Comparison Between a Single-Lead ECG Garment Device and a Holter Monitor: A Signal Quality Assessment.

Wearable electronics are increasingly common and useful as health monitoring devices, many of which feature the ability to record a single-lead electrocardiogram (ECG). However, recording the ECG commonly requires the user to touch the device to complete the lead circuit, which prevents continuous data acquisition. An alternative approach to enable continuous monitoring without user initiation is to embed the leads in a garment. This study assessed ECG data obtained from the YouCare device (a novel sensorized garment) via comparison with a conventional Holter monitor. A cohort of thirty patients (age range: 20-82 years; 16 females and 14 males) were enrolled and monitored for twenty-four hours with both the YouCare device and a Holter monitor. ECG data from both devices were qualitatively assessed by a panel of three expert cardiologists and quantitatively analyzed using specialized software. Patients also responded to a survey about the comfort of the YouCare device as compared to the Holter monitor. The YouCare device was assessed to have 70% of its ECG signals as "Good", 12% as "Acceptable", and 18% as "Not Readable". The R-wave, independently recorded by the YouCare device and Holter monitor, were synchronized within measurement error during 99.4% of cardiac cycles. In addition, patients found the YouCare device more comfortable than the Holter monitor (comfortable 22 vs. 5 and uncomfortable 1 vs. 18, respectively). Therefore, the quality of ECG data collected from the garment-based device was comparable to a Holter monitor when the signal was sufficiently acquired, and the garment was also comfortable.

Validation of a New and Straightforward Algorithm to Evaluate Signal Quality during ECG Monitoring with Wearable Devices Used in a Clinical Setting.

BACKGROUND: Wearable devices represent a new approach for monitoring key clinical parameters, such as ECG signals, for research and health purposes. These devices could outcompete medical devices in terms of affordability and use in out-clinic settings, allowing remote monitoring. The major limitation, especially when compared to implantable devices, is the presence of artifacts. Several authors reported a relevant percentage of recording time with poor/unusable traces for ECG, potentially hampering the use of these devices for this purpose. For this reason, it is of the utmost importance to develop a simple and inexpensive system enabling the user of the wearable devices to have immediate feedback on the quality of the acquired signal, allowing for real-time correction. METHODS: A simple algorithm that can work in real time to verify the quality of the ECG signal (acceptable and unacceptable) was validated. Based on simple statistical parameters, the algorithm was blindly tested by comparison with ECG tracings previously classified by two expert cardiologists. RESULTS: The classifications of 7200 10s-signal samples acquired on 20 patients with a commercial wearable ECG monitor were compared. The algorithm has an overall efficiency of approximately 95%, with a sensitivity of 94.7% and a specificity of 95.3%. CONCLUSIONS: The results demonstrate that even a simple algorithm can be used to classify signal coarseness, and this could allow real-time intervention by the subject or the technician.

The Use of Anemia Control Model Is Associated with Improved Hemoglobin Target Achievement, Lower Rates of Inappropriate Erythropoietin Stimulating Agents, and Severe Anemia among Dialysis Patients.

INTRODUCTION: The Anemia Control Model (ACM) is a certified medical device suggesting the optimal ESA and iron dosage for patients on hemodialysis. We sought to assess the effectiveness and safety of ACM in a large cohort of hemodialysis patients. METHODS: This is a retrospective study of dialysis patients treated in NephroCare centers between June 1, 2013 and December 31, 2019. We compared patients treated according to ACM suggestions and patients treated in clinics where ACM was not activated. We stratified patients belonging to the reference group by historical target achievement rates in their referral centers (tier 1: <70%; tier 2: 70-80%; tier 3: >80%). Groups were matched by propensity score. RESULTS: After matching, we obtained four groups with 85,512 patient-months each. ACM had 18% higher target achievement rate, 63% smaller inappropriate ESA administration rate, and 59% smaller severe anemia risk compared to Tier 1 centers (all p < 0.01). The corresponding risk ratios for ACM compared to Tier 2 centers were 1.08 (95% CI: 1.08-1.09), 0.49 (95% CI: 0.47-0.51), and 0.64 (95% CI: 0.61-0.68); for ACM compared to Tier 3 centers, 1.01 (95% CI: 1.01-1.02), 0.66 (95% CI: 0.63-0.69), and 0.94 (95% CI: 0.88-1.00), respectively. ACM was associated with statistically significant reductions in ESA dose administration. CONCLUSION: ACM was associated with increased hemoglobin target achievement rate, decreased inappropriate ESA usage and a decreased incidence of severe anemia among patients treated according to ACM suggestion.

European Nephrologists' Attitudes toward the Application of Artificial Intelligence in Clinical Practice: A Comprehensive Survey.

INTRODUCTION: The rapid advancement of artificial intelligence and big data analytics, including descriptive, diagnostic, predictive, and prescriptive analytics, has the potential to revolutionize many areas of medicine, including nephrology and dialysis. Artificial intelligence and big data analytics can be used to analyze large amounts of patient medical records, including laboratory results and imaging studies, to improve the accuracy of diagnosis, enhance early detection, identify patterns and trends, and personalize treatment plans for patients with kidney disease. Additionally, artificial intelligence and big data analytics can be used to identify patients' treatment who are not receiving adequate care, highlighting care inefficiencies in the dialysis provider, optimizing patient outcomes, reducing healthcare costs, and consequently creating values for all the involved stakeholders. OBJECTIVES: We present the results of a comprehensive survey aimed at exploring the attitudes of European physicians from eight countries working within a major hemodialysis network (Fresenius Medical Care NephroCare) toward the application of artificial intelligence in clinical practice. METHODS: An electronic survey on the implementation of artificial intelligence in hemodialysis clinics was distributed to 1,067 physicians. Of the 1,067 individuals invited to participate in the study, 404 (37.9%) professionals agreed to participate in the survey. RESULTS: The survey showed that a substantial proportion of respondents believe that artificial intelligence has the potential to support physicians in reducing medical malpractice or mistakes. CONCLUSION: While artificial intelligence's potential benefits are recognized in reducing medical errors and improving decision-making, concerns about treatment plan consistency, personalization, privacy, and the human aspects of patient care persist. Addressing these concerns will be crucial for successfully integrating artificial intelligence solutions in nephrology practice.

From electronic health records to clinical management systems: how the digital transformation can support healthcare services.

Healthcare systems worldwide are currently undergoing significant transformations in response to increasing costs, a shortage of healthcare professionals and the growing complexity of medical needs among the population. Value-based healthcare reimbursement systems are emerging as an attempt to incentivize patient-centricity and cost containment. From a technological perspective, the transition to digitalized services is intended to support these transformations. A Health Information System (HIS) is a technological solution designed to govern the data flow generated and consumed by healthcare professionals and administrative staff during the delivery of healthcare services. However, the exponential growth of digital capabilities and applied advanced analytics has expanded their traditional functionalities and brought the promise of automating administrative procedures and simple repetitive tasks, while enhancing the efficiency and outcomes of healthcare services by incorporating decision support tools for clinical management. The future of HIS is headed towards modular architectures that can facilitate implementation and adaptation to different environments and systems, as well as the integration of various tools, such as artificial intelligence (AI) models, in a seamless way. As an example, we present the experience and future developments of the European Clinical Database (EuCliD®). EuCliD is a multilingual HIS used by 20 000 nurses and physicians on a daily basis to manage 105 000 patients treated in 1100 clinics in 43 different countries. EuCliD encompasses patients' follow-up, automatic reporting and mobile applications while enabling efficient management of clinical processes. It is also designed to incorporate multiagent systems to automate repetitive tasks, AI modules and advanced dynamic dashboards.

Development and validation of AI-based triage support algorithms for prevention of intradialytic hypotension.

BACKGROUND: Intradialytic hypotension remains one of the most recurrent complications of dialysis sessions. Inadequate management can lead to adverse outcomes, highlighting the need to develop personalized approaches for the prevention of intradialytic hypotension. Here, we sought to develop and validate two AI-based risk models predicting the occurrence of symptomatic intradialytic hypotension at different time points. METHODS: The models were built using the XGBoost algorithm and they predict the occurrence of intradialytic hypotension in the next dialysis session and in the next month. The initial dataset, obtained from routinely collected data in the EuCliD® Database, was split to perform model derivation, training and validation. Model performance was evaluated by concordance statistic and calibration charts; the importance of features was assessed with the Shapley Additive Explanation (SHAP) methodology. RESULTS: The final dataset included 1,249,813 dialysis sessions, and the incidence rate of intradialytic hypotension was 10.07% (95% CI 10.02-10.13). Our models retained good discrimination (AUC around 0.8) and a suitable calibration yielding to the selection of three classification thresholds identifying four distinct risk groups. Variables providing the most significant impact on risk estimates were blood pressure dynamics and other metrics mirroring hemodynamic instability over time. CONCLUSIONS: Recurrent symptomatic intradialytic hypotension could be reliably and accurately predicted using routinely collected data during dialysis treatment and standard clinical care. Clinical application of these prediction models would allow for personalized risk-based interventions for preventing and managing intradialytic hypotension.

Electrocardiogram Monitoring Wearable Devices and Artificial-Intelligence-Enabled Diagnostic Capabilities: A Review.

Worldwide, population aging and unhealthy lifestyles have increased the incidence of high-risk health conditions such as cardiovascular diseases, sleep apnea, and other conditions. Recently, to facilitate early identification and diagnosis, efforts have been made in the research and development of new wearable devices to make them smaller, more comfortable, more accurate, and increasingly compatible with artificial intelligence technologies. These efforts can pave the way to the longer and continuous health monitoring of different biosignals, including the real-time detection of diseases, thus providing more timely and accurate predictions of health events that can drastically improve the healthcare management of patients. Most recent reviews focus on a specific category of disease, the use of artificial intelligence in 12-lead electrocardiograms, or on wearable technology. However, we present recent advances in the use of electrocardiogram signals acquired with wearable devices or from publicly available databases and the analysis of such signals with artificial intelligence methods to detect and predict diseases. As expected, most of the available research focuses on heart diseases, sleep apnea, and other emerging areas, such as mental stress. From a methodological point of view, although traditional statistical methods and machine learning are still widely used, we observe an increasing use of more advanced deep learning methods, specifically architectures that can handle the complexity of biosignal data. These deep learning methods typically include convolutional and recurrent neural networks. Moreover, when proposing new artificial intelligence methods, we observe that the prevalent choice is to use publicly available databases rather than collecting new data.

Chronic kidney disease-associated pruritus (CKD-aP) is associated with worse quality of life and increased healthcare utilization among dialysis patients.

PURPOSE: Chronic pruritus significantly impairs hemodialysis patients' health status and quality of life (QOL) and it is associated with higher mortality rate, more frequent hospitalizations, poorer dialysis and medication adherence, and deteriorated mental status. However, pruritus is still underestimated, underdiagnosed, and undertreated in the real-life clinical scenario. We investigated prevalence, clinical characteristics, clinical correlates, severity as well as physical and psychological burden of chronic pruritus among adult hemodialysis patients in a large international real-world cohort. METHODS: We conducted a retrospective cross-sectional study of patients registered in 152 Fresenius Medical Care (FMC) NephroCare clinics located in Italy, France, Ireland, United Kingdom, and Spain. Demographic and medical data were retrieved from the EuCliD® (European Clinical) database, while information on pruritus and QoL were abstracted from KDQOL™-36 and 5-D Itch questionnaire scores. RESULTS: A total of 6221 patients were included, of which 1238 were from France, 163 Ireland, 1469 Italy, 2633 Spain, and 718 UK. The prevalence of mild-to-severe pruritus was 47.9% (n = 2977 patients). Increased pruritus severity was associated with increased use of antidepressants, antihistamines, and gabapentin. Patients with severe pruritus more likely suffered from diabetes, more frequently missed dialysis sessions, and underwent more hospitalizations due to infections. Both mental and physical QOL scores were progressively lower as the severity of pruritus increased; this association was robust to adjustment for potential confounders. CONCLUSION: This international real-world analysis confirms that chronic pruritus is a highly prevalent condition among dialysis patients and highlights its considerable burden on several dimensions of patients' life.

Microalgae as a Nutraceutical Tool to Antagonize the Impairment of Redox Status Induced by SNPs: Implications on Insulin Resistance.

Microalgae represent a growing innovative source of nutraceuticals such as carotenoids and phenolic compound which are naturally present within these single-celled organisms or can be induced in response to specific growth conditions. The presence of the unfavourable allelic variant in genes involved in the control of oxidative stress, due to one or more SNPs in gene encoding protein involved in the regulation of redox balance, can lead to pathological conditions such as insulin resistance, which, in turn, is directly involved in the pathogenesis of type 2 diabetes mellitus. In this review we provide an overview of the main SNPs in antioxidant genes involved in the promotion of insulin resistance with a focus on the potential role of microalgae-derived antioxidant molecules as novel nutritional tools to mitigate oxidative stress and improve insulin sensitivity.

Erythrocyte Plasma Membrane Lipid Composition Mirrors That of Neurons and Glial Cells in Murine Experimental In Vitro and In Vivo Inflammation.

Lipid membrane turnover and myelin repair play a central role in diseases and lesions of the central nervous system (CNS). The aim of the present study was to analyze lipid composition changes due to inflammatory conditions. We measured the fatty acid (FA) composition in erythrocytes (RBCs) and spinal cord tissue (gas chromatography) derived from mice affected by experimental allergic encephalomyelitis (EAE) in acute and remission phases; cholesterol membrane content (Filipin) and GM1 membrane assembly (CT-B) in EAE mouse RBCs, and in cultured neurons, oligodendroglial cells and macrophages exposed to inflammatory challenges. During the EAE acute phase, the RBC membrane showed a reduction in polyunsaturated FAs (PUFAs) and an increase in saturated FAs (SFAs) and the omega-6/omega-3 ratios, followed by a restoration to control levels in the remission phase in parallel with an increase in monounsaturated fatty acid residues. A decrease in PUFAs was also shown in the spinal cord. CT-B staining decreased and Filipin staining increased in RBCs during acute EAE, as well as in cultured macrophages, neurons and oligodendrocyte precursor cells exposed to inflammatory challenges. This regulation in lipid content suggests an increased cell membrane rigidity during the inflammatory phase of EAE and supports the investigation of peripheral cell membrane lipids as possible biomarkers for CNS lipid membrane concentration and assembly.

Algorithm for Mobile Platform-Based Real-Time QRS Detection.

Recent advancements in smart, wearable technologies have allowed the detection of various medical conditions. In particular, continuous collection and real-time analysis of electrocardiogram data have enabled the early identification of pathologic cardiac rhythms. Various algorithms to assess cardiac rhythms have been developed, but these utilize excessive computational power. Therefore, adoption to mobile platforms requires more computationally efficient algorithms that do not sacrifice correctness. This study presents a modified QRS detection algorithm, the AccYouRate Modified Pan-Tompkins (AMPT), which is a simplified version of the well-established Pan-Tompkins algorithm. Using archived ECG data from a variety of publicly available datasets, relative to the Pan-Tompkins, the AMPT algorithm demonstrated improved computational efficiency by 5-20×, while also universally enhancing correctness, both of which favor translation to a mobile platform for continuous, real-time QRS detection.

Effectiveness of cold HD for the prevention of HD hypotension and mortality in the general HD population.

BACKGROUND: Cold hemodialysis (HD) prevented intradialysis hypotension (IDH) in small, short-term, randomized trials in selected patients with IDH. Whether this treatments prevents IDH and mortality in the HD population at large is unknown. METHODS: We investigated the relationship between dialysate temperature and the risk of IDH, i.e. nadir blood pressure <90 mmHg (generalized estimating equation model) and all-cause mortality (Cox's regression) in an incident cohort of HD patients (n = 8071). To control for confounding by bias by indication and other factors we applied instrumental variables adjusting for case mix at facility level. RESULTS: Twenty-seven percent of patients in the study cohort were systematically treated with a dialysate temperature ≤35.5°C. Over a median follow-up of 13.6 months (interquartile range 5.2-26.1 months), a 0.5°C reduction of the dialysate temperature was associated with a small (-2.4%) reduction of the risk of IDH [odds ratio (OR) 0.976, 95% confidence interval (CI) 0.957-0.995, P = .013]. In case-mix, facility-level adjusted analysis, the association became much stronger (OR 0.67, 95% CI 0.63-0.72, risk reduction = 33%, P < .001). In contrast, colder dialysate temperature had no effect on mortality both in the unadjusted [hazard ratio (HR) (0.5°C decrease) 1.074, 95% CI 0.972-1.187, P = .16] and case-mix-adjusted analysis at facility level (HR 1.01, 95% CI 0.88-1.16, P = .84). Similar results were registered in additional analyses by instrumental variables applying the median dialysate temperature or the facility percentage of patients prescribed a dialysate temperature <36°C. Further analyses restricted to patients with recurrent IDH fully confirmed these findings. CONCLUSIONS: Cold HD was associated with IDH in the HD population but had no association with all-cause mortality.

International consensus conference recommendations on ultrasound education for undergraduate medical students.

OBJECTIVES: The purpose of this study is to provide expert consensus recommendations to establish a global ultrasound curriculum for undergraduate medical students. METHODS: 64 multi-disciplinary ultrasound experts from 16 countries, 50 multi-disciplinary ultrasound consultants, and 21 medical students and residents contributed to these recommendations. A modified Delphi consensus method was used that included a systematic literature search, evaluation of the quality of literature by the GRADE system, and the RAND appropriateness method for panel judgment and consensus decisions. The process included four in-person international discussion sessions and two rounds of online voting. RESULTS: A total of 332 consensus conference statements in four curricular domains were considered: (1) curricular scope (4 statements), (2) curricular rationale (10 statements), (3) curricular characteristics (14 statements), and (4) curricular content (304 statements). Of these 332 statements, 145 were recommended, 126 were strongly recommended, and 61 were not recommended. Important aspects of an undergraduate ultrasound curriculum identified include curricular integration across the basic and clinical sciences and a competency and entrustable professional activity-based model. The curriculum should form the foundation of a life-long continuum of ultrasound education that prepares students for advanced training and patient care. In addition, the curriculum should complement and support the medical school curriculum as a whole with enhanced understanding of anatomy, physiology, pathophysiological processes and clinical practice without displacing other important undergraduate learning. The content of the curriculum should be appropriate for the medical student level of training, evidence and expert opinion based, and include ongoing collaborative research and development to ensure optimum educational value and patient care. CONCLUSIONS: The international consensus conference has provided the first comprehensive document of recommendations for a basic ultrasound curriculum. The document reflects the opinion of a diverse and representative group of international expert ultrasound practitioners, educators, and learners. These recommendations can standardize undergraduate medical student ultrasound education while serving as a basis for additional research in medical education and the application of ultrasound in clinical practice.

Impact of Point-of-Care Ultrasound on Secondary Triage: A Pilot Study.

OBJECTIVES: In mass casualty scenarios, patients with apparent hemodynamic and respiratory stability might have occult life-threatening injuries. These patients could benefit from more accurate triage methods. This study assessed the impact of point-of-care ultrasound on the accuracy of secondary triage conducted at an advanced medical post to enhance the detection of patients who, despite their apparent clinically stable condition, could benefit from earlier evacuation to definitive care or immediate life-saving treatment. METHODS: A mass casualty simulated event consisting of a bomb blast in a remote area was conducted with 10 simulated casualties classified as YELLOW at the primary triage scene; patients were evaluated by 4 physicians at an advanced medical post. Three patients had, respectively, hemoperitoneum, pneumothorax, and hemothorax. Only 2 physicians had sonographic information. RESULTS: All 4 physicians were able to suspect hemoperitoneum as a possible critical condition to be managed first, but only physicians with additional sonographic information accurately detected pneumothorax and hemothorax, thus deciding to immediately evacuate or treat.

Optical tissue clearing associated with 3D imaging: application in preclinical and clinical studies.

Understanding the inner morphology of intact tissues is one of the most competitive challenges in modern biology. Since the beginning of the twentieth century, optical tissue clearing (OTC) has provided solutions for volumetric imaging, allowing the microscopic visualization of thick sections of tissue, organoids, up to whole organs and organisms (for example, mouse or rat). Recently, tissue clearing has also been introduced in clinical settings to achieve a more accurate diagnosis with the support of 3D imaging. This review aims to give an overview of the most recent developments in OTC and 3D imaging and to illustrate their role in the field of medical diagnosis, with a specific focus on clinical applications.

Reduced motion external defibrillation: Reduced subject motion with equivalent defibrillation efficiency validated in swine.

BACKGROUND: External defibrillators are used for arrhythmia cardioversion and for defibrillating during cardiac arrest. During defibrillation, short-duration biphasic pulses cause intense motion due to rapid chest-wall muscle contraction. A reduced motion external defibrillator (RMD) was constructed by integrating a commercial defibrillator with a Tetanizing-waveform generator. A long-duration, low-amplitude, tetanizing waveform slowly stimulated the chest musculature before the biphasic pulse, reducing muscle contraction during the shock. OBJECTIVE: The purpose of this study was to evaluate RMD defibrillation in swine for subject motion during defibrillation pulses and for defibrillation effectiveness. RMD defibrillation can reduce the duration of arrhythmia ablation therapy or simplify cardioversion procedures. METHODS: The tetanizing unit delivered a triangular 1-kHz pulse of 0.25- to 2.0-second duration and 10- to 100-V peak amplitude, subsequently triggering the conventional defibrillator to output standard 1- to 200-J energy biphasic pulses at the next R wave. Forward limb motion was evaluated by measuring peak acceleration and limb work during RMD (tetanizing + biphasic) or biphasic pulse-only waveforms at 10-3-second sampling rate. Seven swine were arrested electrically and subsequently defibrillated. Biphasic pulse-only and RMD defibrillations were repeated 25-35 times per swine, varying tetanizing parameters and biphasic pulse energy. Defibrillation thresholds (DFTs) were established by measuring the minimum energy required to restore sinus rhythm with biphasic pulse-only or RMD defibrillations. RESULTS: Two forward-limb acceleration peaks occurred during both the tetanizing waveform and biphasic pulse, indicating rapid and slower nociceptic (pain sensation) nerve fiber activation. Optimal RMD tetanizing parameters (25-35 V, 0.25- to 0.75-second duration), relative to biphasic pulse-only defibrillations, resulted in 74% ± 10% smaller peak accelerations and 85% ± 10% reduced limb work. DFT energies were identical when comparing RMD to biphasic pulse-only defibrillations. CONCLUSION: Relative to conventional defibrillations, RMD defibrillations maintain rhythm restoration efficiency with drastically reduced subject motion.

Biological Response of Irisin Induced by Different Types of Exercise in Obese Subjects: A Non-Inferiority Controlled Randomized Study.

Background: Weight loss through physical exercise is warranted among obese individuals. Recently, a greater benefit in cardiorespiratory fitness was achievable with high-intensity interval training (HIIT) as compared with moderate intensity continuous training. The beneficial effect of training on CV health might be related to a specific modulation of circulating irisin, an adypo-myokine implicated in the regulation of energy expenditure. Methods: The present study investigates the circulating plasma levels of irisin at baseline and in response to 12-week of training program either with HIIT or moderate-intensity continuous training (MICT) among young female and male obese subjects. Clinical, anthropometric, and training characteristics for each participant were available. A sex-disaggregated data for circulating plasma levels of irisin pre- and post-training are provided as well as an adjusted multivariate linear regression model to identify the determinants of post-training irisin levels. Results: Data from a total of 32 obese healthy individuals (47% female, mean age 38.7 years, mean BMI 35.6 kg/m2), randomized in a 1:1 manner to HIIT or MICT were analyzed. Circulating plasma levels of irisin similarly and significantly decreased in both MICT and HIIT interventional groups. Females had higher post-exercise irisin levels than males (6.32 [5.51-6.75] vs. 4.97 [4.57-5.72] µg/mL, p = 0.001). When stratified by an interventional group, a statistically significant difference was observed only for the MICT group (male, 4.76 [4.20-5.45] µg/mL vs. female 6.48 [4.88-6.84] µg/mL p = 0.03). The circulating post-training level of irisin was independently associated with post-training fat-free mass (ß -0.34, 95% confidence interval, CI -0.062, -0.006, p = 0.019) in a model adjusted confounders. When female sex was added into the adjusted model, it was retained as the only factor independently associated with irisin levels (ß 1.22, 95% CI, 0.50, 1.93, p = 0.002). Conclusions: In obese healthy subjects, circulating irisin levels were reduced in response to 12-weeks of exercise involving either HIIT or MICT. A sex-specific differences in circulating irisin levels at baseline and as biological response to chronic exercise was described. Sex-specific biological response of irisin to exercise should be further explored to tailor sex-specific training approaches for improving the cardiovascular health of obese healthy subjects.

Modifiable Risk Factors Are Important Predictors of COVID-19-Related Mortality in Patients on Hemodialysis.

Introduction: Patients with end-stage kidney disease face a higher risk of severe outcomes from SARS-CoV-2 infection. Moreover, it is not well known to what extent potentially modifiable risk factors contribute to mortality risk. In this historical cohort study, we investigated the incidence and risk factors for 30-day mortality among hemodialysis patients with SARS-CoV-2 infection treated in the European Fresenius Medical Care NephroCare network using conventional and machine learning techniques. Methods: We included adult hemodialysis patients with the first documented SARS-CoV-2 infection between February 1, 2020, and March 31, 2021, registered in the clinical database. The index date for the analysis was the first SARS-CoV-2 suspicion date. Patients were followed for up to 30 days until April 30, 2021. Demographics, comorbidities, and various modifiable risk factors, expressed as continuous parameters and as key performance indicators (KPIs), were considered to tap multiple dimensions including hemodynamic control, nutritional state, and mineral metabolism in the 6 months before the index date. We used logistic regression (LR) and XGBoost models to assess risk factors for 30-day mortality. Results: We included 9,211 patients (age 65.4 ± 13.7 years, dialysis vintage 4.2 ± 3.7 years) eligible for the study. The 30-day mortality rate was 20.8%. In LR models, several potentially modifiable factors were associated with higher mortality: body mass index (BMI) 30-40 kg/m2 (OR: 1.28, CI: 1.10-1.50), single-pool Kt/V (OR off-target vs on-target: 1.19, CI: 1.02-1.38), overhydration (OR: 1.15, CI: 1.01-1.32), and both low (<2.5 mg/dl) and high (≥5.5 mg/dl) serum phosphate levels (OR: 1.52, CI: 1.07-2.16 and OR: 1.17, CI: 1.01-1.35). On-line hemodiafiltration was protective in the model using KPIs (OR: 0.86, CI: 0.76-0.97). SHapley Additive exPlanations analysis in XGBoost models shows a high influence on prediction for several modifiable factors as well, including inflammatory parameters, high BMI, and fluid overload. In both LR and XGBoost models, age, gender, and comorbidities were strongly associated with mortality. Conclusion: Both conventional and machine learning techniques showed that KPIs and modifiable risk factors in different dimensions ascertained 6 months before the COVID-19 suspicion date were associated with 30-day COVID-19-related mortality. Our results suggest that adequate dialysis and achieving KPI targets remain of major importance during the COVID-19 pandemic as well.

The Cardiovascular Literature-Based Risk Algorithm (CALIBRA): Predicting Cardiovascular Events in Patients With Non-Dialysis Dependent Chronic Kidney Disease.

Background and Objectives: Cardiovascular (CV) disease is the main cause of morbidity and mortality in patients suffering from chronic kidney disease (CKD). Although it is widely recognized that CV risk assessment represents an essential prerequisite for clinical management, existing prognostic models appear not to be entirely adequate for CKD patients. We derived a literature-based, naïve-bayes model predicting the yearly risk of CV hospitalizations among patients suffering from CKD, referred as the CArdiovascular, LIterature-Based, Risk Algorithm (CALIBRA). Methods: CALIBRA incorporates 31 variables including traditional and CKD-specific risk factors. It was validated in two independent CKD populations: the FMC NephroCare cohort (European Clinical Database, EuCliD®) and the German Chronic Kidney Disease (GCKD) study prospective cohort. CALIBRA performance was evaluated by c-statistics and calibration charts. In addition, CALIBRA discrimination was compared with that of three validated tools currently used for CV prediction in CKD, namely the Framingham Heart Study (FHS) risk score, the atherosclerotic cardiovascular disease risk score (ASCVD), and the Individual Data Analysis of Antihypertensive Intervention Trials (INDANA) calculator. Superiority was defined as a ΔAUC>0.05. Results: CALIBRA showed good discrimination in both the EuCliD® medical registry (AUC 0.79, 95%CI 0.76-0.81) and the GCKD cohort (AUC 0.73, 95%CI 0.70-0.76). CALIBRA demonstrated improved accuracy compared to the benchmark models in EuCliD® (FHS: ΔAUC=-0.22, p<0.001; ASCVD: ΔAUC=-0.17, p<0.001; INDANA: ΔAUC=-0.14, p<0.001) and GCKD (FHS: ΔAUC=-0.16, p<0.001; ASCVD: ΔAUC=-0.12, p<0.001; INDANA: ΔAUC=-0.04, p<0.001) populations. Accuracy of the CALIBRA score was stable also for patients showing missing variables. Conclusion: CALIBRA provides accurate and robust stratification of CKD patients according to CV risk and allows score calculations with improved accuracy compared to established CV risk scores also in real-world clinical cohorts with considerable missingness rates. Our results support the generalizability of CALIBRA across different CKD populations and clinical settings.

Effectiveness of COVID-19 vaccines in a large European hemodialysis cohort.

Background: Hemodialysis patients have high-risk of severe SARS-CoV-2 infection but were unrepresented in randomized controlled trials evaluating the safety and efficacy of COVID-19 vaccines. We estimated the real-world effectiveness of COVID-19 vaccines in a large international cohort of hemodialysis patients. Methods: In this historical, 1:1 matched cohort study, we included adult hemodialysis patients receiving treatment from December 1, 2020, to May 31, 2021. For each vaccinated patient, an unvaccinated control was selected among patients registered in the same country and attending a dialysis session around the first vaccination date. Matching was based on demographics, clinical characteristics, past COVID-19 infections and a risk score representing the local background risk of infection at vaccination dates. We estimated the effectiveness of mRNA and viral-carrier COVID-19 vaccines in preventing infection and mortality rates from a time-dependent Cox regression stratified by country. Results: In the effectiveness analysis concerning mRNA vaccines, we observed 850 SARS-CoV-2 infections and 201 COVID-19 related deaths among the 28110 patients during a mean follow up of 44 ± 40 days. In the effectiveness analysis concerning viral-carrier vaccines, we observed 297 SARS-CoV-2 infections and 64 COVID-19 related deaths among 12888 patients during a mean follow up of 48 ± 32 days. We observed 18.5/100-patient-year and 8.5/100-patient-year fewer infections and 5.4/100-patient-year and 5.2/100-patient-year fewer COVID-19 related deaths among patients vaccinated with mRNA and viral-carrier vaccines respectively, compared to matched unvaccinated controls. Estimated vaccine effectiveness at days 15, 30, 60 and 90 after the first dose of a mRNA vaccine was: for infection, 41.3%, 54.5%, 72.6% and 83.5% and, for death, 33.1%, 55.4%, 80.1% and 91.2%. Estimated vaccine effectiveness after the first dose of a viral-carrier vaccine was: for infection, 38.3% without increasing over time and, for death, 56.6%, 75.3%, 92.0% and 97.4%. Conclusion: In this large, real-world cohort of hemodialyzed patients, mRNA and viral-carrier COVID-19 vaccines were associated with reduced COVID-19 related mortality. Additionally, we observed a strong reduction of SARS-CoV-2 infection in hemodialysis patients receiving mRNA vaccines.