Chronic kidney disease and clinical outcomes in patients with COVID-19 in Japan View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2022-06-03

AUTHORS

Ryosuke Sato, Yasushi Matsuzawa, Hisao Ogawa, Kazuo Kimura, Nobuo Tsuboi, Takashi Yokoo, Hirokazu Okada, Masaaki Konishi, Jin Kirigaya, Kazuki Fukui, Kengo Tsukahara, Hiroyuki Shimizu, Keisuke Iwabuchi, Yu Yamada, Kenichiro Saka, Ichiro Takeuchi, Naoki Kashihara, Kouichi Tamura

ABSTRACT

BackgroundIdentifying predictive factors for coronavirus disease 2019 (COVID-19) is crucial for risk stratification and intervention. Kidney dysfunction contributes to the severity of various infectious diseases. However, the association between on-admission kidney dysfunction and the clinical outcome in COVID-19 patients is unclear.MethodsThis study was a multicenter retrospective observational cohort study of COVID-19 patients, diagnosed by polymerase chain reaction. We retrospectively analyzed 500 COVID-19 patients (mean age: 51 ± 19 years) admitted to eight hospitals in Japan. Kidney dysfunction was defined as a reduced estimated glomerular filtration rate (< 60 mL/min/1.73 m2) or proteinuria (≥ 1 + dipstick proteinuria) on admission. The primary composite outcome included in-hospital death, extracorporeal membrane oxygenation, mechanical ventilation (invasive and noninvasive methods), and intensive care unit (ICU) admission.ResultsOverall, 171 (34.2%) patients presented with on-admission kidney dysfunction, and the primary composite outcome was observed in 60 (12.0%) patients. Patients with kidney dysfunction showed higher rates of in-hospital death (12.3 vs. 1.2%), mechanical ventilation (13.5 vs. 4.0%), and ICU admission (18.1 vs. 5.2%) than those without it. Categorical and multivariate regression analyses revealed that kidney dysfunction was substantially associated with the primary composite outcome. Thus, on-admission kidney dysfunction was common in COVID-19 patients. Furthermore, it correlated significantly and positively with COVID-19 severity and mortality.ConclusionsOn-admission kidney dysfunction was associated with disease severity and poor short-term prognosis in patients with COVID-19. Thus, on-admission kidney dysfunction has the potential to stratify risks in COVID-19 patients. More... »

PAGES

974-981

Journal

TITLE

Clinical and Experimental Nephrology

ISSUE

10

VOLUME

26

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10157-022-02240-x

DOI

http://dx.doi.org/10.1007/s10157-022-02240-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1148409148

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/35657437


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/2008/11", 
        "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": "Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "COVID-19", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Hospital Mortality", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Intensive Care Units", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Japan", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Middle Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Proteinuria", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Renal Insufficiency, Chronic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Retrospective Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Risk Factors", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "SARS-CoV-2", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Division of Cardiology, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, 232-0024, Yokohama City, Japan", 
          "id": "http://www.grid.ac/institutes/grid.413045.7", 
          "name": [
            "Division of Cardiology, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, 232-0024, Yokohama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sato", 
        "givenName": "Ryosuke", 
        "id": "sg:person.012341501403.01", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012341501403.01"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Division of Cardiology, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, 232-0024, Yokohama City, Japan", 
          "id": "http://www.grid.ac/institutes/grid.413045.7", 
          "name": [
            "Division of Cardiology, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, 232-0024, Yokohama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Matsuzawa", 
        "givenName": "Yasushi", 
        "id": "sg:person.0621771644.10", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0621771644.10"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Kumamoto University, Kumamoto, Japan", 
          "id": "http://www.grid.ac/institutes/grid.274841.c", 
          "name": [
            "Kumamoto University, Kumamoto, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ogawa", 
        "givenName": "Hisao", 
        "id": "sg:person.01301470144.06", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01301470144.06"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Division of Cardiology, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, 232-0024, Yokohama City, Japan", 
          "id": "http://www.grid.ac/institutes/grid.413045.7", 
          "name": [
            "Division of Cardiology, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, 232-0024, Yokohama City, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kimura", 
        "givenName": "Kazuo", 
        "id": "sg:person.016170645072.55", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016170645072.55"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Division of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, Tokyo, Japan", 
          "id": "http://www.grid.ac/institutes/grid.411898.d", 
          "name": [
            "Division of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tsuboi", 
        "givenName": "Nobuo", 
        "id": "sg:person.01205054154.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01205054154.42"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Division of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, Tokyo, Japan", 
          "id": "http://www.grid.ac/institutes/grid.411898.d", 
          "name": [
            "Division of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yokoo", 
        "givenName": "Takashi", 
        "id": "sg:person.01122657316.61", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01122657316.61"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Nephrology, Faculty of Medicine, Saitama Medical University, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410802.f", 
          "name": [
            "Department of Nephrology, Faculty of Medicine, Saitama Medical University, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Okada", 
        "givenName": "Hirokazu", 
        "id": "sg:person.0700630035.01", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0700630035.01"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Medical Science and Cardiorenal Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.268441.d", 
          "name": [
            "Department of Medical Science and Cardiorenal Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Konishi", 
        "givenName": "Masaaki", 
        "id": "sg:person.01205511734.72", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01205511734.72"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Emergency Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.268441.d", 
          "name": [
            "Department of Emergency Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kirigaya", 
        "givenName": "Jin", 
        "id": "sg:person.010043017333.72", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010043017333.72"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiology, Kanagawa Cardiovascular and Respiratory Center, Yokohama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.419708.3", 
          "name": [
            "Department of Cardiology, Kanagawa Cardiovascular and Respiratory Center, Yokohama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fukui", 
        "givenName": "Kazuki", 
        "id": "sg:person.0650622624.12", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0650622624.12"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Division of Cardiology, Fujisawa City Hospital, Fujisawa, Japan", 
          "id": "http://www.grid.ac/institutes/grid.415120.3", 
          "name": [
            "Division of Cardiology, Fujisawa City Hospital, Fujisawa, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tsukahara", 
        "givenName": "Kengo", 
        "id": "sg:person.0606320560.88", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0606320560.88"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Clinical Laboratory Medicine, Fujisawa City Hospital, Fujisawa, Japan", 
          "id": "http://www.grid.ac/institutes/grid.415120.3", 
          "name": [
            "Department of Clinical Laboratory Medicine, Fujisawa City Hospital, Fujisawa, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shimizu", 
        "givenName": "Hiroyuki", 
        "id": "sg:person.012233340733.22", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012233340733.22"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of General Medicine, Kanagawa Prefectural Ashigarakami Hospital, Ashigara, Japan", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Department of General Medicine, Kanagawa Prefectural Ashigarakami Hospital, Ashigara, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Iwabuchi", 
        "givenName": "Keisuke", 
        "id": "sg:person.013030721333.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013030721333.44"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Division of Cardiology, Kanagawa Prefectural Ashigarakami Hospital, Ashigara, Japan", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Division of Cardiology, Kanagawa Prefectural Ashigarakami Hospital, Ashigara, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yamada", 
        "givenName": "Yu", 
        "id": "sg:person.013626301733.05", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013626301733.05"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Division of Cardiology, Yokosuka City Hospital, Yokosuka, Japan", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Division of Cardiology, Yokosuka City Hospital, Yokosuka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Saka", 
        "givenName": "Kenichiro", 
        "id": "sg:person.014423662333.83", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014423662333.83"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Emergency Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.268441.d", 
          "name": [
            "Department of Emergency Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Takeuchi", 
        "givenName": "Ichiro", 
        "id": "sg:person.01211314122.49", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01211314122.49"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Nephrology and Hypertension, Kawasaki Medical School, Okayama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.415086.e", 
          "name": [
            "Department of Nephrology and Hypertension, Kawasaki Medical School, Okayama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kashihara", 
        "givenName": "Naoki", 
        "id": "sg:person.01035226441.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01035226441.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Medical Science and Cardiorenal Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.268441.d", 
          "name": [
            "Department of Medical Science and Cardiorenal Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tamura", 
        "givenName": "Kouichi", 
        "id": "sg:person.013174322507.05", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013174322507.05"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1186/s13054-020-02995-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1127864644", 
          "https://doi.org/10.1186/s13054-020-02995-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00134-020-06153-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1128447330", 
          "https://doi.org/10.1007/s00134-020-06153-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/s41440-020-00535-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1130238072", 
          "https://doi.org/10.1038/s41440-020-00535-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/s41581-020-00356-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1131761047", 
          "https://doi.org/10.1038/s41581-020-00356-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/s41586-020-2521-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1129059914", 
          "https://doi.org/10.1038/s41586-020-2521-4"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2022-06-03", 
    "datePublishedReg": "2022-06-03", 
    "description": "BackgroundIdentifying predictive factors for coronavirus disease 2019 (COVID-19) is crucial for risk stratification and intervention. Kidney dysfunction contributes to the severity of various infectious diseases. However, the association between on-admission kidney dysfunction and the clinical outcome in COVID-19 patients is unclear.MethodsThis study was a multicenter retrospective observational cohort study of COVID-19 patients, diagnosed by polymerase chain reaction. We retrospectively analyzed 500 COVID-19 patients (mean age: 51\u2009\u00b1\u200919\u00a0years) admitted to eight hospitals in Japan. Kidney dysfunction was defined as a reduced estimated glomerular filtration rate (<\u200960\u00a0mL/min/1.73 m2) or proteinuria (\u2265\u20091\u2009+\u2009dipstick proteinuria) on admission. The primary composite outcome included in-hospital death, extracorporeal membrane oxygenation, mechanical ventilation (invasive and noninvasive methods), and intensive care unit (ICU) admission.ResultsOverall, 171 (34.2%) patients presented with on-admission kidney dysfunction, and the primary composite outcome was observed in 60 (12.0%) patients. Patients with kidney dysfunction showed higher rates of in-hospital death (12.3 vs. 1.2%), mechanical ventilation (13.5 vs. 4.0%), and ICU admission (18.1 vs. 5.2%) than those without it. Categorical and multivariate regression analyses revealed that kidney dysfunction was substantially associated with the primary composite outcome. Thus, on-admission kidney dysfunction was common in COVID-19 patients. Furthermore, it correlated significantly and positively with COVID-19 severity and mortality.ConclusionsOn-admission kidney dysfunction was associated with disease severity and poor short-term prognosis in patients with COVID-19. Thus, on-admission kidney dysfunction has the potential to stratify risks in COVID-19 patients.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s10157-022-02240-x", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1117096", 
        "issn": [
          "1342-1751", 
          "1437-7799"
        ], 
        "name": "Clinical and Experimental Nephrology", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "10", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "26"
      }
    ], 
    "keywords": [
      "COVID-19 patients", 
      "primary composite outcome", 
      "kidney dysfunction", 
      "composite outcome", 
      "hospital death", 
      "clinical outcomes", 
      "mechanical ventilation", 
      "multicenter retrospective observational cohort study", 
      "intensive care unit admission", 
      "poor short-term prognosis", 
      "retrospective observational cohort study", 
      "care unit admission", 
      "observational cohort study", 
      "chronic kidney disease", 
      "glomerular filtration rate", 
      "short-term prognosis", 
      "COVID-19 severity", 
      "coronavirus disease 2019", 
      "COVID-19", 
      "unit admission", 
      "ICU admission", 
      "cohort study", 
      "membrane oxygenation", 
      "risk stratification", 
      "predictive factors", 
      "kidney disease", 
      "polymerase chain reaction", 
      "filtration rate", 
      "disease 2019", 
      "MethodsThis study", 
      "patients", 
      "dysfunction", 
      "disease severity", 
      "infectious diseases", 
      "admission", 
      "chain reaction", 
      "severity", 
      "outcomes", 
      "regression analysis", 
      "high rate", 
      "disease", 
      "ventilation", 
      "death", 
      "proteinuria", 
      "prognosis", 
      "ResultsOverall", 
      "hospital", 
      "mortality", 
      "oxygenation", 
      "intervention", 
      "risk", 
      "association", 
      "study", 
      "rate", 
      "stratification", 
      "factors", 
      "Japan", 
      "potential", 
      "analysis", 
      "reaction"
    ], 
    "name": "Chronic kidney disease and clinical outcomes in patients with COVID-19 in Japan", 
    "pagination": "974-981", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1148409148"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10157-022-02240-x"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "35657437"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10157-022-02240-x", 
      "https://app.dimensions.ai/details/publication/pub.1148409148"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-12-01T06:44", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221201/entities/gbq_results/article/article_947.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s10157-022-02240-x"
  }
]
 

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/s10157-022-02240-x'

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/s10157-022-02240-x'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10157-022-02240-x'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10157-022-02240-x'


 

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

344 TRIPLES      21 PREDICATES      103 URIs      90 LITERALS      20 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10157-022-02240-x schema:about N09b68c013e5c4fd495008ba23abcfdd5
2 N148473338af242cda5a06329c835bcb3
3 N27066844ddbc4e48b4f45054905eb91a
4 N3c3ff2f679a34310b272f3a073add596
5 N4175799d809d40dbb9845e7aea6c98b9
6 N49e1c81af2694921aef27719e8cbdc62
7 N818dbc324a294030a806490673fd6138
8 N8e4c3445bab048cbbdb303f415e53c97
9 Nafd4a4efcd164911a02578b378d08cc7
10 Nb561b721f0cf4ce0b5382e75227ac7df
11 Ne085a98a8533434598f2524f2b727744
12 Neb0420a7590d438cb702984cae6d9bfc
13 Nf8356d056f604835b2c0888fb18bfffa
14 anzsrc-for:11
15 anzsrc-for:1103
16 schema:author Nd4d12118f97645968a0f20ddd858b7e9
17 schema:citation sg:pub.10.1007/s00134-020-06153-9
18 sg:pub.10.1038/s41440-020-00535-8
19 sg:pub.10.1038/s41581-020-00356-5
20 sg:pub.10.1038/s41586-020-2521-4
21 sg:pub.10.1186/s13054-020-02995-3
22 schema:datePublished 2022-06-03
23 schema:datePublishedReg 2022-06-03
24 schema:description BackgroundIdentifying predictive factors for coronavirus disease 2019 (COVID-19) is crucial for risk stratification and intervention. Kidney dysfunction contributes to the severity of various infectious diseases. However, the association between on-admission kidney dysfunction and the clinical outcome in COVID-19 patients is unclear.MethodsThis study was a multicenter retrospective observational cohort study of COVID-19 patients, diagnosed by polymerase chain reaction. We retrospectively analyzed 500 COVID-19 patients (mean age: 51 ± 19 years) admitted to eight hospitals in Japan. Kidney dysfunction was defined as a reduced estimated glomerular filtration rate (< 60 mL/min/1.73 m2) or proteinuria (≥ 1 + dipstick proteinuria) on admission. The primary composite outcome included in-hospital death, extracorporeal membrane oxygenation, mechanical ventilation (invasive and noninvasive methods), and intensive care unit (ICU) admission.ResultsOverall, 171 (34.2%) patients presented with on-admission kidney dysfunction, and the primary composite outcome was observed in 60 (12.0%) patients. Patients with kidney dysfunction showed higher rates of in-hospital death (12.3 vs. 1.2%), mechanical ventilation (13.5 vs. 4.0%), and ICU admission (18.1 vs. 5.2%) than those without it. Categorical and multivariate regression analyses revealed that kidney dysfunction was substantially associated with the primary composite outcome. Thus, on-admission kidney dysfunction was common in COVID-19 patients. Furthermore, it correlated significantly and positively with COVID-19 severity and mortality.ConclusionsOn-admission kidney dysfunction was associated with disease severity and poor short-term prognosis in patients with COVID-19. Thus, on-admission kidney dysfunction has the potential to stratify risks in COVID-19 patients.
25 schema:genre article
26 schema:isAccessibleForFree true
27 schema:isPartOf N2308246a1245446ba4c893aae1dfc863
28 N36bbac1da07b463092328fdce716f656
29 sg:journal.1117096
30 schema:keywords COVID-19
31 COVID-19 patients
32 COVID-19 severity
33 ICU admission
34 Japan
35 MethodsThis study
36 ResultsOverall
37 admission
38 analysis
39 association
40 care unit admission
41 chain reaction
42 chronic kidney disease
43 clinical outcomes
44 cohort study
45 composite outcome
46 coronavirus disease 2019
47 death
48 disease
49 disease 2019
50 disease severity
51 dysfunction
52 factors
53 filtration rate
54 glomerular filtration rate
55 high rate
56 hospital
57 hospital death
58 infectious diseases
59 intensive care unit admission
60 intervention
61 kidney disease
62 kidney dysfunction
63 mechanical ventilation
64 membrane oxygenation
65 mortality
66 multicenter retrospective observational cohort study
67 observational cohort study
68 outcomes
69 oxygenation
70 patients
71 polymerase chain reaction
72 poor short-term prognosis
73 potential
74 predictive factors
75 primary composite outcome
76 prognosis
77 proteinuria
78 rate
79 reaction
80 regression analysis
81 retrospective observational cohort study
82 risk
83 risk stratification
84 severity
85 short-term prognosis
86 stratification
87 study
88 unit admission
89 ventilation
90 schema:name Chronic kidney disease and clinical outcomes in patients with COVID-19 in Japan
91 schema:pagination 974-981
92 schema:productId N175feb12b2ec4fe29b198d1949116ca2
93 Na2cfe72ce1e74b07bbe98e3a96483a65
94 Nf96e0c049fd94664ae6b311f543498f8
95 schema:sameAs https://app.dimensions.ai/details/publication/pub.1148409148
96 https://doi.org/10.1007/s10157-022-02240-x
97 schema:sdDatePublished 2022-12-01T06:44
98 schema:sdLicense https://scigraph.springernature.com/explorer/license/
99 schema:sdPublisher N2f479ecade9e4993a6a358cb78c3a4fb
100 schema:url https://doi.org/10.1007/s10157-022-02240-x
101 sgo:license sg:explorer/license/
102 sgo:sdDataset articles
103 rdf:type schema:ScholarlyArticle
104 N068a778779c34a50a96f5bb02174372a rdf:first sg:person.0606320560.88
105 rdf:rest N9056d20c14b4460da5187c8863464d96
106 N09b68c013e5c4fd495008ba23abcfdd5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
107 schema:name Risk Factors
108 rdf:type schema:DefinedTerm
109 N0ae04417731f4aacac51acb5a3178f98 rdf:first sg:person.01301470144.06
110 rdf:rest N63fcc384bd0748c58e2a83fef1fa676e
111 N0b71f377437a4da397b4851edcfdfa54 rdf:first sg:person.01035226441.27
112 rdf:rest Nd7bc31d68d084d4995ede88fde825bda
113 N148473338af242cda5a06329c835bcb3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
114 schema:name Middle Aged
115 rdf:type schema:DefinedTerm
116 N175feb12b2ec4fe29b198d1949116ca2 schema:name pubmed_id
117 schema:value 35657437
118 rdf:type schema:PropertyValue
119 N2308246a1245446ba4c893aae1dfc863 schema:volumeNumber 26
120 rdf:type schema:PublicationVolume
121 N27066844ddbc4e48b4f45054905eb91a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
122 schema:name Hospital Mortality
123 rdf:type schema:DefinedTerm
124 N2f479ecade9e4993a6a358cb78c3a4fb schema:name Springer Nature - SN SciGraph project
125 rdf:type schema:Organization
126 N36bbac1da07b463092328fdce716f656 schema:issueNumber 10
127 rdf:type schema:PublicationIssue
128 N3c3ff2f679a34310b272f3a073add596 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
129 schema:name Renal Insufficiency, Chronic
130 rdf:type schema:DefinedTerm
131 N4175799d809d40dbb9845e7aea6c98b9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
132 schema:name Retrospective Studies
133 rdf:type schema:DefinedTerm
134 N4609373fb62249e49061f4697a804a9d rdf:first sg:person.010043017333.72
135 rdf:rest N573a86ca848547d4bb48149b299ec95f
136 N49e1c81af2694921aef27719e8cbdc62 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
137 schema:name Adult
138 rdf:type schema:DefinedTerm
139 N573a86ca848547d4bb48149b299ec95f rdf:first sg:person.0650622624.12
140 rdf:rest N068a778779c34a50a96f5bb02174372a
141 N63fcc384bd0748c58e2a83fef1fa676e rdf:first sg:person.016170645072.55
142 rdf:rest N6aa902f842e9408eb22fbf784a84a809
143 N67c743152ce84740a6c5502c28551d13 rdf:first sg:person.01211314122.49
144 rdf:rest N0b71f377437a4da397b4851edcfdfa54
145 N6aa902f842e9408eb22fbf784a84a809 rdf:first sg:person.01205054154.42
146 rdf:rest Nfa8174611b2945c6a5f098d5d8dd526e
147 N6fafebd0ad9941649aa77d4ab14f322c rdf:first sg:person.01205511734.72
148 rdf:rest N4609373fb62249e49061f4697a804a9d
149 N791f0bdc48fe4d4caf84bff1cb632e0f rdf:first sg:person.013626301733.05
150 rdf:rest Nbd3e1b58de2640009f9833868d440ffe
151 N818dbc324a294030a806490673fd6138 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
152 schema:name Humans
153 rdf:type schema:DefinedTerm
154 N8e4c3445bab048cbbdb303f415e53c97 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
155 schema:name SARS-CoV-2
156 rdf:type schema:DefinedTerm
157 N9056d20c14b4460da5187c8863464d96 rdf:first sg:person.012233340733.22
158 rdf:rest Nd56b5e6469564040ac9351369397d6fc
159 N9dda3c11fabb4125adfc1f582a27cbba rdf:first sg:person.0700630035.01
160 rdf:rest N6fafebd0ad9941649aa77d4ab14f322c
161 Na2cfe72ce1e74b07bbe98e3a96483a65 schema:name dimensions_id
162 schema:value pub.1148409148
163 rdf:type schema:PropertyValue
164 Nafd4a4efcd164911a02578b378d08cc7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
165 schema:name Proteinuria
166 rdf:type schema:DefinedTerm
167 Nb561b721f0cf4ce0b5382e75227ac7df schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
168 schema:name Aged
169 rdf:type schema:DefinedTerm
170 Nbd3e1b58de2640009f9833868d440ffe rdf:first sg:person.014423662333.83
171 rdf:rest N67c743152ce84740a6c5502c28551d13
172 Nd4d12118f97645968a0f20ddd858b7e9 rdf:first sg:person.012341501403.01
173 rdf:rest Nd618738276dd46e5b2e9937f1cac1c61
174 Nd56b5e6469564040ac9351369397d6fc rdf:first sg:person.013030721333.44
175 rdf:rest N791f0bdc48fe4d4caf84bff1cb632e0f
176 Nd618738276dd46e5b2e9937f1cac1c61 rdf:first sg:person.0621771644.10
177 rdf:rest N0ae04417731f4aacac51acb5a3178f98
178 Nd7bc31d68d084d4995ede88fde825bda rdf:first sg:person.013174322507.05
179 rdf:rest rdf:nil
180 Ne085a98a8533434598f2524f2b727744 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
181 schema:name COVID-19
182 rdf:type schema:DefinedTerm
183 Neb0420a7590d438cb702984cae6d9bfc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
184 schema:name Intensive Care Units
185 rdf:type schema:DefinedTerm
186 Nf8356d056f604835b2c0888fb18bfffa schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
187 schema:name Japan
188 rdf:type schema:DefinedTerm
189 Nf96e0c049fd94664ae6b311f543498f8 schema:name doi
190 schema:value 10.1007/s10157-022-02240-x
191 rdf:type schema:PropertyValue
192 Nfa8174611b2945c6a5f098d5d8dd526e rdf:first sg:person.01122657316.61
193 rdf:rest N9dda3c11fabb4125adfc1f582a27cbba
194 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
195 schema:name Medical and Health Sciences
196 rdf:type schema:DefinedTerm
197 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
198 schema:name Clinical Sciences
199 rdf:type schema:DefinedTerm
200 sg:journal.1117096 schema:issn 1342-1751
201 1437-7799
202 schema:name Clinical and Experimental Nephrology
203 schema:publisher Springer Nature
204 rdf:type schema:Periodical
205 sg:person.010043017333.72 schema:affiliation grid-institutes:grid.268441.d
206 schema:familyName Kirigaya
207 schema:givenName Jin
208 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010043017333.72
209 rdf:type schema:Person
210 sg:person.01035226441.27 schema:affiliation grid-institutes:grid.415086.e
211 schema:familyName Kashihara
212 schema:givenName Naoki
213 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01035226441.27
214 rdf:type schema:Person
215 sg:person.01122657316.61 schema:affiliation grid-institutes:grid.411898.d
216 schema:familyName Yokoo
217 schema:givenName Takashi
218 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01122657316.61
219 rdf:type schema:Person
220 sg:person.01205054154.42 schema:affiliation grid-institutes:grid.411898.d
221 schema:familyName Tsuboi
222 schema:givenName Nobuo
223 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01205054154.42
224 rdf:type schema:Person
225 sg:person.01205511734.72 schema:affiliation grid-institutes:grid.268441.d
226 schema:familyName Konishi
227 schema:givenName Masaaki
228 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01205511734.72
229 rdf:type schema:Person
230 sg:person.01211314122.49 schema:affiliation grid-institutes:grid.268441.d
231 schema:familyName Takeuchi
232 schema:givenName Ichiro
233 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01211314122.49
234 rdf:type schema:Person
235 sg:person.012233340733.22 schema:affiliation grid-institutes:grid.415120.3
236 schema:familyName Shimizu
237 schema:givenName Hiroyuki
238 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012233340733.22
239 rdf:type schema:Person
240 sg:person.012341501403.01 schema:affiliation grid-institutes:grid.413045.7
241 schema:familyName Sato
242 schema:givenName Ryosuke
243 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012341501403.01
244 rdf:type schema:Person
245 sg:person.01301470144.06 schema:affiliation grid-institutes:grid.274841.c
246 schema:familyName Ogawa
247 schema:givenName Hisao
248 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01301470144.06
249 rdf:type schema:Person
250 sg:person.013030721333.44 schema:affiliation grid-institutes:None
251 schema:familyName Iwabuchi
252 schema:givenName Keisuke
253 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013030721333.44
254 rdf:type schema:Person
255 sg:person.013174322507.05 schema:affiliation grid-institutes:grid.268441.d
256 schema:familyName Tamura
257 schema:givenName Kouichi
258 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013174322507.05
259 rdf:type schema:Person
260 sg:person.013626301733.05 schema:affiliation grid-institutes:None
261 schema:familyName Yamada
262 schema:givenName Yu
263 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013626301733.05
264 rdf:type schema:Person
265 sg:person.014423662333.83 schema:affiliation grid-institutes:None
266 schema:familyName Saka
267 schema:givenName Kenichiro
268 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014423662333.83
269 rdf:type schema:Person
270 sg:person.016170645072.55 schema:affiliation grid-institutes:grid.413045.7
271 schema:familyName Kimura
272 schema:givenName Kazuo
273 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016170645072.55
274 rdf:type schema:Person
275 sg:person.0606320560.88 schema:affiliation grid-institutes:grid.415120.3
276 schema:familyName Tsukahara
277 schema:givenName Kengo
278 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0606320560.88
279 rdf:type schema:Person
280 sg:person.0621771644.10 schema:affiliation grid-institutes:grid.413045.7
281 schema:familyName Matsuzawa
282 schema:givenName Yasushi
283 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0621771644.10
284 rdf:type schema:Person
285 sg:person.0650622624.12 schema:affiliation grid-institutes:grid.419708.3
286 schema:familyName Fukui
287 schema:givenName Kazuki
288 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0650622624.12
289 rdf:type schema:Person
290 sg:person.0700630035.01 schema:affiliation grid-institutes:grid.410802.f
291 schema:familyName Okada
292 schema:givenName Hirokazu
293 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0700630035.01
294 rdf:type schema:Person
295 sg:pub.10.1007/s00134-020-06153-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1128447330
296 https://doi.org/10.1007/s00134-020-06153-9
297 rdf:type schema:CreativeWork
298 sg:pub.10.1038/s41440-020-00535-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1130238072
299 https://doi.org/10.1038/s41440-020-00535-8
300 rdf:type schema:CreativeWork
301 sg:pub.10.1038/s41581-020-00356-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1131761047
302 https://doi.org/10.1038/s41581-020-00356-5
303 rdf:type schema:CreativeWork
304 sg:pub.10.1038/s41586-020-2521-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1129059914
305 https://doi.org/10.1038/s41586-020-2521-4
306 rdf:type schema:CreativeWork
307 sg:pub.10.1186/s13054-020-02995-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1127864644
308 https://doi.org/10.1186/s13054-020-02995-3
309 rdf:type schema:CreativeWork
310 grid-institutes:None schema:alternateName Department of General Medicine, Kanagawa Prefectural Ashigarakami Hospital, Ashigara, Japan
311 Division of Cardiology, Kanagawa Prefectural Ashigarakami Hospital, Ashigara, Japan
312 Division of Cardiology, Yokosuka City Hospital, Yokosuka, Japan
313 schema:name Department of General Medicine, Kanagawa Prefectural Ashigarakami Hospital, Ashigara, Japan
314 Division of Cardiology, Kanagawa Prefectural Ashigarakami Hospital, Ashigara, Japan
315 Division of Cardiology, Yokosuka City Hospital, Yokosuka, Japan
316 rdf:type schema:Organization
317 grid-institutes:grid.268441.d schema:alternateName Department of Emergency Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan
318 Department of Medical Science and Cardiorenal Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan
319 schema:name Department of Emergency Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan
320 Department of Medical Science and Cardiorenal Medicine, Yokohama City University Graduate School of Medicine, Yokohama, Japan
321 rdf:type schema:Organization
322 grid-institutes:grid.274841.c schema:alternateName Kumamoto University, Kumamoto, Japan
323 schema:name Kumamoto University, Kumamoto, Japan
324 rdf:type schema:Organization
325 grid-institutes:grid.410802.f schema:alternateName Department of Nephrology, Faculty of Medicine, Saitama Medical University, Saitama, Japan
326 schema:name Department of Nephrology, Faculty of Medicine, Saitama Medical University, Saitama, Japan
327 rdf:type schema:Organization
328 grid-institutes:grid.411898.d schema:alternateName Division of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, Tokyo, Japan
329 schema:name Division of Nephrology and Hypertension, Department of Internal Medicine, The Jikei University School of Medicine, Tokyo, Japan
330 rdf:type schema:Organization
331 grid-institutes:grid.413045.7 schema:alternateName Division of Cardiology, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, 232-0024, Yokohama City, Japan
332 schema:name Division of Cardiology, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, 232-0024, Yokohama City, Japan
333 rdf:type schema:Organization
334 grid-institutes:grid.415086.e schema:alternateName Department of Nephrology and Hypertension, Kawasaki Medical School, Okayama, Japan
335 schema:name Department of Nephrology and Hypertension, Kawasaki Medical School, Okayama, Japan
336 rdf:type schema:Organization
337 grid-institutes:grid.415120.3 schema:alternateName Department of Clinical Laboratory Medicine, Fujisawa City Hospital, Fujisawa, Japan
338 Division of Cardiology, Fujisawa City Hospital, Fujisawa, Japan
339 schema:name Department of Clinical Laboratory Medicine, Fujisawa City Hospital, Fujisawa, Japan
340 Division of Cardiology, Fujisawa City Hospital, Fujisawa, Japan
341 rdf:type schema:Organization
342 grid-institutes:grid.419708.3 schema:alternateName Department of Cardiology, Kanagawa Cardiovascular and Respiratory Center, Yokohama, Japan
343 schema:name Department of Cardiology, Kanagawa Cardiovascular and Respiratory Center, Yokohama, Japan
344 rdf:type schema:Organization
 




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


...