Utility of predictive tools for risk stratification of elderly individuals with all-cause acute respiratory infection View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03-30

AUTHORS

Allison S. Bloom, Sunil Suchindran, Julie Steinbrink, Micah T. McClain

ABSTRACT

PURPOSE: A number of scoring tools have been developed to predict illness severity and patient outcome for proven pneumonia, however, less is known about the utility of clinical prediction scores for all-cause acute respiratory infection (ARI), especially in elderly subjects who are at increased risk of poor outcomes. METHODS: We retrospectively analyzed risk factors and outcomes of individuals ≥ 60 years of age presenting to the emergency department with a clinical diagnosis of ARI. RESULTS: Of 276 individuals in the study, 40 had proven viral infection and 52 proven bacterial infection, but 184 patients with clinically adjudicated ARI (67%) remained without a proven microbial etiology despite extensive clinical (and expanded research) workup. Patients who were older, had multiple comorbidities, or who had proven bacterial infection were more likely to require hospital and ICU admission. We identified a novel model based on 11 demographic and clinical variables that were significant risk factors for ICU admission or mortality in elderly subjects with all-cause ARI. As comparators, a modified PORT score was found to correlate more closely with all-cause ARI severity than a modified CURB-65 score (r, 0.54, 0.39). Interestingly, modified Jackson symptom scores were found to inversely correlate with severity (r, - 0.34) but show potential for differentiating viral and bacterial etiologies. CONCLUSIONS: Modified PORT, CURB-65, Jackson symptom scores, and a novel ARI scoring tool presented herein all offer predictive ability for all-cause ARI in elderly subjects. Such broadly applicable scoring metrics have the potential to assist in treatment and triage decisions at the point of care. More... »

PAGES

1-11

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s15010-019-01299-1

DOI

http://dx.doi.org/10.1007/s15010-019-01299-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113144356

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30929142


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": "Duke University", 
          "id": "https://www.grid.ac/institutes/grid.26009.3d", 
          "name": [
            "Duke University School of Medicine, Durham, NC, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bloom", 
        "givenName": "Allison S.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Duke University", 
          "id": "https://www.grid.ac/institutes/grid.26009.3d", 
          "name": [
            "Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Suchindran", 
        "givenName": "Sunil", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Duke University Hospital", 
          "id": "https://www.grid.ac/institutes/grid.189509.c", 
          "name": [
            "Division of Infectious Diseases, Duke University Medical Center, Durham, NC, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Steinbrink", 
        "givenName": "Julie", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Durham VA Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.410332.7", 
          "name": [
            "Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, USA", 
            "Division of Infectious Diseases, Duke University Medical Center, Durham, NC, USA", 
            "Durham Veteran\u2019s Affairs Medical Center, Durham, NC, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "McClain", 
        "givenName": "Micah T.", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1378/chest.101.6.1644", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006971593"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/cc4955", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007597722", 
          "https://doi.org/10.1186/cc4955"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/thx.2009.130799", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012047521"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/thx.2009.130799", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012047521"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s15010-002-2083-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016189477", 
          "https://doi.org/10.1007/s15010-002-2083-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pmed.1002022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017293090"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejm199701233360402", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018073258"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jama.289.2.179", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019601589"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/jcm.01447-09", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020314395"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1203/pdr.0b013e3181e9f3a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020623346", 
          "https://doi.org/10.1203/pdr.0b013e3181e9f3a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1203/pdr.0b013e3181e9f3a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020623346", 
          "https://doi.org/10.1203/pdr.0b013e3181e9f3a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1203/pdr.0b013e3181e9f3a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020623346", 
          "https://doi.org/10.1203/pdr.0b013e3181e9f3a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s13073-014-0111-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024584206", 
          "https://doi.org/10.1186/s13073-014-0111-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s13073-014-0111-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024584206", 
          "https://doi.org/10.1186/s13073-014-0111-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1742-6723.2007.01003.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026059902"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/scitranslmed.aad6873", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026204671"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0002-9343(85)90361-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028578066"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jemermed.2011.05.072", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029023245"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/thx.51.10.1010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029217815"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/thx.51.10.1010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029217815"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.vaccine.2006.09.041", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030005760"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/imj.12445", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032003682"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/archinte.1958.00260140099015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033222001"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/cid/cir050", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040226237"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/archinte.159.9.970", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044023001"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa1500245", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044458611"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/thorax.58.5.377", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044558168"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/thorax.58.5.377", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044558168"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jinf.2008.11.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045607508"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1473-3099(04)00931-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046507411"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jama.1997.03550230056037", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046626715"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1553-2712.2010.00664.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049624708"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1553-2712.2010.00664.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049624708"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/archinte.167.4.ioi60207", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049856625"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jama.292.11.1333", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053576575"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.18637/jss.v033.i01", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068672496"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.18637/jss.v033.i01", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068672496"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.7326/0003-4819-115-6-428", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1073695999"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.7326/0003-4819-138-2-200301210-00012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1073706042"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1078351973", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/oxfordjournals.qjmed.a068093", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083631000"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/14651858.cd007498.pub3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092191486"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.biopha.2017.11.149", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1099701551"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12879-018-2984-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101001371", 
          "https://doi.org/10.1186/s12879-018-2984-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.15585/mmwr.mm6722a4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1104472080"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3389/fcimb.2018.00382", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107901117"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3389/fcimb.2018.00382", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107901117"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.2517-6161.1996.tb02080.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110458978"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.2517-6161.1996.tb02080.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110458978"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-03-30", 
    "datePublishedReg": "2019-03-30", 
    "description": "PURPOSE: A number of scoring tools have been developed to predict illness severity and patient outcome for proven pneumonia, however, less is known about the utility of clinical prediction scores for all-cause acute respiratory infection (ARI), especially in elderly subjects who are at increased risk of poor outcomes.\nMETHODS: We retrospectively analyzed risk factors and outcomes of individuals \u2265\u200960\u00a0years of age presenting to the emergency department with a clinical diagnosis of ARI.\nRESULTS: Of 276 individuals in the study, 40 had proven viral infection and 52 proven bacterial infection, but 184 patients with clinically adjudicated ARI (67%) remained without a proven microbial etiology despite extensive clinical (and expanded research) workup. Patients who were older, had multiple comorbidities, or who had proven bacterial infection were more likely to require hospital and ICU admission. We identified a novel model based on 11 demographic and clinical variables that were significant risk factors for ICU admission or mortality in elderly subjects with all-cause ARI. As comparators, a modified PORT score was found to correlate more closely with all-cause ARI severity than a modified CURB-65 score (r, 0.54, 0.39). Interestingly, modified Jackson symptom scores were found to inversely correlate with severity (r, -\u20090.34) but show potential for differentiating viral and bacterial etiologies.\nCONCLUSIONS: Modified PORT, CURB-65, Jackson symptom scores, and a novel ARI scoring tool presented herein all offer predictive ability for all-cause ARI in elderly subjects. Such broadly applicable scoring metrics have the potential to assist in treatment and triage decisions at the point of care.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s15010-019-01299-1", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1016707", 
        "issn": [
          "0300-8126", 
          "1439-0973"
        ], 
        "name": "Infection", 
        "type": "Periodical"
      }
    ], 
    "name": "Utility of predictive tools for risk stratification of elderly individuals with all-cause acute respiratory infection", 
    "pagination": "1-11", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "a60cab518af3de5a127eda7259eabc8bec30fbf1a6a1a7ce1c4f5d06e14e0e78"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30929142"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "0365307"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s15010-019-01299-1"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1113144356"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s15010-019-01299-1", 
      "https://app.dimensions.ai/details/publication/pub.1113144356"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:29", 
    "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/v90/0000000370_0000000370/records_46747_00000003.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs15010-019-01299-1"
  }
]
 

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/s15010-019-01299-1'

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/s15010-019-01299-1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s15010-019-01299-1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s15010-019-01299-1'


 

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

210 TRIPLES      21 PREDICATES      65 URIs      18 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s15010-019-01299-1 schema:about anzsrc-for:11
2 anzsrc-for:1103
3 schema:author N465767b20c3c42ce97b4bfd68fe6093e
4 schema:citation sg:pub.10.1007/s15010-002-2083-4
5 sg:pub.10.1186/cc4955
6 sg:pub.10.1186/s12879-018-2984-1
7 sg:pub.10.1186/s13073-014-0111-5
8 sg:pub.10.1203/pdr.0b013e3181e9f3a0
9 https://app.dimensions.ai/details/publication/pub.1078351973
10 https://doi.org/10.1001/archinte.159.9.970
11 https://doi.org/10.1001/archinte.167.4.ioi60207
12 https://doi.org/10.1001/archinte.1958.00260140099015
13 https://doi.org/10.1001/jama.1997.03550230056037
14 https://doi.org/10.1001/jama.289.2.179
15 https://doi.org/10.1001/jama.292.11.1333
16 https://doi.org/10.1002/14651858.cd007498.pub3
17 https://doi.org/10.1016/0002-9343(85)90361-4
18 https://doi.org/10.1016/j.biopha.2017.11.149
19 https://doi.org/10.1016/j.jemermed.2011.05.072
20 https://doi.org/10.1016/j.jinf.2008.11.007
21 https://doi.org/10.1016/j.vaccine.2006.09.041
22 https://doi.org/10.1016/s1473-3099(04)00931-4
23 https://doi.org/10.1056/nejm199701233360402
24 https://doi.org/10.1056/nejmoa1500245
25 https://doi.org/10.1093/cid/cir050
26 https://doi.org/10.1093/oxfordjournals.qjmed.a068093
27 https://doi.org/10.1111/imj.12445
28 https://doi.org/10.1111/j.1553-2712.2010.00664.x
29 https://doi.org/10.1111/j.1742-6723.2007.01003.x
30 https://doi.org/10.1111/j.2517-6161.1996.tb02080.x
31 https://doi.org/10.1126/scitranslmed.aad6873
32 https://doi.org/10.1128/jcm.01447-09
33 https://doi.org/10.1136/thorax.58.5.377
34 https://doi.org/10.1136/thx.2009.130799
35 https://doi.org/10.1136/thx.51.10.1010
36 https://doi.org/10.1371/journal.pmed.1002022
37 https://doi.org/10.1378/chest.101.6.1644
38 https://doi.org/10.15585/mmwr.mm6722a4
39 https://doi.org/10.18637/jss.v033.i01
40 https://doi.org/10.3389/fcimb.2018.00382
41 https://doi.org/10.7326/0003-4819-115-6-428
42 https://doi.org/10.7326/0003-4819-138-2-200301210-00012
43 schema:datePublished 2019-03-30
44 schema:datePublishedReg 2019-03-30
45 schema:description PURPOSE: A number of scoring tools have been developed to predict illness severity and patient outcome for proven pneumonia, however, less is known about the utility of clinical prediction scores for all-cause acute respiratory infection (ARI), especially in elderly subjects who are at increased risk of poor outcomes. METHODS: We retrospectively analyzed risk factors and outcomes of individuals ≥ 60 years of age presenting to the emergency department with a clinical diagnosis of ARI. RESULTS: Of 276 individuals in the study, 40 had proven viral infection and 52 proven bacterial infection, but 184 patients with clinically adjudicated ARI (67%) remained without a proven microbial etiology despite extensive clinical (and expanded research) workup. Patients who were older, had multiple comorbidities, or who had proven bacterial infection were more likely to require hospital and ICU admission. We identified a novel model based on 11 demographic and clinical variables that were significant risk factors for ICU admission or mortality in elderly subjects with all-cause ARI. As comparators, a modified PORT score was found to correlate more closely with all-cause ARI severity than a modified CURB-65 score (r, 0.54, 0.39). Interestingly, modified Jackson symptom scores were found to inversely correlate with severity (r, - 0.34) but show potential for differentiating viral and bacterial etiologies. CONCLUSIONS: Modified PORT, CURB-65, Jackson symptom scores, and a novel ARI scoring tool presented herein all offer predictive ability for all-cause ARI in elderly subjects. Such broadly applicable scoring metrics have the potential to assist in treatment and triage decisions at the point of care.
46 schema:genre research_article
47 schema:inLanguage en
48 schema:isAccessibleForFree false
49 schema:isPartOf sg:journal.1016707
50 schema:name Utility of predictive tools for risk stratification of elderly individuals with all-cause acute respiratory infection
51 schema:pagination 1-11
52 schema:productId N23abb415ce78433193b0c2628a75b904
53 N27395b9e00c34634ad7f86341fc67f29
54 N4b275667b5e44d67987b4e7537e1ce9a
55 N90de9439095f41eca451e8cd2910aad4
56 Nd1a0404fd7d34f6e860b69bdd6236084
57 schema:sameAs https://app.dimensions.ai/details/publication/pub.1113144356
58 https://doi.org/10.1007/s15010-019-01299-1
59 schema:sdDatePublished 2019-04-11T13:29
60 schema:sdLicense https://scigraph.springernature.com/explorer/license/
61 schema:sdPublisher N8002bed489564370883a2c1ab83bde49
62 schema:url https://link.springer.com/10.1007%2Fs15010-019-01299-1
63 sgo:license sg:explorer/license/
64 sgo:sdDataset articles
65 rdf:type schema:ScholarlyArticle
66 N028a75b2aeb743429d9065a0a4d8d3d7 schema:affiliation https://www.grid.ac/institutes/grid.26009.3d
67 schema:familyName Bloom
68 schema:givenName Allison S.
69 rdf:type schema:Person
70 N1466a742dea843e88084b39eb270a498 rdf:first N981b848865734a2a8a9b85c52595b2db
71 rdf:rest Naf3c402b1d1f44cea240212ca5a18a78
72 N23abb415ce78433193b0c2628a75b904 schema:name dimensions_id
73 schema:value pub.1113144356
74 rdf:type schema:PropertyValue
75 N27395b9e00c34634ad7f86341fc67f29 schema:name doi
76 schema:value 10.1007/s15010-019-01299-1
77 rdf:type schema:PropertyValue
78 N465767b20c3c42ce97b4bfd68fe6093e rdf:first N028a75b2aeb743429d9065a0a4d8d3d7
79 rdf:rest Neef4c49a67de47ccb6a9b8cdad8f76a5
80 N4896d33b1aa64623a552a81b3a213366 schema:affiliation https://www.grid.ac/institutes/grid.410332.7
81 schema:familyName McClain
82 schema:givenName Micah T.
83 rdf:type schema:Person
84 N4b275667b5e44d67987b4e7537e1ce9a schema:name pubmed_id
85 schema:value 30929142
86 rdf:type schema:PropertyValue
87 N8002bed489564370883a2c1ab83bde49 schema:name Springer Nature - SN SciGraph project
88 rdf:type schema:Organization
89 N90de9439095f41eca451e8cd2910aad4 schema:name readcube_id
90 schema:value a60cab518af3de5a127eda7259eabc8bec30fbf1a6a1a7ce1c4f5d06e14e0e78
91 rdf:type schema:PropertyValue
92 N981b848865734a2a8a9b85c52595b2db schema:affiliation https://www.grid.ac/institutes/grid.189509.c
93 schema:familyName Steinbrink
94 schema:givenName Julie
95 rdf:type schema:Person
96 Naf3c402b1d1f44cea240212ca5a18a78 rdf:first N4896d33b1aa64623a552a81b3a213366
97 rdf:rest rdf:nil
98 Nd1a0404fd7d34f6e860b69bdd6236084 schema:name nlm_unique_id
99 schema:value 0365307
100 rdf:type schema:PropertyValue
101 Nd870274928f941249c445e1e35190e2e schema:affiliation https://www.grid.ac/institutes/grid.26009.3d
102 schema:familyName Suchindran
103 schema:givenName Sunil
104 rdf:type schema:Person
105 Neef4c49a67de47ccb6a9b8cdad8f76a5 rdf:first Nd870274928f941249c445e1e35190e2e
106 rdf:rest N1466a742dea843e88084b39eb270a498
107 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
108 schema:name Medical and Health Sciences
109 rdf:type schema:DefinedTerm
110 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
111 schema:name Clinical Sciences
112 rdf:type schema:DefinedTerm
113 sg:journal.1016707 schema:issn 0300-8126
114 1439-0973
115 schema:name Infection
116 rdf:type schema:Periodical
117 sg:pub.10.1007/s15010-002-2083-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016189477
118 https://doi.org/10.1007/s15010-002-2083-4
119 rdf:type schema:CreativeWork
120 sg:pub.10.1186/cc4955 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007597722
121 https://doi.org/10.1186/cc4955
122 rdf:type schema:CreativeWork
123 sg:pub.10.1186/s12879-018-2984-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101001371
124 https://doi.org/10.1186/s12879-018-2984-1
125 rdf:type schema:CreativeWork
126 sg:pub.10.1186/s13073-014-0111-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024584206
127 https://doi.org/10.1186/s13073-014-0111-5
128 rdf:type schema:CreativeWork
129 sg:pub.10.1203/pdr.0b013e3181e9f3a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020623346
130 https://doi.org/10.1203/pdr.0b013e3181e9f3a0
131 rdf:type schema:CreativeWork
132 https://app.dimensions.ai/details/publication/pub.1078351973 schema:CreativeWork
133 https://doi.org/10.1001/archinte.159.9.970 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044023001
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1001/archinte.167.4.ioi60207 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049856625
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1001/archinte.1958.00260140099015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033222001
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1001/jama.1997.03550230056037 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046626715
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1001/jama.289.2.179 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019601589
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1001/jama.292.11.1333 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053576575
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1002/14651858.cd007498.pub3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092191486
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1016/0002-9343(85)90361-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028578066
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1016/j.biopha.2017.11.149 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099701551
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1016/j.jemermed.2011.05.072 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029023245
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1016/j.jinf.2008.11.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045607508
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1016/j.vaccine.2006.09.041 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030005760
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1016/s1473-3099(04)00931-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046507411
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1056/nejm199701233360402 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018073258
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1056/nejmoa1500245 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044458611
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1093/cid/cir050 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040226237
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1093/oxfordjournals.qjmed.a068093 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083631000
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1111/imj.12445 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032003682
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1111/j.1553-2712.2010.00664.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1049624708
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1111/j.1742-6723.2007.01003.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1026059902
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1111/j.2517-6161.1996.tb02080.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1110458978
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1126/scitranslmed.aad6873 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026204671
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1128/jcm.01447-09 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020314395
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1136/thorax.58.5.377 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044558168
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1136/thx.2009.130799 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012047521
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1136/thx.51.10.1010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029217815
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1371/journal.pmed.1002022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017293090
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1378/chest.101.6.1644 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006971593
188 rdf:type schema:CreativeWork
189 https://doi.org/10.15585/mmwr.mm6722a4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104472080
190 rdf:type schema:CreativeWork
191 https://doi.org/10.18637/jss.v033.i01 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068672496
192 rdf:type schema:CreativeWork
193 https://doi.org/10.3389/fcimb.2018.00382 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107901117
194 rdf:type schema:CreativeWork
195 https://doi.org/10.7326/0003-4819-115-6-428 schema:sameAs https://app.dimensions.ai/details/publication/pub.1073695999
196 rdf:type schema:CreativeWork
197 https://doi.org/10.7326/0003-4819-138-2-200301210-00012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1073706042
198 rdf:type schema:CreativeWork
199 https://www.grid.ac/institutes/grid.189509.c schema:alternateName Duke University Hospital
200 schema:name Division of Infectious Diseases, Duke University Medical Center, Durham, NC, USA
201 rdf:type schema:Organization
202 https://www.grid.ac/institutes/grid.26009.3d schema:alternateName Duke University
203 schema:name Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, USA
204 Duke University School of Medicine, Durham, NC, USA
205 rdf:type schema:Organization
206 https://www.grid.ac/institutes/grid.410332.7 schema:alternateName Durham VA Medical Center
207 schema:name Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, USA
208 Division of Infectious Diseases, Duke University Medical Center, Durham, NC, USA
209 Durham Veteran’s Affairs Medical Center, Durham, NC, USA
210 rdf:type schema:Organization
 




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


...