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A Phenotypic Approach for IUIS PID Classification and Diagnosis: Guidelines for Clinicians at the Bedside

Overview of attention for article published in Journal of Clinical Immunology, May 2013
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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1 policy source
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1 X user
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1 Facebook page

Citations

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159 Mendeley
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Title
A Phenotypic Approach for IUIS PID Classification and Diagnosis: Guidelines for Clinicians at the Bedside
Published in
Journal of Clinical Immunology, May 2013
DOI 10.1007/s10875-013-9901-6
Pubmed ID
Authors

Ahmed Aziz Bousfiha, Leïla Jeddane, Fatima Ailal, Waleed Al Herz, Mary Ellen Conley, Charlotte Cunningham-Rundles, Amos Etzioni, Alain Fischer, Jose Luis Franco, Raif S. Geha, Lennart Hammarström, Shigeaki Nonoyama, Hans D. Ochs, Chaim M. Roifman, Reinhard Seger, Mimi L. K. Tang, Jennifer M. Puck, Helen Chapel, Luigi D. Notarangelo, Jean-Laurent Casanova

Abstract

The number of genetically defined Primary Immunodeficiency Diseases (PID) has increased exponentially, especially in the past decade. The biennial classification published by the IUIS PID expert committee is therefore quickly expanding, providing valuable information regarding the disease-causing genotypes, the immunological anomalies, and the associated clinical features of PIDs. These are grouped in eight, somewhat overlapping, categories of immune dysfunction. However, based on this immunological classification, the diagnosis of a specific PID from the clinician's observation of an individual clinical and/or immunological phenotype remains difficult, especially for non-PID specialists. The purpose of this work is to suggest a phenotypic classification that forms the basis for diagnostic trees, leading the physician to particular groups of PIDs, starting from clinical features and combining routine immunological investigations along the way. We present 8 colored diagnostic figures that correspond to the 8 PID groups in the IUIS Classification, including all the PIDs cited in the 2011 update of the IUIS classification and most of those reported since.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 159 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 2 1%
Sweden 1 <1%
Czechia 1 <1%
United Kingdom 1 <1%
Italy 1 <1%
Argentina 1 <1%
Belgium 1 <1%
Denmark 1 <1%
Japan 1 <1%
Other 0 0%
Unknown 149 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 14%
Other 22 14%
Researcher 21 13%
Professor > Associate Professor 15 9%
Student > Master 15 9%
Other 40 25%
Unknown 23 14%
Readers by discipline Count As %
Medicine and Dentistry 70 44%
Agricultural and Biological Sciences 20 13%
Biochemistry, Genetics and Molecular Biology 15 9%
Immunology and Microbiology 14 9%
Unspecified 2 1%
Other 6 4%
Unknown 32 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 25 June 2021.
All research outputs
#7,156,473
of 25,292,646 outputs
Outputs from Journal of Clinical Immunology
#538
of 1,795 outputs
Outputs of similar age
#55,559
of 199,165 outputs
Outputs of similar age from Journal of Clinical Immunology
#4
of 10 outputs
Altmetric has tracked 25,292,646 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 1,795 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one has gotten more attention than average, scoring higher than 69% of its peers.
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 199,165 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.