• Je něco špatně v tomto záznamu ?

Data analysis of diagnostic accuracies in 12-lead electrocardiogram interpretation by junior medical fellows

T. Novotny, RR. Bond, I. Andrsova, L. Koc, M. Sisakova, DD. Finlay, D. Guldenring, J. Spinar, M. Malik,

. 2015 ; 48 (6) : 988-94. [pub] 20150812

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc16028203

BACKGROUND: The electrocardiogram (ECG) is the most commonly used diagnostic procedure for assessing the cardiovascular system. The aim of this study was to compare ECG diagnostic skill among fellows of cardiology and of other internal medicine specialties (non-cardiology fellows). METHODS: A total of 2900 ECG interpretations were collected. A set of 100 clinical 12-lead ECG tracings were selected and classified into 12 diagnostic categories. The ECGs were evaluated by 15 cardiology fellows and of 14 non-cardiology fellows. Diagnostic interpretations were classified as (1) correct, (2) almost correct, (3) incorrect, and (4) dangerously incorrect. Multivariate logistic regression was used to assess confounding factors and to determine the odds ratios for the months of experience, age, sex, and the distinction between cardiology and non-cardiology fellows. RESULTS: The mean rate of correct diagnoses by cardiology vs. non-cardiology fellows was 48.9±8.9% vs. 35.9±8.0% (p=0.001; 70.1% vs. 55.0% for the aggregate of 'correct' and 'almost correct' diagnoses). There were 10.2±5.6% of interpretations classified as 'dangerously incorrect' by cardiology fellows vs. 16.3±5.0% by non-cardiology fellows (p=0.008). The cardiology fellows achieved statistically significantly greater diagnostic accuracy in 7 out of the 12 diagnostic classes. In multivariable logistic regression, the distinction between cardiology and non-cardiology fellows was the only independent statistically significant (p<0.001) predictor of whether the reader is likely correct or incorrect. Being a non-cardiology fellow reduced the probability of correct classification by 42% (odds ratio [95% confidence interval]: 0.58 [0.50; 0.68]). CONCLUSIONS: Although cardiology fellows out-performed the others, skills in ECG interpretation were found not adequately proficient. A comprehensive approach to ECG education is necessary. Further studies are needed to evaluate proper methods of training, testing, and continuous medical education in ECG interpretation.

Citace poskytuje Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc16028203
003      
CZ-PrNML
005      
20250610101113.0
007      
ta
008      
161005s2015 xxu f 000 0|eng||
009      
AR
024    7_
$a 10.1016/j.jelectrocard.2015.08.023 $2 doi
024    7_
$a 10.1016/j.jelectrocard.2015.08.023 $2 doi
035    __
$a (PubMed)26381796
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a xxu
100    1_
$a Novotný, Tomáš, $d 1969- $u Department of Internal Medicine and Cardiology, University Hospital Brno and Faculty of Medicine of Masaryk University, Brno, Czech Republic. Electronic address: novotny-t@seznam.cz. $7 xx0055126
245    10
$a Data analysis of diagnostic accuracies in 12-lead electrocardiogram interpretation by junior medical fellows / $c T. Novotny, RR. Bond, I. Andrsova, L. Koc, M. Sisakova, DD. Finlay, D. Guldenring, J. Spinar, M. Malik,
520    9_
$a BACKGROUND: The electrocardiogram (ECG) is the most commonly used diagnostic procedure for assessing the cardiovascular system. The aim of this study was to compare ECG diagnostic skill among fellows of cardiology and of other internal medicine specialties (non-cardiology fellows). METHODS: A total of 2900 ECG interpretations were collected. A set of 100 clinical 12-lead ECG tracings were selected and classified into 12 diagnostic categories. The ECGs were evaluated by 15 cardiology fellows and of 14 non-cardiology fellows. Diagnostic interpretations were classified as (1) correct, (2) almost correct, (3) incorrect, and (4) dangerously incorrect. Multivariate logistic regression was used to assess confounding factors and to determine the odds ratios for the months of experience, age, sex, and the distinction between cardiology and non-cardiology fellows. RESULTS: The mean rate of correct diagnoses by cardiology vs. non-cardiology fellows was 48.9±8.9% vs. 35.9±8.0% (p=0.001; 70.1% vs. 55.0% for the aggregate of 'correct' and 'almost correct' diagnoses). There were 10.2±5.6% of interpretations classified as 'dangerously incorrect' by cardiology fellows vs. 16.3±5.0% by non-cardiology fellows (p=0.008). The cardiology fellows achieved statistically significantly greater diagnostic accuracy in 7 out of the 12 diagnostic classes. In multivariable logistic regression, the distinction between cardiology and non-cardiology fellows was the only independent statistically significant (p<0.001) predictor of whether the reader is likely correct or incorrect. Being a non-cardiology fellow reduced the probability of correct classification by 42% (odds ratio [95% confidence interval]: 0.58 [0.50; 0.68]). CONCLUSIONS: Although cardiology fellows out-performed the others, skills in ECG interpretation were found not adequately proficient. A comprehensive approach to ECG education is necessary. Further studies are needed to evaluate proper methods of training, testing, and continuous medical education in ECG interpretation.
650    _2
$a dospělí $7 D000328
650    _2
$a srdeční arytmie $x diagnóza $7 D001145
650    _2
$a klinické kompetence $x statistika a číselné údaje $7 D002983
650    _2
$a chybná diagnóza $x statistika a číselné údaje $7 D003951
650    _2
$a elektrokardiografie $x statistika a číselné údaje $7 D004562
650    _2
$a ženské pohlaví $7 D005260
650    _2
$a lidé $7 D006801
650    _2
$a mužské pohlaví $7 D008297
650    _2
$a odchylka pozorovatele $7 D015588
650    _2
$a lékaři $x statistika a číselné údaje $7 D010820
650    _2
$a reprodukovatelnost výsledků $7 D015203
650    _2
$a senzitivita a specificita $7 D012680
651    _2
$a Evropa $7 D005060
655    _2
$a časopisecké články $7 D016428
655    _2
$a práce podpořená grantem $7 D013485
700    1_
$a Bond, Raymond Robert $u Faculty of Computing and Engineering, Ulster University, United Kingdom.
700    1_
$a Andrsova, Irena $u Department of Internal Medicine and Cardiology, University Hospital Brno and Faculty of Medicine of Masaryk University, Brno, Czech Republic. $7 gn_A_00006740
700    1_
$a Koc, Lumir $u Department of Internal Medicine and Cardiology, University Hospital Brno and Faculty of Medicine of Masaryk University, Brno, Czech Republic.
700    1_
$a Sisakova, Martina $u Department of Internal Medicine and Cardiology, University Hospital Brno and Faculty of Medicine of Masaryk University, Brno, Czech Republic.
700    1_
$a Finlay, Dewar Darren $u Faculty of Computing and Engineering, Ulster University, United Kingdom.
700    1_
$a Guldenring, Daniel $u Faculty of Computing and Engineering, Ulster University, United Kingdom.
700    1_
$a Spinar, Jindrich $u Department of Internal Medicine and Cardiology, University Hospital Brno and Faculty of Medicine of Masaryk University, Brno, Czech Republic.
700    1_
$a Malik, Marek $u St. Paul's Cardiac Electrophysiology, University of London, and Imperial College, London, United Kingdom.
773    0_
$w MED00010003 $t Journal of electrocardiology $x 1532-8430 $g Roč. 48, č. 6 (2015), s. 988-94
856    41
$u https://pubmed.ncbi.nlm.nih.gov/26381796 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y a $z 0
990    __
$a 20161005 $b ABA008
991    __
$a 20250610101106 $b ABA008
999    __
$a ok $b bmc $g 1166517 $s 952833
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2015 $b 48 $c 6 $d 988-94 $e 20150812 $i 1532-8430 $m Journal of electrocardiology $n J Electrocardiol $x MED00010003
LZP    __
$a Pubmed-20161005

Najít záznam

Citační ukazatele

Nahrávání dat ...

Možnosti archivace

Nahrávání dat ...