Background Preliminary evidence suggests that hemodialysis patients have a blunted early serological response to SARS-CoV-2 vaccination. Optimizing vaccination strategy in this population requires a thorough understanding of predictors and dynamics of humoral and cellular immune responses to different SARS-CoV2 vaccines. Methods This prospective multicenter study of 543 hemodialysis patients and 75 healthy volunteers evaluated the immune responses at 4 or 5 weeks and 8 or 9 weeks after administration of the BNT162b2 or mRNA-1273 vaccine, respectively. We assessed anti-SARS-CoV-2 spike antibodies and T cell responses by IFN-γ of peripheral blood lymphocytes upon SARS-CoV-2 glycoprotein stimulation (QuantiFERON assay) and evaluated potential predictors of the responses. Results Compared with healthy volunteers, hemodialysis patients had an incomplete, delayed humoral immune response and a blunted cellular immune response. Geometric mean antibody titers at both time points were significantly greater in patients vaccinated with mRNA-1273 versus BNT162b2, and a larger proportion of them achieved the threshold of 4160 AU/ml, corresponding with high neutralizing antibody titers in vitro (53.6% versus 31.8% at 8 or 9 weeks, P<0.0001). Patients vaccinated with mRNA-1273 versus BNT162b2 exhibited significantly greater median QuantiFERON responses at both time points, and a larger proportion achieved the threshold of 0.15 IU/ml (64.4% versus 46.9% at 8 or 9 weeks, P<0.0001). Multivariate analysis identified COVID-19 experience, vaccine type, use of immunosuppressive drugs, serum albumin, lymphocyte count, hepatitis B vaccine nonresponder status, and dialysis vintage as independent predictors of the humoral and cellular responses. Conclusions The mRNA-1273 vaccine's greater immunogenicity may be related to its higher mRNA dose. This suggests that a high-dose vaccine might improve the impaired immune response to SARS-CoV-2 vaccination in hemodialysis patients.

Background: Haemodialysis (HD) patients are burdened by frequent fluid shifts which amplify their comorbidities. Bioimpedance (bioZ) is a promising technique to monitor changes in fluid status. The aim of this study is to investigate if the thoracic bioZ signal can track fluid changes during a HD session. Methods: Prevalent patients from a single centre HD unit were monitored during one to six consecutive HD sessions using a wearable multi-frequency thoracic bioZ device. Ultrafiltration volume (UFV) was determined based on the interdialytic weight gain and target dry weight set by clinicians. The correlation between the bioZ signal and UFV was analysed on population level. Additionally regression models were built and validated per dialysis session. Results: 66 patients were included, resulting in a total of 133 HD sessions. Spearman correlation between the thoracic bioZ and UFV showed a significant strong correlation of 0.755 (p < 0.01) on population level. Regression analysis per session revealed a strong relation between the bioZ value and the UFV (R 2 = 0.982). The fluid extraction prediction error of the leave-one-out cross validation was very small (56.2 ml [− 121.1-194.1 ml]) across all sessions at all frequencies. Conclusions: This study demonstrated that thoracic bioZ is strongly correlated with fluid shifts during HD over a large range of UFVs. Furthermore, leave-one-out cross validation is a step towards personalized fluid monitoring during HD and could contribute to the creation of autonomous dialysis.

Intra-abdominal hypertension (IAH) causes severe organ dysfunction. Our aim is to evaluate the effect of increased intra-abdominal pressure (IAP) on renal function, hypothesizing that venous congestion may increase proteinuria and fluid retention without endothelial dysfunction. Three urine samples were collected from 32 non-pregnant women undergoing laparoscopic-assisted vaginal hysterectomy (LAVH) and from 10 controls placed in Trendelenburg position for 60 min. Urine sampling was done before (PRE), during or immediately after (PER), and two hours after (POST) the procedure. Urinary albumin, protein and creatinine concentrations were measured in each sample, and ratios were calculated and compared within and between groups. During LAVH, the albumin/creatinine ratio (ACR) increased and persisted POST-procedure, which was not observed in controls. A positive correlation existed between the LAVH duration and the relative change in both ACR and protein/creatinine ratio (PCR) PER- and POST-procedure. Iatrogenic IAH increases urinary ACR and PCR in non-pregnant women via a process of venous congestion. This mechanism might explain the presentation of one specific subtype of late-onset preeclampsia, where no drop of maternal cardiac output is observed.

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Cardiovascular diseases (CVD) are often characterized by their multifactorial complexity. This makes remote monitoring and ambulatory cardiac rehabilitation (CR) therapy challenging. Current wearable multimodal devices enable remote monitoring. Machine learning (ML) and artificial intelligence (AI) can help in tackling multifaceted datasets. However, for clinical acceptance, easy interpretability of the AI models is crucial. The goal of the present study was to investigate whether a multi-parameter sensor could be used during a standardized activity test to interpret functional capacity in the longitudinal follow-up of CR patients. A total of 129 patients were followed for 3 months during CR using 6-min walking tests (6MWT) equipped with a wearable ECG and accelerometer device. Functional capacity was assessed based on 6MWT distance (6MWD). Linear and nonlinear interpretable models were explored to predict 6MWD. The t-distributed stochastic neighboring embedding (t-SNE) technique was exploited to embed and visualize high dimensional data. The performance of support vector machine (SVM) models, combining different features and using different kernel types, to predict functional capacity was evaluated. The SVM model, using chronotropic response and effort as input features, showed a mean absolute error of 42.8 m (±36.8 m). The 3D-maps derived using the t-SNE technique visualized the relationship between sensor-derived biomarkers and functional capacity, which enables tracking of the evolution of patients throughout the CR program. The current study showed that wearable monitoring combined with interpretable ML can objectively track clinical progression in a CR population. These results pave the road towards ambulatory CR.

Background Cardiac rehabilitation (CR) is known for its beneficial effects on functional capacity and is a key component within current cardiovascular disease management strategies. In addition, a larger increase in functional capacity is accompanied by better clinical outcomes. However, not all patients respond in a similar way to CR. Therefore, a patient-tailored approach to CR could open up the possibility to achieve an optimal increase in functional capacity in every patient. Before treatment can be optimized, the differences in response of patients in terms of cardiac adaptation to exercise should first be understood. In addition, digital biomarkers to steer CR need to be identified. Objective The aim of the study was to investigate the difference in cardiac response between patients characterized by a clear improvement in functional capacity and patients showing only a minor improvement following CR therapy. Methods A total of 129 patients in CR performed a 6-minute walking test (6MWT) at baseline and during four consecutive short-term follow-up tests while being equipped with a wearable electrocardiogram (ECG) device. The 6MWTs were used to evaluate functional capacity. Patients were divided into high- and low-response groups, based on the improvement in functional capacity during the CR program. Commonly used heart rate parameters and cardiac digital biomarkers representative of the heart rate behavior during the 6MWT and their evolution over time were investigated. Results All participating patients improved in functional capacity throughout the CR program (P<.001). The heart rate parameters, which are commonly used in practice, evolved differently for both groups throughout CR. The peak heart rate (HRpeak) from patients in the high-response group increased significantly throughout CR, while no change was observed in the low-response group (F4,92=8.321, P<.001). Similar results were obtained for the recovery heart rate (HRrec) values, which increased significantly over time during every minute of recuperation, for the high-response group (HRrec1: P<.001, HRrec2: P<.001, HRrec3: P<.001, HRrec4: P<.001, and HRrec5: P=.02). The other digital biomarkers showed that the evolution of heart rate behavior during a standardized activity test differed throughout CR between both groups. These digital biomarkers, derived from the continuous measurements, contribute to more in-depth insight into the progression of patients’ cardiac responses. Conclusions This study showed that when using wearable sensor technology, the differences in response of patients to CR can be characterized by means of commonly used heart rate parameters and digital biomarkers that are representative of cardiac response to exercise. These digital biomarkers, derived by innovative analysis techniques, allow for more in-depth insights into the cardiac response of cardiac patients during standardized activity. These results open up the possibility to optimized and more patient-tailored treatment strategies and to potentially improve CR outcome.

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To optimize exercise management in cardiac patients following a cardiac rehabilitation (CR) program, it is important to study short-term changes of parameters, representative for exercise capacity. We hypothesize that a detailed study of these parameters could provide more insight into the actual improvement of the patients. Therefore, the progression of heart rate variability (HRV) parameters during short-term intervals throughout CR was investigated in this study.Electrocardiographic (ECG) signals, recorded with a wearable device in 129 patients following a CR program, were analyzed. Patients participated in a follow up protocol. Analyses on the normalized power in the low frequency band (LFn) and the root mean square of successive differences (RMSSD) were performed for patients on and off drug therapy.Although no significant differences were found, treating CR patients with ACE-inhibition or beta blockers (BB) tended to have an influence on the HRV parameters. The progression of the HRV parameters throughout CR was mostly characterized by a non-monotonic trend. These insights elucidate the changes occurring in the regulatory mechanisms. Moreover, findings of this work give new valuable insights for the close monitoring of disease progression during CR in future applications.