| Title |
Hemodialysis Water Parameters as Predisposing Factors for Anemia in Patients in Dialytic Treatment: Application of Mixed Regression Models
|
|---|---|
| Published in |
Biological Trace Element Research, September 2018
|
| DOI | 10.1007/s12011-018-1515-7 |
| Pubmed ID | |
| Authors |
Meire Nikaido Suzuki, Brisa Maria Fregonesi, Carolina Sampaio Machado, Guilherme Sgobbi Zagui, Luciana Kusumota, Adriano Kamimura Suzuki, José Abrão Cardeal da Costa, Jordi Sierra Llopart, Martí Nadal, Jose Luis Domingo, Susana Segura-Muñoz |
| Abstract |
Contamination by metals and microbiological agents in hemodialysis water can cause clinical intercurrences in hemodialysis patients. Evaluating and assuring minimum levels of contamination from metals and microorganisms in hemodialysis water can improve patient safety. The objective of this study was to assess hemodialysis water quality in a major tertiary hospital in Brazil and investigate the relationship between hemodialysis water quality and clinical intercurrences in hemodialysis patients. A prospective-observational cohort study for evaluation of water quality parameters and clinical intercurrences present by patients (n = 52) were performed from May 2014 to April 2015. Mixed linear regression models and binary regression models were fitted for water quality parameters and patients' clinical parameters. The increase in the levels of copper and nitrate in hemodialysis water was significant (p < 0.05) to explain anemia. Bone pain was related to age, sex (female), and hemodialysis treatment duration (years). Hypotensive episodes were related to serum sodium decrease. Aluminum in hemodialysis water was present in an average concentration higher than the permitted threshold (15.35 ± 14.53 μg/L). Cadmium, total coliforms, Escherichia coli, and endotoxins in hemodialysis water were not detected and the heterotrophic bacteria count was below the reference limit. These parameters' concentrations varied during the study, evidencing the need for continuous monitoring. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 35 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 11% |
| Student > Bachelor | 4 | 11% |
| Professor | 3 | 9% |
| Student > Ph. D. Student | 2 | 6% |
| Student > Master | 2 | 6% |
| Other | 4 | 11% |
| Unknown | 16 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 11% |
| Medicine and Dentistry | 3 | 9% |
| Veterinary Science and Veterinary Medicine | 2 | 6% |
| Nursing and Health Professions | 2 | 6% |
| Environmental Science | 1 | 3% |
| Other | 5 | 14% |
| Unknown | 18 | 51% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 September 2018.
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#20,533,292
of 23,103,436 outputs
Outputs from Biological Trace Element Research
#1,596
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Outputs of similar age
#293,713
of 337,432 outputs
Outputs of similar age from Biological Trace Element Research
#27
of 39 outputs
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