Evaluation of cytokine profiles in rheumatoid arthritis patients with clinically active disease and normal inflammatory indices View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Asha M. Alex, Harlan Sayles, Ted R. Mikuls, Gail S. Kerr

ABSTRACT

OBJECTIVE: To assess the potential utility of a cytokine measurement in rheumatoid arthritis (RA) patients with active joint disease but normal acute phase reactants (APR). METHODS: RA patients in a longitudinal observational registry with available cytokine array data were included. Patients were categorized based on agreement/disagreement of physical examination and APR measurements: concordant high (CH) [high tender and/or swollen joint counts (TJC + SJC > 3) and APR (ESR ≥ 28 mm/h + CRP ≥ 1.5 mg/L)]; concordant low (CL) [TJC + SJC ≤ 3 and normal APR]. Discordant (D) [TJC + SJC > 3 and normal APR] patients were stratified into low, medium, and high-disease activity (DL, DM, DH). Weighted-average and log-transformed cytokine scores were calculated based on results of a cytokine array. Chi-square tests compared categorical variables by concordance status; t tests, Wilcoxon rank-sum tests, ANOVA models, and ordinary least squares (OLS) regressions were used to compare continuous measures. RESULTS: RA patients (n = 1467) were predominantly male (91%). Compared to CH patients (n = 174), D (n = 434) were younger, less frequently seropositive, with lower TJC, SJC, and DAS28-3v scores (p < 0.001). Cytokine scores for DL, DM, and DH groups were lower than CH patients (p < 0.001) and did not differ between DL, DM, and DH subgroups and were similar to CL (n = 356) patients. In multivariable analyses including CH and D patients, log-cytokine score was associated with higher DAS28-3v scores (p = 0.029). In multivariable analyses including CL patients, concordance status (p = 0.011) and ACPA (p = 0.013) were predictors of higher log cytokine score. CONCLUSION: In this study, cytokine scores did not identify active joint disease in RA patients with normal APR. More... »

PAGES

1075-1081

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10067-018-4379-5

DOI

http://dx.doi.org/10.1007/s10067-018-4379-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1110332835

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30506404


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "MedStar Georgetown University Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411663.7", 
          "name": [
            "Medstar Georgetown University Hospital, Washington, DC, USA", 
            "Washington DC Veteran Affairs Medical Center, Washington, DC, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Alex", 
        "givenName": "Asha M.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "VA Nebraska Western Iowa Health Care System", 
          "id": "https://www.grid.ac/institutes/grid.478099.b", 
          "name": [
            "University of Nebraska Medical Center & VA Nebraska-Western Iowa Health Care System, Omaha, NE, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sayles", 
        "givenName": "Harlan", 
        "id": "sg:person.01161040575.70", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01161040575.70"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "VA Nebraska Western Iowa Health Care System", 
          "id": "https://www.grid.ac/institutes/grid.478099.b", 
          "name": [
            "University of Nebraska Medical Center & VA Nebraska-Western Iowa Health Care System, Omaha, NE, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mikuls", 
        "givenName": "Ted R.", 
        "id": "sg:person.0614462332.23", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0614462332.23"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Washington DC VA Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.413721.2", 
          "name": [
            "Medstar Georgetown University Hospital, Washington, DC, USA", 
            "Washington DC Veteran Affairs Medical Center, Washington, DC, USA", 
            "Howard University, Washington, DC, USA", 
            "Rheumatology Section, 151K, Veterans Affairs Medical Center, 50 Irving St, NW, 20422, Washington, DC, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kerr", 
        "givenName": "Gail S.", 
        "id": "sg:person.01264232224.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01264232224.27"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1136/annrheumdis-2012-201505", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001309249"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/art.30199", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001752048"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00296-007-0357-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006215879", 
          "https://doi.org/10.1007/s00296-007-0357-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00296-007-0357-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006215879", 
          "https://doi.org/10.1007/s00296-007-0357-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/03009742.2016.1211315", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009979388"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/art.39735", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014916063"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/acr.20685", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017527155"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0060635", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021004977"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/art.39714", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024375628"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/ard.2007.084459", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024548365"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/annrheumdis-2013-204986", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026678007"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/art.23945", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035650388"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/annrheumdis-2011-200963", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040636168"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.aca.2014.10.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040914090"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/rheumatology/kes362", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045764929"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/art.1780380107", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048589850"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/rheumatology/kes281", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051911263"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/ar4469", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052083668", 
          "https://doi.org/10.1186/ar4469"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/rheumatology/kew285", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060012856"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1077137726", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-04", 
    "datePublishedReg": "2019-04-01", 
    "description": "OBJECTIVE: To assess the potential utility of a cytokine measurement in rheumatoid arthritis (RA) patients with active joint disease but normal acute phase reactants (APR).\nMETHODS: RA patients in a longitudinal observational registry with available cytokine array data were included. Patients were categorized based on agreement/disagreement of physical examination and APR measurements: concordant high (CH) [high tender and/or swollen joint counts (TJC + SJC >\u20093) and APR (ESR \u2265\u200928\u00a0mm/h + CRP \u2265\u20091.5\u00a0mg/L)]; concordant low (CL) [TJC + SJC \u2264\u20093 and normal APR]. Discordant (D) [TJC + SJC >\u20093 and normal APR] patients were stratified into low, medium, and high-disease activity (DL, DM, DH). Weighted-average and log-transformed cytokine scores were calculated based on results of a cytokine array. Chi-square tests compared categorical variables by concordance status; t tests, Wilcoxon rank-sum tests, ANOVA models, and ordinary least squares (OLS) regressions were used to compare continuous measures.\nRESULTS: RA patients (n\u2009=\u20091467) were predominantly male (91%). Compared to CH patients (n\u2009=\u2009174), D (n\u2009=\u2009434) were younger, less frequently seropositive, with lower TJC, SJC, and DAS28-3v scores (p\u2009<\u20090.001). Cytokine scores for DL, DM, and DH groups were lower than CH patients (p\u2009<\u20090.001) and did not differ between DL, DM, and DH subgroups and were similar to CL (n\u2009=\u2009356) patients. In multivariable analyses including CH and D patients, log-cytokine score was associated with higher DAS28-3v scores (p\u2009=\u20090.029). In multivariable analyses including CL patients, concordance status (p\u2009=\u20090.011) and ACPA (p\u2009=\u20090.013) were predictors of higher log cytokine score.\nCONCLUSION: In this study, cytokine scores did not identify active joint disease in RA patients with normal APR.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10067-018-4379-5", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1093299", 
        "issn": [
          "0770-3198", 
          "1434-9949"
        ], 
        "name": "Clinical Rheumatology", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "38"
      }
    ], 
    "name": "Evaluation of cytokine profiles in rheumatoid arthritis patients with clinically active disease and normal inflammatory indices", 
    "pagination": "1075-1081", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "77e5bcea89fc1531d2991aafcd38e9136786bbc38e61a0ab5e94d6b32b48f348"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30506404"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "8211469"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10067-018-4379-5"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1110332835"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10067-018-4379-5", 
      "https://app.dimensions.ai/details/publication/pub.1110332835"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:21", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000368_0000000368/records_78972_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs10067-018-4379-5"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10067-018-4379-5'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10067-018-4379-5'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10067-018-4379-5'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10067-018-4379-5'


 

This table displays all metadata directly associated to this object as RDF triples.

157 TRIPLES      21 PREDICATES      48 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10067-018-4379-5 schema:about anzsrc-for:11
2 anzsrc-for:1103
3 schema:author N75a02a0a82914ba29227e001fe20f41b
4 schema:citation sg:pub.10.1007/s00296-007-0357-y
5 sg:pub.10.1186/ar4469
6 https://app.dimensions.ai/details/publication/pub.1077137726
7 https://doi.org/10.1002/acr.20685
8 https://doi.org/10.1002/art.1780380107
9 https://doi.org/10.1002/art.23945
10 https://doi.org/10.1002/art.30199
11 https://doi.org/10.1002/art.39714
12 https://doi.org/10.1002/art.39735
13 https://doi.org/10.1016/j.aca.2014.10.009
14 https://doi.org/10.1080/03009742.2016.1211315
15 https://doi.org/10.1093/rheumatology/kes281
16 https://doi.org/10.1093/rheumatology/kes362
17 https://doi.org/10.1093/rheumatology/kew285
18 https://doi.org/10.1136/annrheumdis-2011-200963
19 https://doi.org/10.1136/annrheumdis-2012-201505
20 https://doi.org/10.1136/annrheumdis-2013-204986
21 https://doi.org/10.1136/ard.2007.084459
22 https://doi.org/10.1371/journal.pone.0060635
23 schema:datePublished 2019-04
24 schema:datePublishedReg 2019-04-01
25 schema:description OBJECTIVE: To assess the potential utility of a cytokine measurement in rheumatoid arthritis (RA) patients with active joint disease but normal acute phase reactants (APR). METHODS: RA patients in a longitudinal observational registry with available cytokine array data were included. Patients were categorized based on agreement/disagreement of physical examination and APR measurements: concordant high (CH) [high tender and/or swollen joint counts (TJC + SJC > 3) and APR (ESR ≥ 28 mm/h + CRP ≥ 1.5 mg/L)]; concordant low (CL) [TJC + SJC ≤ 3 and normal APR]. Discordant (D) [TJC + SJC > 3 and normal APR] patients were stratified into low, medium, and high-disease activity (DL, DM, DH). Weighted-average and log-transformed cytokine scores were calculated based on results of a cytokine array. Chi-square tests compared categorical variables by concordance status; t tests, Wilcoxon rank-sum tests, ANOVA models, and ordinary least squares (OLS) regressions were used to compare continuous measures. RESULTS: RA patients (n = 1467) were predominantly male (91%). Compared to CH patients (n = 174), D (n = 434) were younger, less frequently seropositive, with lower TJC, SJC, and DAS28-3v scores (p < 0.001). Cytokine scores for DL, DM, and DH groups were lower than CH patients (p < 0.001) and did not differ between DL, DM, and DH subgroups and were similar to CL (n = 356) patients. In multivariable analyses including CH and D patients, log-cytokine score was associated with higher DAS28-3v scores (p = 0.029). In multivariable analyses including CL patients, concordance status (p = 0.011) and ACPA (p = 0.013) were predictors of higher log cytokine score. CONCLUSION: In this study, cytokine scores did not identify active joint disease in RA patients with normal APR.
26 schema:genre research_article
27 schema:inLanguage en
28 schema:isAccessibleForFree false
29 schema:isPartOf N3d79829e6fd5494ca1c7dd5be7d47fe0
30 Nae7f2a6de1dd418588e123e1fa328ffe
31 sg:journal.1093299
32 schema:name Evaluation of cytokine profiles in rheumatoid arthritis patients with clinically active disease and normal inflammatory indices
33 schema:pagination 1075-1081
34 schema:productId N09bd41ee02fd4fe58264b430c05b4c4a
35 N3a186e3de3494d33bd97359ca1aa115b
36 N858e0451ea984286a144c88170771f64
37 N99fbeef6c3c3467aae90861035bf193b
38 Nc9814a631d7145078c272802f4758917
39 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110332835
40 https://doi.org/10.1007/s10067-018-4379-5
41 schema:sdDatePublished 2019-04-11T13:21
42 schema:sdLicense https://scigraph.springernature.com/explorer/license/
43 schema:sdPublisher Nb137314e2a974cd295c7fe757b991e78
44 schema:url https://link.springer.com/10.1007%2Fs10067-018-4379-5
45 sgo:license sg:explorer/license/
46 sgo:sdDataset articles
47 rdf:type schema:ScholarlyArticle
48 N09bd41ee02fd4fe58264b430c05b4c4a schema:name readcube_id
49 schema:value 77e5bcea89fc1531d2991aafcd38e9136786bbc38e61a0ab5e94d6b32b48f348
50 rdf:type schema:PropertyValue
51 N0a8cfbc32bf641f19fbc33b92b539ea9 schema:affiliation https://www.grid.ac/institutes/grid.411663.7
52 schema:familyName Alex
53 schema:givenName Asha M.
54 rdf:type schema:Person
55 N3a186e3de3494d33bd97359ca1aa115b schema:name pubmed_id
56 schema:value 30506404
57 rdf:type schema:PropertyValue
58 N3d79829e6fd5494ca1c7dd5be7d47fe0 schema:volumeNumber 38
59 rdf:type schema:PublicationVolume
60 N58ae981d8b224803b36a79a2d9e3b531 rdf:first sg:person.01264232224.27
61 rdf:rest rdf:nil
62 N75a02a0a82914ba29227e001fe20f41b rdf:first N0a8cfbc32bf641f19fbc33b92b539ea9
63 rdf:rest Nbb7b5c6b390c45a3b5b3461849aab244
64 N858e0451ea984286a144c88170771f64 schema:name dimensions_id
65 schema:value pub.1110332835
66 rdf:type schema:PropertyValue
67 N99fbeef6c3c3467aae90861035bf193b schema:name doi
68 schema:value 10.1007/s10067-018-4379-5
69 rdf:type schema:PropertyValue
70 Nae6497aa1681415bab834b2e9e3a3e0e rdf:first sg:person.0614462332.23
71 rdf:rest N58ae981d8b224803b36a79a2d9e3b531
72 Nae7f2a6de1dd418588e123e1fa328ffe schema:issueNumber 4
73 rdf:type schema:PublicationIssue
74 Nb137314e2a974cd295c7fe757b991e78 schema:name Springer Nature - SN SciGraph project
75 rdf:type schema:Organization
76 Nbb7b5c6b390c45a3b5b3461849aab244 rdf:first sg:person.01161040575.70
77 rdf:rest Nae6497aa1681415bab834b2e9e3a3e0e
78 Nc9814a631d7145078c272802f4758917 schema:name nlm_unique_id
79 schema:value 8211469
80 rdf:type schema:PropertyValue
81 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
82 schema:name Medical and Health Sciences
83 rdf:type schema:DefinedTerm
84 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
85 schema:name Clinical Sciences
86 rdf:type schema:DefinedTerm
87 sg:journal.1093299 schema:issn 0770-3198
88 1434-9949
89 schema:name Clinical Rheumatology
90 rdf:type schema:Periodical
91 sg:person.01161040575.70 schema:affiliation https://www.grid.ac/institutes/grid.478099.b
92 schema:familyName Sayles
93 schema:givenName Harlan
94 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01161040575.70
95 rdf:type schema:Person
96 sg:person.01264232224.27 schema:affiliation https://www.grid.ac/institutes/grid.413721.2
97 schema:familyName Kerr
98 schema:givenName Gail S.
99 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01264232224.27
100 rdf:type schema:Person
101 sg:person.0614462332.23 schema:affiliation https://www.grid.ac/institutes/grid.478099.b
102 schema:familyName Mikuls
103 schema:givenName Ted R.
104 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0614462332.23
105 rdf:type schema:Person
106 sg:pub.10.1007/s00296-007-0357-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1006215879
107 https://doi.org/10.1007/s00296-007-0357-y
108 rdf:type schema:CreativeWork
109 sg:pub.10.1186/ar4469 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052083668
110 https://doi.org/10.1186/ar4469
111 rdf:type schema:CreativeWork
112 https://app.dimensions.ai/details/publication/pub.1077137726 schema:CreativeWork
113 https://doi.org/10.1002/acr.20685 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017527155
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1002/art.1780380107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048589850
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1002/art.23945 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035650388
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1002/art.30199 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001752048
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1002/art.39714 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024375628
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1002/art.39735 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014916063
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1016/j.aca.2014.10.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040914090
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1080/03009742.2016.1211315 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009979388
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1093/rheumatology/kes281 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051911263
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1093/rheumatology/kes362 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045764929
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1093/rheumatology/kew285 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060012856
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1136/annrheumdis-2011-200963 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040636168
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1136/annrheumdis-2012-201505 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001309249
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1136/annrheumdis-2013-204986 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026678007
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1136/ard.2007.084459 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024548365
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1371/journal.pone.0060635 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021004977
144 rdf:type schema:CreativeWork
145 https://www.grid.ac/institutes/grid.411663.7 schema:alternateName MedStar Georgetown University Hospital
146 schema:name Medstar Georgetown University Hospital, Washington, DC, USA
147 Washington DC Veteran Affairs Medical Center, Washington, DC, USA
148 rdf:type schema:Organization
149 https://www.grid.ac/institutes/grid.413721.2 schema:alternateName Washington DC VA Medical Center
150 schema:name Howard University, Washington, DC, USA
151 Medstar Georgetown University Hospital, Washington, DC, USA
152 Rheumatology Section, 151K, Veterans Affairs Medical Center, 50 Irving St, NW, 20422, Washington, DC, USA
153 Washington DC Veteran Affairs Medical Center, Washington, DC, USA
154 rdf:type schema:Organization
155 https://www.grid.ac/institutes/grid.478099.b schema:alternateName VA Nebraska Western Iowa Health Care System
156 schema:name University of Nebraska Medical Center & VA Nebraska-Western Iowa Health Care System, Omaha, NE, USA
157 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...