Ontology type: schema:ScholarlyArticle
2017-04
AUTHORSValerie D. Nolt, Alexandra Victoria Kibler, G. Lucy Wilkening, Tanya J. Fabian
ABSTRACTBACKGROUND: Second-generation antipsychotics (SGAs) are prescribed for a variety of indications and are strongly associated with adverse metabolic effects. Studies of pediatric outpatients have revealed several deficiencies in monitoring practices for adverse effects associated with SGAs. OBJECTIVE: Our objective was to characterize SGA prescribing and metabolic parameter monitoring (MPM) in an inpatient pediatric population. METHODS: Patients aged <18 years and discharged on SGA treatment between 1 November 2013 and 30 April 2014 from an inpatient psychiatric institution in Pittsburgh, PA, USA were included. Electronic medical records (EMRs) were reviewed for patient age and weight and for parameters used by the International Diabetes Federation (IDF) to define metabolic syndrome: waist circumference, fasting blood glucose, triglycerides, high-density lipoprotein, and blood pressure. The primary outcome was the percent of patients with completed MPM, defined as all parameters being available within the patient's EMR in any form, except estimates. Secondary outcomes included percent of patients with existing metabolic syndrome or obesity according to IDF criteria, average total daily dose of individual SGAs, and frequency of individual SGA utilization. Data were analyzed utilizing univariate descriptive statistics. RESULTS: A total of 243 patients met inclusion criteria and were included in the analysis. For the primary outcome, 13.2% (n = 32) of patients had completed MPM for all parameters. Blood pressure was the most frequently documented parameter (n = 241; 99.2%), whereas waist circumference was the least (n = 67; 28%). Risperidone was the most commonly prescribed SGA (n = 99; 41%; average daily dose 1.92 mg). CONCLUSIONS: Compared with outpatient studies, rates of documented MPM for certain parameters (i.e., fasting blood glucose, lipids) is higher for pediatric inpatients treated with SGAs. However, several monitoring deficiencies are still noted. More... »
PAGES139-146
http://scigraph.springernature.com/pub.10.1007/s40272-016-0209-x
DOIhttp://dx.doi.org/10.1007/s40272-016-0209-x
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1006926196
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/28074349
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/2008/1103",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Clinical Sciences",
"type": "DefinedTerm"
},
{
"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"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Adolescent",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Antipsychotic Agents",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Child",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Child, Preschool",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Female",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Humans",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Inpatients",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Male",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Metabolic Syndrome",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Obesity",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Retrospective Studies",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Risperidone",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Triglycerides",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "University of Kentucky HealthCare",
"id": "https://www.grid.ac/institutes/grid.413001.7",
"name": [
"University of Kentucky HealthCare, Lexington, KY, USA"
],
"type": "Organization"
},
"familyName": "Nolt",
"givenName": "Valerie D.",
"id": "sg:person.010475534553.01",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010475534553.01"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Penn State Milton S. Hershey Medical Center",
"id": "https://www.grid.ac/institutes/grid.240473.6",
"name": [
"Penn State Milton S Hershey Medical Center, Pittsburgh, PA, USA"
],
"type": "Organization"
},
"familyName": "Kibler",
"givenName": "Alexandra Victoria",
"type": "Person"
},
{
"affiliation": {
"name": [
"University of the Incarnate Word Feik School of Pharmacy, 4301 Broadway, Box 99, 78209, San Antonio, TX, USA"
],
"type": "Organization"
},
"familyName": "Wilkening",
"givenName": "G. Lucy",
"id": "sg:person.012356472741.21",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012356472741.21"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of Pittsburgh Medical Center",
"id": "https://www.grid.ac/institutes/grid.412689.0",
"name": [
"University of Pittsburgh School of Pharmacy, Pittsburgh, PA, USA",
"Western Psychiatric Institute and Clinic of the University of Pittsburgh Medical Center, Pittsburgh, PA, USA"
],
"type": "Organization"
},
"familyName": "Fabian",
"givenName": "Tanya J.",
"id": "sg:person.01216634717.74",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01216634717.74"
],
"type": "Person"
}
],
"citation": [
{
"id": "https://doi.org/10.1001/archpediatrics.2010.48",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014329042"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/070674371205700107",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021080008"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1177/070674371205700107",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1021080008"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1475-6773.2012.01461.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1025828258"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.orcp.2015.04.002",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028195162"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1111/j.1399-5448.2007.00271.x",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1031851006"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1001/jamapsychiatry.2015.0500",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036801244"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1001/jama.2009.1549",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1037002275"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.5863/1551-6776-18.4.292",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1040037207"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1001/archgenpsychiatry.2012.647",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1040658858"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.2337/diacare.27.2.596",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046635689"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.jpeds.2004.06.044",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053597482"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1089/cap.2013.0133",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1059241728"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3928/00904481-20121221-01",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1071714711"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3928/00904481-20130128-11",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1071714738"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1077951899",
"type": "CreativeWork"
}
],
"datePublished": "2017-04",
"datePublishedReg": "2017-04-01",
"description": "BACKGROUND: Second-generation antipsychotics (SGAs) are prescribed for a variety of indications and are strongly associated with adverse metabolic effects. Studies of pediatric outpatients have revealed several deficiencies in monitoring practices for adverse effects associated with SGAs.\nOBJECTIVE: Our objective was to characterize SGA prescribing and metabolic parameter monitoring (MPM) in an inpatient pediatric population.\nMETHODS: Patients aged <18\u00a0years and discharged on SGA treatment between 1 November 2013 and 30 April 2014 from an inpatient psychiatric institution in Pittsburgh, PA, USA were included. Electronic medical records (EMRs) were reviewed for patient age and weight and for parameters used by the International Diabetes Federation (IDF) to define metabolic syndrome: waist circumference, fasting blood glucose, triglycerides, high-density lipoprotein, and blood pressure. The primary outcome was the percent of patients with completed MPM, defined as all parameters being available within the patient's EMR in any form, except estimates. Secondary outcomes included percent of patients with existing metabolic syndrome or obesity according to IDF criteria, average total daily dose of individual SGAs, and frequency of individual SGA utilization. Data were analyzed utilizing univariate descriptive statistics.\nRESULTS: A total of 243 patients met inclusion criteria and were included in the analysis. For the primary outcome, 13.2% (n\u00a0=\u00a032) of patients had completed MPM for all parameters. Blood pressure was the most frequently documented parameter (n\u00a0=\u00a0241; 99.2%), whereas waist circumference was the least (n\u00a0=\u00a067; 28%). Risperidone was the most commonly prescribed SGA (n\u00a0=\u00a099; 41%; average daily dose 1.92\u00a0mg).\nCONCLUSIONS: Compared with outpatient studies, rates of documented MPM for certain parameters (i.e., fasting blood glucose, lipids) is higher for pediatric inpatients treated with SGAs. However, several monitoring deficiencies are still noted.",
"genre": "research_article",
"id": "sg:pub.10.1007/s40272-016-0209-x",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1020815",
"issn": [
"1174-5878",
"1179-2019"
],
"name": "Pediatric Drugs",
"type": "Periodical"
},
{
"issueNumber": "2",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "19"
}
],
"name": "Second-Generation Antipsychotic Utilization and Metabolic Parameter Monitoring in an Inpatient Pediatric Population: A Retrospective Analysis",
"pagination": "139-146",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"20fe5ef030ac5e2da7ba87bee96a7b789b56b18a28061a31ef6bde2208ffae48"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"28074349"
]
},
{
"name": "nlm_unique_id",
"type": "PropertyValue",
"value": [
"100883685"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s40272-016-0209-x"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1006926196"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s40272-016-0209-x",
"https://app.dimensions.ai/details/publication/pub.1006926196"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T09:38",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000346_0000000346/records_99833_00000000.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1007%2Fs40272-016-0209-x"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
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/s40272-016-0209-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/s40272-016-0209-x'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s40272-016-0209-x'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s40272-016-0209-x'
This table displays all metadata directly associated to this object as RDF triples.
194 TRIPLES
21 PREDICATES
57 URIs
34 LITERALS
22 BLANK NODES