Serveur d'exploration sur la grippe en Allemagne

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[Influenza and community acquired pneumonia in German primary care].

Identifieur interne : 000079 ( Main/Exploration ); précédent : 000078; suivant : 000080

[Influenza and community acquired pneumonia in German primary care].

Auteurs : Aryna Zanuzdana [Allemagne] ; Karla Köpke [Allemagne] ; Walter Haas [Allemagne]

Source :

RBID : pubmed:27695937

Descripteurs français

English descriptors

Abstract

Influenza and community-acquired pneumonia (CAP) impose a considerable annual burden on the German primary care system. Yet there is a lack of epidemiological data from the country's outpatient sector on groups at risk as well as on the complications of these diseases.The Robert Koch Institute (RKI) initiated the study to identify population groups at increased risk for influenza or CAP as well as related comorbidities and sequelae. We present the methodology of the study and the descriptive analysis of the patients.ICD-10-based data was collected in 89 primary health care practices between January 2012 and April 2015 using a data extraction tool developed on behalf of the RKI. Case-based anonymized information was recorded for all patients in whom influenza, CAP or other acute respiratory infections (ARI) were diagnosed. For each patient information on all diagnoses including the date were retrospectively and prospectively collected (each for six months) as well as age, sex and influenza vaccination.Data on 156,803 patients with ARI was collected, of them 7909 patients with influenza (within influenza waves) and 8528 patients with CAP diagnoses. Influenza diagnoses showed a strong seasonal pattern and captured annual influenza waves in Germany. Of the influenza cases 1.6 % had a following diagnosis of CAP within 30 days. Age-specific prevalence of chronic diseases such as asthma and diabetes was significantly higher in the study population as compared to the German population.The developed tool delivers in a standardized fashion ICD-10-coded epidemiological data on population-based burden of influenza and CAP in Germany. As the descriptive analysis showed, the collected dataset is a reliable and solid basis for the further investigations of the study questions.

DOI: 10.1007/s00103-016-2442-4
PubMed: 27695937


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<div type="abstract" xml:lang="en">Influenza and community-acquired pneumonia (CAP) impose a considerable annual burden on the German primary care system. Yet there is a lack of epidemiological data from the country's outpatient sector on groups at risk as well as on the complications of these diseases.The Robert Koch Institute (RKI) initiated the study to identify population groups at increased risk for influenza or CAP as well as related comorbidities and sequelae. We present the methodology of the study and the descriptive analysis of the patients.ICD-10-based data was collected in 89 primary health care practices between January 2012 and April 2015 using a data extraction tool developed on behalf of the RKI. Case-based anonymized information was recorded for all patients in whom influenza, CAP or other acute respiratory infections (ARI) were diagnosed. For each patient information on all diagnoses including the date were retrospectively and prospectively collected (each for six months) as well as age, sex and influenza vaccination.Data on 156,803 patients with ARI was collected, of them 7909 patients with influenza (within influenza waves) and 8528 patients with CAP diagnoses. Influenza diagnoses showed a strong seasonal pattern and captured annual influenza waves in Germany. Of the influenza cases 1.6 % had a following diagnosis of CAP within 30 days. Age-specific prevalence of chronic diseases such as asthma and diabetes was significantly higher in the study population as compared to the German population.The developed tool delivers in a standardized fashion ICD-10-coded epidemiological data on population-based burden of influenza and CAP in Germany. As the descriptive analysis showed, the collected dataset is a reliable and solid basis for the further investigations of the study questions.</div>
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<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline">
<Year>2017</Year>
<Month>5</Month>
<Day>4</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez">
<Year>2016</Year>
<Month>10</Month>
<Day>4</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList>
<ArticleId IdType="pubmed">27695937</ArticleId>
<ArticleId IdType="doi">10.1007/s00103-016-2442-4</ArticleId>
<ArticleId IdType="pii">10.1007/s00103-016-2442-4</ArticleId>
</ArticleIdList>
</PubmedData>
</pubmed>
<affiliations>
<list>
<country>
<li>Allemagne</li>
</country>
<region>
<li>Berlin</li>
</region>
<settlement>
<li>Berlin</li>
</settlement>
</list>
<tree>
<country name="Allemagne">
<region name="Berlin">
<name sortKey="Zanuzdana, Aryna" sort="Zanuzdana, Aryna" uniqKey="Zanuzdana A" first="Aryna" last="Zanuzdana">Aryna Zanuzdana</name>
</region>
<name sortKey="Haas, Walter" sort="Haas, Walter" uniqKey="Haas W" first="Walter" last="Haas">Walter Haas</name>
<name sortKey="Kopke, Karla" sort="Kopke, Karla" uniqKey="Kopke K" first="Karla" last="Köpke">Karla Köpke</name>
</country>
</tree>
</affiliations>
</record>

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