ID

41445

Descripción

This version of the GECCO dataset is mainly based on https://art-decor.org/art-decor/decor-datasets--covid19f- on the "final" version published mid to end September 2020. A few items implicated by comments/descriptions of items on art-decor have been added: "Datum der letzten Impfung" (date of last vaccination for all listed vaccinations), "Schweregrad" (Severity of Kidney Diseases), "Ort" (Location of vacation in the last 14 days), "Befund bildgebender Verfahren im Rahmen von COVID-19" added separately for all types of imaging procedures listed, "Symptom Schweregrad" (Severity of Symptoms) for each symptom listed, and an "NCT-/EudraCT-Nummer" item for Study participation. Official German text from http://cocos.team/datasets.html: Zur Bewältigung der aktuellen Pandemie und der damit einhergehenden Behandlung von Patienten fördert das Bundesministerium für Bildung und Forschung (BMBF) ein nationales Netzwerk der Universitätsmedizin im Kampf gegen COVID-19. Unter anderem soll das Netzwerk die Daten der behandelten COVID-19 Patienten systematisch erfassen und bündeln. Die Forschenden sollen die Behandlung der COVID-19-Patienten standardisiert erheben, verfolgen und analysieren. Die hohe Bedrohungslage hat zu intensiver wissenschaftlicher Aktivität zu COVID-19 geführt, wozu zahlreiche regionale, nationale und internationale epidemiologische Erhebungen und Registerstudien zählen. Der Konsensusdatensatz gibt der Wissenschaft um COVID-19 eine gemeinsame Sprache und Arbeitsgrundlage. Inofficial translation: In order to cope with the current pandemic and the associated treatment of patients, the Federal Ministry of Education and Research (BMBF) is funding a national network of university medicine in the fight against COVID-19. Among other things, the network will systematically collect and bundle the data of the treated COVID-19 patients. The researchers are to collect, track and analyze the treatment of COVID-19 patients in a standardized way. The high threat level has led to intensive scientific activity on COVID-19, including numerous regional, national and international epidemiological surveys and register studies. The consensus data set provides a common language and working basis for the science around COVID-19. Additional source: https://simplifier.net/ForschungsnetzCovid-19/ResearchDatasetGECCO/~overview Not yet integrated: Items for "Data Absent Reason", "Certainty of Presence", "Uncertainty of Presence", and "Certainty of absence"; "therapeutic intention", "Medication Statement Status", "EventStatus"; longer versions of the ValueSets published separately from the variables in art-decor.

Link

https://art-decor.org/art-decor/decor-datasets--covid19f-

Palabras clave

  1. 29/9/20 29/9/20 - Sarah Riepenhausen
  2. 29/9/20 29/9/20 - Sarah Riepenhausen
  3. 9/10/20 9/10/20 -
  4. 28/10/20 28/10/20 -
  5. 13/1/21 13/1/21 - Sarah Riepenhausen
  6. 3/2/21 3/2/21 - Sarah Riepenhausen
  7. 3/2/21 3/2/21 - Sarah Riepenhausen
  8. 25/8/21 25/8/21 - Sarah Riepenhausen
  9. 2/9/21 2/9/21 - Sarah Riepenhausen
  10. 6/9/21 6/9/21 - Sarah Riepenhausen
  11. 5/1/23 5/1/23 - Sarah Riepenhausen
Titular de derechos de autor

Nationales Forschungsnetzwerk der Universitätsmedizin zu Covid-19

Subido en

9 de octubre de 2020

DOI

Para solicitar uno, por favor iniciar sesión.

Licencia

Creative Commons BY 4.0

Comentarios del modelo :

Puede comentar sobre el modelo de datos aquí. A través de las burbujas de diálogo en los grupos de elementos y elementos, puede agregar comentarios específicos.

Comentarios de grupo de elementos para :

Comentarios del elemento para :

Para descargar modelos de datos, debe haber iniciado sesión. Por favor iniciar sesión o Registrate gratis.

GECCO - German Corona Consensus - Covid-19 Research-Dataset

Vitalparameter

Vitalparameter
Descripción

Vitalparameter

Alias
UMLS CUI-1
C0518766
Kohlendioxidpartialdruck
Descripción

Kommentar: FHIR-Mapping: Observation Versionsdatum: 2020-04-08

Tipo de datos

float

Unidades de medida
  • mm[Hg]
Alias
UMLS CUI [1]
C1822070
LOINC[1]
2019-8
LOINC[2]
11557-6
LOINC[3]
2020-6
mm[Hg]
Sauerstoffpartialdruck
Descripción

Kommentar: FHIR-Mapping: Observation Versionsdatum: 2020-04-08

Tipo de datos

float

Unidades de medida
  • mm[Hg]
Alias
UMLS CUI [1]
C0391840
LOINC[1]
2703-7
LOINC[2]
11556-8
LOINC[3]
2704-5
mm[Hg]
FiO2
Descripción

Kommentar: FHIR-Mapping: Observation Operationalisierung: Synonym: fraction of inspired oxygen inspiratorische Sauerstofffraktion Versionsdatum: 2020-04-08

Tipo de datos

float

Unidades de medida
  • %
Alias
UMLS CUI [1]
C0428167
SNOMED CT[1]
250774007
LOINC[1]
3150-0
%
pH-Wert
Descripción

Kommentar: FHIR-Mapping: Observation Versionsdatum: 2020-04-08

Tipo de datos

float

Unidades de medida
  • [pH]
Alias
UMLS CUI [1]
C0202165
LOINC[1]
2753-2
LOINC[2]
2746-6
LOINC[3]
2745-8
LOINC[4]
2744-1
LOINC[5]
19213-8
LOINC[6]
11558-4
[pH]
Sepsis-related organ failure assessment score
Descripción

Kommentar: FHIR-Mapping: Observation Versionsdatum: 2020-04-08

Tipo de datos

integer

Alias
UMLS CUI [1]
C3494459
Atemfrequenz
Descripción

Kommentar: FHIR-Mapping: Observation Versionsdatum: 2020-04-08

Tipo de datos

float

Unidades de medida
  • {breaths}/min
Alias
UMLS CUI [1]
C0231832
SNOMED CT[1]
86290005
LOINC[1]
9279-1
{breaths}/min
Blutdruck diastolisch
Descripción

Kommentar: FHIR-Mapping: Observation Versionsdatum: 2020-04-08

Tipo de datos

float

Unidades de medida
  • mm[Hg]
Alias
UMLS CUI [1]
C0428883
SNOMED CT[1]
271650006
LOINC[1]
8462-4
mm[Hg]
Blutdruck systolisch
Descripción

Kommentar: FHIR-Mapping: Observation Versionsdatum: 2020-04-08

Tipo de datos

float

Unidades de medida
  • mm[Hg]
Alias
UMLS CUI [1]
C0871470
SNOMED CT[1]
271649006
LOINC[1]
8480-6
mm[Hg]
Herzfrequenz
Descripción

Kommentar: FHIR-Mapping: Observation Versionsdatum: 2020-04-08

Tipo de datos

float

Unidades de medida
  • {beats}/min
Alias
UMLS CUI [1]
C0018810
SNOMED CT[1]
364075005
LOINC[1]
8867-4
{beats}/min
Körpertemperatur
Descripción

Kommentar: FHIR-Mapping: Observation Versionsdatum: 2020-04-08

Tipo de datos

float

Unidades de medida
  • Cel
Alias
UMLS CUI [1]
C0005903
SNOMED CT[1]
386725007
LOINC[1]
8310-5
Cel
Periphere Sauerstoffsättigung
Descripción

Kommentar: FHIR-Mapping: Observation Units: Versionsdatum: 2020-04-08

Tipo de datos

float

Unidades de medida
  • %
Alias
UMLS CUI [1]
C0428179
SNOMED CT[1]
431314004
LOINC[1]
2708-6
LOINC[2]
59408-5
LOINC[3]
20564-1
%

Similar models

Vitalparameter

Name
Tipo
Description | Question | Decode (Coded Value)
Tipo de datos
Alias
Item Group
Vitalparameter
C0518766 (UMLS CUI-1)
PaCO2
Item
Kohlendioxidpartialdruck
float
C1822070 (UMLS CUI [1])
2019-8 (LOINC[1])
11557-6 (LOINC[2])
2020-6 (LOINC[3])
PaO2
Item
Sauerstoffpartialdruck
float
C0391840 (UMLS CUI [1])
2703-7 (LOINC[1])
11556-8 (LOINC[2])
2704-5 (LOINC[3])
FiO2
Item
FiO2
float
C0428167 (UMLS CUI [1])
250774007 (SNOMED CT[1])
3150-0 (LOINC[1])
pH-Wert
Item
pH-Wert
float
C0202165 (UMLS CUI [1])
2753-2 (LOINC[1])
2746-6 (LOINC[2])
2745-8 (LOINC[3])
2744-1 (LOINC[4])
19213-8 (LOINC[5])
11558-4 (LOINC[6])
SOFA-Score
Item
Sepsis-related organ failure assessment score
integer
C3494459 (UMLS CUI [1])
Atemfrequenz
Item
Atemfrequenz
float
C0231832 (UMLS CUI [1])
86290005 (SNOMED CT[1])
9279-1 (LOINC[1])
Blutdruck diastolisch
Item
Blutdruck diastolisch
float
C0428883 (UMLS CUI [1])
271650006 (SNOMED CT[1])
8462-4 (LOINC[1])
Blutdruck systolisch
Item
Blutdruck systolisch
float
C0871470 (UMLS CUI [1])
271649006 (SNOMED CT[1])
8480-6 (LOINC[1])
Herzfrequenz
Item
Herzfrequenz
float
C0018810 (UMLS CUI [1])
364075005 (SNOMED CT[1])
8867-4 (LOINC[1])
Körpertemperatur
Item
Körpertemperatur
float
C0005903 (UMLS CUI [1])
386725007 (SNOMED CT[1])
8310-5 (LOINC[1])
Periphere Sauerstoffsättigung
Item
Periphere Sauerstoffsättigung
float
C0428179 (UMLS CUI [1])
431314004 (SNOMED CT[1])
2708-6 (LOINC[1])
59408-5 (LOINC[2])
20564-1 (LOINC[3])

Utilice este formulario para comentarios, preguntas y sugerencias.

Los campos marcados con * son obligatorios.

Do you need help on how to use the search function? Please watch the corresponding tutorial video for more details and learn how to use the search function most efficiently.

Watch Tutorial