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Modeling delay to diagnosis for Amyotrophic lateral sclerosis: under reporting and incidence estimates

Overview of attention for article published in BMC Neurology, December 2012
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Title
Modeling delay to diagnosis for Amyotrophic lateral sclerosis: under reporting and incidence estimates
Published in
BMC Neurology, December 2012
DOI 10.1186/1471-2377-12-160
Pubmed ID
Authors

Irene Rocchetti, Domenica Taruscio, Daniela Pierannunzio

Abstract

This paper provides a strategy to obtain a reliable estimate of the incidence rate for Amyotrophic lateral sclerosis based on data from the National Registry of Rare Diseases (NRRD). In fact, unobserved cases may be due to the fact that "a long time" may intercour between the suspect of having the disease (onset) and the date the disease is diagnosed. Potential factors that may influence the probability of experiencing the event (diagnosis) conditionally on the onset (suspected) are investigated. Since we are treating rare diseases, the role of social and economic factors is not that obvious; latent as well as observed factors may influence the delay to diagnosis.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Kenya 1 6%
Unknown 16 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 18%
Librarian 2 12%
Other 2 12%
Student > Master 2 12%
Student > Bachelor 1 6%
Other 5 29%
Unknown 2 12%
Readers by discipline Count As %
Medicine and Dentistry 7 41%
Agricultural and Biological Sciences 4 24%
Biochemistry, Genetics and Molecular Biology 3 18%
Neuroscience 1 6%
Unknown 2 12%

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 24 December 2012.
All research outputs
#16,630,006
of 21,342,999 outputs
Outputs from BMC Neurology
#1,659
of 2,260 outputs
Outputs of similar age
#215,510
of 292,627 outputs
Outputs of similar age from BMC Neurology
#130
of 155 outputs
Altmetric has tracked 21,342,999 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,260 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.6. This one is in the 22nd percentile – i.e., 22% 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 292,627 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 155 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.