Development and validation of a risk score to predict mortality during TB treatment in patients with TB-diabetes comorbidity View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Duc T. Nguyen, Edward A. Graviss

ABSTRACT

BACKGROUND: Making an accurate prognosis for mortality during tuberculosis (TB) treatment in TB-diabetes (TB-DM) comorbid patients remains a challenge for health professionals, especially in low TB prevalent populations, due to the lack of a standardized prognostic model. METHODS: Using de-identified data from TB-DM patients from Texas, who received TB treatment had a treatment outcome of completed treatment or died before completion, reported to the National TB Surveillance System from January 2010-December 2016, we developed and internally validated a mortality scoring system, based on the regression coefficients. RESULTS: Of 1227 included TB-DM patients, 112 (9.1%) died during treatment. The score used nine characteristics routinely collected by most TB programs. Patients were divided into three groups based on their score: low-risk (< 12 points), medium-risk (12-21 points) and high-risk (≥22 points). The model had good performance (with an area under the receiver operating characteristic (ROC) curve of 0.83 in development and 0.82 in validation), and good calibration. A practical mobile calculator app was also created ( https://oaa.app.link/Isqia5rN6K ). CONCLUSION: Using demographic and clinical characteristics which are available from most TB programs at the patient's initial visits, our simple scoring system had good performance and may be a practical clinical tool for TB health professionals in identifying TB-DM comorbid patients with a high mortality risk. More... »

PAGES

10

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12879-018-3632-5

DOI

http://dx.doi.org/10.1186/s12879-018-3632-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111159465

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30611208


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/2008/1117", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Public Health and Health Services", 
        "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": "Houston Methodist", 
          "id": "https://www.grid.ac/institutes/grid.63368.38", 
          "name": [
            "Department of Pathology and Genomic Medicine, Houston Methodist Research Institute, Mail Station: R6-414, 6670 Bertner Ave, 77030, Houston, TX, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nguyen", 
        "givenName": "Duc T.", 
        "id": "sg:person.07547110652.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07547110652.69"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Houston Methodist", 
          "id": "https://www.grid.ac/institutes/grid.63368.38", 
          "name": [
            "Department of Pathology and Genomic Medicine, Houston Methodist Research Institute, Mail Station: R6-414, 6670 Bertner Ave, 77030, Houston, TX, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Graviss", 
        "givenName": "Edward A.", 
        "id": "sg:person.01110004277.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01110004277.08"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/s1473-3099(09)70282-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000015156"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa053241", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004523839"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1741-7015-9-81", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008255861", 
          "https://doi.org/10.1186/1741-7015-9-81"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0162797", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010607646"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1590/s1806-37132013000500009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011998877"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/tmi.12120", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016705534"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12879-016-1640-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017582920", 
          "https://doi.org/10.1186/s12879-016-1640-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12879-016-1640-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017582920", 
          "https://doi.org/10.1186/s12879-016-1640-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.tube.2016.09.024", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023009267"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep21610", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027312509", 
          "https://doi.org/10.1038/srep21610"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/ageing/afs028", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032392519"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijid.2014.11.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034518058"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/jmps.1999.1278", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037812558"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0092077", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043986000"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10985-004-0384-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047230276", 
          "https://doi.org/10.1007/s10985-004-0384-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s2213-8587(14)70110-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048114840"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.annepidem.2014.01.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048312696"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5588/ijtld.12.0476", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052364678"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/thoraxjnl-2015-207686", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062822963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/thoraxjnl-2015-207686", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062822963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1183/09031936.00138712", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064123847"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2471/blt.10.085738", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1070837779"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/003335491012500307", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074209822"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/003335491012500307", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074209822"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12879-017-2309-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084612359", 
          "https://doi.org/10.1186/s12879-017-2309-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12879-017-2309-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084612359", 
          "https://doi.org/10.1186/s12879-017-2309-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0187967", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092842754"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jinf.2018.02.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103189816"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0196022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103394301"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-12", 
    "datePublishedReg": "2019-12-01", 
    "description": "BACKGROUND: Making an accurate prognosis for mortality during tuberculosis (TB) treatment in TB-diabetes (TB-DM) comorbid patients remains a challenge for health professionals, especially in low TB prevalent populations, due to the lack of a standardized prognostic model.\nMETHODS: Using de-identified data from TB-DM patients from Texas, who received TB treatment had a treatment outcome of completed treatment or died before completion, reported to the National TB Surveillance System from January 2010-December 2016, we developed and internally validated a mortality scoring system, based on the regression coefficients.\nRESULTS: Of 1227 included TB-DM patients, 112 (9.1%) died during treatment. The score used nine characteristics routinely collected by most TB programs. Patients were divided into three groups based on their score: low-risk (<\u200912 points), medium-risk (12-21 points) and high-risk (\u226522 points). The model had good performance (with an area under the receiver operating characteristic (ROC) curve of 0.83 in development and 0.82 in validation), and good calibration. A practical mobile calculator app was also created ( https://oaa.app.link/Isqia5rN6K ).\nCONCLUSION: Using demographic and clinical characteristics which are available from most TB programs at the patient's initial visits, our simple scoring system had good performance and may be a practical clinical tool for TB health professionals in identifying TB-DM comorbid patients with a high mortality risk.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s12879-018-3632-5", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1024946", 
        "issn": [
          "1471-2334"
        ], 
        "name": "BMC Infectious Diseases", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "19"
      }
    ], 
    "name": "Development and validation of a risk score to predict mortality during TB treatment in patients with TB-diabetes comorbidity", 
    "pagination": "10", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "763f2024b8d79c6a11eebae61e4d5bb435d3cf9eb80440d1a075536b3220b2fb"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30611208"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "100968551"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s12879-018-3632-5"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1111159465"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s12879-018-3632-5", 
      "https://app.dimensions.ai/details/publication/pub.1111159465"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T08:37", 
    "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/v90/0000000315_0000000315/records_6336_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1186%2Fs12879-018-3632-5"
  }
]
 

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.10.1186/s12879-018-3632-5'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12879-018-3632-5'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12879-018-3632-5'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12879-018-3632-5'


 

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

155 TRIPLES      21 PREDICATES      54 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s12879-018-3632-5 schema:about anzsrc-for:11
2 anzsrc-for:1117
3 schema:author N21bba4b737c24fb6b7df6681ede09333
4 schema:citation sg:pub.10.1007/s10985-004-0384-x
5 sg:pub.10.1038/srep21610
6 sg:pub.10.1186/1741-7015-9-81
7 sg:pub.10.1186/s12879-016-1640-x
8 sg:pub.10.1186/s12879-017-2309-9
9 https://doi.org/10.1006/jmps.1999.1278
10 https://doi.org/10.1016/j.annepidem.2014.01.012
11 https://doi.org/10.1016/j.ijid.2014.11.018
12 https://doi.org/10.1016/j.jinf.2018.02.009
13 https://doi.org/10.1016/j.tube.2016.09.024
14 https://doi.org/10.1016/s1473-3099(09)70282-8
15 https://doi.org/10.1016/s2213-8587(14)70110-x
16 https://doi.org/10.1056/nejmoa053241
17 https://doi.org/10.1093/ageing/afs028
18 https://doi.org/10.1111/tmi.12120
19 https://doi.org/10.1136/thoraxjnl-2015-207686
20 https://doi.org/10.1177/003335491012500307
21 https://doi.org/10.1183/09031936.00138712
22 https://doi.org/10.1371/journal.pone.0092077
23 https://doi.org/10.1371/journal.pone.0162797
24 https://doi.org/10.1371/journal.pone.0187967
25 https://doi.org/10.1371/journal.pone.0196022
26 https://doi.org/10.1590/s1806-37132013000500009
27 https://doi.org/10.2471/blt.10.085738
28 https://doi.org/10.5588/ijtld.12.0476
29 schema:datePublished 2019-12
30 schema:datePublishedReg 2019-12-01
31 schema:description BACKGROUND: Making an accurate prognosis for mortality during tuberculosis (TB) treatment in TB-diabetes (TB-DM) comorbid patients remains a challenge for health professionals, especially in low TB prevalent populations, due to the lack of a standardized prognostic model. METHODS: Using de-identified data from TB-DM patients from Texas, who received TB treatment had a treatment outcome of completed treatment or died before completion, reported to the National TB Surveillance System from January 2010-December 2016, we developed and internally validated a mortality scoring system, based on the regression coefficients. RESULTS: Of 1227 included TB-DM patients, 112 (9.1%) died during treatment. The score used nine characteristics routinely collected by most TB programs. Patients were divided into three groups based on their score: low-risk (< 12 points), medium-risk (12-21 points) and high-risk (≥22 points). The model had good performance (with an area under the receiver operating characteristic (ROC) curve of 0.83 in development and 0.82 in validation), and good calibration. A practical mobile calculator app was also created ( https://oaa.app.link/Isqia5rN6K ). CONCLUSION: Using demographic and clinical characteristics which are available from most TB programs at the patient's initial visits, our simple scoring system had good performance and may be a practical clinical tool for TB health professionals in identifying TB-DM comorbid patients with a high mortality risk.
32 schema:genre research_article
33 schema:inLanguage en
34 schema:isAccessibleForFree true
35 schema:isPartOf N4d91081e05b54f32bcb6d6da7fc9c470
36 Ncbc24017d1ea4c78845e6946b94080b5
37 sg:journal.1024946
38 schema:name Development and validation of a risk score to predict mortality during TB treatment in patients with TB-diabetes comorbidity
39 schema:pagination 10
40 schema:productId N66d9b2846a344300be097f509393111f
41 Naad9eb615970476ea731cd98b5eacdd0
42 Nb81b90dc23e843a6b6c26424fac08e24
43 Nc78372abdbb1447e9be3e3c3427a5e56
44 Ndfbf414fb78b4243aff578014d74616b
45 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111159465
46 https://doi.org/10.1186/s12879-018-3632-5
47 schema:sdDatePublished 2019-04-11T08:37
48 schema:sdLicense https://scigraph.springernature.com/explorer/license/
49 schema:sdPublisher Nab3b0bea2bfd48098652ebddf954e620
50 schema:url https://link.springer.com/10.1186%2Fs12879-018-3632-5
51 sgo:license sg:explorer/license/
52 sgo:sdDataset articles
53 rdf:type schema:ScholarlyArticle
54 N21bba4b737c24fb6b7df6681ede09333 rdf:first sg:person.07547110652.69
55 rdf:rest N7005003a6f154ac9bb36991c293bcc49
56 N4d91081e05b54f32bcb6d6da7fc9c470 schema:volumeNumber 19
57 rdf:type schema:PublicationVolume
58 N66d9b2846a344300be097f509393111f schema:name pubmed_id
59 schema:value 30611208
60 rdf:type schema:PropertyValue
61 N7005003a6f154ac9bb36991c293bcc49 rdf:first sg:person.01110004277.08
62 rdf:rest rdf:nil
63 Naad9eb615970476ea731cd98b5eacdd0 schema:name dimensions_id
64 schema:value pub.1111159465
65 rdf:type schema:PropertyValue
66 Nab3b0bea2bfd48098652ebddf954e620 schema:name Springer Nature - SN SciGraph project
67 rdf:type schema:Organization
68 Nb81b90dc23e843a6b6c26424fac08e24 schema:name readcube_id
69 schema:value 763f2024b8d79c6a11eebae61e4d5bb435d3cf9eb80440d1a075536b3220b2fb
70 rdf:type schema:PropertyValue
71 Nc78372abdbb1447e9be3e3c3427a5e56 schema:name doi
72 schema:value 10.1186/s12879-018-3632-5
73 rdf:type schema:PropertyValue
74 Ncbc24017d1ea4c78845e6946b94080b5 schema:issueNumber 1
75 rdf:type schema:PublicationIssue
76 Ndfbf414fb78b4243aff578014d74616b schema:name nlm_unique_id
77 schema:value 100968551
78 rdf:type schema:PropertyValue
79 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
80 schema:name Medical and Health Sciences
81 rdf:type schema:DefinedTerm
82 anzsrc-for:1117 schema:inDefinedTermSet anzsrc-for:
83 schema:name Public Health and Health Services
84 rdf:type schema:DefinedTerm
85 sg:journal.1024946 schema:issn 1471-2334
86 schema:name BMC Infectious Diseases
87 rdf:type schema:Periodical
88 sg:person.01110004277.08 schema:affiliation https://www.grid.ac/institutes/grid.63368.38
89 schema:familyName Graviss
90 schema:givenName Edward A.
91 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01110004277.08
92 rdf:type schema:Person
93 sg:person.07547110652.69 schema:affiliation https://www.grid.ac/institutes/grid.63368.38
94 schema:familyName Nguyen
95 schema:givenName Duc T.
96 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07547110652.69
97 rdf:type schema:Person
98 sg:pub.10.1007/s10985-004-0384-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1047230276
99 https://doi.org/10.1007/s10985-004-0384-x
100 rdf:type schema:CreativeWork
101 sg:pub.10.1038/srep21610 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027312509
102 https://doi.org/10.1038/srep21610
103 rdf:type schema:CreativeWork
104 sg:pub.10.1186/1741-7015-9-81 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008255861
105 https://doi.org/10.1186/1741-7015-9-81
106 rdf:type schema:CreativeWork
107 sg:pub.10.1186/s12879-016-1640-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1017582920
108 https://doi.org/10.1186/s12879-016-1640-x
109 rdf:type schema:CreativeWork
110 sg:pub.10.1186/s12879-017-2309-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084612359
111 https://doi.org/10.1186/s12879-017-2309-9
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1006/jmps.1999.1278 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037812558
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1016/j.annepidem.2014.01.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048312696
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1016/j.ijid.2014.11.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034518058
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1016/j.jinf.2018.02.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103189816
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1016/j.tube.2016.09.024 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023009267
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1016/s1473-3099(09)70282-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000015156
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1016/s2213-8587(14)70110-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1048114840
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1056/nejmoa053241 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004523839
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1093/ageing/afs028 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032392519
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1111/tmi.12120 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016705534
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1136/thoraxjnl-2015-207686 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062822963
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1177/003335491012500307 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074209822
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1183/09031936.00138712 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064123847
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1371/journal.pone.0092077 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043986000
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1371/journal.pone.0162797 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010607646
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1371/journal.pone.0187967 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092842754
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1371/journal.pone.0196022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103394301
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1590/s1806-37132013000500009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011998877
148 rdf:type schema:CreativeWork
149 https://doi.org/10.2471/blt.10.085738 schema:sameAs https://app.dimensions.ai/details/publication/pub.1070837779
150 rdf:type schema:CreativeWork
151 https://doi.org/10.5588/ijtld.12.0476 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052364678
152 rdf:type schema:CreativeWork
153 https://www.grid.ac/institutes/grid.63368.38 schema:alternateName Houston Methodist
154 schema:name Department of Pathology and Genomic Medicine, Houston Methodist Research Institute, Mail Station: R6-414, 6670 Bertner Ave, 77030, Houston, TX, USA
155 rdf:type schema:Organization
 




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


...