Search

Your search keyword '"Raimann J.G."' showing total 3 results
Start Over Author "Raimann J.G." Language english
3 results on '"Raimann J.G."'

1. Unraveling the relationship between mortality, hyponatremia, inflammation and malnutrition in hemodialysis patients: results from the international MONDO initiative

Author

Dekker, M.J.E., Marcelli, D., Canaud, B., Konings, C.J.A.M., Leunissen, K.M., Levin, N.W., Carioni, P., Maheshwari, V., Raimann, J.G., van der Sande, F.M., Usvyat, L.A., Kotanko, P., and Kooman, J.P.

Subjects
Mortality, Inflammation -- Physiological aspects, Hyponatremia -- Physiological aspects, Hemodialysis patients -- Health aspects, Food/cooking/nutrition, Health
Abstract

BACKGROUND/OBJECTIVES: Hyponatremia is a risk factor for mortality in hemodialysis (HD) patients. It is not well known to which extent the comorbidities, malnutrition, fluid status imbalance and inflammation are related to hyponatremia and affect outcomes. SUBJECTS/METHODS: We studied 8883 patients from the European subset of the international MONitoring Dialysis Outcomes initiative. Nutritional and fluid statuses were assessed by bioimpedance spectroscopy. Fluid depletion was defined as overhydration ≤ -1.1 l and fluid overload as overhydration >+1.1 l, respectively. Malnutrition was defined as a lean tissue index below the 10th percentile of age- and gender-matched healthy controls. Hyponatremia and inflammation were defined as serum sodium levels < 135 mEq/l and C-reactive protein levels >6.0 mg/l, respectively. We used logistic regression to test for predictors of hyponatremia and Cox proportional hazards analysis to assess the association with all-cause mortality. RESULTS: Hyponatremia was predicted by the presence of malnutrition (odds ratio (OR) = 1.49 (95% confidence interval (CI) = 1.30-1.70), inflammation (OR= 1.44 (95% CI = 1.26-1.64)) and fluid overload ((> +1.1 l to +2.5 l) OR = 0.73 (95% CI = 0.62-0.85)) but not by fluid depletion (OR =1.34 (95% CI = 0.92-1.96)). Malnutrition, inflammation, fluid overload, fluid depletion and hyponatremia (hazard ratio =1.70 (95% CI = 1.46-1.99)) were independent predictors for all-cause mortality. CONCLUSIONS: In HD patients, hyponatremia is associated with malnutrition, inflammation and fluid overload. Hyponatremia maintained predictive for all-cause mortality after adjustment for malnutrition, inflammation and fluid status abnormalities. The presence of hyponatremia may assist in identifying HD patients at increased risk of death. European Journal of Clinical Nutrition (2016) 70, 779-784; doi: 10.1038/ejcn.2016.49; published online 20 April 2016, INTRODUCTION Hyponatremia has recently emerged as a risk factor for mortality in chronic hemodialysis (HD) patients. (1-3) The association between hyponatremia and mortality is not limited to HD patients but [...]

Published
2016
Full Text
View/download PDF

3. Quantification and classification of potassium and calcium disorders with the electrocardiogram: What do clinical studies, modeling, and reconstruction tell us?

Author

Nicolas Pilia, Jochen G. Raimann, Peter Kotanko, Axel Loewe, Cristiana Corsi, Simonetta Genovesi, Olaf Dössel, Stefano Severi, Pilia, N, Severi, S, Raimann, J, Genovesi, S, Dossel, O, Kotanko, P, Corsi, C, Loewe, A, Pilia N., Severi S., Raimann J.G., Genovesi S., Dossel O., Kotanko P., Corsi C., and Loewe A.

Subjects
CHRONIC KIDNEY-DISEASE, lcsh:Medical technology, BIG DATA, Computer science, lcsh:Biotechnology, Biomedical Engineering, Biophysics, Reviews, Bioengineering, electrocardiogram, Machine learning, computer.software_genre, HYPERKALEMIA, End stage renal disease, Biomaterials, lcsh:TP248.13-248.65, end stage renal disease, Wearable technology, Engineering & allied operations, HEART-RATE-VARIABILITY, business.industry, ECG, potassium, QT INTERVAL, IN-VIVOHEMODIALYSIS, electrolyte concentration, Clinical Practice, lcsh:R855-855.5, Calcium concentration, Artificial intelligence, ddc:620, VENTRICULAR REPOLARIZATION, Calcium disorder, business, computer, SUDDEN CARDIAC DEATH
Abstract

Diseases caused by alterations of ionic concentrations are frequently observed challenges and play an important role in clinical practice. The clinically established method for the diagnosis of electrolyte concentration imbalance is blood tests. A rapid and non-invasive point-of-care method is yet needed. The electrocardiogram (ECG) could meet this need and becomes an established diagnostic tool allowing home monitoring of the electrolyte concentration also by wearable devices. In this review, we present the current state of potassium and calcium concentration monitoring using the ECG and summarize results from previous work. Selected clinical studies are presented, supporting or questioning the use of the ECG for the monitoring of electrolyte concentration imbalances. Differences in the findings from automatic monitoring studies are discussed, and current studies utilizing machine learning are presented demonstrating the potential of the deep learning approach. Furthermore, we demonstrate the potential of computational modeling approaches to gain insight into the mechanisms of relevant clinical findings and as a tool to obtain synthetic data for methodical improvements in monitoring approaches.

Published
2020

Catalog

Books, media, physical & digital resources
See catalog results