact Identification Algorithm Cleans High-Frequency Arterial Line Data With High Accuracy in Critically Ill Patients.

Multicenter observational study. ICUs across Ontario, Canada. Nested cohort of ICU patients with shock and/or respiratory failure requiring invasive mechanical ventilation. High-frequency blood pressure data was analyzed. Systolic, diastolic, and mean arterial pressure minute averages were calculated. For manual analysis, a trained researcher retrospectively reviewed mean arterial pressure data, removing values that were deemed nonphysiological. The algorithm was implemented and identified artifactual data. Arterial line data was extracted from 15 patients. A trained researcher manually reviewed 40,798 minute-by-minute data points, then subsequently analyzed them with the algorithm. Manual review resulted in the identification of 119 artifacts (0.29%). The optimized algorithm identified 116 (97%) of these artifacts. Five hundred thirty-seven data points were erroneously removed or modified. Compared with manual review, the modified algorithm incorporating absolute thresholds of greater than 30 and less than 200 mm Hg had 97.5% sensitivity, 98.7% specificity, and a Matthew correlation coefficient of 0.41. The error-checking algorithm had high sensitivity and specificity in detecting arterial line blood pressure artifacts compared with manual data cleaning. Given the growing use of large datasets and machine learning in critical care research, methods to validate the quality of high-frequency data is important to optimize algorithm performance and prevent spurious associations based on artifactual data.

P94: COVID-19-related ARDS Supported with Extracorporeal Membrane Oxygenation: Using Machine Learning Models to Improve Care

Background: Revised guidelines clarify indications for extracorporeal membrane oxygenation (ECMO) support in patients with COVID-19-related acute respiratory distress syndrome (ARDS). Commercially available ECMO analytics software records granular perfusion data continuously throughout the run. To date, electronic-medical record (EMR) clinical data has not been integrated with ECMO perfusion data and analyzed with machine learning-based algorithms to improve patient care. Methods: Retrospective chart review was performed on all SARS-CoV2 positive patients cannulated to veno-venous ECMO at an urban high-volume regional referral center from March 1st, 2020, through December 31st, 2021. Categorical data including patient demographics, clinical outcomes, and laboratory data (complete blood count, basic metabolic panel, arterial blood gas, lactate, anticoagulation assays) and vital signs (pulse, arterial line blood pressure, oxygen saturation) were collected for the entirety of the ECMO run. Time-series perfusion data (arterial flow normalized to body surface area (BSA), sweep gas, delta pressures normalized to arterial flow) were captured every 60-120 seconds. We constructed a predictive long-short term memory (LSTM) predictive model that integrated clinical and time-series data using an extended machine learning (ML) framework with neural network. Primary outcome was successful ECMO decannulation. Data were truncated to discrete and relative timepoints (7, 14, 21 days, or percent of the run). Receiver operating characteristic (ROC) curves show the model’s diagnostic accuracy. Results: 42 patients were included in the analysis (30 male, 12 female). Mean age was 43.9 (SD=11.5) years old, and mean duration of ECMO run was 36.2 (SD=30.1) days. 24 patients were successfully decannulated and 4 are currently supported on ECMO. When provided the complete data, the LSTM model showed an area under the ROC curve >0.95, demonstrating strong diagnostic accuracy in predicting successful ECMO decannulation (Figure 1A). When data were truncated to only the first two weeks of the ECMO run, the area under the ROC curve was 0.93 (Fig. 1B). Patterns of arterial flow normalized to BSA and sweep gas normalized to flow also appear different in patients with divergent clinical outcomes (Fig 2). Conclusion: Characterizing key determinants of ECMO support may offer intensive care unit healthcare teams potentially lifesaving information in real-time. Our machine-learning model successfully integrates clinical and perfusion data from the mind’s eye of a clinician managing the care of a patient supported with ECMO. We have identified critical variables with the most meaningful impact on the mechanics of ECMO support. Our model may also help predict patient outcomes into and offer clinicians opportunities for interventions to improve care.

Comparison of the injection of low-molecular weight heparin in the arterial vs. venous blood line for preventing extracorporeal circuit clotting during hemodialysis.

Low-molecular weight heparins (LMWH) are widely used for preventing clotting during hemodialysis (HD). Although injection in the venous blood line is recommended to avoid initial loss of LMWH through the dialyzer, LMWH is still frequently administered in the arterial blood line at the start of dialysis. This study aimed to compare the safety and efficacy of the same enoxaparin dose administered through the venous blood line or arterial blood line. We also evaluated antifactor Xa (aXa) activity according to the injection route and dialysis modalities: high-flux (HF) HD, medium cut-off (MCO) HD, and online hemodiafiltration (OL-HDF). Forty-three patients were studied over 18 consecutive dialysis sessions using a fixed enoxaparin dose (20 or 40 mg), first administered through the arterial blood line bolus and then through the venous blood line for another 18 sessions. Compared to arterial blood line administration, venous blood line bolus resulted in a significant increase in median post-dialysis aXa activity: 0.16 (0.1-0.6) IU/ml versus 0.31 (0.1-1.3) IU/ml, respectively, p=0.006. After arterial blood line bolus of 40 mg enoxaparin, median post-dialysis aXa activity was significantly lower with OL-HDF compared to HF-HD: 0.14 (0.1-0.35) versus 0.32 (0.15-0.49), p=0.02. A trend for lower clotting within lines and bubble trap using venous blood line bolus was observed. In conclusion, venous blood line enoxaparin injection is safe in OL-HDF patients. However, in HF-HD and MCO-HD, venous blood line injection of 40 mg enoxaparin may increase overdosing risk. Thus, aXa activity should be monitored in HF-HD and MCO-HD patients at risk of bleeding and/or on vitamin K antagonists and careful surveillance is required when administering a 40 mg enoxaparin dose through the venous blood line route.

Comparison of the injection of low molecular weight heparin in arterial or venous bloodline for preventing extracorporeal circuit clotting during hemodialysis

Low molecular weight heparins (LMWH) are widely used for preventing clotting during hemodialysis (HD). Although injection in venous bloodline (VBL) is recommended to avoid initial loss of LMWH through the dialyzer, LMWH is still frequently administered in the arterial blood line (ABL) at the start of dialysis. The aim of this study was to compare the efficacy and safety of same enoxaparin dose administered through VBL or ABL. We also evaluated antifactor Xa (aXa) activity according to the injection route and dialysis modalities: high-flux (HF) HD, medium cut-off (MCO) HD and on-line hemodiafiltration (OL-HDF). This open, single-center prospective study was conducted at the Poitiers university Hospital HD unit. Forty-three patients were studied over 18 consecutive dialysis sessions using a fixed enoxaparin dose (20 or 40 mg) first administered through ABL bolus and then through VBL for another 18 sessions. Compared to ABL, VBL bolus resulted in significant increase in median post-dialysis aXa activity: 0.16 (0.1–0.6) IU/mL vs. 0.31 (0.1–1.3) IU/mL, respectively, P = 0.006. After ABL bolus of enoxaparin 40 mg, median post-dialysis aXa activity was significantly lower with OL-HDF compared to HF-HD: 0.14 (0.1–0.35) vs. 0.32 (0.15–0.49), P = 0.02. A trend for lower clotting within lines and bubble trap using VBL bolus was observed. In conclusion, VBL enoxaparin injection is safe in OL-HDF patients. However, in HF-HD and MCO-HD, VBL injection of enoxaparin 40 mg may increase overdosing risk. Thus, aXa activity should be monitored in HF-HD and MCO-HD patients at risk of bleeding and/or on vitamin K antagonists, and careful surveillance is required when administering enoxaparin dose 40 mg through the VBL route.

Imputation of the continuous arterial line blood pressure waveform from non-invasive measurements using deep learning

In two-thirds of intensive care unit (ICU) patients and 90% of surgical patients, arterial blood pressure (ABP) is monitored non-invasively but intermittently using a blood pressure cuff. Since even a few minutes of hypotension increases the risk of mortality and morbidity, for the remaining (high-risk) patients ABP is measured continuously using invasive devices, and derived values are extracted from the recorded waveforms. However, since invasive monitoring is associated with major complications (infection, bleeding, thrombosis), the ideal ABP monitor should be both non-invasive and continuous. With large volumes of high-fidelity physiological waveforms, it may be possible today to impute a physiological waveform from other available signals. Currently, the state-of-the-art approaches for ABP imputation only aim at intermittent systolic and diastolic blood pressure imputation, and there is no method that imputes the continuous ABP waveform. Here, we developed a novel approach to impute the continuous ABP waveform non-invasively using two continuously-monitored waveforms that are currently part of the standard-of-care, the electrocardiogram (ECG) and photo-plethysmogram (PPG), by adapting a deep learning architecture designed for image segmentation. Using over 150,000 min of data collected at two separate health systems from 463 patients, we demonstrate that our model provides a highly accurate prediction of the continuous ABP waveform (root mean square error 5.823 (95% CI 5.806–5.840) mmHg), as well as the derived systolic (mean difference 2.398 ± 5.623 mmHg) and diastolic blood pressure (mean difference − 2.497 ± 3.785 mmHg) compared to arterial line measurements. Our approach can potentially be used to measure blood pressure continuously and non-invasively for all patients in the acute care setting, without the need for any additional instrumentation beyond the current standard-of-care.

Blood Volume Monitoring: A Clinical Tool to Guide Ultrafiltration in Volume Control and Optimisation of Intradialytic Blood Pressure

The importance of extracellular volume control and avoidance of volume overload has been well documented in relation to the management of patients with chronic haemodialysis. Chronic volume overload results in poorly controlled hypertension, increased cardiovascular events, and increased all-cause mortality. Traditional methods of dry weight assessment have relied on clinical assessment to guide volume status. The challenge of achieving the balance between dry weights and preventing intradialytic complications is a formidable one. In order to achieve this, reproducible and sensitive methods are desirable to aid objective quantification of volume status. One such method is by the use of blood volume monitoring, which is achieved by real-time calculation of changes in relative blood volume via a cuvette placed in the arterial blood-line, which can be used to guide ultrafiltration targets during the haemodialysis session. This review article examines the use of blood volume monitoring as a tool to guide ultrafiltration during dialysis and to examine the current evidence to supports its use in assessing dry weight and in preventing intradialytic hypotension events.

MO660INTERRELATIONSHIP BETWEEN PROTEIN BOUND UREMIC TOXIN INDOXYL SULFATE CONCENTRATION IN BLOOD AND SPENT DIALYSATE DURING HEMODIALYSIS TREATMENT

Abstract Background and Aims Indoxyl sulfate (IS) is a representative of the protein-bound uremic retention solutes [1]. Among CKD patients, high serum levels of IS are associated with high cardiovascular and all-cause mortality – IS is linked to cardiovascular outcomes, induces acceleration of atherosclerosis and abnormal bone metabolism [2,3]. Optical monitoring of the uremic marker molecules in the spent dialysate has been proposed [4] to estimate on-line concentration and removal of uremic toxins, allowing to assess total removed solute and removal rate of uremic toxins. Although several studies have been published covering the on-line optical monitoring of the spent dialysate, there is scarce knowledge about relation between spent dialysate and blood concentrations for protein-bound uremic solutes. The aim of this study was to evaluate the relationship between protein bound uremic toxin IS concentration in blood and spent dialysate during hemodialysis (HD) and hemodiafiltration (HDF) with different treatment settings, with the potential of evaluating uremic toxins’ levels in blood by assessing uremic toxins’ concentration in spent dialysate. Method 22 ESKD patients (16 male and 8 female, 55±17 years) on chronic HDF were enrolled into the study (fistula N=15, graft N=7). For each patient 4 midweek dialysis sessions (length 240min, HD: N=1, Qb=200ml/min, Qd=300ml/min, 1,5m2; HDF: N=3, median (interquartile range) Qb = 298 (296-356) ml/min, Qd= 795 (500-800) ml/min, Vsubst = 21.8 (15-24.5) L, 1,8m2 and 2,2m2) were included. During each dialysis session, blood samples were taken at 0 min (start) and 240 min from the arterial blood line, and dialysate samples were taken at 7 min and 240 min from the outlet of the dialysis machine. After sample processing, serum total, serum free and spent dialysate IS concentrations were determined by HPLC. Regression analysis was carried out. Results Median (interquartile range) IS concentrations in blood were 10.02 (6.68 - 14.68) µmol/L for free IS, 101.33 (56.99- 125.66) µmol/L for total IS, and 3.74 (2.35- 5.93) µmol/L in dialysate at the beginning of dialysis, and 6.07 (3.58- 9.00) µmol/L, 56.70 (28.91-80.67) µmol/L, 1.94 (1.15-2.98) µmol/L at the end of dialysis, respectively. There was a strong correlation between IS concentration in blood and dialysate at the beginning and at the end of dialysis even without data normalization by treatment settings (Fig. 1), with the strongest correlation between free IS concentration and IS in dialysate at 240 min (R2 = 0,976) and at the beginning of dialysis (R2 = 0,962). The reason for the higher correlation between free IS in blood and IS in dialysate is that only protein non-bound fraction of IS is available for removal by dialysis from blood into dialysate. Conclusion There is a strong correlation between IS concentrations in blood and dialysate with different treatment settings during whole dialysis. Assessment of protein bound uremic toxins’ concentration in the spent dialysate by optical sensor could thus also provide information about the concentration of uremic toxins in blood. [1] Vanholder et al 2018; [2] Yamamoto et al 2020; [3] Barreto et al 2009; [4] Lauri et al 2019;

Monitoring relative blood volume changes during hemodialysis: Impact of the priming procedure.

The monitoring of relative blood volume (RBV) changes during hemodialysis is increasingly used to evaluate the effect of dialyzer ultrafiltration on intravascular volume to guide the removal of excess fluid in a manner that maintains hemodynamic stability of the patient. RBV monitoring is typically based on an optical or acoustic sensor placed in the arterial blood line that measures a marker of hemoconcentration, such as hematocrit, hemoglobin, or total blood protein. However, the accuracy of RBV monitors and the impact of their clinical use remain the subject of ongoing debate. Here, we show that, depending on the procedure of filling the extracorporeal circuit with the patient's blood at the beginning of the dialysis session, theindications of an RBV monitor may be misleading as to the actual changes of the intravascular volume. When the blood is first pumped into the dialyzer, the priming fluid (saline) that fills the circuit may be either infused into the patient or disposed of to a drain bag. In the latter case, the intravascular volume is suddenly reduced, which is not accounted for by RBV monitors that track only the subsequent reductions in blood volume due to dialyzer ultrafiltration. Weanalyzed this general aspect of RBV monitoring using model-based simulations and showed quantitatively how RBV changes calculated using hematocrit differ depending on the priming procedure.

Extraction of implantable cardiac devices: the role of transesophageal echocardiography monitoring

Introduction Background: Data for the utility of continuous trans-esophageal echocardiography (TEE) monitoring during trans venous lead extraction remain scarce. Removal of the implanted transvenous lead system can be a significantly complex procedure, facing main complications. Our objective: the retrospective assessment of the TEE in the monitoring during trans venous lead extraction of implantable cardiac devices (pacemaker and implantable cardiac defibrillator). Methods From November 2013 to November 2018 the transvenous lead extraction of 93 leads in 50 patients was reviewed. Lead extraction techniques combined traction and mechanical approach by the same surgeon. Extraction procedures were performed under general anesthesia either total intravenous or inhalation anesthesia. Invasive arterial line blood pressure and continuous TEE monitoring were performed. TEE images of different projections were acquired and stored before and immediately after the extraction of each lead. Results From the 50 patients (mean age 58.9 years, 64% male, 1.86% lead per patient) which had the following indication: lead dysfunction (24%), upgrade (8%), infection (54%), or other (14%). The lead extraction was complete for 69 out of 93 leads (74.19%), partial extraction was for 24 leads out of 93 leads (25.80%). General anesthesia by total intravenous (30%) and inhalation anesthesia (70%). New TEE findings following TEE were observed in 7 of 50 cases (14%). Two cases which had new mild tricuspid regurgitation without the need of re-intervention, new appearance or worsening of tricuspid regurgitation in three cases which needed non-emergency re-intervention and pericardial effusion in two cases. No cases needed rescue surgery. In all other cases, TEE findings did not entail immediate diagnostic or therapeutic measures. Discussion New findings necessitating immediate therapeutic measures occurred zero cases, no mortality, yet all patients with new TEE findings had strict observational control. We suggest TEE monitoring during trans venous lead extraction, as it provides useful real-time information and should be standard of care monitoring during lead extraction, to guide trans operative and postoperative management. TEE presents some non-negligible risks associated with its use and is a costly procedure, such investment, however, may have a high return in terms of increased patient safety.

Hemodialysis-induced changes in hematocrit, hemoglobin and total protein: Implications for relative blood volume monitoring.

BackgroundRelative blood volume (RBV) changes during hemodialysis (HD) are typically estimated based on online measurements of hematocrit, hemoglobin or total blood protein. The aim of this study was to assess changes in the above parameters during HD in order to compare the potential differences in the RBV changes estimated by individual methods.Methods25 anuric maintenance HD patients were monitored during a 1-week conventional HD treatment. Blood samples were collected from the arterial dialysis blood line at the beginning and at the end of each HD session. The analysis of blood samples was performed using the hematology analyzer Advia 2120 and clinical chemistry analyzer Advia 1800 (Siemens Healthcare).ResultsDuring the analyzed 30 HD sessions with ultrafiltration in the range 0.7–4.0 L (2.5 ± 0.8 L) hematocrit (HCT) increased by 9.1 ± 7.0% (mean ± SD), hemoglobin (HGB) increased by 10.6 ± 6.3%, total plasma protein (TPP) increased by 15.6 ± 9.5%, total blood protein (TBP) increased by 10.4 ± 5.8%, red blood cell count (RBC) increased by 10.8 ± 7.1%, while mean corpuscular red cell volume (MCV) decreased by 1.5 ± 1.1% (all changes statistically significant, p < 0.001). HGB increased on average by 1.5% more than HCT (p < 0.001). The difference between HGB and TBP increase was insignificant (p = 0.16).ConclusionsTracking HGB or TBP can be treated as equivalent for the purpose of estimating RBV changes during HD. Due to the reduction of MCV, the HCT-based estimate of RBV changes may underestimate the actual blood volume changes.

Removal of Protein-Bound Uremic Toxins during Hemodialysis Using a Binding Competitor.

Current hemodialysis techniques fail to efficiently remove the protein-bound uremic toxins p-cresyl sulfate and indoxyl sulfate due to their high degree of albumin binding. Ibuprofen, which shares the same primary albumin binding site with p-cresyl sulfate and indoxyl sulfate, can be infused during hemodialysis to displace these toxins, thereby augmenting their removal. We infused 800 mg ibuprofen into the arterial bloodline between minutes 21 and 40 of a conventional 4-hour high-flux hemodialysis treatment. We measured arterial, venous, and dialysate outlet concentrations of indoxyl sulfate, p-cresyl sulfate, tryptophan, ibuprofen, urea, and creatinine before, during, and after the ibuprofen infusion. We report clearances of p-cresyl sulfate and indoxyl sulfate before and during ibuprofen infusion and dialysate concentrations of protein-bound uremic toxins normalized to each patient's average preinfusion concentrations. We studied 18 patients on maintenance hemodialysis: age 36±11 years old, ten women, and mean vintage of 37±37 months. Compared with during the preinfusion period, the median (interquartile range) clearances of indoxyl sulfate and p-cresyl sulfate increased during ibuprofen infusion from 6.0 (6.5) to 20.2 (27.1) ml/min and from 4.4 (6.7) to 14.9 (27.1) ml/min (each P<0.001), respectively. Relative median (interquartile range) protein-bound uremic toxin dialysate outlet levels increased from preinfusion 1.0 (reference) to 2.4 (1.2) for indoxyl sulfate and to 2.4 (1.0) for p-cresyl sulfate (each P<0.001). Although median serum post- and predialyzer levels in the preinfusion period were similar, infusion led to a marked drop in serum postdialyzer levels for both indoxyl sulfate and p-cresyl sulfate (-1.0 and -0.3 mg/dl, respectively; each P<0.001). The removal of the nonprotein-bound solutes creatinine and urea was not increased by the ibuprofen infusion. Infusion of ibuprofen into the arterial bloodline during hemodialysis significantly increases the dialytic removal of indoxyl sulfate and p-cresyl sulfate and thereby, leads to greater reduction in their serum levels.

Error-checking intraoperative arterial line blood pressures.

Electronic medical records now store a wealth of intraoperative hemodynamic data. However, analysis of such data is plagued by artifacts related to the monitoring environment. Here, we present an algorithm for automated identification of artifacts and replacement using interpolation of arterial line blood pressures. After IRB approval, minute-by-minute digital recordings of systolic, diastolic, and mean arterial pressures (MAP) obtained during anesthesia care were analyzed using predetermined metrics to identify values anomalous from adjacent neighbors. Anomalous data points were then replaced with linear interpolation of neighbors. The algorithm was then validated against manual artifact identification in 54 anesthesia records and 41,384 arterial line measurements. To assess the algorithm's effect on data analysis, we calculated the percent of time spent with MAP below 55mmHg and above 100mmHg for both raw and conditioned datasets. Manual review of the dataset identified 1.23% of all pressure readings as artifactual. When compared to manual review, the algorithm identified artifacts with 87.0% sensitivity and 99.4% specificity. The average difference between manual review and algorithm in identifying the start of arterial line monitoring was 0.17, and 2.1min for the end of monitoring. Application of the algorithm decreased the percent of time below 55mmHg from 4.3 to 2.0% (2.1% with manual review) and time above 100mmHg from 8.8 to 7.3% (7.3% manual). This algorithm's performance was comparable to manual review by a human anesthesiologist and reduced the incidence of abnormal MAP values identified using a sample analysis tool.

VAVD vacuum may cause bubble transgression in membrane oxygenators.

Vacuum-assisted venous drainage (VAVD) is widely used to enhance venous blood return from patients undergoing cardiopulmonary bypass (CPB). This vacuum can accidentally reach the oxygenator of the heart-lung machine and draw gas bubbles into the blood. This is known as bubble transgression (BT) and may cause air emboli in the arterial blood line. In order to avoid BT and minimize the risk of patient injury, knowledge of oxygenator tolerance to vacuum load is critical. Thus, the main aim of this thesis was to investigate how much vacuum a membrane oxygenator can withstand before BT appears. We investigated four different adult oxygenators: Quadrox-i, Affinity Fusion, Capiox RX25 and Inspire 6M. They were tested in an in vitro setup where VAVD vacuum was allowed to reach the oxygenator through a non-occlusive roller pump. An ultrasonic clinical bubble counter, Gampt BCC 200, was used to count bubbles on the arterial line when the arterial pump was restarted. We observed a significant increase in bubble count for two of the oxygenators, caused by -30 mmHg of VAVD vacuum in the blood reservoir (Affinity Fusion and Inspire 6M). Massive air ingress was shown in two of the oxygenators, caused by -30 mmHg of VAVD vacuum in the reservoir (Capiox RX25) and -40 mmHg of VAVD vacuum in the reservoir (Affinity Fusion). VAVD vacuum may cause bubble transgression in an oxygenator. This was shown for all the oxygenators in this test. VAVD vacuum may cause visible massive air ingress in an oxygenator. This was shown for two of the oxygenators in this test (Capiox RX25 and Affinity Fusion). An alarm triggering on negative pressure in the oxygenator or a pressure relief valve might improve safety when using VAVD.

Citrate Anticoagulation in Tandem Membrane Plasma-Exchange or Immunoadsorption and Hemodialysis in Patients With Immunological Diseases and Dialysis-Dependence.

In 1996 we performed tandem membrane plasma exchange-hemodialysis in a 3-year-old girl and tandem immunoadsorption-hemodialysis with citrate as the only anticoagulant in a patient with Goodpasture's syndrome. In the present study, we evaluated the feasibility, efficacy and safety of 24 tandem plasma exchange/immunoadsorption hemodialysis procedures in four different circuit setups with citrate as the only anticoagulant. In two setups, the tandem procedures were connected in series (plasma exchange hemodialysis and immunoadsorption hemodialysis), while in the other two setups they were in parallel (plasma exchange hemodialysis with independent blood circuits and plasma exchange hemodialysis with independent arterial blood lines, but with a common return line). All tandem procedures were feasible, efficient and safe. No serious side-effects were recorded. The most elegant setup was the procedure with independent, parallel blood circuits. However, serial tandem procedures provided for the elimination of citrate and normalization of electrolytes before blood was returned to the patient.