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Predicting hemoglobin levels in whole blood donors using transition models and mixed effects models

Overview of attention for article published in BMC Medical Research Methodology, May 2013
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Title
Predicting hemoglobin levels in whole blood donors using transition models and mixed effects models
Published in
BMC Medical Research Methodology, May 2013
DOI 10.1186/1471-2288-13-62
Pubmed ID
Authors

Kazem Nasserinejad, Wim de Kort, Mireille Baart, Arnošt Komárek, Joost van Rosmalen, Emmanuel Lesaffre

Abstract

To optimize the planning of blood donations but also to continue motivating the volunteers it is important to streamline the practical organization of the timing of donations. While donors are asked to return for donation after a suitable period, still a relevant proportion of blood donors is deferred from donation each year due to a too low hemoglobin level. Rejection of donation may demotivate the candidate donor and implies an inefficient planning of the donation process. Hence, it is important to predict the future hemoglobin level to improve the planning of donors' visits to the blood bank.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 3%
Unknown 33 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 21%
Researcher 5 15%
Student > Postgraduate 4 12%
Lecturer 2 6%
Professor 2 6%
Other 4 12%
Unknown 10 29%
Readers by discipline Count As %
Medicine and Dentistry 10 29%
Biochemistry, Genetics and Molecular Biology 4 12%
Agricultural and Biological Sciences 3 9%
Mathematics 1 3%
Business, Management and Accounting 1 3%
Other 4 12%
Unknown 11 32%
Attention Score in Context

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 06 May 2013.
All research outputs
#13,384,129
of 22,709,015 outputs
Outputs from BMC Medical Research Methodology
#1,278
of 2,003 outputs
Outputs of similar age
#101,685
of 192,695 outputs
Outputs of similar age from BMC Medical Research Methodology
#19
of 24 outputs
Altmetric has tracked 22,709,015 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,003 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 192,695 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.