| Title |
Factors affecting the development of adverse drug reactions to β-blockers in hospitalized cardiac patient population
|
|---|---|
| Published in |
Patient preference and adherence, August 2016
|
| DOI | 10.2147/ppa.s108579 |
| Pubmed ID | |
| Authors |
Snežana Mugoša, Nataša Djordjević, Nina Djukanović, Dragana Protić, Zoran Bukumirić, Ivan Radosavljević, Aneta Bošković, Zoran Todorović |
| Abstract |
The aim of the present study was to undertake a study on the prevalence of cytochrome P450 2D6 (CYP2D6) poor metabolizer alleles (*3, *4, *5, and *6) on a Montenegrin population and its impact on developing adverse drug reactions (ADRs) of β-blockers in a hospitalized cardiac patient population. A prospective study was conducted in the Cardiology Center of the Clinical Center of Montenegro and included 138 patients who had received any β-blocker in their therapy. ADRs were collected using a specially designed questionnaire, based on the symptom list and any signs that could point to eventual ADRs. Data from patients' medical charts, laboratory tests, and other available parameters were observed and combined with the data from the questionnaire. ADRs to β-blockers were observed in 15 (10.9%) patients. There was a statistically significant difference in the frequency of ADRs in relation to genetically determined enzymatic activity (P<0.001), with ADRs' occurrence significantly correlating with slower CYP2D6 metabolism. Our study showed that the adverse reactions to β-blockers could be predicted by the length of hospitalization, CYP2D6 poor metabolizer phenotype, and the concomitant use of other CYP2D6-metabolizing drugs. Therefore, in hospitalized patients with polypharmacy CYP2D6 genotyping might be useful in detecting those at risk of ADRs. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 14% |
| Researcher | 3 | 14% |
| Student > Master | 3 | 14% |
| Student > Bachelor | 2 | 9% |
| Professor > Associate Professor | 2 | 9% |
| Other | 5 | 23% |
| Unknown | 4 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 45% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 14% |
| Psychology | 3 | 14% |
| Unspecified | 1 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 4 | 18% |
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 03 August 2016.
All research outputs
#17,811,816
of 22,881,964 outputs
Outputs from Patient preference and adherence
#1,170
of 1,606 outputs
Outputs of similar age
#268,581
of 366,376 outputs
Outputs of similar age from Patient preference and adherence
#62
of 79 outputs
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