Neonatal endocrine labomas - pitfalls and challenges in reporting neonatal hormonal reports View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-09

AUTHORS

Sachin Chittawar, Deep Dutta, Deepak Khandelwal, Rajiv Singla, Society for Promotion of Education in Endocrinology & Diabetes (SPEED) Group

ABSTRACT

This review highlights pitfalls and challenges in interpreting neonatal hormone reports. Pre-analytical errors contribute to nearly 50% of all errors. Modern chemiluminescence assay are more accurate, have lower risk of Hook's effect, but continue to have problems of assay interference. Liquid chromatography mass spectroscopy is gold standard for most hormone assays. Neonatal hypoglycemia diagnostic cut-offs are lower than adults. Random growth hormone testing is of value in diagnosing growth hormone deficiency in neonates. 17-hydroxy-progesterone testing in first three days of life for congenital adrenal hyperplasia (CAH) remains a challenge due to cross-reactivity with maternal circulating steroids, prematurity and lack of adrenal maturation. Both T4 and TSH testing is encouraged after 48 hours of delivery for diagnosing neonatal hypothyroidism; repeat testing should be done immediately for confirmation of diagnosis. There is an urgent need to develop age- sex- and ethnicity-based normative data for different hormone parameters in neonates. Laboratory should develop their own neonatal references and avoid using ranges from manufacturers. In neonatal endocrinopathies, the clinical scenario should primarily dictate the treatment formulation with hormonal assay to supplement treatment. More... »

PAGES

757-762

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13312-017-1170-7

DOI

http://dx.doi.org/10.1007/s13312-017-1170-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1092116417

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28984256


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": "Endocrine System Diseases", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Hormones", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Infant, Newborn", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Infant, Newborn, Diseases", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Neonatal Screening", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Thyroid Function Tests", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Hamidia Hospital", 
          "id": "https://www.grid.ac/institutes/grid.460852.d", 
          "name": [
            "Division of Endocrinology, Department of Medicine, Gandhi Medical College (GMC) and Hamidia Hospital, Bhopal, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chittawar", 
        "givenName": "Sachin", 
        "id": "sg:person.01257553764.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01257553764.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Department of Endocrinology, Venkateshwar Hospitals, Sector 18A, Dwarka, New Delhi, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Dutta", 
        "givenName": "Deep", 
        "id": "sg:person.0762376566.47", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0762376566.47"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Department of Endocrinology, Maharaja Agrasen Hospital, Dwarka; New Delhi, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Khandelwal", 
        "givenName": "Deepak", 
        "id": "sg:person.0715574175.55", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715574175.55"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Department of Endocrinology, Kalpravriksh Superspeciality Clinic, Dwarka; New Delhi, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Singla", 
        "givenName": "Rajiv", 
        "id": "sg:person.0633772014.78", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0633772014.78"
        ], 
        "type": "Person"
      }, 
      {
        "familyName": "Society for Promotion of Education in Endocrinology & Diabetes (SPEED) Group", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1515/jpem.2010.143", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000170534"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4103/2230-8210.103041", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002630357"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jpeds.2015.03.057", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003959542"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1309/c52d-by0u-vxxu-r360", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004211805"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.nut.2016.09.014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007772323"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jpeds.2015.02.045", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009613757"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2013/638257", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013200157"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1289/ehp.7994", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027131628"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0022-3476(95)70229-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034245487"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4103/2230-8210.149316", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037090253"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ejim.2016.07.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038635901"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa1504909", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047924981"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12098-007-0092-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050670391", 
          "https://doi.org/10.1007/s12098-007-0092-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/adc.67.7.920", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051899977"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00431-007-0565-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052787216", 
          "https://doi.org/10.1007/s00431-007-0565-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1210/jc.2004-0869", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064287891"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1210/jc.2004-2136", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064288152"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1210/jc.2005-1049", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064288578"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1210/jc.2009-2631", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064291902"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1210/jc.2011-1175", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064292866"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1210/jc.85.11.4266", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064301144"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1210/jcem.85.11.6998", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064323180"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.17925/ee.2012.08.01.53", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068543154"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.18773/austprescr.2005.096", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068690082"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3238/arztebl.2011.0011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1078340798"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1078619273", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1078872114", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2017-09", 
    "datePublishedReg": "2017-09-01", 
    "description": "This review highlights pitfalls and challenges in interpreting neonatal hormone reports. Pre-analytical errors contribute to nearly 50% of all errors. Modern chemiluminescence assay are more accurate, have lower risk of Hook's effect, but continue to have problems of assay interference. Liquid chromatography mass spectroscopy is gold standard for most hormone assays. Neonatal hypoglycemia diagnostic cut-offs are lower than adults. Random growth hormone testing is of value in diagnosing growth hormone deficiency in neonates. 17-hydroxy-progesterone testing in first three days of life for congenital adrenal hyperplasia (CAH) remains a challenge due to cross-reactivity with maternal circulating steroids, prematurity and lack of adrenal maturation. Both T4 and TSH testing is encouraged after 48 hours of delivery for diagnosing neonatal hypothyroidism; repeat testing should be done immediately for confirmation of diagnosis. There is an urgent need to develop age- sex- and ethnicity-based normative data for different hormone parameters in neonates. Laboratory should develop their own neonatal references and avoid using ranges from manufacturers. In neonatal endocrinopathies, the clinical scenario should primarily dictate the treatment formulation with hormonal assay to supplement treatment.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s13312-017-1170-7", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1077082", 
        "issn": [
          "0019-6061", 
          "0974-7559"
        ], 
        "name": "Indian Pediatrics", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "9", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "54"
      }
    ], 
    "name": "Neonatal endocrine labomas - pitfalls and challenges in reporting neonatal hormonal reports", 
    "pagination": "757-762", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "144a01778c6e844d915fb91362ad6c1c693d8051a4886ac102fc6d5cd0ae9cdb"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "28984256"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "2985062R"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s13312-017-1170-7"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1092116417"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s13312-017-1170-7", 
      "https://app.dimensions.ai/details/publication/pub.1092116417"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T01:53", 
    "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/v90/0000000001_0000000264/records_8700_00000484.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007/s13312-017-1170-7"
  }
]
 

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/s13312-017-1170-7'

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/s13312-017-1170-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s13312-017-1170-7'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s13312-017-1170-7'


 

This table displays all metadata directly associated to this object as RDF triples.

209 TRIPLES      21 PREDICATES      63 URIs      28 LITERALS      16 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s13312-017-1170-7 schema:about N0bb3e66f15f34e90bb9669800aa373e2
2 N2a16a9507ad54b58875b772618222abe
3 N4ecacf5072484cc48021648cadbfb8b6
4 N5176e505d8904acc8a6c9f73d7423d28
5 Nc0afb7657df04d7c907be2d9be36e241
6 Nc5a4a2ae00e14f5ca1913bc8cb86fa4f
7 Nf5e51ca6fd574b158306fd5fc83a4d77
8 anzsrc-for:11
9 anzsrc-for:1103
10 schema:author Nac1041ad765f459bba59d3cb229b44a6
11 schema:citation sg:pub.10.1007/s00431-007-0565-1
12 sg:pub.10.1007/s12098-007-0092-0
13 https://app.dimensions.ai/details/publication/pub.1078619273
14 https://app.dimensions.ai/details/publication/pub.1078872114
15 https://doi.org/10.1016/j.ejim.2016.07.012
16 https://doi.org/10.1016/j.jpeds.2015.02.045
17 https://doi.org/10.1016/j.jpeds.2015.03.057
18 https://doi.org/10.1016/j.nut.2016.09.014
19 https://doi.org/10.1016/s0022-3476(95)70229-6
20 https://doi.org/10.1056/nejmoa1504909
21 https://doi.org/10.1136/adc.67.7.920
22 https://doi.org/10.1155/2013/638257
23 https://doi.org/10.1210/jc.2004-0869
24 https://doi.org/10.1210/jc.2004-2136
25 https://doi.org/10.1210/jc.2005-1049
26 https://doi.org/10.1210/jc.2009-2631
27 https://doi.org/10.1210/jc.2011-1175
28 https://doi.org/10.1210/jc.85.11.4266
29 https://doi.org/10.1210/jcem.85.11.6998
30 https://doi.org/10.1289/ehp.7994
31 https://doi.org/10.1309/c52d-by0u-vxxu-r360
32 https://doi.org/10.1515/jpem.2010.143
33 https://doi.org/10.17925/ee.2012.08.01.53
34 https://doi.org/10.18773/austprescr.2005.096
35 https://doi.org/10.3238/arztebl.2011.0011
36 https://doi.org/10.4103/2230-8210.103041
37 https://doi.org/10.4103/2230-8210.149316
38 schema:datePublished 2017-09
39 schema:datePublishedReg 2017-09-01
40 schema:description This review highlights pitfalls and challenges in interpreting neonatal hormone reports. Pre-analytical errors contribute to nearly 50% of all errors. Modern chemiluminescence assay are more accurate, have lower risk of Hook's effect, but continue to have problems of assay interference. Liquid chromatography mass spectroscopy is gold standard for most hormone assays. Neonatal hypoglycemia diagnostic cut-offs are lower than adults. Random growth hormone testing is of value in diagnosing growth hormone deficiency in neonates. 17-hydroxy-progesterone testing in first three days of life for congenital adrenal hyperplasia (CAH) remains a challenge due to cross-reactivity with maternal circulating steroids, prematurity and lack of adrenal maturation. Both T4 and TSH testing is encouraged after 48 hours of delivery for diagnosing neonatal hypothyroidism; repeat testing should be done immediately for confirmation of diagnosis. There is an urgent need to develop age- sex- and ethnicity-based normative data for different hormone parameters in neonates. Laboratory should develop their own neonatal references and avoid using ranges from manufacturers. In neonatal endocrinopathies, the clinical scenario should primarily dictate the treatment formulation with hormonal assay to supplement treatment.
41 schema:genre research_article
42 schema:inLanguage en
43 schema:isAccessibleForFree false
44 schema:isPartOf N1cb9f282f1ef4c46a643b9d13ed35457
45 N46413c7da1324aefaf0217b9bfd8c71f
46 sg:journal.1077082
47 schema:name Neonatal endocrine labomas - pitfalls and challenges in reporting neonatal hormonal reports
48 schema:pagination 757-762
49 schema:productId N00903a66d62e4f8aac153ad35ab9ecf2
50 N550e3669b1f149ec9ef0a412b1ac1541
51 N5e8a1a0d99804fc2a641185facb929b8
52 Ncbb6c3cef21c49beb9764eaa93f81a62
53 Ndc7a68f3176d4bbd9ce6ea435c4d02df
54 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092116417
55 https://doi.org/10.1007/s13312-017-1170-7
56 schema:sdDatePublished 2019-04-11T01:53
57 schema:sdLicense https://scigraph.springernature.com/explorer/license/
58 schema:sdPublisher N270c6853b24341ddabc0614298c15d7a
59 schema:url http://link.springer.com/10.1007/s13312-017-1170-7
60 sgo:license sg:explorer/license/
61 sgo:sdDataset articles
62 rdf:type schema:ScholarlyArticle
63 N00903a66d62e4f8aac153ad35ab9ecf2 schema:name pubmed_id
64 schema:value 28984256
65 rdf:type schema:PropertyValue
66 N0bb3e66f15f34e90bb9669800aa373e2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
67 schema:name Thyroid Function Tests
68 rdf:type schema:DefinedTerm
69 N1cb9f282f1ef4c46a643b9d13ed35457 schema:volumeNumber 54
70 rdf:type schema:PublicationVolume
71 N232bd0ae32b2400891a67a424c2c0103 schema:name Department of Endocrinology, Venkateshwar Hospitals, Sector 18A, Dwarka, New Delhi, India
72 rdf:type schema:Organization
73 N270c6853b24341ddabc0614298c15d7a schema:name Springer Nature - SN SciGraph project
74 rdf:type schema:Organization
75 N28e0d141a4ee4c6f91afa09fd817fef0 rdf:first sg:person.0762376566.47
76 rdf:rest N2955293cc70242338dfbdb4a442e7428
77 N2955293cc70242338dfbdb4a442e7428 rdf:first sg:person.0715574175.55
78 rdf:rest N5a5c7ddd6360493daac0f51e3969b514
79 N2a16a9507ad54b58875b772618222abe schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
80 schema:name Endocrine System Diseases
81 rdf:type schema:DefinedTerm
82 N43b17abbaa464f17af215c8e410ba1a9 rdf:first N640134c29bf14b0fac658f320b00f589
83 rdf:rest rdf:nil
84 N46413c7da1324aefaf0217b9bfd8c71f schema:issueNumber 9
85 rdf:type schema:PublicationIssue
86 N4ecacf5072484cc48021648cadbfb8b6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
87 schema:name Humans
88 rdf:type schema:DefinedTerm
89 N5176e505d8904acc8a6c9f73d7423d28 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
90 schema:name Neonatal Screening
91 rdf:type schema:DefinedTerm
92 N550e3669b1f149ec9ef0a412b1ac1541 schema:name doi
93 schema:value 10.1007/s13312-017-1170-7
94 rdf:type schema:PropertyValue
95 N5a5c7ddd6360493daac0f51e3969b514 rdf:first sg:person.0633772014.78
96 rdf:rest N43b17abbaa464f17af215c8e410ba1a9
97 N5e8a1a0d99804fc2a641185facb929b8 schema:name readcube_id
98 schema:value 144a01778c6e844d915fb91362ad6c1c693d8051a4886ac102fc6d5cd0ae9cdb
99 rdf:type schema:PropertyValue
100 N640134c29bf14b0fac658f320b00f589 schema:familyName Society for Promotion of Education in Endocrinology & Diabetes (SPEED) Group
101 rdf:type schema:Person
102 N913c0407f01d4b4aac11f2aab508cafb schema:name Department of Endocrinology, Maharaja Agrasen Hospital, Dwarka; New Delhi, India
103 rdf:type schema:Organization
104 Nac1041ad765f459bba59d3cb229b44a6 rdf:first sg:person.01257553764.24
105 rdf:rest N28e0d141a4ee4c6f91afa09fd817fef0
106 Nb18ec89ff54e45b59ba55480a22d4d7c schema:name Department of Endocrinology, Kalpravriksh Superspeciality Clinic, Dwarka; New Delhi, India
107 rdf:type schema:Organization
108 Nc0afb7657df04d7c907be2d9be36e241 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
109 schema:name Hormones
110 rdf:type schema:DefinedTerm
111 Nc5a4a2ae00e14f5ca1913bc8cb86fa4f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
112 schema:name Infant, Newborn
113 rdf:type schema:DefinedTerm
114 Ncbb6c3cef21c49beb9764eaa93f81a62 schema:name nlm_unique_id
115 schema:value 2985062R
116 rdf:type schema:PropertyValue
117 Ndc7a68f3176d4bbd9ce6ea435c4d02df schema:name dimensions_id
118 schema:value pub.1092116417
119 rdf:type schema:PropertyValue
120 Nf5e51ca6fd574b158306fd5fc83a4d77 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
121 schema:name Infant, Newborn, Diseases
122 rdf:type schema:DefinedTerm
123 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
124 schema:name Medical and Health Sciences
125 rdf:type schema:DefinedTerm
126 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
127 schema:name Clinical Sciences
128 rdf:type schema:DefinedTerm
129 sg:journal.1077082 schema:issn 0019-6061
130 0974-7559
131 schema:name Indian Pediatrics
132 rdf:type schema:Periodical
133 sg:person.01257553764.24 schema:affiliation https://www.grid.ac/institutes/grid.460852.d
134 schema:familyName Chittawar
135 schema:givenName Sachin
136 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01257553764.24
137 rdf:type schema:Person
138 sg:person.0633772014.78 schema:affiliation Nb18ec89ff54e45b59ba55480a22d4d7c
139 schema:familyName Singla
140 schema:givenName Rajiv
141 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0633772014.78
142 rdf:type schema:Person
143 sg:person.0715574175.55 schema:affiliation N913c0407f01d4b4aac11f2aab508cafb
144 schema:familyName Khandelwal
145 schema:givenName Deepak
146 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715574175.55
147 rdf:type schema:Person
148 sg:person.0762376566.47 schema:affiliation N232bd0ae32b2400891a67a424c2c0103
149 schema:familyName Dutta
150 schema:givenName Deep
151 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0762376566.47
152 rdf:type schema:Person
153 sg:pub.10.1007/s00431-007-0565-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052787216
154 https://doi.org/10.1007/s00431-007-0565-1
155 rdf:type schema:CreativeWork
156 sg:pub.10.1007/s12098-007-0092-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050670391
157 https://doi.org/10.1007/s12098-007-0092-0
158 rdf:type schema:CreativeWork
159 https://app.dimensions.ai/details/publication/pub.1078619273 schema:CreativeWork
160 https://app.dimensions.ai/details/publication/pub.1078872114 schema:CreativeWork
161 https://doi.org/10.1016/j.ejim.2016.07.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038635901
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1016/j.jpeds.2015.02.045 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009613757
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1016/j.jpeds.2015.03.057 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003959542
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1016/j.nut.2016.09.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007772323
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1016/s0022-3476(95)70229-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034245487
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1056/nejmoa1504909 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047924981
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1136/adc.67.7.920 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051899977
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1155/2013/638257 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013200157
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1210/jc.2004-0869 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064287891
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1210/jc.2004-2136 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064288152
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1210/jc.2005-1049 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064288578
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1210/jc.2009-2631 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064291902
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1210/jc.2011-1175 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064292866
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1210/jc.85.11.4266 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064301144
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1210/jcem.85.11.6998 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064323180
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1289/ehp.7994 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027131628
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1309/c52d-by0u-vxxu-r360 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004211805
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1515/jpem.2010.143 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000170534
196 rdf:type schema:CreativeWork
197 https://doi.org/10.17925/ee.2012.08.01.53 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068543154
198 rdf:type schema:CreativeWork
199 https://doi.org/10.18773/austprescr.2005.096 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068690082
200 rdf:type schema:CreativeWork
201 https://doi.org/10.3238/arztebl.2011.0011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1078340798
202 rdf:type schema:CreativeWork
203 https://doi.org/10.4103/2230-8210.103041 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002630357
204 rdf:type schema:CreativeWork
205 https://doi.org/10.4103/2230-8210.149316 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037090253
206 rdf:type schema:CreativeWork
207 https://www.grid.ac/institutes/grid.460852.d schema:alternateName Hamidia Hospital
208 schema:name Division of Endocrinology, Department of Medicine, Gandhi Medical College (GMC) and Hamidia Hospital, Bhopal, India
209 rdf:type schema:Organization
 




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


...