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/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adult", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Anti-Bacterial Agents", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Body Temperature", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cesarean Section", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Follow-Up Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Obesity", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Pregnancy", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Risk Factors", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Surgical Wound Infection", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Thermography", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Young Adult", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Faculty of Health and Wellbeing, Montgomery House, Sheffield Hallam University, 32 Collegiate Crescent, S102BP, Sheffield, England", 
          "id": "http://www.grid.ac/institutes/grid.5884.1", 
          "name": [
            "Faculty of Health and Wellbeing, Montgomery House, Sheffield Hallam University, 32 Collegiate Crescent, S102BP, Sheffield, England"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Childs", 
        "givenName": "Charmaine", 
        "id": "sg:person.01257534515.81", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01257534515.81"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Faculty of Health and Wellbeing, Montgomery House, Sheffield Hallam University, 32 Collegiate Crescent, S102BP, Sheffield, England", 
          "id": "http://www.grid.ac/institutes/grid.5884.1", 
          "name": [
            "Faculty of Health and Wellbeing, Montgomery House, Sheffield Hallam University, 32 Collegiate Crescent, S102BP, Sheffield, England"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wright", 
        "givenName": "Nicola", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Electronic and Electrical Engineering, Portobello Centre, University of Sheffield, S1 4ET, Sheffield, England", 
          "id": "http://www.grid.ac/institutes/grid.11835.3e", 
          "name": [
            "Department of Electronic and Electrical Engineering, Portobello Centre, University of Sheffield, S1 4ET, Sheffield, England"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Willmott", 
        "givenName": "Jon", 
        "id": "sg:person.01154224541.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01154224541.18"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Electronic and Electrical Engineering, Portobello Centre, University of Sheffield, S1 4ET, Sheffield, England", 
          "id": "http://www.grid.ac/institutes/grid.11835.3e", 
          "name": [
            "Department of Electronic and Electrical Engineering, Portobello Centre, University of Sheffield, S1 4ET, Sheffield, England"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Davies", 
        "givenName": "Matthew", 
        "id": "sg:person.016103367307.22", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016103367307.22"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Sheffield Hallam University, 32 Collegiate Crescent, S10 2BP, Sheffield, England", 
          "id": "http://www.grid.ac/institutes/grid.5884.1", 
          "name": [
            "Sheffield Hallam University, 32 Collegiate Crescent, S10 2BP, Sheffield, England"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kilner", 
        "givenName": "Karen", 
        "id": "sg:person.0767412175.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0767412175.50"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institute of Skin Integrity and Infection Prevention, University of Huddersfield, Queensgate, HD1 3DH, Huddersfield, England", 
          "id": "http://www.grid.ac/institutes/grid.15751.37", 
          "name": [
            "Institute of Skin Integrity and Infection Prevention, University of Huddersfield, Queensgate, HD1 3DH, Huddersfield, England"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ousey", 
        "givenName": "Karen", 
        "id": "sg:person.01174203441.64", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01174203441.64"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Faculty of Health and Wellbeing, Sheffield Hallam University, 32 Collegiate Crescent, S10 2BP, Sheffield, England", 
          "id": "http://www.grid.ac/institutes/grid.5884.1", 
          "name": [
            "Faculty of Health and Wellbeing, Sheffield Hallam University, 32 Collegiate Crescent, S10 2BP, Sheffield, England"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Soltani", 
        "givenName": "Hora", 
        "id": "sg:person.01047474273.14", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01047474273.14"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Obstetrics and Gynaecology, Jessop Hospital, Tree Root Walk, S10 2SF, Sheffield, England", 
          "id": "http://www.grid.ac/institutes/grid.414978.7", 
          "name": [
            "Obstetrics and Gynaecology, Jessop Hospital, Tree Root Walk, S10 2SF, Sheffield, England"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Madhuvrata", 
        "givenName": "Priya", 
        "id": "sg:person.0602303737.40", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0602303737.40"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Biomedical Statistics, University of Huddersfield, Queensgate, HD1 3DH, Huddersfield, England", 
          "id": "http://www.grid.ac/institutes/grid.15751.37", 
          "name": [
            "Biomedical Statistics, University of Huddersfield, Queensgate, HD1 3DH, Huddersfield, England"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Stephenson", 
        "givenName": "John", 
        "id": "sg:person.01072137616.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01072137616.62"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s11999-013-3346-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012399940", 
          "https://doi.org/10.1007/s11999-013-3346-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1245/s10434-012-2448-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014369732", 
          "https://doi.org/10.1245/s10434-012-2448-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-981-10-3147-2_21", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084724832", 
          "https://doi.org/10.1007/978-981-10-3147-2_21"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-01-07", 
    "datePublishedReg": "2019-01-07", 
    "description": "BackgroundProphylactic antibiotics are commonly prescribed intra-operatively after caesarean section birth, often at high doses. Even so, wound infections are not uncommon and obesity increases the risk. Currently, no independent wound assessment technology is available to stratify women to low or high risk of surgical site infection (SSI).Study Aim: to investigate the potential of non-invasive infrared thermography (IRT), performed at short times after surgery, to predict later SSI.MethodsIRT was undertaken in hospital on day 2 with community follow up (days 7, 15, 30) after surgery. Thermal maps of wound site and abdomen were accompanied by digital photographs, the latter used for wound assessment by six experienced healthcare professionals. Confirmatory diagnosis of SSI was made on the basis of antibiotic prescribing by the woman\u2019s community physician with logistic regression models derived to model dichotomous outcomes.ResultsFifty-three women aged 21\u201344\u2009years with BMI 30.1\u201343.9 Kg.m\u2212\u20092 were recruited. SSI rate (within 30\u2009days) was 28%. Inter-rater variability for \u2018professional\u2019 opinion of wound appearance showed poor levels of agreement. Two regions of interest were interrogated; wound site and abdomen. Wound site temperature was consistently elevated (1.5\u2009\u00b0C) above abdominal temperature with similar values at days 2,7,15 in those who did and did not, develop SSI. Mean abdominal temperature was lower in women who subsequently developed SSI; significantly so at day 7. A unit (1\u2009\u00b0C) reduction in abdominal temperature was associated with a 3-fold raised odds of infection. The difference between the sites (wound minus abdomen temperature) was significantly associated with odds of infection; with a 1\u2009\u00b0C widening in temperature associated with an odds ratio for SSI of 2.25 (day 2) and 2.5 (day 7). Correct predictions for wound outcome using logistic regression models ranged from 70 to 79%;ConclusionsIRT imaging of wound and abdomen in obese women undergoing c-section improves upon visual (subjective) wound assessment. The proportion of cases correctly classified using the wound-abdominal temperature differences holds promise for precision and performance of IRT as an independent SSI prognostic tool and future technology to aid decision making in antibiotic prescribing.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/s13756-018-0461-7", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.5071623", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1046972", 
        "issn": [
          "2047-2994"
        ], 
        "name": "Antimicrobial Resistance & Infection Control", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "8"
      }
    ], 
    "keywords": [
      "surgical site infection", 
      "odds of infection", 
      "logistic regression models", 
      "site infection", 
      "antibiotic prescribing", 
      "obese women", 
      "community physicians", 
      "late surgical-site infection", 
      "wound assessment", 
      "caesarean section births", 
      "proportion of cases", 
      "abdominal temperature", 
      "experienced healthcare professionals", 
      "SSI rates", 
      "caesarean section", 
      "regression models", 
      "wound infection", 
      "wound outcomes", 
      "odds ratio", 
      "surgical wounds", 
      "BMI 30.1", 
      "high risk", 
      "prognostic tool", 
      "dichotomous outcomes", 
      "non-invasive infrared thermography", 
      "day 2", 
      "confirmatory diagnosis", 
      "day 7", 
      "high doses", 
      "inter-rater variability", 
      "wound appearance", 
      "healthcare professionals", 
      "infection", 
      "C-section", 
      "abdomen", 
      "women", 
      "prescribing", 
      "surgery", 
      "wound site", 
      "poor level", 
      "odds", 
      "wounds", 
      "outcomes", 
      "risk", 
      "unit reduction", 
      "days", 
      "early stages", 
      "obesity", 
      "digital photographs", 
      "region of interest", 
      "hospital", 
      "thermographic profiles", 
      "physicians", 
      "doses", 
      "diagnosis", 
      "assessment", 
      "birth", 
      "antibiotics", 
      "differences", 
      "imaging", 
      "professionals", 
      "aim", 
      "years", 
      "proportion", 
      "sites", 
      "short time", 
      "levels", 
      "intra", 
      "cases", 
      "appearance", 
      "similar values", 
      "rate", 
      "reduction", 
      "infrared thermography", 
      "profile", 
      "stage", 
      "promise", 
      "Kg", 
      "assessment technology", 
      "ratio", 
      "time", 
      "opinion", 
      "potential", 
      "photographs", 
      "variability", 
      "correct prediction", 
      "sections", 
      "model", 
      "tool", 
      "values", 
      "decisions", 
      "basis", 
      "region", 
      "community", 
      "interest", 
      "thermography", 
      "prediction", 
      "site temperature", 
      "technology", 
      "agreement", 
      "precision", 
      "maps", 
      "performance", 
      "thermal maps", 
      "future technologies", 
      "temperature", 
      "temperature difference", 
      "Infrared"
    ], 
    "name": "The surgical wound in infrared: thermographic profiles and early stage test-accuracy to predict surgical site infection in obese women during the first 30 days after caesarean section", 
    "pagination": "7", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1111255617"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s13756-018-0461-7"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30637101"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s13756-018-0461-7", 
      "https://app.dimensions.ai/details/publication/pub.1111255617"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-05-20T07:36", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220519/entities/gbq_results/article/article_822.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/s13756-018-0461-7"
  }
]

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

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

305 TRIPLES      22 PREDICATES      150 URIs      139 LITERALS      20 BLANK NODES