-
Something wrong with this record ?
Analysis of obstetricians' decision making on CTG recordings
J. Spilka, V. Chudáček, P. Janků, L. Hruban, M. Burša, M. Huptych, L. Zach, L. Lhotská,
Language English Country United States
Document type Journal Article, Research Support, Non-U.S. Gov't
Grant support
NT11124
MZ0
CEP Register
Digital library NLK
Full text - Article
Source
NLK
Free Medical Journals
from 2001 to 1 year ago
- MeSH
- Cardiotocography statistics & numerical data MeSH
- Humans MeSH
- Decision Support Techniques * MeSH
- Observer Variation MeSH
- Obstetrics statistics & numerical data MeSH
- Reproducibility of Results MeSH
- Pattern Recognition, Automated methods MeSH
- Sensitivity and Specificity MeSH
- Decision Support Systems, Clinical * MeSH
- Artificial Intelligence * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Interpretation of cardiotocogram (CTG) is a difficult task since its evaluation is complicated by a great inter- and intra-individual variability. Previous studies have predominantly analyzed clinicians' agreement on CTG evaluation based on quantitative measures (e.g. kappa coefficient) that do not offer any insight into clinical decision making. In this paper we aim to examine the agreement on evaluation in detail and provide data-driven analysis of clinical evaluation. For this study, nine obstetricians provided clinical evaluation of 634 CTG recordings (each ca. 60min long). We studied the agreement on evaluation and its dependence on the increasing number of clinicians involved in the final decision. We showed that despite of large number of clinicians the agreement on CTG evaluations is difficult to reach. The main reason is inherent inter- and intra-observer variability of CTG evaluation. Latent class model provides better and more natural way to aggregate the CTG evaluation than the majority voting especially for larger number of clinicians. Significant improvement was reached in particular for the pathological evaluation - giving a new insight into the process of CTG evaluation. Further, the analysis of latent class model revealed that clinicians unconsciously use four classes when evaluating CTG recordings, despite the fact that the clinical evaluation was based on FIGO guidelines where three classes are defined.
References provided by Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc15023473
- 003
- CZ-PrNML
- 005
- 20181008103527.0
- 007
- ta
- 008
- 150709s2014 xxu f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1016/j.jbi.2014.04.010 $2 doi
- 035 __
- $a (PubMed)24747355
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxu
- 100 1_
- $a Spilka, Jiří $u Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic. Electronic address: spilka.jiri@fel.cvut.cz.
- 245 10
- $a Analysis of obstetricians' decision making on CTG recordings / $c J. Spilka, V. Chudáček, P. Janků, L. Hruban, M. Burša, M. Huptych, L. Zach, L. Lhotská,
- 520 9_
- $a Interpretation of cardiotocogram (CTG) is a difficult task since its evaluation is complicated by a great inter- and intra-individual variability. Previous studies have predominantly analyzed clinicians' agreement on CTG evaluation based on quantitative measures (e.g. kappa coefficient) that do not offer any insight into clinical decision making. In this paper we aim to examine the agreement on evaluation in detail and provide data-driven analysis of clinical evaluation. For this study, nine obstetricians provided clinical evaluation of 634 CTG recordings (each ca. 60min long). We studied the agreement on evaluation and its dependence on the increasing number of clinicians involved in the final decision. We showed that despite of large number of clinicians the agreement on CTG evaluations is difficult to reach. The main reason is inherent inter- and intra-observer variability of CTG evaluation. Latent class model provides better and more natural way to aggregate the CTG evaluation than the majority voting especially for larger number of clinicians. Significant improvement was reached in particular for the pathological evaluation - giving a new insight into the process of CTG evaluation. Further, the analysis of latent class model revealed that clinicians unconsciously use four classes when evaluating CTG recordings, despite the fact that the clinical evaluation was based on FIGO guidelines where three classes are defined.
- 650 12
- $a umělá inteligence $7 D001185
- 650 _2
- $a kardiotokografie $x statistika a číselné údaje $7 D015148
- 650 12
- $a systémy pro podporu klinického rozhodování $7 D020000
- 650 12
- $a metody pro podporu rozhodování $7 D003661
- 650 _2
- $a lidé $7 D006801
- 650 _2
- $a odchylka pozorovatele $7 D015588
- 650 _2
- $a porodnictví $x statistika a číselné údaje $7 D009774
- 650 _2
- $a rozpoznávání automatizované $x metody $7 D010363
- 650 _2
- $a reprodukovatelnost výsledků $7 D015203
- 650 _2
- $a senzitivita a specificita $7 D012680
- 655 _2
- $a časopisecké články $7 D016428
- 655 _2
- $a práce podpořená grantem $7 D013485
- 700 1_
- $a Chudáček, Václav $u Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic.
- 700 1_
- $a Janků, Petr $u Department of Gynecology and Obstetrics, Teaching Hospital of Masaryk University in Brno, Czech Republic.
- 700 1_
- $a Hruban, Lukáš $u Department of Gynecology and Obstetrics, Teaching Hospital of Masaryk University in Brno, Czech Republic.
- 700 1_
- $a Burša, Miroslav $u Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic.
- 700 1_
- $a Huptych, Michal $u Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic.
- 700 1_
- $a Zach, Lukáš $u Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic.
- 700 1_
- $a Lhotská, Lenka $u Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic.
- 773 0_
- $w MED00006571 $t Journal of biomedical informatics $x 1532-0480 $g Roč. 51, č. - (2014), s. 72-79
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/24747355 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y a $z 0
- 990 __
- $a 20150709 $b ABA008
- 991 __
- $a 20181008104013 $b ABA008
- 999 __
- $a ok $b bmc $g 1083810 $s 906466
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2014 $b 51 $c - $d 72-79 $i 1532-0480 $m Journal of biomedical informatics $n J Biomed Inform $x MED00006571
- GRA __
- $a NT11124 $p MZ0
- LZP __
- $a Pubmed-20150709