| Title |
Does the type of treatment have an influence on utility values in a glaucoma population?
|
|---|---|
| Published in |
Clinical Ophthalmology, September 2015
|
| DOI | 10.2147/opth.s92653 |
| Pubmed ID | |
| Authors |
Ricardo Augusto Paletta Guedes, Vanessa Maria Paletta Guedes, Sirley Maria Freitas, Alfredo Chaoubah |
| Abstract |
To assess the impact of glaucoma therapy on utility values in a glaucoma population. A cross-sectional study of consecutive glaucoma patients was conducted. Utility values were obtained using the time trade-off method. Visual function variables (visual acuity and mean deviation in the better eye) and sociodemographic and clinical characteristics (age, sex, race, educational level, type of glaucoma, current and past glaucoma treatments, and comorbidities) were also obtained for statistical analysis. We divided the patients into three groups: medical treatment (group 1), surgical treatment (group 2), and mixed surgical and medical treatment (group 3). Mean age of the study population (n=225) was 65.7 years. After controlling for glaucoma stage (early, moderate, and advanced), the difference among the groups in mean utility values was not statistically significant. Number of medications per patient, type of medication, or type of surgical technique did not have an impact on the utility values. Our findings suggest that the type of therapy did not affect the utility values in a glaucoma population. |
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 % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 17% |
| Lecturer > Senior Lecturer | 2 | 11% |
| Other | 2 | 11% |
| Student > Bachelor | 2 | 11% |
| Student > Postgraduate | 2 | 11% |
| Other | 4 | 22% |
| Unknown | 3 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 39% |
| Computer Science | 3 | 17% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 11% |
| Unspecified | 1 | 6% |
| Nursing and Health Professions | 1 | 6% |
| Other | 2 | 11% |
| Unknown | 2 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 09 September 2015.
All research outputs
#16,048,009
of 25,374,647 outputs
Outputs from Clinical Ophthalmology
#1,344
of 3,712 outputs
Outputs of similar age
#147,241
of 276,791 outputs
Outputs of similar age from Clinical Ophthalmology
#25
of 84 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,712 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 58% of its peers.
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We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.