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Case definitions in Swedish register data to identify systemic lupus erythematosus

Overview of attention for article published in BMJ Open, January 2016
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Title
Case definitions in Swedish register data to identify systemic lupus erythematosus
Published in
BMJ Open, January 2016
DOI 10.1136/bmjopen-2015-007769
Pubmed ID
Authors

Elizabeth V Arkema, Andreas Jönsen, Lars Rönnblom, Elisabet Svenungsson, Christopher Sjöwall, Julia F Simard

Abstract

To develop and investigate the utility of several different case definitions for systemic lupus erythematosus (SLE) using national register data in Sweden. The reference standard consisted of clinically confirmed SLE cases pooled from four major clinical centres in Sweden (n=929), and a sample of non-SLE comparators randomly selected from the National Population Register (n=24 267). Demographics, comorbidities, prescriptions and autoimmune disease family history were obtained from multiple registers and linked to the reference standard. We first used previously published SLE definitions to create algorithms for SLE. We also used modern data mining techniques (penalised least absolute shrinkage and selection operator logistic regression, elastic net regression and classification trees) to objectively create data-driven case definitions. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for the case definitions identified. Defining SLE by using only hospitalisation data resulted in the lowest sensitivity (0.79). When SLE codes from the outpatient register were included, sensitivity and PPV increased (PPV between 0.97 and 0.98, sensitivity between 0.97 and 0.99). Addition of medication information did not greatly improve the algorithm's performance. The application of data mining methods did not yield different case definitions. The use of SLE International Classification of Diseases (ICD) codes in outpatient clinics increased the accuracy for identifying individuals with SLE using Swedish registry data. This study implies that it is possible to use ICD codes from national registers to create a cohort of individuals with SLE.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 21%
Student > Master 7 18%
Other 4 11%
Student > Ph. D. Student 4 11%
Lecturer 2 5%
Other 8 21%
Unknown 5 13%
Readers by discipline Count As %
Medicine and Dentistry 17 45%
Agricultural and Biological Sciences 3 8%
Engineering 2 5%
Mathematics 1 3%
Environmental Science 1 3%
Other 5 13%
Unknown 9 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 10 March 2019.
All research outputs
#14,292,663
of 25,394,764 outputs
Outputs from BMJ Open
#14,515
of 25,600 outputs
Outputs of similar age
#187,481
of 399,964 outputs
Outputs of similar age from BMJ Open
#284
of 430 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 25,600 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one is in the 42nd percentile – i.e., 42% 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 399,964 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 52% of its contemporaries.
We're also able to compare this research output to 430 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.