Serveur d'exploration sur SGML

Attention, ce site est en cours de développement !
Attention, site généré par des moyens informatiques à partir de corpus bruts.
Les informations ne sont donc pas validées.

Association Patterns in Open Data to Explore Ciprofloxacin Adverse Events

Identifieur interne : 000018 ( Main/Exploration ); précédent : 000017; suivant : 000019

Association Patterns in Open Data to Explore Ciprofloxacin Adverse Events

Auteurs : P. Yildirim

Source :

RBID : PMC:4704041

Abstract

SummaryBackground

Ciprofloxacin is one of the main drugs to treat bacterial infections. Bacterial infections can lead to high morbidity, mortality, and costs of treatment in the world. In this study, an analysis was conducted using the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) database on the adverse events of ciprofloxacin.

Objectives

The aim of this study was to explore unknown associations among the adverse events of ciprofloxacin, patient demographics and adverse event outcomes.

Methods

A search of FDA AERS reports was performed and some statistics was highlighted. The most frequent adverse events and event outcomes of ciprofloxacin were listed, age and gender specific distribution of adverse events are reported, then the apriori algorithm was applied to the dataset to obtain some association rules and objective measures were used to select interesting ones. Furthermore, the results were compared against classical data mining algorithms and discussed.

Results

The search resulted in 6 531 reports. The reports included within the dataset consist of 3 585 (55.8%) female and 2 884 (44.1%) male patients. The mean age of patients is 54.59 years. Preschool child, middle aged and aged groups have most adverse events reports in all groups. Pyrexia has the highest frequency with ciprofloxacin, followed by pain, diarrhoea, and anxiety in this order and the most frequent adverse event outcome is hospitalization. Age and gender based differences in the events in patients were found. In addition, some of the interesting associations obtained from the Apriori algorithm include not only psychiatric disorders but specifically their manifestation in specific gender groups.

Conclusions

The FDA AERS offers an important data resource to identify new or unknown adverse events of drugs in the biomedical domain. The results that were obtained in this study can provide valuable information for medical researchers and decision makers at the pharmaceutical research field.


Url:
DOI: 10.4338/ACI-2015-06-RA-0076
PubMed: 26763627
PubMed Central: 4704041


Affiliations:


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


Le document en format XML

<record>
<TEI>
<teiHeader>
<fileDesc>
<titleStmt>
<title xml:lang="en">Association Patterns in Open Data to Explore Ciprofloxacin Adverse Events</title>
<author>
<name sortKey="Yildirim, P" sort="Yildirim, P" uniqKey="Yildirim P" first="P." last="Yildirim">P. Yildirim</name>
</author>
</titleStmt>
<publicationStmt>
<idno type="wicri:source">PMC</idno>
<idno type="pmid">26763627</idno>
<idno type="pmc">4704041</idno>
<idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4704041</idno>
<idno type="RBID">PMC:4704041</idno>
<idno type="doi">10.4338/ACI-2015-06-RA-0076</idno>
<date when="2015">2015</date>
<idno type="wicri:Area/Pmc/Corpus">000000</idno>
<idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000000</idno>
<idno type="wicri:Area/Pmc/Curation">000000</idno>
<idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000000</idno>
<idno type="wicri:Area/Pmc/Checkpoint">000016</idno>
<idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">000016</idno>
<idno type="wicri:Area/Ncbi/Merge">000121</idno>
<idno type="wicri:Area/Ncbi/Curation">000121</idno>
<idno type="wicri:Area/Ncbi/Checkpoint">000121</idno>
<idno type="wicri:Area/Main/Merge">000018</idno>
<idno type="wicri:Area/Main/Curation">000018</idno>
<idno type="wicri:Area/Main/Exploration">000018</idno>
</publicationStmt>
<sourceDesc>
<biblStruct>
<analytic>
<title xml:lang="en" level="a" type="main">Association Patterns in Open Data to Explore Ciprofloxacin Adverse Events</title>
<author>
<name sortKey="Yildirim, P" sort="Yildirim, P" uniqKey="Yildirim P" first="P." last="Yildirim">P. Yildirim</name>
</author>
</analytic>
<series>
<title level="j">Applied Clinical Informatics</title>
<idno type="eISSN">1869-0327</idno>
<imprint>
<date when="2015">2015</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc>
<textClass></textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">
<title>Summary</title>
<sec>
<title>Background</title>
<p>Ciprofloxacin is one of the main drugs to treat bacterial infections. Bacterial infections can lead to high morbidity, mortality, and costs of treatment in the world. In this study, an analysis was conducted using the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) database on the adverse events of ciprofloxacin.</p>
</sec>
<sec>
<title>Objectives</title>
<p>The aim of this study was to explore unknown associations among the adverse events of ciprofloxacin, patient demographics and adverse event outcomes.</p>
</sec>
<sec>
<title>Methods</title>
<p>A search of FDA AERS reports was performed and some statistics was highlighted. The most frequent adverse events and event outcomes of ciprofloxacin were listed, age and gender specific distribution of adverse events are reported, then the apriori algorithm was applied to the dataset to obtain some association rules and objective measures were used to select interesting ones. Furthermore, the results were compared against classical data mining algorithms and discussed.</p>
</sec>
<sec>
<title>Results</title>
<p>The search resulted in 6 531 reports. The reports included within the dataset consist of 3 585 (55.8%) female and 2 884 (44.1%) male patients. The mean age of patients is 54.59 years. Preschool child, middle aged and aged groups have most adverse events reports in all groups. Pyrexia has the highest frequency with ciprofloxacin, followed by pain, diarrhoea, and anxiety in this order and the most frequent adverse event outcome is hospitalization. Age and gender based differences in the events in patients were found. In addition, some of the interesting associations obtained from the Apriori algorithm include not only psychiatric disorders but specifically their manifestation in specific gender groups.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>The FDA AERS offers an important data resource to identify new or unknown adverse events of drugs in the biomedical domain. The results that were obtained in this study can provide valuable information for medical researchers and decision makers at the pharmaceutical research field.</p>
</sec>
</div>
</front>
</TEI>
<affiliations>
<list></list>
<tree>
<noCountry>
<name sortKey="Yildirim, P" sort="Yildirim, P" uniqKey="Yildirim P" first="P." last="Yildirim">P. Yildirim</name>
</noCountry>
</tree>
</affiliations>
</record>

Pour manipuler ce document sous Unix (Dilib)

EXPLOR_STEP=$WICRI_ROOT/Wicri/Informatique/explor/SgmlV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000018 | SxmlIndent | more

Ou

HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000018 | SxmlIndent | more

Pour mettre un lien sur cette page dans le réseau Wicri

{{Explor lien
   |wiki=    Wicri/Informatique
   |area=    SgmlV1
   |flux=    Main
   |étape=   Exploration
   |type=    RBID
   |clé=     PMC:4704041
   |texte=   Association Patterns in Open Data to Explore Ciprofloxacin Adverse Events
}}

Pour générer des pages wiki

HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i   -Sk "pubmed:26763627" \
       | HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd   \
       | NlmPubMed2Wicri -a SgmlV1 

Wicri

This area was generated with Dilib version V0.6.33.
Data generation: Mon Jul 1 14:26:08 2019. Site generation: Wed Apr 28 21:40:44 2021