Fetal echocardiography for congenital heart disease diagnosis: a meta-analysis, power analysis and missing data analysis.

European Journal of Preventive Cardiology http://cpr.sagepub.com/

Fetal echocardiography for congenital heart disease diagnosis: a meta-analysis, power analysis and missing data analysis Hong Liu, Jie Zhou, Qiao-Ling Feng, Hai-Tao Gu, Gang Wan, Huo-Ming Zhang, Yong-Jun Xie and Xiao-Song Li European Journal of Preventive Cardiology published online 25 September 2014 DOI: 10.1177/2047487314551547 The online version of this article can be found at: http://cpr.sagepub.com/content/early/2014/09/25/2047487314551547

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EURO PEAN SO CIETY O F CARDIOLOGY ®

Original scientific paper

Fetal echocardiography for congenital heart disease diagnosis: a meta-analysis, power analysis and missing data analysis

European Journal of Preventive Cardiology 0(00) 1–17 ! The European Society of Cardiology 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/2047487314551547 ejpc.sagepub.com

Hong Liu1,2,3,*, Jie Zhou4,*, Qiao-Ling Feng5,*, Hai-Tao Gu1,2,3, Gang Wan6, Huo-Ming Zhang7, Yong-Jun Xie8 and Xiao-Song Li9

Abstract Background: Prenatal ultrasonography is the most widely available diagnostic test for fetal congenital heart disease (CHD), but the factors influencing its diagnostic accuracy remain uncertain despite extensive research. The aim of the present study was to evaluate the potential role of demographic, clinical and ultrasonographic characteristics on diagnostic yields for detecting CHD. Methods: A systematic search of PubMed, ISI Web of Science, SinoMed, and the Cochrane Library was performed to identify studies assessing the accuracy of prenatal ultrasound in the detection of CHD. A random effects model was used to generate pooled sensitivity and specificity in addition to summary receiver operating characteristic (SROC) curves. Results: Overall, prenatal ultrasound in the detection of CHD had a moderate sensitivity of 68.1% (95% CI 59.6–75.5) and a favorable specificity of 99.9% (99.7–99.9). Risk level and gestation age were independent predictors of diagnostic performance for detecting CHD (p ¼ 0.004 vs. p ¼ 0.002, respectively). The pooled sensitivities significantly increased to varying extents with the following echocardiographic views: 48.7% (34.8–67.2) for four-chamber view (4CV); 58.0% (40.3–73.9) for a combination of 4CV and outflow tract views (OTV); 73.5% (59.2–84.1) for combination of 4CV, OTV and three vessels and trachea view (3VTV); 77.1% (62.0–87.5) for extensive cardiac echocardiography examination (ECEE); and 89.6% (81.0–94.6) for spatiotemporal image correlation (STIC). Conclusions: Prenatal ultrasound is a powerful tool for the diagnosis of CHD; however, a single ultrasonographic regime is not definitive on its own and must be interpreted in the context of demographic and clinical characteristics.

Keywords Heart defect, congenital, echocardiography, fetus, pediatrics Received 4 June 2014; accepted 26 August 2014

1

Department of Cardiothoracic Surgery, First Affiliated Hospital of Nanjing Medical University, PR China 2 Collaborative Group of Congenital Heart Disease, Department of Pediatric Cardiology, Jiangsu Women’s and Children’s Health of Nanjing Medical University, PR China 3 Research Institute of Heart, Lung and Blood Vessel Diseases, Jiangsu Provincial Academy of Clinical Medicine, PR China 4 Study Group of Echocardiography, Department of Sonographic Diagnostic Medicine, First Affiliated Hospital of Nanjing Medical University, PR China 5 Key Laboratory of Diagnostic Medicine of Education Ministry, Institute of Laboratory Medicine, Chongqing Medical University, PR China 6 Department of Radiology, General Clinical Center for Radiation Oncology, Affiliated Cancer Hospital of Guangxi Medical University, PR China

7 Institute of Fluid Measurement and Simulation, Department of Mechanics, College of Metrology & Measurement Engineering, China Jiliang University, PR China 8 National Experimental Center for Medical Simulation of China, Laboratory of Anthropotomy & Histo-Embryology, School of Basic Medical Sciences, Chengdu Medical College, PR China 9 Department of Health Statistics, National Center for Chinese Clinical Trial Register, School of Public Health, Sichuan University Western China School of Medicine, PR China

*Hong Liu, Jie Zhou and Qiao-Ling Feng contributed equally to this work. Corresponding author: Hai-Tao Gu, Collaborative Group of Congenital Heart Disease, Department of Cardiothoracic Surgery, First Affiliated Hospital of Nanjing Medical University, 140 Guangzhou Road, Nanjing 210029, Jiangsu, PR China. Email: [email protected]



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Introduction Congenital heart disease (CHD) is the most common birth abnormality, with an estimated incidence of approximately 4–13 per 1000 live births.1–3 According to the WHO,4 cardiac defects account for 42% of infant deaths and have become the leading cause of infant mortality. Both short- and long-term prognostic outcomes for fetuses with cardiac anomalies have shown encouraging improvements since the advent of prenatal ultrasonography, which is at present the most powerful tool for detecting fetal CHD.5–9 However, of all possible cardiac defects, structural cardiac anomalies are still most frequently missed by prenatal ultrasonographic detection.10,11 These miss rates vary widely12 because of differences in examiner experience, maternal obesity, abdominal scars, amniotic fluid volume and fetal position.13,14 The ISUOG has recently updated the Practice Guidelines15 for sonographic screening examinations of fetal hearts to include outflow tract views (OTV) and four-chamber views (4CV) among the procedures recommended during routine screenings.16 The new Practice Guidelines for prenatal detection are mainly available for the evaluation of mid-gestation fetuses,17–20 but uncertainties linger regarding different risk populations or during the first trimester. Unfortunately, in the guidelines, the use of three vessels and trachea view (3VTV)21,22 and color Doppler flow imaging (CDFI)23,24 is not mandatory, although it is at times attempted. Moreover, the increasingly available M-mode and three-dimensional (3D/4D) volume spatiotemporal image correlation (STIC)25 were only briefly mentioned, with insufficient details, in the guidelines. Although trans-vaginal sonography (TVS) in the first trimester was proposed for fetal screening in the AIUM Practice Guidelines in addition to trans-abdominal sonography (TAS) in the second trimester,26 no specialized guidelines were dedicated to fetal CHD diagnosis. Previous studies have focused on the individual diagnostic performance of prenatal sonographic detection of fetal CHD in specific risk populations,27 gestational ages28,29,30 and echocardiographic views31,32. However, no consensus has been reached as to the optimal examination approach for cardiac screening because of lack of direct comparisons of different indices. Therefore, with the assistance of missing data analysis, power analysis and regression analysis, we performed this systematic review dedicated to bettering understanding of the demographic, clinical and echocardiographic characteristics of CHD and to determining the diagnostic accuracy of prenatal ultrasonography for diagnoses of CHD. Prospectively designed studies were particularly valuable because of their superior methodological evidence.

Methods Conception and design The study’s design was elaborated by a multidisciplinary effort based on the methodological approaches outlined in the Cochrane Handbook for Systematic Review of Diagnostic Test Accuracy. This study was registered as CRD42014009763 at the Center of Review and Dissemination (CRD) of York University, the NIHR International Prospective Register of Systematic Reviews.

Eligibility criteria for considering studies The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement was used as a guideline to conduct this analysis.33 Articles were identified by searches using the PICOS criteria detailed in PRISMA, including participants (P): fetus with cardiac defects; interventions (I): ultrasonographic regimes; comparisons (C): reference standards such as postnatal ultrasonography; outcome (O): diagnostic sensitivity and specificity; and study designs (S): prospective design.

Search methods for the identification of studies A systematic electronic literature search of PubMed, ISI Web of Science, SinoMed and the Cochrane Library was performed to identify studies assessing the accuracy of prenatal ultrasonography for CHD diagnosis until April 2014, with languages restricted to only English or Chinese. Further relevant articles were retrieved for recall completion by searching the reference lists of the identified trials, as well as other related systematic and narrative reviews.

Study selection and data extraction Three investigators independently identified original articles using pre-specified inclusion and exclusion criteria. The inclusion criteria favored studies comparing prenatal ultrasonography with a reference standard. The exclusion criteria were as follows: sample size less than 15 patients, inability to obtain either two-by two tables or data allowing their construction, and overlapping patient data in different studies. Disagreement over the eligibility of any study was resolved by discussion until a consensus was reached. Among the full articles included, several overall data items were extracted independently regarding relevant demographic, clinical and echocardiographic parameters and diagnosis-related variables, such as true positives, true negatives, false positives and false negatives.



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Additional data were requested from the original study investigators if necessary.

Assessment of methodological quality The methodological quality was assessed independently by a subset of criteria from the Quality Assessment of Studies of Diagnostic Accuracy included in Systematic Reviews (QUADAS).34 Discrepancies in judgment were resolved by consensus.

Data synthesis and analysis Data analysis. Diagnostic indices were pooled using DerSimonian-Laird’s random effects model35 depending on the presence of heterogeneity. Summary receiver operating characteristic (SROC) curves were constructed to summarize the studies’ results using a Littenberg-Moses regression model.36 Each study was analyzed based on inverse variance weights. To detect heterogeneity, diagnostic odds ratios (DORs) were analyzed using 2 tests; to quantify the extent of heterogeneity, I2 statistics were used.37 Meta-regression and subgroup analysis. Meta-regression was performed to evaluate the importance of potential effect variables explaining variation between studies.36,37 Relative diagnostic odds ratios (RDOR) were calculated using meta-regression random effects models to evaluate the diagnostic performance. Subgroup analysis was performed to address the statistical heterogeneity derived from the meta-regression analysis and the clinical heterogeneity arising from differences in echocardiographic variables. Area under curves (AUCs) between subgroups were graphically displayed using SROC curves.38 Additional analysis. Spearman rank correlation was performed to explore the threshold effect.36,39 The missing data were analyzed if they were still unavailable despite contacting the authors using a predictive model based on multiple imputations40 to reduce potential bias and to increase the accuracy of subsequent analysis.41,42 We evaluated the pre-test probabilities of risk populations versus corresponding post-test probabilities, depending on the summary sensitivity and specificity by Fagan plot analysis.43,44 Publication bias was examined visually by inspecting the funnel plots and statistically using Egger’s regression model.45,46 Power analysis, which is used to determinate how likely the statistical testing of an individual study would be able to detect the effects of a given sample size in a particular situation for a matched pair design with a binary response outcome, was performed for each of the studies included according to the formula derived by Lachin.47

All analyses were conducted using the MADIS module of Stata version 10 (Stata Corp, College Station, TX, USA), except for those of publication bias, which used Meta-Analyst Beta 3.13 (Tufts Medical Center, Boston, MA, USA); of meta-regression and threshold, which used Meta-DiSc version 1.4 (Clinical Biostatistics Unit, Ramoń y Cajal Hospital, Madrid, Spain); and of missing data, which used SOLAS version 4.1 (Statistical Solutions, Boston, MA, USA).

Results Literature search results A total of 1798 potentially relevant articles were retrieved by the aforementioned methods, of which 873 were initially considered potentially eligible after removing the duplicates. Ultimately, a total of 58 comparisons in 42 articles on fetal CHD diagnosis were included for analysis (Figure 1). The demographic, clinical and echocardiographic baseline characteristics are displayed in Tables 1 and 2.

Quality assessment Using the items for evaluating diagnostic studies with QUADAS-2, the risk of bias and applicability concerns for all studies were assessed. Overall, most studies had a moderate methodological quality with very minimal concerns regarding the applicability of the test in clinical practice.

Threshold analysis Spearman rank correlations of sensitivity against (1–specificity) were performed to further explore any threshold effects. The overall result suggested that there was no indication of any threshold effect (Spearman correlation coefficient: 0.167, p ¼ 0.210).

Meta-regression analysis Overall, prenatal ultrasonography for the detection of fetal CHD had a moderate sensitivity of 68.1% (95% CI 59.6–75.5) and the high specificity of 99.9% (99.7– 99.9). Out of all of the parameters, the risk level and gestational age were significant sources of heterogeneity for univariate analysis (p ¼ 0.016 vs. p ¼ 0.011, respectively). Simultaneously, risk level and gestation age were independent predictors for multivariate analysis (p ¼ 0.004 vs. p ¼ 0.002, respectively) of diagnostic performance, which was strongly associated with the diagnostic accuracy of prenatal ultrasonography for CHD diagnosis. However, none of the other demographic



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Identification

PRISMA 2009 Flow Diagram

1750 Citations identified through database searching

48 Additional records identified through other sources

1798 Potentially relevant articles

Screening

925 Records removed for duplicates

873 Relevant articles for initial eligibility

Eligibility

626 Excluded based on title/abstract 384 Unrelated to the study 125 Review articles 78 Case reports 21 Unable to translate in English 17 Could not be retrieved 147 Full-text articles assessed for eligibility

Included

105 Excluded by full-text articles 45 Unsuitable study design 26 Unable to construct table 17 Possible overlapping data 13 Included less than 15 patients 4 Unable to derive specificity

42 Articles included in quantitative synthesis (meta-analysis)

Figure 1. Flow chart of the search strategy and selection of reports.

variables, clinical variables or echocardiographic variables were statistically significant sources of variability (p > 0.05) for univariate and multivariate analysis (Table 3).

Comparison of risk level population and gestational age Prenatal ultrasonography for the median-risk population had the highest sensitivity, followed by high,

unselected and low risk. Specificity for the high-risk population was inferior to that for the low, unselected and median risks. RDOR for the low risk was similar to that for the unselected risk (p > 0.05) and high risk (p > 0.05). Three studies77,82,88 were excluded because of their case-controlled designs. Both sensitivity and specificity in the second and third trimesters were superior to those in the first trimester (p < 0.05). RDOR in the second and third trimester was higher than that in the first trimester (p < 0.05). One study75 was excluded


TRC

Stumpflen 199657


TRC

TRC

TRC

TRC

Carvalho 199861

Zosmer 199962

Zosmer 199962

Stefos 199963

TRC

TRC

TRC

TRC&DGH

TRC

Rustico 200065

Rustico 200065

Haak 200266

Comas Gabriel 200267

Galindo 200368

TRC

TRC

Kirk 199760

Ozkutlu 1999

TRC&DGH

Todros 199759

64

TRC

Hsieh 199658

TRC

TRC

Stumpflen 199657

Hsieh 1996

TRC&DGH

Buskens 199656

Multiple

Multiple

Single

Single

Single

Single

Single

Single

Single

Single

Single

Multiple

Single

Single

Single

Single

Multiple

Single

Single

Single

Single

Single

Single

Multiple

Single

Single

Single

Spain

Spain

Netherlands

Italy

Italy

Turkey

Greece

UK

UK

UK

USA

Italy

Chinese Taipei

Chinese Taipei

Australia

Australia

Netherlands

Italy

USA

USA

Israel

USA

Israel

UK

UK

Italy

Japan

Geographic area

5 (1997–2001)

3 (1999–2001)

3a

7 (1991–1997)

7 (1991–1997)

3 (1996–1998)

7 (1990–1996)

2 (1997–1998)

2 (1997–1998)

3 (1995–1997)

3 (1993–1995)

5 (1991–1995)

6 (1990–1995)

6 (1990–1995)

2 (1993–1994)

2 (1993–1994)

3 (1991–1993)

7 (1986–1992)

3 (1991–1993)

3 (1991–1993)

3 (1991–1993)

3 (1990–1992)

3 (1988–1990)

3 (1988–1990)

4 (1988–1991)

5 (1985–1989)

3 (1984–1986)

Study period/range (year)

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Study design

32 (16–44)

17–46

32 (24–42)

30 (17–43)

30 17–43)

29 (16–41)

31b

32b

32b

30b

28b

30b

31b

31b

35b

31b

29 (14–47)

15–39

31b

30b

29b

28b

25 (18–45)

30b

31b

31b

31b

Maternal age (years)

3 months AB

3 months AB

1 year AB

3 months AB

3 months AB

AB

3 months AB

3 weeks AB

3 weeks AB

AB

AB

5 days AB

AB

AB

4 years AB

4 years AB

6 months AB

24 months AB

AB

AB

AB

AB

AB

3 months AB

1 week AB

1 week AB

AB

Follow-up period

353

334

40

221

4785

128

7236

323

75

15

16,121

8299

1659

826

904

2181

5319

7024

1136

886

660

6244

5347

23,861

8523

9016

299

Number of fetus

32/353 (90.65%)

48/334 (143.71%)

13/40 (325.00%)

5/221 (22.62%)

41/4785 (8.57%)

9/128 (70.31%)

31/7236 (4.28%)

27/323 (83.59%)

2/75 (26.67%)

4/15 (266.67%)

111/16,121 (6.86%)

40/8299 (4.82%)

61/1659 (36.78%)

9/826 (10.90%)

35/904 (38.72%)

17/2181 (7.80%)

44/5319 (8.27%)

65/7024 (9.25%)

14/1136 (12.32%)

16/886 (18.06%)

9/660 (13.64%)

54/6244 (8.65%)

23/5347 (4.30%)

69/23,861 (2.90%)

25/8523 (2.93%)

47/9016 (5.21%)

6/299 (20.07%)

CHD prevalence

PECHO/ PM A

PECHO/ PM A

LPECHO /PECHO / PM A



PECHO/ PMA/angiography

PECHO /PM A

LPECHO/PECHO/ PM A

LPECHO/PECHO/ PM A

PLECHO/PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO

PECHO

PLECHO/PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

Reference standard

(continued)

Y (NP)

Y (27/48)

Y (10/13)

Y (NP)

Y (12/41)

N

Y (NP)

Y (4/29)

Y (4/29)

Y (NP)

Y (13/111)

N

N

N

Y (13/35)

Y (4/17)

N

Y (11/65)

Y (10/30)

Y (10/30)

N

N

Y (2/23)

N

Y (2/9)

Y (21/47)

N

Karyotype analysis

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58

TRC

TRC

Rustico 199555

Ott 1995

54

TRC

TRC

Kirk 199452

Ott 199554

TRC

Achiron 199251

TRC

DGH

Sharland 199214

Achiron 199453

TRC

DGH

Luck 199250

Vergani 1992

DGH

Hata 198848

49

Setting

Author/year

Study centre

Table 1. Baseline demographic and clinical characteristics of included studies.

XML Template (2014) [24.9.2014–9:34am] //blrnas3.glyph.com/cenpro/ApplicationFiles/Journals/SAGE/3B2/CPRJ/Vol00000/140126/APPFile/SG-CPRJ140126.3d [1–17] [PREPRINTER stage]

TRC

TRC

TRC

TRC&DGH

TRC&DGH

TRC

TRC

TRC

TRC

TRC&DGH

TRC

TRC

TRC

TRC&DGH

TRC

TRC

TRC&DGH

Tegnander 200674

Plesinac 200775

Thangaroopan 200876

Paladini 200877

Vinals 200878

Bennasar 200979

Bennasar 200979

Wu 200980

Xu 200981

Espinoza 201082

Bennasar 201083

Bennasar 201083

Yagel 201184


Abdul Haium 201185

Prats 201286

He 201387

Votino 201388 Multiple

Single

Single

Multiple

Single

Single

Single

Multiple

Single

Single

Single

Single

Multiple

Multiple

Multiple

Single

Single

Single

Multiple

Multiple

Single

Single

Single

Study centre

Belgium and Lebanon

PR China

Spain (Europe)

UK

Israel

Spain

Spain

USA and Italy and Israel and Chile

PR China

PR China

Spain

Spain

Chile and UK and Peru

Italy

Canada

Serbia

Norway

Norway

PR China

Italy

Germany

Turkey

PR China

Geographic area

4 (2009–2012)

2 (2010–2011)

7 (2003–2009)

13 (1997–2009)

5 (2005–2009)

2

2

4 (2006–2009)

2 (2006–2007)

1 (2007)

2 (2006–2007)

2 (2006–2007)

3a

4 (2005–2008)

12 (1994–2005)

5 (1999–2003)

11 (1991–2001)

11 (1991–2001)

3 (2003–2004)

3 (2002–2004)

8 (1997–2004)

5 (1999–2003)

6 (2000–2005)

Study period/range (year)

Prospective/case–control

Prospective/ Cohort

Prospective/cohort

Prospective/cohort (ongoing)

Prospective/cohort

Prospective/cohort

Prospective/cohort


Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cross-section (pilot study)


Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Prospective/cohort

Study design

31 (18–48)

29 (17–43)

33 (17–55)

31b

30b

32 (16–43)

32 (16–43)

NP

28 (18–48)

30 (20–40)

35 (23–44)

35 (23–44)

33 (26–41)

NP

28

19–48

29 (15–53)

29 (15–53)

30 (20–48)

29b

35 (15–46)

28 (18–42)

33b

Maternal age (years)

AB

AB

AB

AB

AB

1–49 months AB

1–49 months AB

AB

2–6 months AB

6 months AB

AB

AB

28 days AB

AB

4–96 months AB

37 months AB

2–13 years AB

2–13 years AB

1 month AB

1 week AB

2 weeks AB

AB

4 weeks AB

Follow-up period

121

1,080

9483

64,681

13,101

335 STIC

342 (2-D)

45

4882

8025

24 high risk

45 low risk

35

364

276

517

29,460

29,460

1788

6368

3094

642

383

Number of fetus

27/121 (223.14%)

189/1080 (175.00%)

48/9483 (5.06%)

199/64,681 (3.08%)

193/13,101 (14.73%)

175/335 (522.39%)

175/342 (511.70%)

45/50 (900.00%)

73/4882 (14.95%)

32/8025 (39.88%)

11/69 (154.42%)

11/69 (154.42%)

5/35 (142.86%)

135/364 (370.88%)

41/276 (148.55%)

71/517 (137.33%)

345/29,460 (11.71%)

97/29,460 (3.29%)

38/1788 (21.25%)

58/6368 (9.11%)

38/3094 (12.28%)

45/642 (70.09%)

30/383 (78.33%)

CHD prevalence

LPECH/PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/PM A

PECHO/PMA

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/ PM A

PECHO/PMA/ Surgery

PECHO/ PMA/ Surgery

PECHO/ PM A

PECHO/ PM A

PECHO/ PMA/ CA

PECHO/PMA/ Surgery

PECHO/ PM A

PECHO/ PM A

PECHO/ PMA

PECHO/ PM A

PLECHO/ PECHO / PM A

PECHO/ PMA/ Angiography

PECHO/ PM A

Reference standard

N

N

Y (14/48)

Y (27/199)

N

N

N

N

Y (7/23)

Y (4/26)

Y (1/11)

Y (1/11)

Y (3/5)

N

N

Y (9/71)

Y (27/345)

Y (37/97)

Y (NP)

Y (NP)

Y (NP)

N

Y (7/30)

Karyotype analysis

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CHD: congenital heart disease; TRC: tertiary referral center; DGH: district general hospital; AB: after birth, PECHO: postnatal echocardiography; LPECHO: late perinatal echocardiography; PMA: postmortem autopsy; NP: not provided; CA: clinical assessment; Y: karyotype analysis was performed; N: karyotype analysis was not performed. a Ratio of congenital heart disease with abnormal karyotypes to congenital heart disease, with or without. bThe missing data were completed using multiple imputations based on a predictive model method.

TRC

Tegnander 200674

Zhu 2006

TRC

TRC&DGH

Ogge 200672

73

TRC

TRC

Becker 200671

Ozkutlu 2005

TRC

Zhou 200569

70

Setting

Author/year

Table 1. Continued.


19

Unselected

Luck 199250

Low risk

Low risk

High risk

Low risk

Low risk

Low risk

Low risk

Low risk

Low risk

High risk

Medium risk (low and high)

Low risk

Unselected

High risk

High risk

High risk

Unselected

High risk

Unselected

High risk

High risk

High risk

High risk

High risk

High risk

High risk

Achiron 199453

Ott 1995/a54

Ott 1995/b54

Rustico 1995/a55

Rustico 1995/b55

Buskens 1996/a56

Buskens 1996/b56

Stumpflen 1996/a57

Stumpflen 1996/b57

Hsieh 199658

Todros 199759

Kirk 199760

Carvalho 199861

Zosmer 1999/a62

Zosmer 1999/b62

Stefos 199963

Ozkutlu 199964

Rustico 2000/a65

Rustico 2000/b65

Haak 200266

Comas Gabriel 200267

Galindo 200368

Zhou 2005/a69

Zhou 2005/b69

Ozkutlu 200570

Low risk

Kirk 1994/b52

Kirk 1994/a52

Low risk

Low risk

51

Achiron 1992/b51

Achiron 1992/a

Sharland 1992


18–39

12–17

12–17

19 (12–35)

14.2 (12–17)

11–14

13–15

13–15

15–37

18–22

17–22

11–14

12–13

18 (14–42)

18–40

16–36

27(18–28)

27(18–28)

19 (16–24)

19 (16–24)

20–22

Unselected

Unselected

Unselected

Major

Unselected

Unselected

Unselected

Unselected

Unselected (major/minor)

Unselected

Major

Major

Major

Major

Unselected

Major

Unselected

Unselected

Unselected

Major

Unselected

Unselected

Unselected

Unselected

Unselected

Unselected

Unselected

Unselected

Unselected

Unselected

Unselected

Unselected

Unselected

CHD Spectrum

BCM

BCM

BCM

BCM

BCM

BCM

BCM

BCM

BCM

BCM

BCM

BCM

BCM

BCM

BCM

BCM

BCM

BCM

B-mode

B-mode

BCM

B-mode

BCM

BCM

BCM

BCM

BCM

BCM

BCM

B-mode

B-mod

B-mode

BCM

Echomodality

TAS

TAS

TAS

TASþ TVS

TASþTVS

TVS

TVS

TVS

TAS

TAS

TASþTVS

TASþTVS

TAS

TAS

TAS

TAS

TAS

TAS

TAS

TAS

TAS

TAS

TAS

TAS

TVS

TAS

TAS

TAS

TAS

TAS

TAS

TAS

TAS

Echoapproach

ECEE

4CVþDV(4CV)

4CV

4CVþDV

ECEE

ECEE

4CVþOTV

4CVþOTV

4CVþOTV

4CV

4CVþOTV

4CVþOTV

4CVþOTV

4CVþOTV

4CV

ECEE

4CVþOTV

4CVþOTV

4CV

4CV

BCEE

BCEE

4CVþOTV

4CVþOTV

ECEE

4CVþOTV

4CV

ECEE

4CV

4CV

4CV

4CV

ECEE

Echo-views

2.5, 5.0 MHz

3.5, 6.9 MHz

3.5, 6.9 MHz

3.0–7.5 MHz

3.0, 7.5 MHz

4.0, 8.0 MHz

5.0 MHz

5.0 MHz

3.5, 5.0 MHz

3.5, 3.75 MHz

NP

NP

5.0 MHz

NP

NP

3.5, 5.0 MHz

3.5 MHz

3.5 MHz

3.5, 3.75 MHz

3.5, 3.75 MHz

3.5 MHz

5.0 MHz

NP

NP

6.5, 7.5 MHz

NP

NP

3.0–5.0 MHz

3.0–5.0 MHz

3.5, 5.0 MHz

3.5, 5.0 MHz

3.5, 5.0 MHz

3.5, 5.0 MHz

Transducer frequency

42

25

18

31

38

7

5

4

7

14

24

2

1

73

6

67

31

15

2

2

9

14

2

10

3

36

24

18

11

53

9

33

3

True positive

0

1

1

0

0

1

3

1

0

2

0

0

0

12

6

2

0

0

5

5

3

5

12

2

0

3

1

1

1

96

2

2

0

False positive

3

5

12

1

10

6

0

37

2

17

3

0

3

38

34

3

4

2

42

10

25

17

12

6

6

10

27

5

12

16

16

14

3

False negative

597

352

352

321

286

26

213

4743

119

7203

296

73

11

15998

8253

2413

869

2164

5270

5302

3908

3043

1110

868

651

5068

5915

5323

5323

23696

8498

8967

293

True negative

642

383

383

353

334

40

221

4785

128

7236

323

75

15

16,121

8299

2485

904

2181

5319

5319

3945

3079

1136

886

660

5111

5967

5347

5347

23,861

8523

9016

299

Statistical inclusion

642

401

401

353

334

45

221

4785

128

7236

323

75

15

1

1

1

0.25

1

0.84

1

1

0.94

1

1

0.03

0.34

1

1

0.74

1

1

1

1

1

1

0.03

1

1

1

1

1

1

1

1

1

1

Post power

(continued)

16,121

8638

2512

904

2181

6571

6571

3945

3079

1136

886

660

6244

6244

5400

5400

23,861

8849

9016

299

Initial inclusion

(CPR)

20–22

15–40

15–40

13–15

18 (14–42)

23 (14–42)

21 (18–24)

21 (18–24)

18

18–20

Unselected

Unselected

20–40

Unselected

Hata 198848

Vergani 199249

14

Gestation age (week)

Author/year

Risk level

Table 2. Baseline echocardiographic and statistical characteristics for the included studies.


Liu et al. 7

18 (16–22) –

Low Risk

Low Risk

High Risk

Unselected

Unselected

High risk

High risk

Normal: CHD ¼ 16:10

High risk



Unselected

Unselected

Unselected

Normal: CHD¼45:45

High risk

High risk



Low risk

Low risk

Unselected

High risk

High risk

Ogge` 2006/a72

Ogge` 2006/b72

Zhu 200673

Tegnander 2006/a74

Tegnander 2006/b74

Plesinac 200775

Thangaroopan 200876

Paladini 200877

Vinals 200878

Bennasar 2009/a79

Bennasar 2009/b79

Wu 2009/a80

Wu 2009/b80

Xu 200981

Espinoza 201082

Bennasar 2010/a83

Bennasar 2010/b83

Yagel 2011/a84

Yagel 2011/b84

Abdul Haium 201185

Prats 201286


He 201387

Votino 2013/a88

Votino 2013/b88 Unselected

Unselected

Unselected

Unselected

Major

Unselected

Unselected

3D/4D volume

BCM

3D/4D volume

BCM

BCM

3D/4D volume

BCM

3D/4D

BCM

3D/4D volume

BCM

BCM

BCM

TASþTVS

TASþTVS

TAS

TASþTVS

TAS

TVSþTAS

TVSþTAS

TAS

TAS

TAS

TAS

TAS

TAS

TVS

TVS

TASþTVS

TAS

TAS

TAS

TAS

TAS

TAS

TAS

TAS

TASþTVS

Echoapproach

STIC

ECEE

STIC

4CVþDV(4CV)

4CVþOTV

STIC

ECEE

STIC

ECEE

STIC

4CVþOTVþ3VTV

4CVþOTVþ3VTV

4CV

STIC

ECEE

STIC

STIC

ECEE

ECEE

4CVþOTV

4CVþOTV

ECEE

4CVþOTV

4CV

ECEE

Echo-views

5.0–12.0 MHz

5.0–12.0 MHz

NP

NP

NP

5.0–12.0 MHz

5.0–12.0 MHz

4.0, 8.0 MHz

4.0, 8.0 MHz

NP

3.5, 5 MHz

3.5–5 MHz

3.5, 5.0 MHz

5.0, 9.0 MHz

5.0, 9.0 MHz

4.0, 8.0 MHz

NP

3.5, 7.5 MHz

NP

3.5, 5.0 MHz

3.5, 5.0 MHz

3.5, 5.0 MHz

NP

NP

8.0, 14.0 MHz

Transducer frequency

18

22

184

6

131

181

169

166

172

42

50

26

21

10

10

3

111

4

67

12

55

35

38

35

32

True positive

5

2

4

408

0

0

0

19

17

2

1

4

4

0

2

3

29

6

1

0

1

1

16

14

0

False positive

8

5

5

42

68

12

24

9

3

3

23

6

11

1

1

2

24

35

4

333

42

3

20

23

6

False negative

84

92

887

9027

64482

12908

12908

141

150

43

4808

7989

7989

53

51

27

195

231

445

29115

29362

1749

6294

6296

3056

True negative

115

121

1080

9483

64,681

13,101

13,101

335

342

90

4882

8025

8025

64

64

35

364

276

517

29,460

29,460

1788

6368

6368

3094

Statistical inclusion

139

139

1286

9483

64,681

13,101

13,101

363

363

90

5000

8025

8025

69

69

49

364

353

517

30149

30149

2063

9074

9074

3363

Initial inclusion

0.26

0.59

0.12

1

1

1

1

0.67

0.98

0.08

1

1

1

0.14

0.21

0.09

0.14

0.02

0.95

1

1

1

1

1

1

Post power

BCM: B-mode þ Color Doppler flow imaging(CDFI) þ M-mode; 4CV: four chamber view; OTV: outflow tract view; 3VTV: three vessel trachea view; ECEE: extend cardiac echography examination; STIC: spatio-temporal image correlation; TVS: trans-vaginal sonography; TAS: trans-abdominal sonography; Echo: echocardiography; DV: ductus venosus; Major: definitely considered detectable prenatally; Minor: possibility of prenatal detection is debatable because of size, location or nature of the anomaly; CHD: congenital heart disease; NP: not provided.

13 (11–14)

13 (11–14)

26 (19–37)

11–13

19–22

14–24

14–24

Unselected

Unselected

Unselected

Unselected

Major

Major

3D/4D volume

BCM

3D/4D volume

3D/4D volume

BCM

BCM

BCM

BCM

BCM

B-mode

B-mode

BCM

Echomodality

8

24(11–41)

24 (11–41)

18–26

18–40

20–24

20–24

Unselected

Unselected

Unselected

Major

Unselected

Unselected

Minor

major

Unselected

Unselected

Unselected

Major

CHD Spectrum

(CPR)

13 (11–15)

13 (11–15)

12 (10–14)

20

21 (16–37)

18 (16–22)

26.5 (16–42)

18–24

18–24

11–13


Becker 200671

Gestation age (week)

Risk level

Author/year

Table 2. Continued.




(CPR)


Liu et al.

9 Table 3. Meta-regression analysis of covariates to determine the diagnostic accuracy of echocardiography for fetal congenital heart diseases. Variables Demographic variables Study perioda Publish yeara Study centera Study settinga Clinical variables Maternal agea Reference standarda Study designa CHD spectruma Risk levela Risk levelb Gestational agea Gestational ageb Echocardiographic variables Modalitya Approacha Viewsa

Coefficient

Standard error

RDOR (95%CI)

p

0.260 0.544 1.173 1.262

0.595 0.714 0.738 0.056

1.30 1.72 0.31 0.28

(0.39–4.28) (0.41–7.21) (0.07–1.36) (0.08–1.03)

0.664 0.450 0.118 0.056

0.169 0.285 1.747 1.121 0.974 1.097 1.820 2.169

0.471 0.707 1.338 0.746 0.3905 0.3621 0.693 0.6635

0.84 0.75 0.17 3.07 2.65 3.00 6.17 8.75

(0.33–2.17) (0.18–3.10) (0.01–2.54) (0.69–13.67) (1.21–5.80) (1.45–6.19) (1.54–24.73) (2.31–33.08)

0.720 0.689 0.197 0.138 0.016 0.004 0.011 0.002

0.786 0.471 0.303

0.691 0.653 0.263

2.19 (0.55–8.77) 1.60 (0.43–5.92) 1.35 (0.80–2.29)

0.260 0.474 0.253

a

Univariate meta-regression analysis. bMultivariate meta-regression analysis. CHD: congenital heart diseases; RDOR: relative diagnostic odds ratios; CI: confidence interval.

because of a lack of data and an inappropriate design for missing data analysis (Table 4).

Comparison of echocardiographic characteristics The diagnostic pooled sensitivity for TVSþTAS was the highest, followed by TAS and TVS. TAS had the highest specificity, followed by TVSþTAS and TVS. With regards to the AUC of SROC, the TAS was the same as the TVSþTAS and by far superior to TVS alone (Figure 2A). The pooled sensitivity for the 3D/ 4D volume was the best, followed by the combinations of B-mode, CDFI and M-mode and 2D gray-scale In terms of pooled specificity, the combinations of B-mode, CDFI and M-mode were similar to 2D grayscale, and both were far superior to 3D/4D volume. With regards to the AUC of SROC, B-mode had a similar ability to that of the 3D/4D volume, although both were inferior to that of the combinations of B-mode, CDFI and M-mode (Figure 2B). In the light of the views, STIC had the highest sensitivity, followed by ECEE, 4CVþOTVþ3VTV, 4CVþOTV and 4CV, in descending order. Still, the specificity for the STIC was by far inferior to that for the 4CVþOTVþ3VTV, among which BCM was slightly superior to ECEE. Concerning the AUC of SROC, 4CVþOTVþ3VTV

was the largest, and STIC was smallest. In between, ECEE and 4CVþOTV had a similar AUC that was superior to that of 4CV. However, the results of 4CVþOTVþ3CTV should be interpreted with caution because only two studies were included80,81 (Figure 2C).

Additional analysis Post hoc power was analyzed for each study included, and the results are shown in Table 1. Stratified analysis was performed for post-test probability to allow greater precision regarding the test’s reliability. Considering an average pretest probability of 5.8% for the low-risk population of fetal CHD, 7.1% for the unselected risk and 10.4% for the high risk, the positive results increased the post-test probability to 74.2%, 86.2% and 89.2% chances, respectively, after echocardiographic detection was performed to rule on fetal CHD. Furthermore, the added values of fetal CHD diagnosis for the low-, unselected and high-risk populations were 73.5%, 85.5% and 78.8%, respectively. Likewise, the negative results reduced the post-test probability to approximately 3%, 2% and 2% chances, respectively, after echocardiographic detection to rule out a fetal CHD diagnosis. Publication bias was detected using Egger’s regression model (p ¼ 0.007).


197,536 91,855 8216 31,909 19,872 310,093 103,884 161,861 12,907 36,134 15179 5834 283,996 40135 67,855 247,046 15,064 329,965

16 41 15 16 2 17 8 6 41 11 8 43 7 58

Participants

18 11 21 6

Study number

(25.4–53.9) (49.0–77.4) (79.8–88.6) (85.4–93.6)

(34.8–67.2) (40.3–73.9) (59.2–84.1) (62.0–87.5) (81.0–94.6)

48.0 66.5 91.5 68.1

(32.1–64.3) (56.4–75.4) (84.2–95.6) (59.6–75.5)

(99.8–100) (99.8–100) (97.9–99.5) (99.2–100)

(99.7–100) (99.7–100) (99.9–100) (99.2–99.9) (92.4–99.0)

99.9 99.9 97.7 99.9

(99.8–99.9) (99.7–99.9) (92.5–99.3) (99.7–99.9)

99.3 (96.7–99.9) 99.9 (99.7–99.9) 99.6 (98.6–99.9)

99.9 99.9 100 99.8 97.2

98.9 (97.7–99.5) 99.9 (99.8–99.9)

99.9 99.9 99.0 99.9

Specificity (95% CI) %

(289.7–3518.2) (1598.3–5997.8) (171.4–1399.1) (1599.3–141,559.8)

(247.1–2996.7) (592.0–4945.7) (3028.3–27,696.8) (380.8–5743.2) (64.7–2044.1)

724.1 1507.9 532.9 1153.8

(351.0–1493.5) (615.6–3693.3) (71.8–3952.5) (598.4–2245.0)

267.7 (91.2–785.3) 1376.0 (699.6–2706.3) 1255.6 (109.9–14,351.0)

860.5 1711.0 9158.3 1478.8 363.8

218.2 (55.4–859.4) 1943.0 (960.6–3930.0)

1009.6 3096.2 489.7 15046.6

DOR (95% CI)

0.772 0.908 0.948 0.911

0.192 0.902 0.944

0.933 0.827 0.001 0.886 0.939

0.861 0.908

0.933 0.683 0.837 0.829

Heterogeneity (I2 for DOR)

1.00 2.76 (0.43–17.56) 3.15 (0.38–25.92) –

1.00 3.48 (0.41–29.40) 1.89 (0.35–10.14)

1.00 2.17 (0.38–12.59) 3.35 (0.53–21.11) 1.35 (0.68–2.67) 1.39 (0.57–3.40)

1.00 6.17 (1.54–24.73)

1.00 4.14 (0.65–26.26) 1.64 (0.47–5.69) 4.42 (1.67–11.67)

RDOR (95%CI)

0.276 0.258 –

0.245 0.432

0.373 0.181 0.372 0.457

0.011

0.126 0.426 0.005

p

10

60.9 (25.8–87.5) 65.9 (55.9–74.7) 79.1 (63.2–89.3)

48.7 58.0 73.5 77.1 89.6

63.1 (45.7–77.6) 68.6 (58.6–77.1)

38.6 64.5 80.9 90.3

Sensitivity (95% CI) %

(CPR)


STIC: spatiotemporal image correlation; ECEE: extended cardiac echography examination; 4 CV: 4 chamber view; OTV: outflow tract view; 3VTV: three-vessel trachea view; Echo: echocardiography; AUC: area under the curve of summary receiver operating characteristic (SROC) curve; Echo: echocardiography; CI: confidence interval; DOR: diagnostic odds ratios; RDOR: relative diagnostic odds ratios. a Two studies were excluded because of their case-controlled designs.

Risk levela Low risk Unselected risk High risk Median risk Gestational age First trimester Second/third trimester Echo-Views 4CV 4CVþOTV 4CVþOTVþ3VTV ECEE STIC Echo-approach TVS TAS TVSþTAS Echo-modality B-mode BCM 3D/4D-volume Overall

Variables

Table 4. Subgroup analysis of diagnostic accuracy for fetal congenital heart diseases based on statistical and clinical heterogeneities.




(CPR)


Liu et al.

11

(A) 1

0.9

0.8

0.7

Sensitivity

0.6

0.5

0.4

0.3

0.2 TVS TAS TVS +TAS

0.1

0

1

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0

Specificity

(B) 1

0.9

0.8

0.7

Sensitivity

0.6

0.5

0.4

0.3

0.2 B-mode BCM 0.1

0

3D/4D volume

1

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0

Specificity

Figure 2. Subgroup analysis of the summary receiver operating characteristic (SROC) curve for fetal congenital heart disease diagnosis. Diagnostic performance of subgroup comparisons for echocardiographic approaches (A), modalities (B) and views (C). Each label represents a single study, with the size proportional to the inverse standard error of each study. The area under the curve (AUC) reflects the overall diagnostic performance, with higher values indicating a better test performance. TAS: trans-vaginal sonography; TVS: trans-abdominal sonography; BCM: B-mode þ Color Doppler flow imaging (CDFI)þM-mode; 4CV: four chamber view; OTV: outflow tract view; 3VTV: three vessel trachea view; ECEE: extend cardiac echography examination; STIC: spatio-temporal image correlation. Downloaded from cpr.sagepub.com at TEXAS SOUTHERN UNIVERSITY on October 6, 2014


(CPR)


12


(C) 1

0.9

0.8

0.7

Sensitivity

0.6

0.5

0.4

0.3

4CV

0.2

4CV + OTV 4CV+ OTV + 3VTV ECEE STIC

0.1

0

1

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0

Specificity

Figure 2. Continued.

The new DORs was 6.30 (95% CI 5.66–6.93), significantly lower than the observed DORs of 7.05 (95%CI 6.39–7.70).

Discussion The results of this systematic review indicate that prenatal ultrasonography for CHD diagnosis had a moderate sensitivity with a wide range, high specificity and good consistency. Diagnostic sensitivity was significantly increased with advances in the risk population, progression in gestational age, incorporation of echocardiographic approaches, extension of the echocardiographic view and promotion of the echocardiographic modality. Based on the regression analysis, the risk levels and gestation ages across all related variables were independent predictors of the accuracy of a CHD diagnosis. Importantly, findings suggested that the unselected risk population benefited more notably from prenatal ultrasonographic detection than either the high- or low-risk population in terms of the added value for post-probability. The diagnostic test accuracy of prenatal ultrasounds for detection of CHD has recently come under discussion.27–32 Our systematic review further confirms the

superior diagnostic yields for CHDs across the unselected population to the low-risk populations during the second trimester.27 Other findings include the following: the higher detection rate of integrated TVS and TAS compared with either TAS or TVS alone; the higher detection rate among high-risk populations compared with unselected populations during the first trimester;28 the higher diagnostic accuracy of ECEE compared with basic cardiac echocardiographic examination (BCEE); the inferior sensitivity of ECEE among the low-risk populations compared with the unselected or high-risk populations;29; the feasibility of ultrasound examination in the first trimester for detecting CHD;30 and the higher sensitivities of STIC, ECEE and 4 CVþOTVþ3 VTV compared with 4 CVþOTV/3 VTV or 4 CV.32 However, our findings suggest that the use of Doppler imaging significantly improved the detection rate for CHD,28 and the sensitivity of ECEE among high-risk populations was higher than among unselected populations.29 Compared with previous studies,28–32 we comprehensively considered the demographic, clinical and echocardiographic confounding factors, and conducted additional analysis to further determine the variation in diagnostic accuracy across studies.



(CPR)


Liu et al.

13

Growing evidence suggests a marked increase in prenatal ultrasonography for CHD detection after supplementing the visualizations of OTV or 3VTV with 4CV.89 As expected, the sensitivity for detecting fetal CHD improved with the extension of the views. Because ECEE had advantages in sensitivity and specificity compared with basic cardiac echography examination, ECEE use should be highlighted for high-risk populations.16 STIC has been incorporated into a more detailed anatomical and functional assessment of the fetal heart26–28 that is technologically attributed to its access to three virtually orthogonal planes and multi-planar reconstruction, simultaneously providing positioning and orientation assistance for the examiner.90–92 STIC had serial superiority; however, this modality cannot be recommended as a definitive test for fetal CHD diagnosis because of its inferior specificity.15,16 Summarily, any result from a single view should be interpreted cautiously, and more extensive views should be acquired if possible in cases of complex cardiac abnormalities.15,93 Echocardiography has been used as a tool to diagnose fetal CHD in high-risk populations for many years.94–100 However, its routine use in low or unselected risk populations remains controversial.19,25–27 Our findings indicated that the diagnostic sensitivities significantly increased with advances in the risk population consistent with Randall et al.,29 although the unselected risk population did benefit more notably from prenatal ultrasonographic detection than either the high- or low-risk population in terms of the added value for post-probability. Considering that the majority of women at risk for cardiac abnormalities in pregnancy are much more likely to be missed by simple prenatal screening,101–103 performing routine fetal echocardiography should be proposed for the unselected risk population if appropriate, irrespective of the presence or absence of risk factors for the development of fetal CHD. Currently, the most commonly used modality of prenatal ultrasonography for CHD detection remains the B-mode because of its superior effectiveness, safety, availability, flexibility and acceptability.89 Unfortunately, the independent utility of B-mode only showed an inferior sensitivity of 48.0%. In addition to its spatiotemporal resolution, M-mode has the advantage of facilitating measurements of the fetal myocardial morphology and is able to differentiate among arrhythmia diagnoses.104 In the wake of the B-mode, CDFI has the advantages of optimizing the imaging of various cardiac structures, highlighting abnormal blood flow patterns23–25 and allowing for greater prognostic differentiation.105 Supplementing M-mode and CDFI with B-mode significantly enhanced the diagnostic power to a superior sensitivity of 66.5% for ruling in

fetal CHD to detect fetal CHD. Technologically, 3D/ 4D volume echocardiography allows for the visualization of orthogonal planes and the multi-plane reconstruction of spatial relationships, contributing to a more fluid and representative depiction of the fetal cardiac structures.26–27 Accordingly, prenatal ultrasonography for CHD detection has benefited from an increased efficacy in the full volume dataset since the recent advent of single heart beat acquisition on the basis of real-time 3D echocardiography.89 TVS has been used in prenatal ultrasonography for CHD detection for many years.105–107 An inferior sensitivity after using TVS in the first trimester has been shown and can be attributed to the fact that the development of structure and function in some heart diseases is associated with the progression of gestation.89,108 The lessened capacity for resolution related to the small size of the fetal heart is also likely to play a role in this inferiority. Significantly, the combined use of high-frequency TVS and TAS transducers had a favorable sensitivity of 79.1% and specificity of 99.6% in addition to the highest accuracy, an approximate 20% increase in sensitivity than that of TVS alone. Consequently, becoming familiar with the use of TVS in the first trimester and supplementing it with routine second trimester cardiac examinations is likely to refine subsequent screenings. This measure is also particularly encouraged by ISUOG and AIUM16,28 for high-risk pregnancies with either increased nuchal translucency95–97 or abnormality in ductus venosus98,98 in early gestation. Still, this approach may not be operationally flexible and could become excessively timeconsuming and technologically demanding.53,109,110

Advantages and limitations We conducted a post hoc power analysis and applied it to the sensitivity analysis to determine the stability of the summary results. In contrast with previous studies,29–32 all of the studies we included were prospective, rather than retrospective, in nature, thus enhancing the power of the evidence. Considering the scope of this study, the findings can be generalized to diverse medical settings across all risk populations in progressive gestations for prenatal fetal CHD detection. Inevitably, in addition to publication bias, substantial variation will continue to exist, despite any subgroup analysis. The power to detect relevant differences among subgroups may have been limited by the small number of studies in specific subgroups found here.

Conclusions In summary, prenatal echocardiography is a helpful tool for diagnosing fetal CHDs with favorable



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specificity and moderate sensitivity, especially for unselected and high-risk pregnancies. However, any single ultrasonographic regime cannot be recommended as the definitive test for fetal CHD diagnosis; rather, each must be interpreted in context of the demographic and clinical factors, if feasible. Moreover, continual re-evaluation throughout the entire course of the developing fetal cardiac morphology and hemodynamics is advisable and encouraged. Future research should consider the need to assess the consequences of using echocardiography on prognosis. Considering the challenges of prenatal detection, a multidisciplinary, joint effort is required to achieve optimal results for the fetal heart. Acknowledgements We thank Diana Scriven, Jerry Hintze, Ignatius Yu, Wei Li, Jian-ming Wang, Liang-sheng Xie and Jie Shen for their assistance with the study search and statistical support.

Funding This study was supported by grants from Graduate Practice Innovation Projects (GPIP) of Jiangsu Higher Education Institutions (No. SJZZ2014-0118), Natural Science Foundation (NSF) of Health Ministry of Sichuan Province (No. SKY130299), Continue Medical Education (CME) for CHD (No. 2013320602003), Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions (JX10231081).

Conflict of interest None declared.

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Evaluation of fetal echocardiography as a routine antenatal screening tool for detection of congenital heart disease.

Echocardiography in congenital heart disease.

Echocardiography in congenital heart disease.

Acyanotic congenital heart disease and transesophageal echocardiography.

Congenital heart disease and fetal thoracoabdominal anomalies: associations in utero and the importance of cytogenetic analysis.

Early fetal echocardiography: congenital heart disease detection and diagnostic accuracy in the hands of an experienced fetal cardiology program.

Transesophageal echocardiography in infants and children with congenital heart disease.

Array comparative genomic hybridization and fetal congenital heart defects: a systematic review and meta-analysis.

Missing outcome data in meta-analysis.

Who should be referred? An evaluation of referral indications for fetal echocardiography in the detection of structural congenital heart disease.

Three-dimensional echocardiography in adult congenital heart disease.

Echocardiography in patients with adult congenital heart disease.

Two-dimensional sector scanner echocardiography in cyanotic congenital heart disease.

Comparison of Echocardiography and 64-Multislice Spiral Computed Tomography for the Diagnosis of Pediatric Congenital Heart Disease.

Pediatric prenatal diagnosis of congenital heart disease.

Reoperations for pediatric and congenital heart disease: an analysis of the Society of Thoracic Surgeons (STS) congenital heart surgery database.

Interrogating congenital heart defects with noninvasive fetal echocardiography in a mouse forward genetic screen.

Use of casts in the necropsy diagnosis of fetal congenital heart disease.

Fetal Growth and Neurodevelopmental Outcome in Congenital Heart Disease.

3D echocardiography in congenital heart disease: a valuable tool for the surgeon.

Diagnosis of ischemic heart disease with adenosine echocardiography.

Analysis of Multivariate Disease Classification Data in the Presence of Partially Missing Disease Traits.

Screening for congenital heart disease with the four-chamber view of the fetal heart.

Maternal-fetal attachment and prenatal diagnosis of heart disease.