The time of onset of intradialytic hypotension during a hemodialysis session associates with clinical parameters and mortality

Prognostic Significance of Visit-to-Visit Ultrafiltration Volume Variability in Hemodialysis Patients

Introduction: Patients on chronic hemodialysis (HD) have significantly higher mortality compared with the general population. Cardiovascular (CV) disease is the primary reason for death in these patients. Suboptimal extracellular fluid management increases the CV risk of HD patients. We aimed to study the effect of visit-to-visit ultrafiltration volume (UV) variability on CV events and mortality in chronic HD patients. Patients and Methods: In our study, 173 chronic HD patients were included (median age: 63 ± 13 years; 53% men). Ultrafiltration volume (UV) variability was analyzed retrospectively for 24 months. The standard deviation (SD) and coefficient of variation (CV) were calculated using the indices of UV variability. CV is the SD divided by the mean. The obtained parameters were SD and CV of the UV: UVSD and UVCV. UV data during the observation period were recorded and used to calculate UV variability. Routine transthoracal echocardiography was performed. Results: Patients were divided into groups based on the median of UVSD, low-UVSD (<568 mL) and high-UVSD (≥568 mL) group; and also based on the median of UVCV, low- (<0.29) and high-UVCV (≥0.29) group. All-cause mortality was significantly higher in the high compared to the low-UVSD (21/84 vs. 9/89; p < 0.001) group. Similarly, mortality was higher in the high-UVCV group compared to the low-UVCV group (18/78 vs. 12/95; p = 0.005) after 24 months. Major adverse CV event (MACE) rates were also significantly higher in the high- compared to the low-UVSD group (20/84 vs. 8/89; p < 0.001). Similarly, the MACE rate was significantly higher in the high-UVCV group compared to the low-UVCV group (15/78 vs. 13/95; p = 0.029) after 24 months. There was no significant difference between the groups in CV mortality. UVSD correlated with parathormone (PTH) level (r = 0.416; p = 0.015), and UVCV with total cholesterol (r = 0.419; p = 0.015). Left ventricular end-diastolic diameter (LVEDD) and end-systolic diameter (LVESD) were higher in the high-UVCV group compared to the low-UVCV group (49.95 vs. 52.08; p = 0.013 and 32.19 vs. 34.13; p = 0.034). Conclusions: According to our results, high UVSD and UVCD are associated with increased all-cause mortality and MACE rates but not CV mortality in chronic HD patients. Cardiovascular changes caused by increased UF volume variability during HD may contribute to higher CV morbidity and mortality in these patients.

Research on the development of an intelligent prediction model for blood pressure variability during hemodialysis

OBJECTIVE

Blood pressure fluctuations during dialysis, including intradialytic hypotension (IDH) and intradialytic hypertension (IDHTN), are common complications among patients undergoing maintenance hemodialysis. Early prediction of IDH and IDHTN can help reduce the occurrence of these fluctuations. With the development of artificial intelligence, machine learning and deep learning models have become increasingly sophisticated in the field of hemodialysis. Utilizing machine learning to predict blood pressure fluctuations during dialysis has become a viable predictive method.

METHODS

Our study included data from 67,524 hemodialysis sessions conducted at Ningbo No.2 Hospital and Xiangshan First People's Hospital from August 1, 2019, to September 30, 2023. 47,053 sessions were used for model training and testing, while 20,471 sessions were used for external validation. We collected 45 features, including general information, vital signs, blood routine, blood biochemistry, and other relevant data. Data not meeting the inclusion criteria were excluded, and feature engineering was performed. The definitions of IDH and IDHTN were clarified, and 10 machine learning algorithms were used to build the models. For model development, the dialysis data were randomly split into a training set (80%) and a testing set (20%). To evaluate model performance, six metrics were used: accuracy, precision, recall, F1 score, ROC-AUC, and PR-AUC. Shapley Additive Explanation (SHAP) method was employed to identify eight key features, which were used to develop a clinical application utilizing the Streamlit framework.

RESULTS

Statistical analysis showed that IDH occurred in 56.63% of hemodialysis sessions, while the incidence of IDHTN was 23.53%. Multiple machine learning models (e.g., CatBoost, RF) were developed to predict IDH and IDHTN events. XGBoost performed the best, achieving ROC-AUC scores of 0.89 for both IDH and IDHTN in internal validation, with PR-AUC scores of 0.95 and 0.78, and high accuracy, precision, recall, and F1 scores. The SHAP method identified pre-dialysis systolic blood pressure, BMI, and pre-dialysis mean arterial pressure as the top three important features. It has been translated into a convenient application for use in clinical settings.

CONCLUSION

Using machine learning models to predict IDH and IDHTN during hemodialysis is feasible and provides clinically reliable predictive performance. This can help timely implement interventions during hemodialysis to prevent problems, reduce blood pressure fluctuations during dialysis, and improve patient outcomes.

Rare Clinical Manifestation of Vasculitis

BACKGROUND

Antineutrophil cytoplasm antibody (ANCA)-associated vasculitis usually affects small blood vessels and is characterized by the presence of circulating autoantibodies (c-ANCA or p-ANCA). The risk of cardiovascular events is threefold higher compared to general population, and cardiac manifestations include myocarditis, pericarditis, valvulitis, aortitis, or coronary arteritis. Coronary involvement is very rare, but it is a potentially life-threatening manifestation.

METHODS

We present an atypical cardiac scenario of p-ANCA vasculitis.

RESULTS

A 68-year-old woman with known p-ANCA vasculitis and stage 5 chronic kidney disease (CKD) on hemodialysis presented with dizziness accompanied by low blood pressure and chest pain. Electrocardiogram on arrival showed slightly ST-T changes, with negative cardiac biomarkers and no abnormalities in cardiac regional wall motion. Five hours after presentation, the patient repeated chest pain, accompanied by a drop in blood pressure and junctional escape rhythm. The highly sensitive cardiac troponin I (hs-cTnI) was raised at 560 ng/L. Coronary angiography showed coronary arteries without significant stenosis. The provocative test with intracoronary ergonovine demonstrated coronary vasospasm of the anterior descending artery accompanied by chest pain, with resolution after intracoronary nitroglycerin. Under amlodipine, nitrate, acetylsalicylic acid, statin and corticosteroids the patient did not experience the recurrence of angina.

CONCLUSIONS

This case illustrates coronary involvement, manifested as coronary spasm with favorable outcomes, in systemic vasculitis. The underlying mechanism is immune-mediated inflammation in vascular walls.

The effect of changes in intra-compartmental bioimpedance measurements with early intra-dialytic hypotension during haemodialysis

INTRODUCTION

Intra-dialytic hypotension (IDH) remains the commonest problem associated with routine haemodialysis treatments. Fluid shifts from intracellular(ICW) and extracellular(ECW) compartments to refill plasma volume during haemodialysis with ultrafiltration.

METHODS

We studied the effect of relative changes in ICW and ECW indifferent body segments using multifrequency segmental bioimpedance during haemodialysis and IDH episodes.

RESULTS

Of 42 haemodialysis patients,16 patients (38.1%) developed IDH within the first hour of dialysis. Patients with and without early IDH were well-matched for demographics and starting bioimpedance measurements. However, after 60 min, the relative change in in ECW/ICW ratio between the non-fistula arm and leg was significantly different for the early IDH group median -1.07 (-3.33 to 0.8) versus 0.61 (-0.78 to 1.8), p < 0.05, whereas there no differences in ultrafiltration rate, relative blood volume monitoring or on-line clearance.

CONCLUSION

Monitoring serial changes in fluid status in different body compartments with bioimpedance may potentially prevent IDH in the future.

Association between Visit-to-Visit Ultrafiltration Volume Variability, Vascular Biomarkers and Cardiovascular Parameters in Chronic Hemodialysis Patients

Background. Cardiovascular (CV) diseases are the most common causes of morbidity and mortality in hemodialysis (HD) patients. We studied the effect of high visit-to-visit ultrafiltration (UF) variability on CV abnormalities in HD patients. Methods. Twenty-nine consecutive patients (age: 65.6 ± 10.4 years) were recruited. Samples for routine lab tests were drawn pre-HD for syndecan-1 (SDC-1) and endothelin-1 (ET-1) measurements pre-, mid- and post-HD. Applanation tonometry was performed pre-, mid- and post-HD. Visit-to-visit ultrafiltration volume variability (UVSD) was calculated as the standard deviation of the UF volume/dialysis session in the preceding 12 months. Echocardiography was performed post-HD. Results. Patients were divided into two groups based on the median of UVSD (500 mL). The average UF volume/HD was not different between the groups. Blood pressure (BP) values were similar. Pre-HD cfPWV (10.75 m/s) was lower in the high UVSD group (14.1 m/s, p = 0.03). In the high UVSD group, post-HD cfPWV (13.9 m/s) was higher than the pre-HD cfPWV (p < 0.05). Pre-HD ET-1 was lower in the high UVSD group (8.6 ± 3.9 vs. 10.8 ± 2.7 pg/mL, p < 0.05). Left ventricular end-diastolic diameter (LVEDD) and left ventricular mass index (LVMI) were higher in the high UVSD group (55.7 ± 7.3 vs. 51.0 ± 5.4 mm and 449.9 ± 180.5 vs. 350.3 ± 85.9 g/m², p < 0.005, respectively). Left ventricular ejection fraction (LVEF) was lower in the high UVSD group (53.5 vs. 60, p < 0.05). Conclusions. High UVSD was associated with increased left ventricular hypertrophy and dysfunction and decreased LVEF compared to low visit-to-visit UV variability despite similar UF volumes temporarily compensated by more elastic arteries. The observed abnormalities may increase CV risk.

Novel Method to Monitor Arteriovenous Fistula Maturation: Impact on Catheter Residence Time

INTRODUCTION

Arteriovenous fistula (AVF) maturation assessment is essential to reduce venous catheter residence. We introduced central venous oxygen saturation (ScvO2) and estimated upper body blood flow (eUBBF) to monitor newly created fistula maturation and recorded catheter time in patients with and without ScvO2-based fistula maturation.

METHODS

From 2017 to 2019, we conducted a multicenter quality improvement project (QIP) in hemodialysis patients with the explicit goal to shorten catheter residence time post-AVF creation through ScvO2-based maturation monitoring. In patients with a catheter as vascular access, we tracked ScvO2 and eUBBF pre- and post-AVF creation. The primary outcome was catheter residence time post-AVF creation. We compared catheter residence time post-AVF creation between QIP patients and controls. One control group comprised concurrent patients; a second control group comprised historic controls (2014-2016). We conducted Kaplan-Meier analysis and constructed a Cox proportional hazards model with variables adjustment to assess time-to-catheter removal.

RESULTS

The QIP group comprised 44 patients (59 ± 17 years), the concurrent control group 48 patients (59 ± 16 years), the historic control group 57 patients (58 ± 15 years). Six-month post-AVF creation, the fraction of non-censored patients with catheter in place was 21% in the QIP cohort, 67% in the concurrent control group, and 68% in the historic control group. In unadjusted and adjusted analysis, catheter residence time post-fistula creation was shorter in QIP patients compared to either control groups (p < 0.001).

CONCLUSION

ScvO2-based assessment of fistula maturation is associated with shorter catheter residence post-AVF creation.

Outcomes and complications of hemodialysis in patients with renal cancer following bilateral nephrectomy

Objectives

The management of patients undergoing bilateral nephrectomy for renal cancer presents significant challenges, particularly in addressing hypotension, anemia, and tumor recurrence during hemodialysis.

Case presentation

A patient diagnosed with renal clear cell carcinoma in 2009 was followed until his demise in June 2022, with detailed documentation of symptoms, signs, laboratory results, diagnosis, and treatment. In the presented case, post-nephrectomy, the patient experienced frequent hypotension and anemia during dialysis, improving with erythropoietin-stimulating agents and subsequently with rosuvastatin. Later, multiple metastases were detected, correlating with normalized blood pressure and hemoglobin.

Literature review

A literature search up to September 2023 was also conducted, gathering data on hypotension, anemia, and tumor recurrence post-nephrectomy. Literature analysis of six cases revealed a 100% tumor recurrence rate in elderly patients (>50 years).

Conclusion

Treatment of anemia in bilateral nephrectomy patients warrants consideration of medication-induced tumor recurrence, highlighting early kidney transplantation to avoid adverse reactions like hypotension.

Closed Loop Ultrafiltration Feedback Control in Hemodialysis: A Narrative Review

While life-sustaining, hemodialysis is a non-physiological treatment modality that exerts stress on the patient, primarily due to fluid shifts during ultrafiltration. Automated feedback control systems, integrated with sensors that continuously monitor bio-signals such as blood volume, can adjust hemodialysis treatment parameters, e.g., ultrafiltration rate, in real-time. These systems hold promise to mitigate hemodynamic stress, prevent intradialytic hypotension, and improve the removal of water and electrolytes in chronic hemodialysis patients. However, robust evidence supporting their clinical application remains limited. Based on an extensive literature research, we assess feedback-controlled ultrafiltration systems that have emerged over the past three decades in comparison to conventional hemodialysis treatment. We identified 28 clinical studies. Closed loop ultrafiltration control demonstrated effectiveness in 23 of them. No adverse effects of closed loop ultrafiltration control were reported across all trials. Closed loop ultrafiltration control represents an important advancement towards more physiological hemodialysis. Its development is driven by innovations in real-time bio-signals monitoring, advancement in control theory, and artificial intelligence. We expect these innovations will lead to the prevalent adoption of ultrafiltration control in the future, provided its clinical value is substantiated in adequately randomized controlled trials.

Intradialytic cardiovascular injury is lowest in high-volume haemodiafiltration: a randomized cross-over trial in four intermittent dialysis strategies

Background

Intradialytic hypotension (IDH) and subsequent tissue damage may contribute to the poor outcome of chronic haemodialysis (HD) patients. While the IDH-incidence is lower in high-volume haemodiafiltration (HV-HDF) than in standard HD (S-HD), survival is better in HV-HDF. Tissue injury, as measured by extracellular vesicle (EV)-release, was compared between four modalities.

Methods

Forty chronic patients were cross-over randomized to S-HD, cool-HD (C-HD), low-volume HDF (LV-HDF), and HV-HDF. Blood pressure was recorded every 15 minutes. EVs from circulating blood-cell-elements (bio-incompatibility-related) and cardiovascular (CV) tissues (CV-related), were measured before and after dialysis. The influence of modalities and IDH on the rate of change of EVs was assessed. Both crude and haemoconcentration-adjusted analyses were performed.

Results

Leukocyte and erythrocyte-derived EVs increased in all modalities. Platelet-derived EVs increased more in LV-HDF and HV-HDF (68.4 respectively 56.1 × 106/ml) than in S-HD (27.5 × 106/ml), P values for interaction were <.01 respectively .06. Endothelial-derived CD144+ (2.3 × 106/ml in HV-HDF and 9.8 × 106/ml in S-HD) and cardiomyocyte-derived Connexin-43+ (12.0 respectively 31.9 × 106/ml) EVs increased less in HV-HDF than in S-HD (P for interaction .03 respectively .06). Correction for haemoconcentration attenuated all changes, although the increase in platelet-derived EVs remained significant in LV-HDF and HV-HDF, and CD144+ and Connexin-43+ EVs increased most in S-HD. EV release was similar in patients with varying IDH susceptibility and in sessions with and without IDH.

Conclusions

Most EVs increase during HD and HDF. Regarding platelet-derived EVs, HDF appears less biocompatible than HD. Considering CV-related EVs, tissue injury seems less pronounced in HV-HDF. The finding that EV release is IDH-independent needs confirmation.

Effect of medium cut-off and high-flux hemodialysis membranes on blood pressure assessed by ambulatory blood pressure monitoring

BACKGROUND

Hypertension is one of the most critical risk factors for cardiovascular disease, which is the leading cause of death in hemodialysis (HD) patients. Medium cut-off (MCO) membrane increases the clearance of medium molecules, which could improve blood pressure (BP) control. This study aimed to compare the effect of MCO and high-flux hemodialysis membranes on BP assessed by ambulatory blood pressure monitoring (ABPM).

METHODS

This is a pre-established secondary analysis of a 28-week, randomized, open-label crossover clinical trial. Patients were randomized to HD with MCO or high-flux membranes over 12 weeks, followed by a 4-week washout period, and then switched to the alternate membrane treatment for 12 weeks. ABPM was started before the HD session and ended at least 24 h later in weeks 1, 12, 16, and 28.

RESULTS

32 patients, 59% male, with a mean age of 52.7 years, and 40% with unknown CKD etiology, were enrolled. The dialysis vintage was 8 years, and more than 70% of the patients had hypertension. Regarding 24-h BP control, morning diastolic BP showed an increase in the high-flux compared to stability in the MCO group (interaction effect, p = 0.039). The adjusted ANOVA models showed no significant difference in the morning BP levels between the groups. Considering only the period of the HD session, patients in the MCO, compared to those in the high-flux membrane group, showed greater BP stability during dialysis, characterized by smaller variation in the pre-post HD systolic and minimum systolic BP (treatment effect, p = 0.039, and p = 0.023, respectively).

CONCLUSIONS

MCO membrane seems to have a beneficial effect on morning BP and favors better BP stability during HD sessions.

Digital Health Support: Current Status and Future Development for Enhancing Dialysis Patient Care and Empowering Patients

Chronic kidney disease poses a growing global health concern, as an increasing number of patients progress to end-stage kidney disease requiring kidney replacement therapy, presenting various challenges including shortage of care givers and cost-related issues. In this narrative essay, we explore innovative strategies based on in-depth literature analysis that may help healthcare systems face these challenges, with a focus on digital health technologies (DHTs), to enhance removal and ensure better control of broader spectrum of uremic toxins, to optimize resources, improve care and outcomes, and empower patients. Therefore, alternative strategies, such as self-care dialysis, home-based dialysis with the support of teledialysis, need to be developed. Managing ESKD requires an improvement in patient management, emphasizing patient education, caregiver knowledge, and robust digital support systems. The solution involves leveraging DHTs to automate HD, implement automated algorithm-driven controlled HD, remotely monitor patients, provide health education, and enable caregivers with data-driven decision-making. These technologies, including artificial intelligence, aim to enhance care quality, reduce practice variations, and improve treatment outcomes whilst supporting personalized kidney replacement therapy. This narrative essay offers an update on currently available digital health technologies used in the management of HD patients and envisions future technologies that, through digital solutions, potentially empower patients and will more effectively support their HD treatments.

Transcatheter aortic valve replacement in patients with severe aortic stenosis reduced the frequency of intradialytic hypotension

Intradialytic hypotension (IDH) is a common complication during hemodialysis that increases cardiovascular morbidity and mortality. Aortic stenosis (AS) is a cause of IDH. Transcatheter aortic valve replacement (TAVR) has become an established treatment for patients with severe AS. However, whether TAVR reduce the frequency of IDH has not been investigated. This study aims to verify the efficacy of TAVR for reduction of the frequency of IDH. Consecutive hemodialysis patients who underwent TAVR at Sendai Kosei Hospital from February 2021 to November 2021 with available records 1 month before and 3 months after TAVR were included in the study. IDH was defined as a decrease in systolic blood pressure by 20 mmHg or a decrease in the mean blood pressure by 10 mmHg associated with hypotensive symptoms or requiring intervention. Patients with ≥ 3 episodes of IDH in ten hemodialysis sessions comprised the IDH group. Overall, 18/41 (43.9%) patients were classified into the IDH group. In ten hemodialysis sessions, IDH events were observed 2.1, 4.3, and 0.4 times in the overall cohort, IDH group, and non-IDH group, respectively. After TAVR, the incidence of IDH decreased from 43.2 to 10.3% (p < 0.0001) and IDH improved significantly in 15 patients in the IDH group. The result suggested that severe AS was the major cause of IDH in this cohort, and TAVR may be an effective treatment option for reduction of the frequency of IDH in patients with severe AS.

Risk factors for hypotension in patients with hemodialysis-associated superior vena cava syndrome

OBJECTIVE

We analyzed the risk factors for hypotension in patients with hemodialysis-associated superior vena cava syndrome (SVCS) and effectiveness of endovascular intervention in hypotension related to SVCS.

METHODS

This was a retrospective cohort study. A total of 194 maintenance hemodialysis patients diagnosed with SVCS who were admitted to the Department of Nephrology, West China Hospital of Sichuan University from January 2019 to December 2021 were selected and divided into a hypotension group and a nonhypotension group. Demographic and clinical data were compared. Hypotension simply refers to blood pressure levels of <90/60 mm Hg on a nondialysis day. All patients received endovascular intervention.

RESULTS

Hypotension was found in 85 of the 194 patients. The following factors were significantly different between the hypotension and nonhypotension groups: body mass index, history of hypertension, tunneled-cuffed catheter as the means of dialysis access, azygos ectasis, SVC stenosis of >70% or occlusion, occlusion at the cavitary junction, serum calcium, diastolic left ventricular (LV) posterior wall thickness, LV end-diastolic volume, stroke output, and LV ejection fraction. Multivariate logistic regression analysis showed that hypertension history (OR, 0.314; P = .027), tunneled-cuffed catheter as vascular access (OR, 3.997; P < .001), SVC stenosis of >70% or occlusion (OR, 5.243; P < .001), LV posterior wall thickness (OR, 0.772; P = .044), and serum calcium (OR, 0.146; P = .005) were independent risk factors for hypotension. The mean values of systolic and diastolic blood pressure after intravascular treatment were significantly elevated from those before intervention (P < .001). The primary patency rates of SVC were 66.8%, 58.7%, and 50.0% at 3, 6, and 12 months after the procedure.

CONCLUSIONS

The incidence of hypotension in patients with hemodialysis-associated SVCS is high. The identification of risk factors of hemodialysis-related hypotension provides insight into potential treatment strategies. Endovascular treatment is expected to improve hypotension related to SVCS in hemodialysis patients.

Machine learning-based intradialytic hypotension prediction of patients undergoing hemodialysis: A multicenter retrospective study

BACKGROUND AND OBJECTIVE

Intradialytic hypotension (IDH) is closely associated with adverse clinical outcomes in HD-patients. An IDH predictor model is important for IDH risk screening and clinical decision-making. In this study, we used Machine learning (ML) to develop IDH model for risk prediction in HD patients.

METHODS

62,227 dialysis sessions were randomly partitioned into training data (70%), test data (20%), and validation data (10%). IDH-A model based on twenty-seven variables was constructed for risk prediction for the next HD treatment. IDH-B model based on ten variables from 64,870 dialysis sessions was developed for risk assessment before each HD treatment. Light Gradient Boosting Machine (LightGBM), Linear Discriminant Analysis, support vector machines, XGBoost, TabNet, and multilayer perceptron were used to develop the predictor model.

RESULTS

In IDH-A model, we identified the LightGBM method as the best-performing and interpretable model with C- statistics of 0.82 in Fall30Nadir90 definitions, which was higher than those obtained using the other models (P<0.01). In other IDH standards of Nadir90, Nadir100, Fall20, Fall30, and Fall20Nadir90, the LightGBM method had a performance with C- statistics ranged 0.77 to 0.89. As a complementary application, the LightGBM model in IDH-B model achieved C- statistics of 0.68 in Fall30Nadir90 definitions and 0.69 to 0.78 in the other five IDH standards, which were also higher than the other methods, respectively.

CONCLUSION

Use ML, we identified the LightGBM method as the good-performing and interpretable model. We identified the top variables as the high-risk factors for IDH incident in HD-patient. IDH-A and IDH-B model can usefully complement each other for risk prediction and further facilitate timely intervention through applied into different clinical setting.

Prevalence of post-dialysis fatigue: a systematic review and meta-analysis

OBJECTIVES

The purpose of this study was to synthesise data on the prevalence of post-dialysis fatigue (PDF) among haemodialysis (HD) patients.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

China National Knowledge Infrastructure, Wanfang, Chinese Biological Medical Database, PubMed, EMBASE and Web of Science were searched from their inception to 1 April 2022.

ELIGIBILITY CRITERIA

We selected patients who must receive HD treatment for at least 3 months. Cross-sectional or cohort studies published in Chinese or English were eligible for inclusion. The main search terms used in the abstract were: "renal dialysis", "hemodialysis" and "post-dialysis", in combination with the word "fatigue".

DATA EXTRACTION AND SYNTHESIS

Two investigators independently performed data extraction and quality assessment. Data were pooled to estimate the overall prevalence of PDF among HD patients using the random-effects model. Cochran's Q and I² statistics were adopted to evaluate heterogeneity.

RESULT

A total of 12 studies were included, with 2152 HD patients, of which 1215 were defined as having PDF. The overall prevalence of PDF in HD patients was 61.0% (95% CI: 53.6% to 68.3%, p<0.001, I²=90.0%). Subgroup analysis failed to explain the source of heterogeneity, but univariable meta-regression showed that a mean age of ≥50 years might be the source of heterogeneity. Egger's test revealed no publication bias among the studies (p=0.144).

CONCLUSIONS

PDF is highly prevalent among HD patients.

A comparative study of the definitions of intradialytic hypotension correlated with increased mortality to identify universal predictors

Intradialytic hypotension (IDH) is a common complication in patients undergoing hemodialysis therapy. No consensus on the definition of intradialytic hypotension has been established so far. As a result, coherent and consistent evaluation of its effects and causes is difficult. Some studies have highlighted existing correlations between certain definitions of IDH and the risk of mortality for the patients. This work is mainly focused on these definitions. Our aim is to understand if different IDH definitions, all correlated with increased mortality risk, catch the same onset mechanisms or dynamics. To check whether the dynamics captured by these definitions are similar, we performed analyses of the incidence, of the IDH event onset timing, and checked whether there were similarities between the definitions in those aspects. We evaluated how these definitions overlap with each other and we evaluated which common factors could allow identifying patients at risk of IDH at the beginning of a dialysis session. The definitions of IDH we analyzed through statistical and machine learning approaches, showed a variable incidence on the HD sessions and had different onset time. We found that the set of parameters relevant for the prediction of the IDH was not always the same for the definitions considered. However, it can be observed that some predictors, such as the presence of comorbidities such as diabetes or heart disease, and a low pre-dialysis diastolic blood pressure, have shown universal relevance in highlighting an increased risk of IDH during the treatment. Among those parameters, the one that showed a major importance is the diabetes status of the patients. Diabetes or heart disease presence are permanent risk factors pointing out an increased IDH risk during the treatments, while, pre-dialysis diastolic blood pressure is instead a parameter that can change at every session and should be used to evaluate the specific risk to develop IDH for each session. The identified parameters could be used in the future to train more complex prediction models.

An update review on hemodynamic instability in renal replacement therapy patients

BACKGROUND

Hemodynamic instability in patients undergoing kidney replacement therapy (KRT) is one of the most common and essential factors influencing mortality, morbidity, and the quality of life in this patient population.

METHOD

Decreased cardiac preload, reduced systemic vascular resistance, redistribution of fluids, fluid overload, inflammatory factors, and changes in plasma osmolality have all been implicated in the pathophysiology of hemodynamic instability associated with KRT.

RESULT

A cascade of these detrimental mechanisms may ultimately cause intra-dialytic hypotension, reduced tissue perfusion, and impaired kidney rehabilitation. Multiple parameters, including dialysate composition, temperature, posture during dialysis sessions, physical activity, fluid administrations, dialysis timing, and specific pharmacologic agents, have been studied as possible management modalities. Nevertheless, a clear consensus is not reached.

CONCLUSION

This review includes a thorough investigation of the literature on hemodynamic instability in KRT patients, providing insight on interventions that may potentially minimize factors leading to hemodynamic instability.

Why is Intradialytic Hypotension the Commonest Complication of Outpatient Dialysis Treatments?

Intradialytic hypotension (IDH) is the most frequent complication of hemodialysis (HD) treatments with a frequency of 10% to 12% for patients with chronic kidney disease attending for outpatient treatments and is associated with both temporary ischemic stress to vital organs, including the heart and brain, and increased patient mortality. Although there have been many different definitions of IDH over the years, an absolute nadir systolic blood pressure (SBP) has the strongest association with patient outcomes. The unifying pathophysiology is one of reduced effective blood volume, resulting in lower plasma tonicity, and if this cannot be adequately compensated for by activation of neurohumeral systems, then arteriolar tone and blood pressure fall. The risk factors for developing IDH are numerous, ranging from patient-related factors, including age and comorbidity with reduced cardiac reserve, to patient compliance with dietary and lifestyle advice, to reactions with the extracorporeal circuit and medications, choice of dialysate composition and temperature, setting of postdialysis target weight, ultrafiltration rate, and profiling. Advances in dialysis machine technology by providing real time estimates of the effective circulating volume and adjusting dialysate composition to maintain vascular tonicity are being developed, but currently require more sophisticated biofeedback loops to be clinically effective in preventing IDH. While awaiting advances in artificial intelligence, the clinician continues to rely on patient education to limit interdialytic weight gains, frequent assessment of the postdialysis target weight, adjusting dialysate composition and temperature, introducing convective therapies to increase thermal losses, and altering dialysis session duration and frequency to reduce ultrafiltration rate requirements.

Pre-Dialysis B-Line Quantification at Lung Ultrasound Is a Useful Method for Evaluating the Dry Weight and Predicting the Risk of Intradialytic Hypotension

Intradialytic hypotension (IDH) is a frequent and well-known complication of hemodialysis, occurring in about one third of patients. An integrated approach with different methods is needed to minimize IDH episodes and their complications. In this prospective observational study, recruited patients underwent a multiparametric evaluation of fluid status through a lung ultrasound (LUS) with the quantification of B-lines, a physical examination, blood pressure, NT-proBNP and chest X-rays. The evaluation took place immediately before and at the end of the dialysis session, and the patients were divided into IDH and no-IDH groups. We recruited a total of 107 patients. A pre-dialysis B-line number ≥ 15 showed a high sensitivity in fluid overload diagnosis (94.5%), even higher than a chest X-ray (78%) or physical examination (72%) alone. The identification at the beginning of dialysis of <8 B-lines in the overall cohort or <20 B-lines in patients with NYHA 3−4 class are optimal thresholds for identifying those patients at higher risk of experiencing an IDH episode. In the multivariable analysis, the NYHA class, a low pre-dialysis systolic BP and a low pre-dialysis B-line number were independent risk factors for IDH. At the beginning of dialysis, the B-line quantification at LUS is a valuable and reliable method for evaluating fluid status and predicting IDH episodes. A post-dialysis B-line number <5 may allow for an understanding of whether the IDH episode was caused by dehydration, probably due to due to an overestimation of the dry weight.

Intradialytic hypotension prediction using covariance matrix-driven whale optimizer with orthogonal structure-assisted extreme learning machine

Intradialytic hypotension (IDH) is an adverse event occurred during hemodialysis (HD) sessions with high morbidity and mortality. The key to preventing IDH is predicting its pre-dialysis and administering a proper ultrafiltration prescription. For this purpose, this paper builds a prediction model (bCOWOA-KELM) to predict IDH using indices of blood routine tests. In the study, the orthogonal learning mechanism is applied to the first half of the WOA to improve the search speed and accuracy. The covariance matrix is applied to the second half of the WOA to enhance the ability to get out of local optimum and convergence accuracy. Combining the above two improvement methods, this paper proposes a novel improvement variant (COWOA) for the first time. More, the core of bCOWOA-KELM is that the binary COWOA is utilized to improve the performance of the KELM. In order to verify the comprehensive performance of the study, the paper sets four types of comparison experiments for COWOA based on 30 benchmark functions and a series of prediction experiments for bCOWOA-KELM based on six public datasets and the HD dataset. Finally, the results of the experiments are analyzed separately in this paper. The results of the comparison experiments prove fully that the COWOA is superior to other famous methods. More importantly, the bCOWOA performs better than its peers in feature selection and its accuracy is 92.41%. In addition, bCOWOA improves the accuracy by 0.32% over the second-ranked bSCA and by 3.63% over the worst-ranked bGWO. Therefore, the proposed model can be used for IDH prediction with future applications.

The clinical efficacy of Shenmai injection in the prophylaxis and treatment of intradialytic hypotension: A protocol for systematic review and meta-analysis

BACKGROUND

Intradialytic hypotension (IDH) is a common complication in hemodialysis. IDH can induce vomiting, chest tightness and syncope, and hemodialysis shall be discontinued in patients with severe IDH. As is revealed in related studies, Shenmai injection (SMI) can be used in the prophylaxis and treatment of IDH. However, there is still a lack of consensus about the efficacy among reported studies, which cannot provide compelling evidence. Therefore, a meta-analysis was conducted in this study to further investigate the efficacy and safety of SMI in the prophylaxis and treatment of IDH.

METHODS

PubMed, Web of Science, Scopus, Cochrane Library, Embase, China Scientific Journal Database, China National Knowledge Infrastructure, Chinese Biomedical Literature Database, and Wanfang Data were systematically retrieved from their establishment to June 2022. Subsequently, literature screening, data extraction, quality evaluation and cross-checking of results were performed according to the Cochrane Handbook. Besides, a meta-analysis was performed with the assistance of Revman 5.3 software.

RESULTS

This study will evaluate whether SMI is effective in the prophylaxis and treatment of IDH.

CONCLUSIONS

The latest evidence for the efficacy and safety of SMI in the prevention and treatment of IDH can be provided through this study.

High-Volume Hemodiafiltration and Cool Hemodialysis Have a Beneficial Effect on Intradialytic Hemodynamics: A Randomized Cross-Over Trial of Four Intermittent Dialysis Strategies

Introduction

Compared to standard hemodialysis (S-HD), postdilution hemodiafiltration (HDF) has been associated with improved survival.

Methods

To assess whether intradialytic hemodynamics may play a role in this respect, 40 chronic dialysis patients were cross-over randomized to S-HD (dialysate temperature [Td] 36.5 °C), cooled HD (C-HD; Td 35.5 °C), and HDF (low-volume [LV-HDF)] and high-volume [HV-HDF], both Td 36.5 °C, convection volume 15 liters, and at least 23 liters per session, respectively), each for 2 weeks. Blood pressure (BP) was measured every 15 minutes. The primary endpoint was the number of intradialytic hypotensive (IDH) episodes per session. IDH was defined as systolic BP (SBP) less than 90 mmHg for predialysis SBP less than 160 mmHg and less than 100 mmHg for predialysis SBP greater than or equal to 160 mmHg, independent of symptoms and interventions. A post hoc analysis on early-onset IDH was performed as well. Secondary endpoints included intradialytic courses of SBP, diastolic BP (DBP) and mean arterial pressure (MAP).

Results

During S-HD, IDH occurred 0.68 episodes per session, which was 3.2 and 2.5 times higher than during C-HD (0.21 per session, P < 0.0005) and HV-HDF (0.27 per session, P < 0.0005), respectively. Whereas the latter 2 strategies showed similar frequencies, HV-HDF differed significantly from LV-HDF (P = 0.02). A comparable trend was observed for early-onset IDH: S-HD (0.32 per session), C-HD (0.07 per session, P < 0.0005) and HV-HDF (0.10 per session, P = 0.001). SBP, DBP, and MAP declined during S-HD (−6.8, −5.2, −5.2 mmHg per session; P = 0.004, P < 0.0005, P = 0.002 respectively), which was markedly different from C-HD (P < 0.01).

Conclusion

Though C-HD and HV-HDF showed the lowest IDH frequency and the best intradialytic hemodynamic stability, all parameters were most disrupted in S-HD. Therefore, the survival benefit of HV-HDF over S-HD may be partly caused by a more beneficial intradialytic BP profile.

Multilayer Perceptron-Based Real-Time Intradialytic Hypotension Prediction Using Patient Baseline Information and Heart-Rate Variation

Intradialytic hypotension (IDH) is a common side effect that occurs during hemodialysis and poses a great risk for dialysis patients. Many studies have been conducted so far to predict IDH, but most of these could not be applied in real-time because they used only underlying patient information or static patient disease information. In this study, we propose a multilayer perceptron (MP)-based IDH prediction model using heart rate (HR) information corresponding to time-series information and static data of patients. This study aimed to validate whether HR differences and HR slope information affect real-time IDH prediction in patients undergoing hemodialysis. Clinical data were collected from 80 hemodialysis patients from 9 September to 17 October 2020, in the artificial kidney room at Yeungnam University Medical Center (YUMC), Daegu, South Korea. The patients typically underwent hemodialysis 12 times during this period, 1 to 2 h per session. Therefore, the HR difference and HR slope information within up to 1 h before IDH occurrence were used as time-series input data for the MP model. Among the MP models using the number and data length of different hidden layers, the model using 60 min of data before the occurrence of two layers and IDH showed maximum performance, with an accuracy of 81.5%, a true positive rate of 73.8%, and positive predictive value of 87.3%. This study aimed to predict IDH in real-time by continuously supplying HR information to MP models along with static data such as age, diabetes, hypertension, and ultrafiltration. The current MP model was implemented using relatively limited parameters; however, its performance may be further improved by adding additional parameters in the future, further enabling real-time IDH prediction to play a supporting role for medical staff.

A randomized controlled trial of two dialysate sodium concentrations in hospitalized hemodialysis patients

BACKGROUND

Several large dialysis organizations have lowered the dialysate sodium concentration (DNa) in an effort to ameliorate hypervolemia. The implications of lower DNa on intra-dialytic hypotension (IDH) during hospitalizations of hemodialysis (HD) patients is unclear.

METHODS

In this double-blind, single center, randomized controlled trial (RCT), hospitalized maintenance HD patients were randomized to receive higher (142 mmol/L) or lower (138 mmol/L) DNa for up to six sessions. Blood pressure (BP) was measured in a standardized fashion pre-HD, post-HD and every 15 min during HD. The endpoints were: (i) the average decline in systolic BP (pre-HD minus lowest intra-HD, primary endpoint) and (ii) the proportion of total sessions complicated by IDH (drop of ≥20 mmHg from the pre-HD systolic BP, secondary endpoint).

RESULTS

A total of 139 patients completed the trial, contributing 311 study visits. There were no significant differences in the average systolic blood pressure (SBP) decline between the higher and lower DNa groups (23 ± 16 versus 26 ± 16 mmHg; P = 0.57). The proportion of total sessions complicated by IDH was similar in the higher DNa group, compared with the lower DNa group [54% versus 59%; odds ratio 0.72; 95% confidence interval (95% CI) 0.36-1.44; P = 0.35]. In post hoc analyses adjusting for imbalances in baseline characteristics, higher DNa was associated with 8 mmHg (95% CI 2-13 mmHg) less decline in SBP, compared with lower DNa. Patient symptoms and adverse events were similar between the groups.

CONCLUSIONS

In this RCT for hospitalized maintenance of HD patients, we found no difference in the absolute SBP decline between those who received higher versus lower DNa in intention-to-treat analyses. Post hoc adjusted analyses suggested a lower risk of IDH with higher DNa; thus, larger, multi-center studies to confirm these findings are warranted.

Feasibility of Dialysate Bolus-Based Absolute Blood Volume Estimation in Maintenance Hemodialysis Patients

BACKGROUND

Absolute blood volume (ABV) is a critical component of fluid status, which may inform target weight prescriptions and hemodynamic vulnerability of dialysis patients. Here, we utilized the changes in relative blood volume (RBV), monitored by ultrasound (BVM) upon intradialytic 240 mL dialysate fluid bolus-infusion 1 h after hemodialysis start, to calculate the session-specific ABV. With the main goal of assessing clinical feasibility, our sub-aims were to (i) standardize the BVM-data read-out; (ii) determine optimal time-points for ABV-calculation, "before-" and "after-bolus"; (iii) assess ABV-variation.

METHODS

We used high-level programming language and basic descriptive statistics in a retrospective study of routinely measured BVM-data from 274 hemodialysis sessions in 98 patients.

RESULTS

Regarding (i) and (ii), we automatized the processing of RBV-data, and determined an algorithm to select the adequate RBV-data points for ABV-calculations. Regarding (iii), we found in 144 BVM-curves from 75 patients, that the average ABV ± standard deviation was 5.2 ± 1.5 L and that among those 51 patients who still had ≥2 valid estimates, the average intra-patient standard deviation in ABV was 0.8 L. Twenty-seven of these patients had an average intra-patient standard deviation in ABV <0.5 L.

CONCLUSIONS

We demonstrate feasibility of ABV-calculation by an automated algorithm after dialysate bolus-administration, based on the BVM-curve. Based on our results from this simple "abridged" calculation approach with routine clinical measurements, we encourage the use of multi-compartment modeling and comparison with reference methods of ABV-determination. Hopes are high that clinicians will be able to use ABV to inform target weight prescription, improving hemodynamic stability.

Proportional integral feedback control of ultrafiltration rate in hemodialysis

BACKGROUND

Most hemodialysis patients without residual kidney function accumulate fluid between dialysis session that needs to be removed by ultrafiltration. Ultrafiltration usually results in a decline in relative blood volume (RBV). Recent epidemiological research has identified RBV ranges that were associated with significantly better survival. The objective of this work was to develop an ultrafiltration controller to steer a patient's RBV trajectory into these favorable RBV ranges.

METHODS

We designed a proportional-integral feedback ultrafiltration controller that utilizes signals from a device that reports RBV. The control goal is to attain the RBV trajectory associated with improved patient survival. Additional constraints such as upper and lower bounds of ultrafiltration volume and rate were realized. The controller was evaluated in in silico and ex vivo bench experiments, and in a clinical proof-of-concept study in two maintenance dialysis patients.

RESULTS

In all tests, the ultrafiltration controller performed as expected. In the in silico and ex vivo bench experiments, the controller showed robust reaction toward deliberate disruptive interventions (e.g. signal noise; extreme plasma refill rates). No adverse events were observed in the clinical study.

CONCLUSIONS

The ultrafiltration controller can steer RBV trajectories toward desired RBV ranges while obeying to a set of constraints. Prospective studies in hemodialysis patients with diverse clinical characteristics are warranted to further explore the controllers impact on intradialytic hemodynamic stability, quality of life, and long-term outcomes.

Intradialytic hypotension and objectively measured physical activity among patients on hemodialysis

BACKGROUND

Intradialytic hypotension is related to patient-reported outcomes such as post-dialysis fatigue, but its impact on physical activity has not been fully studied. We aimed to examine the relationship between intradialytic blood pressure (BP) and objectively measured physical activity.

METHODS

In this cross-sectional study, 192 hemodialysis patients underwent 4 weeks of physical activity measurement using triaxial accelerometers to measure step counts and moderate-to-vigorous physical activity (MVPA). Intradialytic BP parameters (pre-dialysis BP, post-dialysis BP, nadir BP, and fall in BP) were measured during all dialysis sessions. Mixed-effects linear regression models were used to analyze associations between intradialytic BP parameters and physical activity (1) after dialysis sessions on dialysis days and (2) on the following non-dialysis days.

RESULTS

The mean age of the patients was 71 years, and 47% had diabetes mellitus. Valid physical activity data were obtained in a total of 1938 dialysis days and 2629 non dialysis days. Lower nadir diastolic BP was significantly associated with lower step counts and shorter moderate-to-vigorous physical activity not only on dialysis days but also on the following non-dialysis days. Nadir diastolic BP showed a higher discrimination capacity for physical inactivity, defined as a step count < 4000 on non-dialysis days, than the other BP parameters. The optimal cutoff point of nadir diastolic BP for discriminating physical inactivity was 68 mmHg; its sensitivity and specificity were 66% and 67%, respectively.

CONCLUSIONS

Lower nadir diastolic BP was strongly associated with lower physical activity on both dialysis and non-dialysis days. Nadir diastolic BP may be a predictor for physical inactivity.

Factors associated with falls in hemodialysis patients: a case-control study

OBJECTIVE

to identify possible associations between a higher probability of falls among hemodialysis patients and laboratory values, comorbidities, pharmacological treatment, hemodynamic changes, dialysis results and stabilometric alterations.

METHOD

this was a retrospective case-control study with hemodialysis patients. Patients in a hemodialysis unit who had suffered one or more falls were included in the case group. Patients from the same unit who had not suffered falls were the controls. Data were gathered from the patients' clinical history and also from the results of a balance test conducted six months before the study.

RESULTS

thirty-one patients were included (10 cases and 21 controls). Intradialytic body weight change was significantly greater among cases (p <0.05). Patients in the case group also presented greater lateral instability after dialysis (p <0.05). Other factors such as high blood pressure, antihypertensives, beta-blockers, and lower heart rates were also associated with falls.

CONCLUSION

a greater intradialytic weight change was associated with an increase in risk of falls. Nursing staff can control these factors to prevent the incidence of falls in dialysis patients.

Real-time prediction of intradialytic relative blood volume: a proof-of-concept for integrated cloud computing infrastructure

BACKGROUND

Inadequate refilling from extravascular compartments during hemodialysis can lead to intradialytic symptoms, such as hypotension, nausea, vomiting, and cramping/myalgia. Relative blood volume (RBV) plays an important role in adapting the ultrafiltration rate which in turn has a positive effect on intradialytic symptoms. It has been clinically challenging to identify changes RBV in real time to proactively intervene and reduce potential negative consequences of volume depletion. Leveraging advanced technologies to process large volumes of dialysis and machine data in real time and developing prediction models using machine learning (ML) is critical in identifying these signals.

METHOD

We conducted a proof-of-concept analysis to retrospectively assess near real-time dialysis treatment data from in-center patients in six clinics using Optical Sensing Device (OSD), during December 2018 to August 2019. The goal of this analysis was to use real-time OSD data to predict if a patient's relative blood volume (RBV) decreases at a rate of at least - 6.5 % per hour within the next 15 min during a dialysis treatment, based on 10-second windows of data in the previous 15 min. A dashboard application was constructed to demonstrate how reporting structures may be developed to alert clinicians in real time of at-risk cases. Data was derived from three sources: (1) OSDs, (2) hemodialysis machines, and (3) patient electronic health records.

RESULTS

Treatment data from 616 in-center dialysis patients in the six clinics was curated into a big data store and fed into a Machine Learning (ML) model developed and deployed within the cloud. The threshold for classifying observations as positive or negative was set at 0.08. Precision for the model at this threshold was 0.33 and recall was 0.94. The area under the receiver operating curve (AUROC) for the ML model was 0.89 using test data.

CONCLUSIONS

The findings from our proof-of concept analysis demonstrate the design of a cloud-based framework that can be used for making real-time predictions of events during dialysis treatments. Making real-time predictions has the potential to assist clinicians at the point of care during hemodialysis.

Intradialytic hypotension: is timing everything?

Intradialytic hypotension (IDH) is a major complication of hemodialysis, leading to myocardial stunning, cerebral hypoperfusion, gut ischemia, loss of residual kidney function, high symptom burden, and death. This study by Keane et al. provides new data on the incidence of IDH over well-defined time intervals during the hemodialysis treatment session, clinical parameters associated with the timing of IDH onset, and whether timing of IDH impacts survival in a nationally representative hemodialysis cohort.