Prenatal detection of major congenital heart disease – optimising resources to improve outcomes

Corcoran, Siobhan; Briggs, Kaleigh; Connor, Hugh O'; Müllers, Sieglinde; Monteith, Cathy; Donnelly, Jennifer; Franklin, Orla; Malone, Fergal D.; Breathnach, Fionnuala

doi:10.1016/j.ejogrb.2016.06.008

Cited by 27 publications

(27 citation statements)

References 14 publications

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“…In the world, the prenatal detection rates varied by regions (13-87%) and CHD subtypes (4.3-100%) [27,[31][32][33][34][35][36]. In the study, we speculated the primary reason for low detection rates in total CHD and ASD were for the large proportion of ASD and PDA.…”

Section: Patients' Characteristics and Risk Factors For Chdmentioning

confidence: 93%

“…For example, there were only 10 cases with truncus arteriosus in study performed in USA, yielding prenatal detection rate of 70% [35]. The terminated CHD proportion was a slightly higher than study in Denmark (57.8%), but perinatal outcomes was better than isolated CHD in Brisbane, Australia [31,36]. Comparison of outcomes should noticed the differences in legal requirement for termination and distribution of CHD categories.…”

Section: Patients' Characteristics and Risk Factors For Chdmentioning

confidence: 94%

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Epidemiology, Prenatal Diagnosis, and Neonatal Outcomes of Congenital Heart Defects in Eastern China: A Hospital-Based Multicenter Study

zhang

Sun

Zhu

et al. 2020

Preprint

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Background : Congenital heart disease (CHD) is one of the most common birth defect. Currently, the reported occurrence of CHD continues to increase at global or regional level. In 2013, Chinese government announced to end 1-child birth policy. We aimed to update the incidence, prenatal diagnosis, and neonatal outcomes of CHD since the ending of 1-child policy, in eastern China. Study design : Data were obtained from the Zhejiang provincial birth defects surveillance system. CHD identified during 2014-2018 were analyzed. Chi-square test, odds ratio (OR) and 95% confidence interval (CI) were used to explore incidence trends, prenatal diagnosis, birth outcomes and associated risk factors with CHD. Results : Overall, 8,546 of 534,002 births were identified with CHD. During the period, the overall incidence of CHD increased significantly, giving an average incidence as 16.0 per 1000 births (95% CI 15.69-16.32). However, the incidence of critical CHD (CCHD) remained stable over time (1.6 per 1000 births, 95% CI 1.47-1.69).Women aged less than 20 years (OR2.1, 95%CI 1.9-2.3) or ≥35 years (OR 1.2, 95% CI 1.2-1.3) were at higher risk of CHD than women aged 21-34 years. Births in urban areas (OR 1.2, 95% CI 1.2-1.3), male sex (OR 1.3, 95% CI 1.3-1.4), and multiple births (OR 4.0, 95% CI 3.7-4.4) had a higher risk of CHD than births in rural areas, female sex, and singletons, respectively. The three major subtypes of CHD were atrial septal defect (ASD, 68.0%), patent ductus arteriosus (PDA, 34.7%), and ventricular septal defect (VSD, 6.4%). A total of 22.2% of CHD was detected prenatally. Regarding to perinatal outcomes, there were 1457 (17.1%) stillbirths, 106 (1.2%) early neonatal deaths, and 6983 (81.7%) live births. Conclusion : The high incidence of CHD might be attributable to the large proportion of mild CHD. Pregnancies in urban areas, male births, and younger or older women were the risk factors for CHD. The prenatal detection rate for overall CHD was low, whereas the rate for CCHD was similar or even higher than other studies. The neonatal outcomes were comparable to previous literatures.

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Section: Patients' Characteristics and Risk Factors For Chdmentioning

confidence: 93%

Section: Patients' Characteristics and Risk Factors For Chdmentioning

confidence: 94%

Epidemiology, Prenatal Diagnosis, and Neonatal Outcomes of Congenital Heart Defects in Eastern China: A Hospital-Based Multicenter Study

zhang

Sun

Zhu

et al. 2020

Preprint

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“…25,26 The use of telediagnosis with fetal cardiac ultrasound image transmission is another alternative that can increase early diagnosis in >50% of cases. 27,28 An efficient and more comprehensive national referral system should be developed. To date, the referral system encompasses preevaluation of patients principally at the main Pediatric Hospital in Luanda (capital) to the Cardio-Thoracic Center of Clínica Girassol.…”

Section: Commentmentioning

confidence: 99%

Single Ventricle Palliation in a Developing Sub-Saharan African Country: What Should be Improved?

Manuel

Morais

Turquetto

et al. 2019

World J Pediatr Congenit Heart Surg

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Introduction: Single ventricle physiology management is challenging, especially in low-income countries. Objective: To report the palliation outcomes of single ventricle patients in a developing African country. Methods: We retrospectively studied 83 consecutive patients subjected to single ventricle palliation in a single center between March 2011 and December 2017. Preoperative data, surgical factors, postoperative results, and survival outcomes were analyzed. The patients were divided by palliation stage: I (pulmonary artery banding [PAB] or Blalock-Taussig shunt [BTS]), II (Glenn procedure), or III (Fontan procedure). Results: Of the 83 patients who underwent palliation (stages I-III), 38 deaths were observed (31 after stage I, six after stage II, and one after stage III) for an overall mortality of 45.7%. The main causes of operative mortality were multiple organ dysfunction due to sepsis, shunt occlusion, and cardiogenic shock. Twenty-eight survivors were lost to follow-up (22 after stage I, six after stage II). Thirteen stage II survivors are still waiting for stage III. The mean follow-up was 366 + 369 days. Five-year survival was 28.4 % for PAB and 30.1% for BTS, while that for stage II and III was 49.8% and 57.1%, respectively. Age (hazard ratio, 0.61; 95% confidence interval: 0.47-0.7; P ¼ .000) and weight at surgery (hazard ratio, 0.45; 95% confidence interval: 0.31-0.64; P ¼ .002) impacted survival. Conclusion: A high-mortality rate was observed in this initial experience, mainly in stage I patients. A large number of patients were lost to follow-up. A task force to improve outcomes is urgently required.

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“…The copyright holder for this preprint this version posted June 24, 2020. ; https://doi.org/10.1101/2020.06.22.20137786 doi: medRxiv preprint considerably 18,19 , showing that improving image acquisition and interpretation can bridge the diagnosis gap; however, these small, single-center programs are difficult to sustain and scale.…”

Section: Introductionmentioning

confidence: 99%

“…Together, these make CHD detection one of the most difficult diagnostic challenges in ultrasound. Quality control studies aimed at addressing these challenges succeeded in increasing CHD detection considerably 18,19 , showing that improving image acquisition and interpretation can bridge the diagnosis gap; however, these small, single-center programs are difficult to sustain and scale.…”

Section: Introductionmentioning

confidence: 99%

Expert-level prenatal detection of complex congenital heart disease from screening ultrasound using deep learning

Arnaout

Curran

Zhao

et al. 2020

Preprint

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Congenital heart disease (CHD) is the most common birth defect. Fetal survey ultrasound is recommended worldwide, including five views of the heart that together could detect 90% of complex CHD. In practice, however, sensitivity is as low as 30%. We hypothesized poor detection results from challenges in acquiring and interpreting diagnostic-quality cardiac views, and that deep learning could improve complex CHD detection. Using 107,823 images from 1,326 retrospective echocardiograms and surveys from 18-24 week fetuses, we trained an ensemble of neural networks to (i) identify recommended cardiac views and (ii) distinguish between normal hearts and complex CHD. Finally, (iii) we used segmentation models to calculate standard fetal cardiothoracic measurements. In a test set of 4,108 fetal surveys (0.9% CHD, >4.4 million images, about 400 times the size of the training dataset) the model achieved an AUC of 0.99, 95% sensitivity (95%CI, 84-99), 96% specificity (95%CI, 95-97), and 100% NPV in distinguishing normal from abnormal hearts. Sensitivity was comparable to clinicians' task-for-task and remained robust on external and lower-quality images. The model's decisions were based on clinically relevant features. Cardiac measurements correlated with reported measures for normal and abnormal hearts. Applied to guidelines-recommended imaging, ensemble learning models could significantly improve detection of fetal CHD and expand telehealth options for prenatal care at a time when the COVID-19 pandemic has further limited patient access to trained providers. This is the first use of deep learning to approximately double standard clinical performance on a critical and global diagnostic challenge.

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Prenatal detection of major congenital heart disease – optimising resources to improve outcomes

Cited by 27 publications

References 14 publications

Epidemiology, Prenatal Diagnosis, and Neonatal Outcomes of Congenital Heart Defects in Eastern China: A Hospital-Based Multicenter Study

Epidemiology, Prenatal Diagnosis, and Neonatal Outcomes of Congenital Heart Defects in Eastern China: A Hospital-Based Multicenter Study

Single Ventricle Palliation in a Developing Sub-Saharan African Country: What Should be Improved?

Expert-level prenatal detection of complex congenital heart disease from screening ultrasound using deep learning

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