Diurnal variations of short-term variation and the impact of multiple recordings on measurement accuracy
Objective: Short-term variation (STV) from computerized cardiotocogram heart rate analysis is a parameter that complements decision making, regarding the delivery of fetuses in several high-risk situations. Although studies on the effects of gestational age and fetal pathology are convincing, there...
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| Veröffentlicht in: | Journal of perinatology 2017-03, Vol.37 (3), p.231-235 |
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| creator | Seliger, G Petroff, D Seeger, S Hoyer, D Tchirikov, M Schneider, U |
| description | Objective:
Short-term variation (STV) from computerized cardiotocogram heart rate analysis is a parameter that complements decision making, regarding the delivery of fetuses in several high-risk situations. Although studies on the effects of gestational age and fetal pathology are convincing, there is a lack of data exploring diurnal variation and the adequacy of a single measurement.
Study Design:
In this prospective observational study, fetal STV was monitored with the AN24 fetal ECG monitor (Monica Healthcare) each hour for at least 10 h in total, beginning at different times. This resulted in data covering all 24 h of the day. Seventy fetuses, low risk with respect to conditions accessible to heart rate monitoring (median 37th week of gestation) were monitored for an average of 12 h. Results of STV per hour were categorized as ‘compromised’ (STV |
| doi_str_mv | 10.1038/jp.2016.202 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_1877815030</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A483831965</galeid><sourcerecordid>A483831965</sourcerecordid><originalsourceid>FETCH-LOGICAL-c513t-660930fbaec8bff11e7f5b6b6692b1d02f6c7843b544326b18df653218b3dce53</originalsourceid><addsrcrecordid>eNqNkt-L1DAQx4Mo3nr65LsUBBHOrvnd9vE4PRUOfNHnkKaTbZa2qUl6cP-96e2pe3KIBCYw85kZvjOD0EuCtwSz-v1-3lJMZDb0EdoQXslSCM4eow2uOCtrxuUJehbjHuM1WD1FJ7SqGRFcblD_wS1h0kNxrYPTyfkpFt4WsfchlQnC-CdQ6KkrUg-FG2dt0oqNy5DcPEARwPjQuWmXs6diBB2XACNMqdDGLEGbm-foidVDhBd3_yn6fvnx28Xn8urrpy8X51elEYSlUkrcMGxbDaZurSUEKita2UrZ0JZ0mFppqpqzVnDOqGxJ3VkpGCV1yzoDgp2it4e6c_A_FohJjS4aGAY9gV-iInVV1URghv8DZQ0hhFU0o6__Qvf-dm5RUUmEoA3H_F9UbstYg8kxtdMDKDdZn_KA1tbqnNcsb6aRq47tA1R-HYzO-Amsy_57CW-OEnrQQ-qjH5bbnd4Hzw6gCT7GAFbNwY063CiC1XpRaj-r9aKyWZW_utO0tCN0v9lfJ5SBdwcg5tC0g3Ak-oF6PwFcudFc</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1873390104</pqid></control><display><type>article</type><title>Diurnal variations of short-term variation and the impact of multiple recordings on measurement accuracy</title><source>MEDLINE</source><source>SpringerNature Journals</source><creator>Seliger, G ; Petroff, D ; Seeger, S ; Hoyer, D ; Tchirikov, M ; Schneider, U</creator><creatorcontrib>Seliger, G ; Petroff, D ; Seeger, S ; Hoyer, D ; Tchirikov, M ; Schneider, U</creatorcontrib><description>Objective:
Short-term variation (STV) from computerized cardiotocogram heart rate analysis is a parameter that complements decision making, regarding the delivery of fetuses in several high-risk situations. Although studies on the effects of gestational age and fetal pathology are convincing, there is a lack of data exploring diurnal variation and the adequacy of a single measurement.
Study Design:
In this prospective observational study, fetal STV was monitored with the AN24 fetal ECG monitor (Monica Healthcare) each hour for at least 10 h in total, beginning at different times. This resulted in data covering all 24 h of the day. Seventy fetuses, low risk with respect to conditions accessible to heart rate monitoring (median 37th week of gestation) were monitored for an average of 12 h. Results of STV per hour were categorized as ‘compromised’ (STV<4 ms) or ‘healthy’, (STV⩾4 ms) to calculate the model of predictability.
Results:
The model proposed (STV of ‘healthy’ fetuses: 9.6±2.6 ms, ‘compromised’ fetuses 3.0±0.5 ms, prevalence 1%) leads to a positive predictive value of 39%, which increased to 68 or 80% given two or three pathological (STV<4 ms) measurements, respectively. Diurnal variation was not observed.
Conclusions:
Single pathological STV values should be corroborated by further measurements in a 24-h interval in otherwise low-risk fetuses before inducing delivery. This may help to avoid unnecessary early births and give the fetus valuable days for intrauterine maturity.</description><identifier>ISSN: 0743-8346</identifier><identifier>EISSN: 1476-5543</identifier><identifier>DOI: 10.1038/jp.2016.202</identifier><identifier>PMID: 27831546</identifier><language>eng</language><publisher>New York: Nature Publishing Group US</publisher><subject>692/700/139/1449 ; Accuracy ; Adequacy ; Adolescent ; Adult ; Cardiotocography - methods ; Childbirth & labor ; Circadian Rhythm ; Circadian rhythms ; Decision analysis ; Decision making ; Diurnal variations ; EKG ; Electrocardiography ; Female ; Fetal Monitoring - methods ; Fetuses ; Germany ; Gestational Age ; Heart rate ; Heart Rate, Fetal ; Hospitals ; Humans ; Linear Models ; Measurement ; Medicine ; Medicine & Public Health ; Observational studies ; Observations ; Obstetrics ; original-article ; Pediatric Surgery ; Pediatrics ; Pregnancy ; Prospective Studies ; Risk ; Surveillance ; Womens health ; Young Adult</subject><ispartof>Journal of perinatology, 2017-03, Vol.37 (3), p.231-235</ispartof><rights>Nature America, Inc., part of Springer Nature. 2017</rights><rights>COPYRIGHT 2017 Nature Publishing Group</rights><rights>Copyright Nature Publishing Group Mar 2017</rights><rights>Nature America, Inc., part of Springer Nature. 2017.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c513t-660930fbaec8bff11e7f5b6b6692b1d02f6c7843b544326b18df653218b3dce53</citedby><cites>FETCH-LOGICAL-c513t-660930fbaec8bff11e7f5b6b6692b1d02f6c7843b544326b18df653218b3dce53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/jp.2016.202$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/jp.2016.202$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27831546$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Seliger, G</creatorcontrib><creatorcontrib>Petroff, D</creatorcontrib><creatorcontrib>Seeger, S</creatorcontrib><creatorcontrib>Hoyer, D</creatorcontrib><creatorcontrib>Tchirikov, M</creatorcontrib><creatorcontrib>Schneider, U</creatorcontrib><title>Diurnal variations of short-term variation and the impact of multiple recordings on measurement accuracy</title><title>Journal of perinatology</title><addtitle>J Perinatol</addtitle><addtitle>J Perinatol</addtitle><description>Objective:
Short-term variation (STV) from computerized cardiotocogram heart rate analysis is a parameter that complements decision making, regarding the delivery of fetuses in several high-risk situations. Although studies on the effects of gestational age and fetal pathology are convincing, there is a lack of data exploring diurnal variation and the adequacy of a single measurement.
Study Design:
In this prospective observational study, fetal STV was monitored with the AN24 fetal ECG monitor (Monica Healthcare) each hour for at least 10 h in total, beginning at different times. This resulted in data covering all 24 h of the day. Seventy fetuses, low risk with respect to conditions accessible to heart rate monitoring (median 37th week of gestation) were monitored for an average of 12 h. Results of STV per hour were categorized as ‘compromised’ (STV<4 ms) or ‘healthy’, (STV⩾4 ms) to calculate the model of predictability.
Results:
The model proposed (STV of ‘healthy’ fetuses: 9.6±2.6 ms, ‘compromised’ fetuses 3.0±0.5 ms, prevalence 1%) leads to a positive predictive value of 39%, which increased to 68 or 80% given two or three pathological (STV<4 ms) measurements, respectively. Diurnal variation was not observed.
Conclusions:
Single pathological STV values should be corroborated by further measurements in a 24-h interval in otherwise low-risk fetuses before inducing delivery. This may help to avoid unnecessary early births and give the fetus valuable days for intrauterine maturity.</description><subject>692/700/139/1449</subject><subject>Accuracy</subject><subject>Adequacy</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Cardiotocography - methods</subject><subject>Childbirth & labor</subject><subject>Circadian Rhythm</subject><subject>Circadian rhythms</subject><subject>Decision analysis</subject><subject>Decision making</subject><subject>Diurnal variations</subject><subject>EKG</subject><subject>Electrocardiography</subject><subject>Female</subject><subject>Fetal Monitoring - methods</subject><subject>Fetuses</subject><subject>Germany</subject><subject>Gestational Age</subject><subject>Heart rate</subject><subject>Heart Rate, Fetal</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Linear Models</subject><subject>Measurement</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Observational studies</subject><subject>Observations</subject><subject>Obstetrics</subject><subject>original-article</subject><subject>Pediatric Surgery</subject><subject>Pediatrics</subject><subject>Pregnancy</subject><subject>Prospective Studies</subject><subject>Risk</subject><subject>Surveillance</subject><subject>Womens health</subject><subject>Young Adult</subject><issn>0743-8346</issn><issn>1476-5543</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNkt-L1DAQx4Mo3nr65LsUBBHOrvnd9vE4PRUOfNHnkKaTbZa2qUl6cP-96e2pe3KIBCYw85kZvjOD0EuCtwSz-v1-3lJMZDb0EdoQXslSCM4eow2uOCtrxuUJehbjHuM1WD1FJ7SqGRFcblD_wS1h0kNxrYPTyfkpFt4WsfchlQnC-CdQ6KkrUg-FG2dt0oqNy5DcPEARwPjQuWmXs6diBB2XACNMqdDGLEGbm-foidVDhBd3_yn6fvnx28Xn8urrpy8X51elEYSlUkrcMGxbDaZurSUEKita2UrZ0JZ0mFppqpqzVnDOqGxJ3VkpGCV1yzoDgp2it4e6c_A_FohJjS4aGAY9gV-iInVV1URghv8DZQ0hhFU0o6__Qvf-dm5RUUmEoA3H_F9UbstYg8kxtdMDKDdZn_KA1tbqnNcsb6aRq47tA1R-HYzO-Amsy_57CW-OEnrQQ-qjH5bbnd4Hzw6gCT7GAFbNwY063CiC1XpRaj-r9aKyWZW_utO0tCN0v9lfJ5SBdwcg5tC0g3Ak-oF6PwFcudFc</recordid><startdate>20170301</startdate><enddate>20170301</enddate><creator>Seliger, G</creator><creator>Petroff, D</creator><creator>Seeger, S</creator><creator>Hoyer, D</creator><creator>Tchirikov, M</creator><creator>Schneider, U</creator><general>Nature Publishing Group US</general><general>Nature Publishing Group</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7RV</scope><scope>7T5</scope><scope>7T7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope></search><sort><creationdate>20170301</creationdate><title>Diurnal variations of short-term variation and the impact of multiple recordings on measurement accuracy</title><author>Seliger, G ; Petroff, D ; Seeger, S ; Hoyer, D ; Tchirikov, M ; Schneider, U</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c513t-660930fbaec8bff11e7f5b6b6692b1d02f6c7843b544326b18df653218b3dce53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>692/700/139/1449</topic><topic>Accuracy</topic><topic>Adequacy</topic><topic>Adolescent</topic><topic>Adult</topic><topic>Cardiotocography - methods</topic><topic>Childbirth & labor</topic><topic>Circadian Rhythm</topic><topic>Circadian rhythms</topic><topic>Decision analysis</topic><topic>Decision making</topic><topic>Diurnal variations</topic><topic>EKG</topic><topic>Electrocardiography</topic><topic>Female</topic><topic>Fetal Monitoring - methods</topic><topic>Fetuses</topic><topic>Germany</topic><topic>Gestational Age</topic><topic>Heart rate</topic><topic>Heart Rate, Fetal</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Linear Models</topic><topic>Measurement</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Observational studies</topic><topic>Observations</topic><topic>Obstetrics</topic><topic>original-article</topic><topic>Pediatric Surgery</topic><topic>Pediatrics</topic><topic>Pregnancy</topic><topic>Prospective Studies</topic><topic>Risk</topic><topic>Surveillance</topic><topic>Womens health</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Seliger, G</creatorcontrib><creatorcontrib>Petroff, D</creatorcontrib><creatorcontrib>Seeger, S</creatorcontrib><creatorcontrib>Hoyer, D</creatorcontrib><creatorcontrib>Tchirikov, M</creatorcontrib><creatorcontrib>Schneider, U</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Nursing & Allied Health Database</collection><collection>Immunology Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>British Nursing Database</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of perinatology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Seliger, G</au><au>Petroff, D</au><au>Seeger, S</au><au>Hoyer, D</au><au>Tchirikov, M</au><au>Schneider, U</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Diurnal variations of short-term variation and the impact of multiple recordings on measurement accuracy</atitle><jtitle>Journal of perinatology</jtitle><stitle>J Perinatol</stitle><addtitle>J Perinatol</addtitle><date>2017-03-01</date><risdate>2017</risdate><volume>37</volume><issue>3</issue><spage>231</spage><epage>235</epage><pages>231-235</pages><issn>0743-8346</issn><eissn>1476-5543</eissn><abstract>Objective:
Short-term variation (STV) from computerized cardiotocogram heart rate analysis is a parameter that complements decision making, regarding the delivery of fetuses in several high-risk situations. Although studies on the effects of gestational age and fetal pathology are convincing, there is a lack of data exploring diurnal variation and the adequacy of a single measurement.
Study Design:
In this prospective observational study, fetal STV was monitored with the AN24 fetal ECG monitor (Monica Healthcare) each hour for at least 10 h in total, beginning at different times. This resulted in data covering all 24 h of the day. Seventy fetuses, low risk with respect to conditions accessible to heart rate monitoring (median 37th week of gestation) were monitored for an average of 12 h. Results of STV per hour were categorized as ‘compromised’ (STV<4 ms) or ‘healthy’, (STV⩾4 ms) to calculate the model of predictability.
Results:
The model proposed (STV of ‘healthy’ fetuses: 9.6±2.6 ms, ‘compromised’ fetuses 3.0±0.5 ms, prevalence 1%) leads to a positive predictive value of 39%, which increased to 68 or 80% given two or three pathological (STV<4 ms) measurements, respectively. Diurnal variation was not observed.
Conclusions:
Single pathological STV values should be corroborated by further measurements in a 24-h interval in otherwise low-risk fetuses before inducing delivery. This may help to avoid unnecessary early births and give the fetus valuable days for intrauterine maturity.</abstract><cop>New York</cop><pub>Nature Publishing Group US</pub><pmid>27831546</pmid><doi>10.1038/jp.2016.202</doi><tpages>5</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0743-8346 |
| ispartof | Journal of perinatology, 2017-03, Vol.37 (3), p.231-235 |
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| source | MEDLINE; SpringerNature Journals |
| subjects | 692/700/139/1449 Accuracy Adequacy Adolescent Adult Cardiotocography - methods Childbirth & labor Circadian Rhythm Circadian rhythms Decision analysis Decision making Diurnal variations EKG Electrocardiography Female Fetal Monitoring - methods Fetuses Germany Gestational Age Heart rate Heart Rate, Fetal Hospitals Humans Linear Models Measurement Medicine Medicine & Public Health Observational studies Observations Obstetrics original-article Pediatric Surgery Pediatrics Pregnancy Prospective Studies Risk Surveillance Womens health Young Adult |
| title | Diurnal variations of short-term variation and the impact of multiple recordings on measurement accuracy |
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