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Research Article | Volume 30 Issue 7 (July, 2025) | Pages 41 - 46
Bridging the Diagnostic Gap: A Retrospective Study on Missed and late Diagnoses of Congenital Heart Disease in Neonates and Children
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 ,
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1
Assistant Professor, MBBS, MD(Pediatrics), Fellow Pediatric Cardiologist, Department of Pediatrics, MGM Medical College, Nerul West, Navi Mumbai – 400703
2
Assistant Professor, MBBS, MD (Pediatrics), Department of Pediatrics , MGM Medical College, Nerul West, Navi Mumbai – 400703
3
Medical Officer, MBBS, DCH, Department of Pediatrics, MGM Medical College, Nerul West, Navi Mumbai – 400703
4
Assistant Professor, MBBS, MD (Pediatrics), Department of Pediatrics, MGM Medical College, Nerul West, Navi Mumbai – 400703
Under a Creative Commons license
Open Access
Received
May 12, 2025
Revised
June 5, 2025
Accepted
June 20, 2025
Published
July 6, 2025
Abstract

Introduction: The most prevalent congenital defect in children is congenital heart disease (CHD), and prompt treatment and better results depend on early detection.  But a lot of instances are diagnosed late, especially in environments with limited resources.  Aims: To evaluate the clinical profiles and determine the risk factors associated with delayed detection of congenital heart disease in children attending a tertiary cardiac care center. Materials & Methods: This was a hospital-based cross-sectional observational study conducted at a tertiary cardiac care center. A total of 1991 pediatric patients diagnosed with CHD were enrolled. Data regarding age at diagnosis, clinical presentation, family history, birth term, consanguinity, and other relevant demographic and clinical factors were collected and analyzed. Patients were categorized into delayed and non-delayed diagnosis groups based on the age at diagnosis, and comparisons were made to identify associated risk factors. Result: Acyanotic CHD was found in 396 cases (56.1%) and cyanotic CHD in 310 cases (43.9%) of the 706 patients with delayed diagnosis.  Only 192 cases (14.9%) of the 1285 individuals with no delayed diagnosis had cyanotic CHD, whereas the majority (1093 cases; 85.1%) had acyanotic CHD.  There was a statistically significant correlation between the kind of CHD and delayed diagnosis (p <.00001). Conclusion: This retrospective investigation led us to the conclusion that the diagnostic gap in children's congenital heart disease (CHD) is influenced by age, gender, parental engagement, religion, geography, and type of CHD. 

Keywords
INTRODUCTION

The most prevalent congenital abnormality in the world is congenital heart disease (CHD).  One out of every 100 kids is born with congenital heart disease (CHD), and one out of every four is born with catastrophic CHD [1].  The yearly mortality rate from congenital heart disease has decreased worldwide.

 

Even though children with congenital heart problems have a higher chance of survival and a higher quality of life, cardiac disorders continue to pose a significant global health concern [2].  According to recent studies, the prevalence of congenital heart disease (CHD) in India has climbed to 8.5–13.6 cases per 1000 children [3].  CHD is a major cause of newborn death in India (10%) [4]. Cognitive impairments and developmental delay are among the frequent morbidities associated with CHD in children (20–30%) [5]. If discovered early and the right medical or surgical intervention is implemented, a sizable percentage of infants born with congenital heart disease may go on to lead normal, productive lives.  When a patient does not require emergency management [6] at the time of diagnosis, when treatment does not pose a significant risk, when alternative management is not required, or when an earlier treatment might improve the patient's outcome [7], the diagnosis of CHD is considered to be correct.  In neonates having heart surgery, delayed diagnosis of congenital heart disease (CHD) is linked to circulatory compromise and organ failure, which prolongs ventilation and increases mortality. One of the most prevalent congenital malformations is congenital heart disease (CHD).  Significant morbidity and mortality result from delayed identification of congenital heart disease (CHD) [8].  Foetal echocardiographic screening or newborn clinical screening can identify the majority of congenital heart abnormalities (CHD) that are relevant.  However, a significant portion of CHD cases are not detected during early clinical screening and are discovered after being hospitalized as children or even as adults.  The overall outcome of children whose underlying significant heart abnormality was not discovered until immediate action was required is frequently impacted by this delay in making the accurate diagnosis early in life.  The purpose of this study was to assess the parameters linked to delayed diagnosis in pediatric patients with congenital heart disease who were evaluated at our hospital. Study the factors associated with delayed diagnosis in congenital heart diseases. Study the Characteristics patient with delayed diagnosis in congenital heart diseases.

MATERIALS AND METHODS

Study type: Hospital-based Cross-sectional Observational Study

 

Study Duration: 1 Year

 

Study site: The study will be conducted in the Department of Paediatric Cardiology, Sri Satya Sai     Sanjeevani center for child heart care, Kharghar, Navi Mumbai, a tertiary care center.

 

Sample Size:  1991 Diagnoses of congenital heart disease in neonates and children

 

Inclusion criteria: 

  • Patients diagnosed with congenital heart disease (cyanotic or acyanotic) confirmed by echocardiography.
  • Age group: Neonates and children up to 18 years of age.
  • Both genders (male and female).

 

Exclusion criteria:

  • Patients with acquired heart diseases (e.g., rheumatic heart disease, infective endocarditis).
  • Patients with previously diagnosed CHD who were referred for follow-up or surgical intervention.
  • Incomplete or missing clinical records, especially regarding timing of diagnosi

 

Study variable

  • Age group
  • Gender
  • Person providing information
  • Religion
  • Background
  • Delayed diagnosis

 

STATISTICAL ANALYSIS:

For statistical analysis, data were initially entered into a Microsoft Excel spreadsheet and then analyzed using SPSS (version 27.0; SPSS Inc., Chicago, IL, USA) and GraphPad Prism (version 5). Numerical variables were summarized using means and standard deviations, while Data were entered into Excel and analyzed using SPSS and GraphPad Prism. Numerical variables were summarized using means and standard deviations, while categorical variables were described with counts and percentages. Two-sample t-tests were used to compare independent groups, while paired t-tests accounted for correlations in paired data. Chi-square tests (including Fisher’s exact test for small sample sizes) were used for categorical data comparisons. P-values ≤ 0.05 were considered statistically significant.

RESULTS

Table 1: distribution of participants by age, gender, person providing information, Religion, Background and Delayed diagnosis

   

Frequency

Percent

P-value

Age group

0 to 1 month

142

7.10%

<0.001

1 month to 1 year

729

36.60%

1 year to 5 years

602

30.20%

5 years to 10 years

333

16.70%

more than 10 years

185

9.30%

Total

1991

100.00%

Gender

Female

916

46.00%

< .00001

Male

1075

54.00%

Total

1991

100.00%

Person providing information

Both Parents

762

38.30%

< .00001

Father

534

26.80%

Mother

607

30.50%

Others

88

4.40%

Total

1991

100.00%

Religion

HINDU

1493

75.00%

< .00001

MUSLIM

474

23.80%

OTHERS

24

1.20%

Total

1991

100.00%

Background

Rural

1139

57.20%

< .00001

Slum

291

14.60%

Tribal

10

0.50%

Urban

551

27.70%

Total

1991

100.00%

Delayed diagnosis

DELAYED

706

35.50%

< .00001.

NOT DELAYED

1285

64.50%

Total

1991

100.00%

 

Table 2: distribution by state

State

Frequency

Percent

P-value

Assam

3

0.2%

< .00001

Bihar

56

2.8%

Chhattisgarh

3

0.2%

Dadra and Nagar Haveli and Daman and Diu

1

0.1%

Delhi

2

0.1%

Gujarat

16

0.8%

Haryana

2

0.1%

Jharkhand

17

0.9%

Karnataka

8

0.4%

Madhya Pradesh

21

1.1%

Maharashtra

1621

81.4%

Meghalaya

1

0.1%

Odisha

1

0.1%

Punjab

1

0.1%

Rajasthan

11

0.6%

Uttar Pradesh

221

11.1%

Uttarakhand

1

0.1%

West Bengal

5

0.3%

Total

1991

100.0%

 

Table 3: distribution of Diagnosis among participants with acyanotic heart disease and cyanotic heart disease

 

Abnormality

ACYANOTIC

Percent

P-value

Acyanotic heart disease

Aortic Stenosis

26

1.7%

< .00001

ASD

354

23.8%

Coarctation of Aorta

21

1.4%

COMPLETE/PARTIAL AVSD

37

2.5%

PDA

189

12.7%

Pulmonary Stenosis

48

3.2%

VSD

772

51.8%

VSD+PS

1

0.1%

OTHERS

41

2.8%

Total

1489

100.0%

Cyanotic heart disease

Abnormality

CYANOTIC

Percent

< .00001

Ebstein Anomaly

6

1.2%

SINGLE VENTRICLE

22

4.4%

TAPVC, PAPVC, PAPVD

82

16.3%

TGA

59

11.8%

TOF

296

59.0%

Truncus Arteriosus

5

1.0%

OTHERS

32

6.4%

Total

502

100.0%

 

Figure 1: Comparison of type of CHD with delayed diagnosis

 

The largest percentage of the 1991 children in our study were between the ages of one month and one year (729 patients, 36.6%), while the smallest percentage were between the ages of 0 and one month (142 patients, 7.1%).  Delays in diagnosis were substantially correlated with age group (p < 0.001). 916 females (46%) and 1075 males (54%) were present.  A statistically significant correlation (p <.00001) was found between gender and delayed diagnosis. Information Provider: In 762 cases (38.3%), the mother provided information alone (30.5%), the father provided information alone (534; 26.8%), and others provided information in 88 cases (4.4%).  There was a significant correlation (p <.00001) between this component and delayed diagnosis. Nearly all of the patients (1493, 75%) were Hindu, followed by Muslims (474, 23.8%), and others (24, 1.2%). There was a strong correlation between religion and delayed diagnosis (p <.00001). Slums (291, 14.6%), urban regions (551, 27.7%), and tribal backgrounds (10, 0.5%) were the next most common places for children to come from.  Diagnostic delay was significantly correlated with background (p <.00001). Of the 1991 children, 1285 (64.5%) received their diagnoses on time, whereas 706 (35.5%) received theirs later.  There was a statistically significant difference (p <.00001).

 

Out of the 1991 patients in our study, Maharashtra had the most contribution (1621 patients, or 81.4%), followed by Uttar Pradesh (221 patients, or 11.1%), and Bihar (56 patients, or 2.8%).  Jharkhand had 17 (0.9%), Gujarat had 16 (0.8%), Rajasthan had 11 (0.6%), Karnataka had 8 (0.4%), West Bengal had 5 (0.3%), and Madhya Pradesh had 21 patients (1.1%).  Meghalaya, Odisha, Punjab, Uttarakhand, and Dadra and Nagar Haveli and Daman and Diu each had one patient (0.1%), whereas Chhattisgarh and Assam had three instances each (0.2%), Delhi, and Haryana had two cases each (0.1%).  There was a statistically significant correlation (p <.00001) between the patient's condition and the results of the diagnosis.

 

The most common condition among the 1991 patients in our study was Ventricular Septal Defect (VSD), which was seen in 772 cases (51.8%), followed by Atrial Septal Defect (ASD) in 354 cases (23.8%), Patent Ductus Arteriosus (PDA) in 189 cases (12.7%), Pulmonary Stenosis in 48 cases (3.2%), Complete/Partial AVSD in 37 cases (2.5%), Aortic Stenosis in 26 cases (1.7%), Coarctation of the Aorta in 21 cases (1.4%), Others in 41 cases (2.8%), and VSD+PS in 1 patient (0.1%). Contrarily, 502 patients (25.2%) had cyanotic heart disease, with Tetralogy of Fallot (TOF) accounting for the majority of cases (296 cases, 59.0%), followed by TAPVC/PAPVC/PAPVD in 82 cases (16.3%), Transposition of Great Arteries (TGA) in 59 cases (11.8%), Single Ventricle in 22 cases (4.4%), Ebstein Anomaly in 6 cases (1.2%), Truncus Arteriosus in 5 cases (1.0%), and Others in 32 cases (6.4%).  A notable pattern in the forms of congenital heart disease identified was shown by the statistically significant differences in the distribution of these anomalies (p <.00001).

 

Of the 706 individuals in our study who had a delayed diagnosis, 310 (43.9%) had cyanotic CHD and 396 (56.1%) had acyanotic CHD.  Only 192 cases (14.9%) of the 1285 individuals with no delayed diagnosis had cyanotic CHD, whereas the majority (1093 cases; 85.1%) had acyanotic CHD.  There was a statistically significant correlation between the kind of CHD and delayed diagnosis (p <.00001).

DISCUSSION

Age and Delayed Diagnosis

In similar study by Murni IK et al [9] (2021) showed that 60.8% of the 838 individuals under the age of 18 had delayed diagnosis.  We discovered that the age group of 0 to 1 month had the fewest delayed diagnoses (142 patients, 7.1%), while the group of 1 month to 1 year had the most (729 patients, 36.6%).  This may be because older infants may have milder, less obvious symptoms, whereas younger newborns are monitored more regularly. A significant correlation between age and delayed diagnosis is shown by a p-value of less than 0.001.

 

Gender and Delayed Diagnosis

In others study by Ooi PH et al [10] (2021) showed that of the 1,234 newborns with a CHD diagnosis, 38% were female and 62% were male. We demonstrated that, of the 1991 children, 1075 were male (54%) and 916 were female (46%), with the likelihood of a delayed diagnosis being higher for males.  This imbalance may be exacerbated by gender disparities in illness presentation or healthcare-seeking behavior. A substantial correlation between gender and delayed diagnosis is shown by a p-value of less than 0.00001.

 

Person Providing Information

We found that 762 cases (38.3%) had information from both parents, 607 cases (30.5%) had information from the mother alone, and 534 cases (26.7%) had information from the father alone.  When only one parent or other person supplied information, delays were more frequent, most likely as a result of decreased awareness or postponed action. A substantial correlation between the source of information and delayed diagnosis is shown by a p-value of less than 0.00001.

 

Religion and Delayed Diagnosis

The majority of children were Hindu (1493 patients, 75%), followed by Muslims (474 patients, 23.8%), and other ethnic groups, according to our data.  Timelines for diagnosis may be impacted by religion's influence on cultural customs, access to healthcare, and the urgency of seeking medical attention. Religion is strongly linked to delayed diagnosis, as indicated by the p-value of less than 0.00001.

 

Geographical Background and Delayed Diagnosis

We found that a sizable fraction of children came from rural areas (1139 patients, 57.2%), whereas less came from slums (291 patients, 14.6%) and urban areas (551 patients, 27.7%).  Delays in diagnosis are probably caused by the inadequate healthcare infrastructure in slum and rural areas. The considerable influence of geographic background on delayed diagnosis is highlighted by the p-value of less than 0.00001.

 

State of Residence and Delayed Diagnosis

81.4% (1621 patients) of the cases were in Maharashtra, followed by Uttar Pradesh (221 patients, 11.1%) and Bihar (56 patients, 2.8%).  Compared to states with fewer resources, Maharashtra and other states with superior healthcare infrastructure had fewer delays. The state of residency has a strong correlation with delayed diagnosis (p-value < 0.00001).

 

Types of Congenital Heart Disease (CHD)

In similar study by Falkentoft AC et al [11] (2018) showed that 450 children with non-cyanotic congenital heart defects, including Ventricular Septal Defect (VSD) and Patent Ductus Arteriosus (PDA), were examined in the study. We demonstrated that Ventricular Septal Defect (VSD) was the most common (772 patients, 51.8%), while acyanotic CHD was more common (1489 patients, 74.8%).  502 patients (25.2%) had cyanotic CHD, with Tetralogy of Fallot (TOF) accounting for the majority (296 cases, 59.0%). A significant correlation between the kind of CHD and delayed diagnosis is indicated by a p-value of less than 0.00001.

 

Delayed Diagnosis and Type of CHD

Of the 706 cases with delayed diagnosis, we found that 310 (43.9%) had cyanotic CHD and 396 (56.1%) had acyanotic CHD.  Given that cyanotic CHD frequently manifests with more acute symptoms, a larger percentage of acyanotic CHD was diagnosed later, most likely due to its less evident symptoms. There is a substantial correlation between the kind of CHD and delayed diagnosis (p-value < 0.00001).

CONCLUSION

We concluded that age, gender, parental participation, religion, region, and type of congenital heart disease (CHD) all have an impact on the diagnostic gap in children's CHD, according to this retrospective study.  Infants between the ages of one month and one year, boys, those living in remote areas, and households with little parental involvement were more likely to have delayed diagnoses.  Compared to acyanotic CHD, cyanotic CHD was more likely to be identified later.  In order to decrease diagnostic delays and enhance outcomes in pediatric congenital heart disease, especially in underprivileged and socioeconomically disadvantaged populations, the data emphasizes the necessity of better early detection techniques, fair access to healthcare, and raised awareness.

REFERENCES
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  2. Zimmerman MS, Smith AG, Sable CA, Echko MM, Wilner LB, Olsen HE, Atalay HT, Awasthi A, Bhutta ZA, Boucher JL, Castro F. Global, regional, and national burden of congenital heart disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. The Lancet Child & Adolescent Health. 2020 Mar 1;4(3):185-200.
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  9. Murni IK, Wirawan MT, Patmasari L, Sativa ER, Arafuri N, Nugroho S, Noormanto. Delayed diagnosis in children with congenital heart disease: a mixed-method study. BMC pediatrics. 2021 Dec;21:1-7.
  10. Ooi PH, Mazurak VC, Bhargava R, Dunichand‐Hoedl A, Ayala Romero R, Gilmour SM, Yap JY, Mager DR. Myopenia and reduced subcutaneous adiposity in children with liver disease are associated with adverse outcomes. Journal of Parenteral and Enteral Nutrition. 2021 Jul;45(5):961-72. Falkentoft AC, Rørth R, Iversen K, Høfsten DE, Kelbæk H, Holmvang L, Frydland M, Schoos MM, Helqvist S, Axelsson A, Clemmensen P. MR‐proADM as a Prognostic Marker in Patients With ST‐Segment–Elevation Myocardial Infarction—DANAMI‐3 (a Danish Study of Optimal Acute Treatment of Patients With STEMI) Substudy. Journal of the American heart association. 2018 May 18;7(11):e008123.
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