Second-Generation Antipsychotic Utilization and Metabolic Parameter Monitoring in an Inpatient Pediatric Population: A Retrospective Analysis View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-04

AUTHORS

Valerie D. Nolt, Alexandra Victoria Kibler, G. Lucy Wilkening, Tanya J. Fabian

ABSTRACT

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. 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... »

PAGES

139-146

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s40272-016-0209-x

DOI

http://dx.doi.org/10.1007/s40272-016-0209-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1006926196

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28074349


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/2008/1103", 
        "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

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/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

Subject Predicate Object
1 sg:pub.10.1007/s40272-016-0209-x schema:about N0cee9faeb3a64c98a265ea1272619e3b
2 N1089230e100d481aa565f4deda18b28a
3 N20567125fdab4ce0a284ee4c0eaa3f9d
4 N25e816d5f4734af4b5eecdc08a201561
5 N46b43cd929bd41aab7305281e5d6b8b6
6 N4c93a7b73b794b3798aa6ab1497a9120
7 N74dafb21d801451bad6566ef1ec0d623
8 N85ace0f391a84c48bf9b2161926e83fe
9 Na738229435594b80bbffb514ffeafb0e
10 Nd67df394b1b34b54a0a4f1cfd62af9f7
11 Nd866cb71bce14a2fa2735a821dc12265
12 Nee18272623b34a24ac04a15707b34754
13 Nf96ba8c3bf6046d0ab4cd1ad460c96e9
14 anzsrc-for:11
15 anzsrc-for:1103
16 schema:author Nc9baddc0d3154d0ba3e19e7365e0c85d
17 schema:citation https://app.dimensions.ai/details/publication/pub.1077951899
18 https://doi.org/10.1001/archgenpsychiatry.2012.647
19 https://doi.org/10.1001/archpediatrics.2010.48
20 https://doi.org/10.1001/jama.2009.1549
21 https://doi.org/10.1001/jamapsychiatry.2015.0500
22 https://doi.org/10.1016/j.jpeds.2004.06.044
23 https://doi.org/10.1016/j.orcp.2015.04.002
24 https://doi.org/10.1089/cap.2013.0133
25 https://doi.org/10.1111/j.1399-5448.2007.00271.x
26 https://doi.org/10.1111/j.1475-6773.2012.01461.x
27 https://doi.org/10.1177/070674371205700107
28 https://doi.org/10.2337/diacare.27.2.596
29 https://doi.org/10.3928/00904481-20121221-01
30 https://doi.org/10.3928/00904481-20130128-11
31 https://doi.org/10.5863/1551-6776-18.4.292
32 schema:datePublished 2017-04
33 schema:datePublishedReg 2017-04-01
34 schema: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. 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.
35 schema:genre research_article
36 schema:inLanguage en
37 schema:isAccessibleForFree false
38 schema:isPartOf N5a873d6aca7b4b3786dfb941ea68bf60
39 Nb20c6edebe304a53ad49aa26c2f241f2
40 sg:journal.1020815
41 schema:name Second-Generation Antipsychotic Utilization and Metabolic Parameter Monitoring in an Inpatient Pediatric Population: A Retrospective Analysis
42 schema:pagination 139-146
43 schema:productId N1da616bbf91246a0a0e8326798192e22
44 N5203ab901f7844629e96cd6ef553c3bf
45 N6a55b8ce0e1a440685113c693ef62b7d
46 N983a22eec0e7496da04a4a6d68fa1311
47 Nd77265aba3bb4ec5839a21b49ac4e64b
48 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006926196
49 https://doi.org/10.1007/s40272-016-0209-x
50 schema:sdDatePublished 2019-04-11T09:38
51 schema:sdLicense https://scigraph.springernature.com/explorer/license/
52 schema:sdPublisher N16f3ebaf6e834873a3e0a44946c8edbe
53 schema:url https://link.springer.com/10.1007%2Fs40272-016-0209-x
54 sgo:license sg:explorer/license/
55 sgo:sdDataset articles
56 rdf:type schema:ScholarlyArticle
57 N0cee9faeb3a64c98a265ea1272619e3b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
58 schema:name Retrospective Studies
59 rdf:type schema:DefinedTerm
60 N1089230e100d481aa565f4deda18b28a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
61 schema:name Adolescent
62 rdf:type schema:DefinedTerm
63 N16f3ebaf6e834873a3e0a44946c8edbe schema:name Springer Nature - SN SciGraph project
64 rdf:type schema:Organization
65 N1da616bbf91246a0a0e8326798192e22 schema:name pubmed_id
66 schema:value 28074349
67 rdf:type schema:PropertyValue
68 N20567125fdab4ce0a284ee4c0eaa3f9d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
69 schema:name Male
70 rdf:type schema:DefinedTerm
71 N25e816d5f4734af4b5eecdc08a201561 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
72 schema:name Female
73 rdf:type schema:DefinedTerm
74 N3740f2b628794167b912c8cbda0602cd rdf:first sg:person.012356472741.21
75 rdf:rest Ne7d7d8339b6b468491e55440e9215f57
76 N43c251671cec4c2ba032235335290f52 rdf:first Naed39a3baef647b196702b7f028db77a
77 rdf:rest N3740f2b628794167b912c8cbda0602cd
78 N46b43cd929bd41aab7305281e5d6b8b6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
79 schema:name Obesity
80 rdf:type schema:DefinedTerm
81 N4c93a7b73b794b3798aa6ab1497a9120 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
82 schema:name Child, Preschool
83 rdf:type schema:DefinedTerm
84 N5203ab901f7844629e96cd6ef553c3bf schema:name nlm_unique_id
85 schema:value 100883685
86 rdf:type schema:PropertyValue
87 N5a873d6aca7b4b3786dfb941ea68bf60 schema:issueNumber 2
88 rdf:type schema:PublicationIssue
89 N64f927f8580c4bcc852d00888c3f969d schema:name University of the Incarnate Word Feik School of Pharmacy, 4301 Broadway, Box 99, 78209, San Antonio, TX, USA
90 rdf:type schema:Organization
91 N6a55b8ce0e1a440685113c693ef62b7d schema:name readcube_id
92 schema:value 20fe5ef030ac5e2da7ba87bee96a7b789b56b18a28061a31ef6bde2208ffae48
93 rdf:type schema:PropertyValue
94 N74dafb21d801451bad6566ef1ec0d623 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
95 schema:name Metabolic Syndrome
96 rdf:type schema:DefinedTerm
97 N85ace0f391a84c48bf9b2161926e83fe schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
98 schema:name Humans
99 rdf:type schema:DefinedTerm
100 N983a22eec0e7496da04a4a6d68fa1311 schema:name dimensions_id
101 schema:value pub.1006926196
102 rdf:type schema:PropertyValue
103 Na738229435594b80bbffb514ffeafb0e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
104 schema:name Antipsychotic Agents
105 rdf:type schema:DefinedTerm
106 Naed39a3baef647b196702b7f028db77a schema:affiliation https://www.grid.ac/institutes/grid.240473.6
107 schema:familyName Kibler
108 schema:givenName Alexandra Victoria
109 rdf:type schema:Person
110 Nb20c6edebe304a53ad49aa26c2f241f2 schema:volumeNumber 19
111 rdf:type schema:PublicationVolume
112 Nc9baddc0d3154d0ba3e19e7365e0c85d rdf:first sg:person.010475534553.01
113 rdf:rest N43c251671cec4c2ba032235335290f52
114 Nd67df394b1b34b54a0a4f1cfd62af9f7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
115 schema:name Inpatients
116 rdf:type schema:DefinedTerm
117 Nd77265aba3bb4ec5839a21b49ac4e64b schema:name doi
118 schema:value 10.1007/s40272-016-0209-x
119 rdf:type schema:PropertyValue
120 Nd866cb71bce14a2fa2735a821dc12265 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
121 schema:name Triglycerides
122 rdf:type schema:DefinedTerm
123 Ne7d7d8339b6b468491e55440e9215f57 rdf:first sg:person.01216634717.74
124 rdf:rest rdf:nil
125 Nee18272623b34a24ac04a15707b34754 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
126 schema:name Child
127 rdf:type schema:DefinedTerm
128 Nf96ba8c3bf6046d0ab4cd1ad460c96e9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
129 schema:name Risperidone
130 rdf:type schema:DefinedTerm
131 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
132 schema:name Medical and Health Sciences
133 rdf:type schema:DefinedTerm
134 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
135 schema:name Clinical Sciences
136 rdf:type schema:DefinedTerm
137 sg:journal.1020815 schema:issn 1174-5878
138 1179-2019
139 schema:name Pediatric Drugs
140 rdf:type schema:Periodical
141 sg:person.010475534553.01 schema:affiliation https://www.grid.ac/institutes/grid.413001.7
142 schema:familyName Nolt
143 schema:givenName Valerie D.
144 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010475534553.01
145 rdf:type schema:Person
146 sg:person.01216634717.74 schema:affiliation https://www.grid.ac/institutes/grid.412689.0
147 schema:familyName Fabian
148 schema:givenName Tanya J.
149 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01216634717.74
150 rdf:type schema:Person
151 sg:person.012356472741.21 schema:affiliation N64f927f8580c4bcc852d00888c3f969d
152 schema:familyName Wilkening
153 schema:givenName G. Lucy
154 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012356472741.21
155 rdf:type schema:Person
156 https://app.dimensions.ai/details/publication/pub.1077951899 schema:CreativeWork
157 https://doi.org/10.1001/archgenpsychiatry.2012.647 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040658858
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1001/archpediatrics.2010.48 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014329042
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1001/jama.2009.1549 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037002275
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1001/jamapsychiatry.2015.0500 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036801244
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1016/j.jpeds.2004.06.044 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053597482
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1016/j.orcp.2015.04.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028195162
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1089/cap.2013.0133 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059241728
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1111/j.1399-5448.2007.00271.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1031851006
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1111/j.1475-6773.2012.01461.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1025828258
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1177/070674371205700107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021080008
176 rdf:type schema:CreativeWork
177 https://doi.org/10.2337/diacare.27.2.596 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046635689
178 rdf:type schema:CreativeWork
179 https://doi.org/10.3928/00904481-20121221-01 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071714711
180 rdf:type schema:CreativeWork
181 https://doi.org/10.3928/00904481-20130128-11 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071714738
182 rdf:type schema:CreativeWork
183 https://doi.org/10.5863/1551-6776-18.4.292 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040037207
184 rdf:type schema:CreativeWork
185 https://www.grid.ac/institutes/grid.240473.6 schema:alternateName Penn State Milton S. Hershey Medical Center
186 schema:name Penn State Milton S Hershey Medical Center, Pittsburgh, PA, USA
187 rdf:type schema:Organization
188 https://www.grid.ac/institutes/grid.412689.0 schema:alternateName University of Pittsburgh Medical Center
189 schema:name University of Pittsburgh School of Pharmacy, Pittsburgh, PA, USA
190 Western Psychiatric Institute and Clinic of the University of Pittsburgh Medical Center, Pittsburgh, PA, USA
191 rdf:type schema:Organization
192 https://www.grid.ac/institutes/grid.413001.7 schema:alternateName University of Kentucky HealthCare
193 schema:name University of Kentucky HealthCare, Lexington, KY, USA
194 rdf:type schema:Organization
 




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


...