Differences in Cardiac Troponin T Composition in Myocardial Infarction and End-Stage Renal Disease Patients: A Blood Tube Effect?

BACKGROUND: Cardiac troponin T (cTnT) is key in diagnosing myocardial infarction (MI) but is also elevated in end-stage renal disease (ESRD) patients. Specific larger cTnT proteoforms were identified for the acute phase of MI, while in serum of ESRD patients solely small cTnT fragments were found. However, others allocated this to a pre-analytic effect due to abundant thrombin generation in serum. Therefore, we investigated the effect of various anticoagulation methods on cTnT composition and concentration and compared the cTnT composition of MI and ESRD patients. METHODS: The agreement of cTnT concentrations between simultaneously collected serum, lithium-heparin (LH) plasma, and ethylenediaminetetraacetic acid (EDTA) plasma was studied using the high-sensitivity (hs-)cTnT immunoassay. cTnT proteoform composition was investigated in a standardized time-dependent manner through spike experiments and in simultaneously collected blood matrixes of MI and ESRD patients. RESULTS: Excellent hs-cTnT concentration agreements were observed across all blood matrixes (slopes > 0.98; 95% CI, 0.96-1.04). Time-dependent degradation (40 kDa intact:29 kDa fragment:15 to 18 kDa fragments) was found in LH plasma and EDTA plasma, and serum in ratios (%) of 90:10:0, 0:5:95, and 0:0:100, respectively (48 h after blood collection). Moreover, gel filtration chromatography (GFC) profiles illustrated mainly larger cTnT proteoforms in MI patients, while in ESRD patients mainly 15 to 18 kDa fragments were found for all matrices. CONCLUSIONS: The extent of cTnT degradation in vitro is dependent on the (anti)coagulation method, without impacting hs-cTnT concentrations. Furthermore, mainly larger cTnT proteoforms were present in MI patients, while in ESRD patients mainly small 15 to 18 kDa cTnT fragments were found. These insights are essential when developing a novel hs-cTnT assay targeting larger cTnT proteoforms.

The Feasibility of Semi-Continuous and Multi-Frequency Thoracic Bioimpedance Measurements by a Wearable Device during Fluid Changes in Hemodialysis Patients.

Repeated single-point measurements of thoracic bioimpedance at a single (low) frequency are strongly related to fluid changes during hemodialysis. Extension to semi-continuous measurements may provide longitudinal details in the time pattern of the bioimpedance signal, and multi-frequency measurements may add in-depth information on the distribution between intra- and extracellular fluid. This study aimed to investigate the feasibility of semi-continuous multi-frequency thoracic bioimpedance measurements by a wearable device in hemodialysis patients. Therefore, thoracic bioimpedance was recorded semi-continuously (i.e., every ten minutes) at nine frequencies (8-160 kHz) in 68 patients during two consecutive hemodialysis sessions, complemented by a single-point measurement at home in-between both sessions. On average, the resistance signals increased during both hemodialysis sessions and decreased during the interdialytic interval. The increase during dialysis was larger at 8 kHz (∆ 32.6 Ω during session 1 and ∆ 10 Ω during session 2), compared to 160 kHz (∆ 29.5 Ω during session 1 and ∆ 5.1 Ω during session 2). Whereas the resistance at 8 kHz showed a linear time pattern, the evolution of the resistance at 160 kHz was significantly different (p < 0.0001). Measuring bioimpedance semi-continuously and with a multi-frequency current is a major step forward in the understanding of fluid dynamics in hemodialysis patients. This study paves the road towards remote fluid monitoring.

Comparison of whole body versus thoracic bioimpedance in relation to ultrafiltration volume and systolic blood pressure during hemodialysis.

In contrast to whole body bioimpedance, which estimates fluid status at a single point in time, thoracic bioimpedance applied by a wearable device could enable continuous measurements. However, clinical experience with thoracic bioimpedance in patients on dialysis is limited. To test the reproducibility of whole body and thoracic bioimpedance measurements and to compare their relationship with hemodynamic changes during hemodialysis, these parameters were measured pre- and end-dialysis in 54 patients during two sessions. The resistance from both bioimpedance techniques was moderately reproducible between two dialysis sessions (intraclass correlations of pre- to end-dialysis whole body and thoracic resistance between session 1 and 2 were 0.711 [0.58-0.8] and 0.723 [0.6-0.81], respectively). There was a very high to high correlation between changes in ultrafiltration volume and changes in whole body thoracic resistance. Changes in systolic blood pressure negatively correlated to both bioimpedance techniques. Although the relationship between changes in ultrafiltration volume and changes in resistance was stronger for whole body bioimpedance, the relationship with changes in blood pressure was at least comparable for thoracic measurements. These results suggest that thoracic bioimpedance, measured by a wearable device, may serve as an interesting alternative to whole body measurements for continuous hemodynamic monitoring during hemodialysis.NEW & NOTEWORTHY We examined the role of whole body and thoracic bioimpedance in hemodynamic changes during hemodialysis. Whole body and thoracic bioimpedance signals were strongly related to ultrafiltration volume and moderately, negatively, to changes in blood pressure. This work supports the further development of a wearable device measuring thoracic bioimpedance longitudinally in patients on hemodialysis. As such, it may serve as an innovative tool for continuous hemodynamic monitoring during hemodialysis in hospital or in a home-based setting.

Branched-chain ketoacid co-ingestion with protein lowers amino acid oxidation during hemodialysis: A randomized controlled cross-over trial.

BACKGROUND & AIMS: Hemodialysis removes amino acids from the circulation, thereby stimulating muscle proteolysis. Protein ingestion during hemodialysis can compensate for amino acid removal but may also increase uremic toxin production. Branched-chain ketoacid (BCKA) co-ingestion may provide an additional anabolic stimulus without adding to uremic toxin accumulation. In the present study we assessed the impact of BCKA co-ingestion with protein on forearm amino acid balance and amino acid oxidation during hemodialysis. METHODS: Nine patients (age: 73 ± 10 y) on chronic hemodialysis participated in this crossover trial. During two 4-h hemodialysis sessions, patients ingested 18 g protein with (PRO + BCKA) or without (PRO) 9 g BCKAs in a randomized order. Test beverages were labeled with L-[ring-13C6]-phenylalanine and provided throughout the last 3 h of hemodialysis as 18 equal sips consumed with 10-min intervals. Arterial and venous plasma as well as breath samples were collected frequently throughout hemodialysis. RESULTS: Arterial plasma total amino acid (TAA) concentrations during PRO and PRO + BCKA treatments were significantly lower after 1 h of hemodialysis (2.6 ± 0.3 and 2.6 ± 0.3 mmol/L, respectively) when compared to pre-hemodialysis concentrations (4.2 ± 1.0 and 4.0 ± 0.5 mmol/L, respectively; time effect: P < 0.001). Arterial plasma TAA concentrations increased throughout test beverage ingestion (time effect: P = 0.027) without differences between treatments (time∗treatment: P = 0.62). Forearm arteriovenous TAA balance during test beverage ingestion did not differ between timepoints (time effect: P = 0.31) or treatments (time∗treatment: P = 0.34). Whole-body phenylalanine oxidation was 33 ± 16% lower during PRO + BCKA when compared to PRO treatments (P < 0.001). CONCLUSIONS: BCKA co-ingestion with protein during hemodialysis does not improve forearm net protein balance but lowers amino acid oxidation.

Interactions between intradialytic central venous oxygen saturation, relative blood volume, and all-cause mortality in maintenance hemodialysis patients.

INTRODUCTION: In maintenance hemodialysis (HD) patients, low central venous oxygen saturation (ScvO2 ) and small decline in relative blood volume (RBV) have been associated with adverse outcomes. Here we explore the joint association between ScvO2 and RBV change in relation to all-cause mortality. METHODS: We conducted a retrospective study in maintenance HD patients with central venous catheters as vascular access. During a 6-month baseline period, Crit-Line (Fresenius Medical Care, Waltham, MA) was used to measure continuously intradialytic ScvO2 and hematocrit-based RBV. We defined four groups per median change of RBV and median ScvO2 . Patients with ScvO2 above median and RBV change below median were defined as reference. Follow-up period was 3 years. We constructed Cox proportional hazards model with adjustment for age, diabetes, and dialysis vintage to assess the association between ScvO2 and RBV and all-cause mortality during follow-up. FINDINGS: Baseline comprised 5231 dialysis sessions in 216 patients. The median RBV change was -5.5% and median ScvO2 was 58.8%. During follow-up, 44 patients (20.4%) died. In the adjusted model, all-cause mortality was highest in patients with ScvO2 below median and RBV change above median (HR 6.32; 95% confidence interval [CI] 1.37-29.06), followed by patients with ScvO2 below median and RBV change below median (HR 5.04; 95% CI 1.14-22.35), and ScvO2 above median and RBV change above median (HR 4.52; 95% CI 0.95-21.36). DISCUSSION: Concurrent combined monitoring of intradialytic ScvO2 and RBV change may provide additional insights into a patient's circulatory status. Patients with low ScvO2 and small changes in RBV may represent a specifically vulnerable group of patients at particularly high risk for adverse outcomes, possibly related to poor cardiac reserve and fluid overload.

The association of prediabetes and type 2 diabetes with hippocampal subfields volume: The Maastricht study.

AIMS/HYPOTHESIS: We investigated whether prediabetes, type 2 diabetes, and continuous measures of hyperglycemia are associated with tissue volume differences in specific subfields of the hippocampus. METHODS: We used cross-sectional data from 4,724 participants (58.7 ± 8.5 years, 51.5% women) of The Maastricht Study, a population-based prospective cohort. Glucose metabolism status was assessed with an oral glucose tolerance test, and defined as type 2 diabetes (n = 869), prediabetes (n = 671), or normal glucose metabolism (n = 3184). We extracted 12 hippocampal subfield volumes per hemisphere with FreeSurfer v6.0 using T1w and FLAIR 3T MRI images. We used multiple linear regression and linear trend analysis, and adjusted for total intracranial volume, demographic, lifestyle, and cardiovascular risk factors. RESULTS: Type 2 diabetes was significantly associated with smaller volumes in the hippocampal subfield fimbria (standardized beta coefficient ± standard error (ß ± SE) = -0.195 ± 0.04, p-value < 0.001), the hippocampus proper, i.e. Cornu Ammonis (CA) 1, CA2/3, CA4, dentate gyrus, subiculum and presubiculum (ß ± SE < -0.105 ± 0.04, p-value < 0.006); as well as the hippocampal tail (ß ± SE = -0.162 ± 0.04, p-value < 0.001). Prediabetes showed no significant associations. However, linear trend analysis indicated a dose-response relation from normal glucose metabolism, to prediabetes, to type 2 diabetes. Multiple continuous measures of hyperglycemia were associated with smaller volumes of the subfields fimbria (ß ± SE < -0.010 ± 0.011, p-value < 0.001), dentate gyrus (ß ± SE < -0.013 ± 0.010, p-value < 0.002), CA3 (ß ± SE < -0.014 ± 0.011, p-value < 0.001), and tail (ß ± SE < -0.006 ± 0.012, p-value < 0.003). CONCLUSIONS/INTERPRETATION: Type 2 diabetes and measures of hyperglycemia are associated with hippocampal subfield atrophy, independently of lifestyle and cardiovascular risk factors. We found evidence for a dose-response relationship from normal glucose metabolism, to prediabetes, to type 2 diabetes. Prediabetes stages could give a window of opportunity for the early prevention of brain disease.

Real-time prediction of intradialytic hypotension using machine learning and cloud computing infrastructure.

BACKGROUND: In maintenance hemodialysis patients, intradialytic hypotension (IDH) is a frequent complication that has been associated with poor clinical outcomes. Prediction of IDH may facilitate timely interventions and eventually reduce IDH rates. METHODS: We developed a machine learning model to predict IDH in in-center hemodialysis patients 15-75 min in advance. IDH was defined as systolic blood pressure (SBP) <90 mmHg. Demographic, clinical, treatment-related and laboratory data were retrieved from electronic health records and merged with intradialytic machine data that were sent in real-time to the cloud. For model development, dialysis sessions were randomly split into training (80%) and testing (20%) sets. The area under the receiver operating characteristic curve (AUROC) was used as a measure of the model's predictive performance. RESULTS: We utilized data from 693 patients who contributed 42 656 hemodialysis sessions and 355 693 intradialytic SBP measurements. IDH occurred in 16.2% of hemodialysis treatments. Our model predicted IDH 15-75 min in advance with an AUROC of 0.89. Top IDH predictors were the most recent intradialytic SBP and IDH rate, as well as mean nadir SBP of the previous 10 dialysis sessions. CONCLUSIONS: Real-time prediction of IDH during an ongoing hemodialysis session is feasible and has a clinically actionable predictive performance. If and to what degree this predictive information facilitates the timely deployment of preventive interventions and translates into lower IDH rates and improved patient outcomes warrants prospective studies.

Wearables in Nephrology: Fanciful Gadgetry or Prêt-à-Porter?

Telemedicine and digitalised healthcare have recently seen exponential growth, led, in part, by increasing efforts to improve patient flexibility and autonomy, as well as drivers from financial austerity and concerns over climate change. Nephrology is no exception, and daily innovations are underway to provide digitalised alternatives to current models of healthcare provision. Wearable technology already exists commercially, and advances in nanotechnology and miniaturisation mean interest is also garnering clinically. Here, we outline the current existing wearable technology pertaining to the diagnosis and monitoring of patients with a spectrum of kidney disease, give an overview of wearable dialysis technology, and explore wearables that do not yet exist but would be of great interest. Finally, we discuss challenges and potential pitfalls with utilising wearable technology and the factors associated with successful implementation.

Deep Learning for Image Analysis in Kidney Care.

Analysis of medical images, such as radiological or tissue specimens, is an indispensable part of medical diagnostics. Conventionally done manually, the process may sometimes be time-consuming and prone to interobserver variability. Image classification and segmentation by deep learning strategies, predominantly convolutional neural networks, may provide a significant advance in the diagnostic process. In renal medicine, most evidence has been generated around the radiological assessment of renal abnormalities and histological analysis of renal biopsy specimens' segmentation. In this article, the basic principles of image analysis by convolutional neural networks, brief descriptions of convolutional neural networks, and their system architecture for image analysis are discussed, in combination with examples regarding their use in image analysis in nephrology.

Biphasic Dynamics of Inflammatory Markers Following Hemodialysis Initiation: Results From the International MONitoring Dialysis Outcome Initiative.

Introduction: Inflammation is highly prevalent among patients with end-stage kidney disease and is associated with adverse outcomes. We aimed to investigate longitudinal changes in inflammatory markers in a diverse international incident hemodialysis patient population. Methods: The MONitoring Dialysis Outcomes (MONDO) Consortium encompasses hemodialysis databases from 31 countries in Europe, North America, South America, and Asia. The MONDO database was queried for inflammatory markers (total white blood cell count [WBC], neutrophil count, lymphocyte count, serum albumin, and C-reactive protein [CRP]) and hemoglobin levels in incident hemodialysis patients. Laboratory parameters were measured every month. Patients were stratified by survival time (≤6 months, >6 to 12 months, >12 to 18 months, >18 to 24 months, >24 to 30 months, >30 to 36 months, and >36 months) following dialysis initiation. We used cubic B-spline basis function to evaluate temporal changes in inflammatory parameters in relationship with patient survival. Results: We studied 18,726 incident hemodialysis patients. Their age at dialysis initiation was 71.3 ± 11.9 years; 10,802 (58%) were males. Within the first 6 months, 2068 (11%) patients died, and 12,295 patients (67%) survived >36 months (survivor cohort). Hemodialysis patients who died showed a distinct biphasic pattern of change in inflammatory markers where an initial decline of inflammation was followed by a rapid rise that was consistently evident approximately 6 months before death. This pattern was similar in all patients who died and was consistent across the survival time intervals. In contrast, in the survivor cohort, we observed initial decline of inflammation followed by sustained low levels of inflammatory biomarkers. Conclusion: Our international study of incident hemodialysis patients highlights a temporal relationship between serial measurements of inflammatory markers and patient survival. This finding may inform the development of prognostic models, such as the integration of dynamic changes in inflammatory markers for individual risk profiling and guiding preventive and therapeutic interventions.

Predicting mortality risk in dialysis: Assessment of risk factors using traditional and advanced modeling techniques within the Monitoring Dialysis Outcomes initiative.

INTRODUCTION: Several factors affect the survival of End Stage Kidney Disease (ESKD) patients on dialysis. Machine learning (ML) models may help tackle multivariable and complex, often non-linear predictors of adverse clinical events in ESKD patients. In this study, we used advanced ML method as well as a traditional statistical method to develop and compare the risk factors for mortality prediction model in hemodialysis (HD) patients. MATERIALS AND METHODS: We included data HD patients who had data across a baseline period of at least 1 year and 1 day in the internationally representative Monitoring Dialysis Outcomes (MONDO) Initiative dataset. Twenty-three input parameters considered in the model were chosen in an a priori manner. The prediction model used 1 year baseline data to predict death in the following 3 years. The dataset was randomly split into 80% training data and 20% testing data for model development. Two different modeling techniques were used to build the mortality prediction model. FINDINGS: A total of 95,142 patients were included in the analysis sample. The area under the receiver operating curve (AUROC) of the model on the test data with XGBoost ML model was 0.84 on the training data and 0.80 on the test data. AUROC of the logistic regression model was 0.73 on training data and 0.75 on test data. Four out of the top five predictors were common to both modeling strategies. DISCUSSION: In the internationally representative MONDO data for HD patients, we describe the development of a ML model and a traditional statistical model that was suitable for classification of a prevalent HD patient's 3-year risk of death. While both models had a reasonably high AUROC, the ML model was able to identify levels of hematocrit (HCT) as an important risk factor in mortality. If implemented in clinical practice, such proof-of-concept models could be used to provide pre-emptive care for HD patients.

Intradialytic Protein Ingestion and Exercise do Not Compromise Uremic Toxin Removal Throughout Hemodialysis.

OBJECTIVE: Dietary protein and physical activity interventions are increasingly implemented during hemodialysis to support muscle maintenance in patients with end-stage renal disease (ESRD). Although muscle maintenance is important, adequate removal of uremic toxins throughout hemodialysis is the primary concern for patients. It remains to be established whether intradialytic protein ingestion and/or exercise modulate uremic toxin removal during hemodialysis. METHODS: We recruited 10 patients with ESRD (age: 65 ± 16 y, BMI: 24.2 ± 4.8 kg/m2) on chronic hemodialysis treatment to participate in this randomized cross-over trial. During hemodialysis, patients were assigned to ingest 40 g protein or a nonprotein placebo both at rest (protein [PRO] and placebo [PLA], respectively) and following 30 min of exercise (PRO + exercise [EX] and PLA + EX, respectively). Blood and spent dialysate samples were collected throughout hemodialysis to assess reduction ratios and removal of urea, creatinine, phosphate, cystatin C, and indoxyl sulfate. RESULTS: The reduction ratios of urea and indoxyl sulfate were higher during PLA (76 ± 6% and 46 ± 9%, respectively) and PLA + EX interventions (77 ± 5% and 45 ± 10%, respectively) when compared to PRO (72 ± 4% and 40 ± 8%, respectively) and PRO + EX interventions (73 ± 4% and 43 ± 7%, respectively; protein effect: P = .001 and P = .023, respectively; exercise effect: P = .25 and P = .52, respectively). Nonetheless, protein ingestion resulted in greater urea removal (P = .046) during hemodialysis. Reduction ratios and removal of creatinine, phosphate, and cystatin C during hemodialysis did not differ following intradialytic protein ingestion or exercise (protein effect: P > .05; exercise effect: P>.05). Urea, creatinine, and phosphate removal were greater throughout the period with intradialytic exercise during PLA + EX and PRO + EX interventions when compared to the same period during PLA and PRO interventions (exercise effect: P = .034, P = .039, and P = .022, respectively). CONCLUSION: The removal of uremic toxins is not compromised by protein feeding and/or exercise implementation during hemodialysis in patients with ESRD.

The cardiometabolic depression subtype and its association with clinical characteristics: The Maastricht Study.

BACKGROUND: Individuals with depression often show an adverse cardiometabolic risk profile and might represent a distinct depression subtype. The aim of this study was to investigate whether a cardiometabolic depression subtype could be identified and to investigate its association with demographics and clinical characteristics (severity, symptomatology, anti-depressant use, persistence and cognitive functioning). METHODS: We used data from The Maastricht Study, a population-based cohort in the southern part of The Netherlands. A total of 248 participants with major depressive disorder were included (mean [SD] age, 58.8 ± 8.5 years; 121 [48.8 %] were men). Major depressive disorder was assessed at baseline by the Mini-International Neuropsychiatric Interview. Cardiometabolic risk factors were defined as indicators of the metabolic syndrome according to the National Cholesterol Education Program Adult Treatment Panel III guidelines. We measured severity and persistence of depressive symptoms by use of the 9-item Patient Health Questionnaire. RESULTS: Latent class analysis resulted in two subtypes, one with cardiometabolic depression (n = 145) and another with non-cardiometabolic depression (n = 103). The cardiometabolic depression subtype was characterized by being male, low education, more severe depressive symptoms, less symptoms of depressed mood and more symptoms of loss of energy, more use of antidepressant medication and lower cognitive functioning. LIMITATIONS: No conclusions can be made about causality. CONCLUSIONS: Latent class analysis suggested a distinct cardiometabolic depression subtype. Participants with cardiometabolic depression differed from participants with non-cardiometabolic depression in terms of demographics and clinical characteristics. The existence of a cardiometabolic depression subtype may indicate the need for prevention and treatment targeting cardiometabolic risk management.

Quadriceps muscle thickness assessed by ultrasound is independently associated with mortality in hemodialysis patients.

BACKGROUND/OBJECTIVES: Estimation of muscle mass is an integral part of nutritional assessment in End-Stage Kidney Disease (ESKD) patients on chronic hemodialysis (HD). In this respect, muscle ultrasound (US) is a valid and reliable tool but has not been previously related to outcomes in this population. Aims of this study were to assess the relationship between quadriceps muscle thickness as assessed by US and outcomes in ESKD patients on HD; we also compared US with anthropometry and malnutrition inflammation score (MIS). SUBJECTS/METHODS: In this prospective study, 181 prevalent patients on HD were included. Thickness of the quadriceps rectus femoris and vastus intermedius (VIT) were assessed separately using ultrasonography, and were indexed for height squared. Mid-arm muscle circumference (MAMC) and area (MAMA) were assessed by anthropometry. MIS was evaluated. In the absence of predetermined cut-offs, values below the median of the distribution of VIT index were considered low. Instead, cut-off for anthropometric values such as MAMC and MAMA were set at ≥90% of agreement with the 50th percentile of the sex- and age-specific normal distribution. Cox-regression analysis was used to assess the association of US, MIS, and anthropometric parameters with mortality. RESULTS: Patients were followed for a median of 35 months. During this period 36% of patients died. Multivariable Cox-regression analysis (adjusted for demographic, biochemical and clinical variables), demonstrated that higher VIT distal index values were independently associated with lower mortality risk (HR: 0.76 (0.59-0.99); P = 0.040), whilst higher MIS values were independently associated with higher (HR 1.22 (1.10-1.35); P < 0.001) mortality risk. When assessing muscle parameters as categorical variables, both low VIT distal index (HR: 1.71 (1.01-2.89); 0.045) and MAMC (HR: 1.74 (1.02-2.96); 0.042) were independently associated with increased risk of death. CONCLUSION: Indexed distal VIT was independently associated with mortality both as continuous and as a categorical variable. Muscle US is a simple practical tool that adds prognostic information to the bedside nutritional assessment in ESKD patients on maintenance HD.

Hidden risks associated with conventional short intermittent hemodialysis: A call for action to mitigate cardiovascular risk and morbidity.

The development of maintenance hemodialysis (HD) for end stage kidney disease patients is a success story that continues to save many lives. Nevertheless, intermittent renal replacement therapy is also a source of recurrent stress for patients. Conventional thrice weekly short HD is an imperfect treatment that only partially corrects uremic abnormalities, increases cardiovascular risk, and exacerbates disease burden. Altering cycles of fluid loading associated with cardiac stretching (interdialytic phase) and then fluid unloading (intradialytic phase) likely contribute to cardiac and vascular damage. This unphysiologic treatment profile combined with cyclic disturbances including osmotic and electrolytic shifts may contribute to morbidity in dialysis patients and augment the health burden of treatment. As such, HD patients are exposed to multiple stressors including cardiocirculatory, inflammatory, biologic, hypoxemic, and nutritional. This cascade of events can be termed the dialysis stress storm and sickness syndrome. Mitigating cardiovascular risk and morbidity associated with conventional intermittent HD appears to be a priority for improving patient experience and reducing disease burden. In this in-depth review, we summarize the hidden effects of intermittent HD therapy, and call for action to improve delivered HD and develop treatment schedules that are better tolerated and associated with fewer adverse effects.