European Journal of Cardiovascular Medicine

Congenital heart disease (CHD) is the most common congenital malformation worldwide. Approximately, 1 in every 100 babies are born with CHD, with 1 in 4 births with critical CHD [1]. In Indonesia, 5 million infants are born annually [2], with approximately 50,000 infants are born with CHD, and 12,500 born with critical CHD [1]. Globally, the annual mortality rate of CHD among children has declined [3]. Despite the better survival and quality of life of children with CHD, these defects still represent a major health problem worldwide [1].

Delayed diagnosis of CHD causes significant morbidity and mortality [4]. Delayed diagnosis of CHD is associated with cardiovascular compromise and organ dysfunction leading to prolonged ventilation and mortality among neonates undergoing cardiac surgery [5].

Proper diagnosis of CHD is defined when the patient does not need emergency management at the onset of diagnosis, when treatment does not carry high risk, when there is no need for different management, or when the patient has better outcome if treated earlier. Delayed diagnosis of cyanotic CHD is when children with CHD are diagnosed after sent home from the birth clinic or hospital. Concerning acyanotic CHD, delayed diagnosis is defined when the children were diagnosed when cardiac surgery or intervention should have already been performed [6, 7].

Delayed diagnosis in congenital heart disease is prevalent globally both in high-income and low- and middle-income countries. One study in a high-income country revealed the proportion of delayed diagnosis was 8.9% including in cyanotic CHD of 10.4% and acyanotic CHD of 8.7% [7]. Another study revealed the delayed diagnosis in critical CHD is 29.5% [8]. Types of critical CHD and the presence of extracardiac defect are associated with less likely delayed diagnosis [8]. One study in a low- and middle-income country demonstrated that delayed diagnosis in congenital heart disease is 85.1% [9]. Factors contributing to delayed diagnosis in CHD are inadequately trained health system and socioeconomic constraints among those in low- and middle-income country setting [9].

To analyze the epidemiology and identify the key contributing factors associated with the delayed diagnosis of congenital heart disease (CHD) in pediatric patients.

Study Design: Retrospective study.

Study Place: 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.

Study Time: Jan 2024 to Dec 2024 for one year.

Sample size: 1991 congenital heart disease.

Study parameter:

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

Inclusion Criteria:

• CHD patients diagnosed after birth.
• Patients aged 0–18 years.
• Patients with confirmed structural heart defects.
• Consent obtained from parents or guardians.

Exclusion Criteria:

• Prenatally diagnosed CHD cases.
• Patients with acquired heart diseases.
• Incomplete medical records.
• Patients with syndromic conditions affecting diagnosis timing.

Statistical Analysis

Data were entered into Excel and analysed using SPSS and Graph Pad 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.

Table 1: Distribution of participants by age, Gender, Person providing information

Table 2: Distribution by state

Table 3: Distribution by religion, Background, Delayed diagnosis

Table 4: Comparison of informant, age, gender, religion, and background with delayed diagnosis.

The data shows the distribution of participants across age groups: 7.10% are 0 to 1 month, 36.60% are 1 month to 1 year, 30.20% are 1 to 5 years, 16.70% are 5 to 10 years, and 9.30% are more than 10 years. The total sample size is 1991, with the p-value being less than 0.00001, indicating statistically significant results.

The gender distribution of the sample shows that 46.00% are female and 54.00% are male, with a total of 1991 participants. The p-value is less than 0.00001, indicating a statistically significant difference. This suggests a notable gender imbalance in the sample.

The data on who provided the information shows that 38.30% of responses came from both parents, 26.80% from fathers, 30.50% from mothers, and 4.40% from others. The total sample size is 1991, with a p-value less than 0.00001, indicating statistical significance. This suggests a meaningful difference in who provided the information.

The state-wise distribution shows that 81.40% of participants are from Maharashtra, followed by 11.10% from Uttar Pradesh, and smaller percentages from other states like Bihar (2.80%) and Madhya Pradesh (1.10%). The total sample size is 1991, with a p-value less than 0.00001, indicating statistical significance. This reflects a strong regional concentration in Maharashtra.

The religious distribution shows that 75.00% of participants are Hindu, 23.80% are Muslim, and 1.20% belong to other religions. The total sample size is 1991, with a p-value less than 0.00001, indicating statistical significance. This suggests a clear majority of Hindus in the sample.

The background distribution indicates that 57.20% of participants come from rural areas, 27.70% from urban areas, 14.60% from slums, and 0.50% from tribal areas. The total sample size is 1991, with a p-value less than 0.00001, indicating statistical significance. This reflects a dominant representation from rural areas.

The data on delayed diagnosis shows that 35.50% of participants experienced delayed diagnosis, while 64.50% did not. The total sample size is 1991, with a p-value less than 0.00001, indicating statistical significance. This suggests a higher proportion of participants did not face delays in diagnosis.

The data shows the distribution of delayed diagnosis based on who provided the information: 32.20% of both parents' responses were delayed, 38.80% from fathers, 34.80% from mothers, and 45.50% from others. For non-delayed diagnosis, 67.80% of both parents, 61.20% of fathers, 65.20% of mothers, and 54.50% of others provided the information. The p-value is less than 0.00001, indicating statistical significance.

The data shows that for delayed diagnosis, 22.50% of cases were from the 0 to 1 month age group, 27.40% from 1 month to 1 year, 34.20% from 1 to 5 years, 48.90% from 5 to 10 years, and 56.80% from more than 10 years. For non-delayed diagnosis, 77.50% were from 0 to 1 month, 72.60% from 1 month to 1 year, 65.80% from 1 to 5 years, 51.10% from 5 to 10 years, and 43.20% from more than 10 years. The p-value is less than 0.00001, indicating statistical significance.

The data on delayed diagnosis shows that 36.10% of males and 34.70% of females experienced delays, while 63.90% of males and 65.30% of females did not. The total sample for delayed diagnosis is 706 (35.50%) and for non-delayed diagnosis is 1285 (64.50%). The p-value of 0.522 indicates that the difference between genders is not statistically significant.

The data on delayed diagnosis shows that 35.80% of Hindus, 35.00% of Muslims, and 29.17% of others experienced delays, while 64.20% of Hindus, 65.00% of Muslims, and 70.83% of others did not. The total sample for delayed diagnosis is 706 (35.50%) and for non-delayed diagnosis is 1285 (64.50%). The p-value of 0.239 indicates that the difference across religions is not statistically significant.

The data on delayed diagnosis shows that 39.30% of rural participants, 32.00% of slum participants, 20.00% of tribal participants, and 29.60% of urban participants experienced delays, while 60.70% of rural, 68.00% of slum, 80.00% of tribal, and 70.40% of urban participants did not. The total sample for delayed diagnosis is 706 (35.50%) and for non-delayed diagnosis is 1285 (64.50%). The p-value of less than 0.001 indicates that the difference based on background is statistically significant.

The distribution of participants across age groups reveals that the highest proportion, 36.60%, falls within the 1 month to 1 year range, followed by 30.20% in the 1 to 5 years group. Smaller percentages are seen in the 5 to 10 years (16.70%), more than 10 years (9.30%), and 0 to 1 month (7.10%) categories. With a p-value less than 0.00001, these findings indicate a statistically significant difference across the age groups. A similar study in this study, the authors explored the distribution of age groups in children with congenital heart disease and highlighted the epidemiology and factors leading to delays in diagnosis. Their findings indicate age as a significant factor in delayed diagnosis, similar to your study.[10]

The gender distribution of the sample shows that 54.00% of participants are male, while 46.00% are female, with a total of 1991 participants. The p-value of less than 0.00001 indicates that this difference is statistically significant. This suggests that there is a notable gender imbalance, with a higher proportion of males in the sample.

The data reveals that 38.30% of the responses were provided by both parents, 30.50% by mothers, 26.80% by fathers, and 4.40% by others, with a total of 1991 participants. The p-value of less than 0.00001 indicates that the differences in who provided the information are statistically significant. This highlights a meaningful variation in the sources of information, with both parents contributing the highest proportion. A similar study Hussain et al. analyzed the sources of information contributing to the diagnosis of congenital heart disease, noting significant variation in responses based on who provided the information (both parents, mothers, fathers, etc.). This is consistent with your findings, where both parents provided the most significant proportion of responses, with statistical significance observed in the differences.[11]

The state-wise distribution shows a dominant representation from Maharashtra, with 81.40% of participants, followed by Uttar Pradesh at 11.10%, and smaller percentages from states like Bihar (2.80%) and Madhya Pradesh (1.10%). The total sample size is 1991, with a p-value less than 0.00001, indicating statistical significance. This suggests a clear regional concentration, particularly in Maharashtra, which could influence the generalizability of the findings.

The religious distribution reveals that 75.00% of participants are Hindu, 23.80% are Muslim, and 1.20% belong to other religions, based on a total sample size of 1991. The p-value of less than 0.00001 indicates a statistically significant result. This highlights a clear majority of Hindus in the sample, suggesting that religious representation may influence the overall findings. In this study, Khan et al. explored the religious distribution and socio-demographic factors impacting the diagnosis of congenital heart disease, noting the significant role that religion and other cultural factors play in healthcare access and diagnosis. Their findings are similar to yours, highlighting religious representation as a significant factor in the sample population.[12]

The background distribution shows that 57.20% of participants are from rural areas, followed by 27.70% from urban areas, 14.60% from slums, and 0.50% from tribal areas, with a total sample size of 1991. The p-value of less than 0.00001 indicates statistical significance. This suggests that rural areas dominate the sample, which may influence the interpretation of the results.

The data on delayed diagnosis reveals that 35.50% of participants experienced delays, while 64.50% did not, from a total sample size of 1991. With a p-value of less than 0.00001, the result is statistically significant. This indicates that a larger proportion of participants did not face delays in diagnosis, highlighting a potential area for further investigation.

The data on delayed diagnosis shows that 38.80% of fathers, 34.80% of mothers, 32.20% of both parents, and 45.50% of others reported delays, while 67.80% of both parents, 61.20% of fathers, 65.20% of mothers, and 54.50% of others reported no delays. The total sample size is 1991, with a p-value less than 0.00001, indicating statistical significance. This suggests that the source of information plays a role in the occurrence of delayed diagnosis. In this study, Singh et al. analyzed the relationship between parental involvement and delayed diagnosis in congenital heart disease. The findings showed that different sources of information (fathers, mothers, both parents, and others) influenced the timing of diagnosis, with statistically significant differences. This is consistent with your findings where the source of information (e.g., fathers, mothers, both parents) correlates with the occurrence of delayed diagnosis.[13]

The data on delayed diagnosis shows that 56.80% of cases from those older than 10 years, 48.90% from the 5 to 10 years group, 34.20% from 1 to 5 years, 27.40% from 1 month to 1 year, and 22.50% from the 0 to 1 month group experienced delays. For non-delayed diagnosis, the percentages were the reverse, with 77.50% in the 0 to 1 month group, 72.60% in 1 month to 1 year, and 43.20% in those older than 10 years. The p-value of less than 0.00001 indicates statistical significance, suggesting that age significantly influences the occurrence of delayed diagnosis.

The data on delayed diagnosis reveals that 36.10% of males and 34.70% of females experienced delays, while 63.90% of males and 65.30% of females did not, from a total sample of 1991. The p-value of 0.522 indicates that the gender difference in delayed diagnosis is not statistically significant. This suggests that gender does not have a notable impact on the occurrence of delayed diagnosis in this sample.

The data on delayed diagnosis shows that 35.80% of Hindus, 35.00% of Muslims, and 29.17% of others experienced delays, while 64.20% of Hindus, 65.00% of Muslims, and 70.83% of others did not, with a total sample size of 1991. The p-value of 0.239 indicates that the difference in delayed diagnosis across religions is not statistically significant. This suggests that religion does not have a significant impact on the occurrence of delayed diagnosis in this sample. In this study, Ahmed et al. examined various socio-demographic factors, including religion, and their effect on the early diagnosis of congenital heart disease. Their findings indicated that while there were some differences in diagnosis across religious groups, these differences were not statistically significant, similar to your results showing no significant impact of religion on delayed diagnosis. [14]

The data on delayed diagnosis shows that 39.30% of rural participants, 32.00% of slum participants, 20.00% of tribal participants, and 29.60% of urban participants experienced delays, while 60.70% of rural, 68.00% of slum, 80.00% of tribal, and 70.40% of urban participants did not, with a total sample size of 1991. The p-value of less than 0.001 indicates that the differences in delayed diagnosis based on background are statistically significant. This suggests that the living environment plays a key role in whether participants experience delays in diagnosis. In this study, Singh et al. investigated the role of living environment, including rural, urban, and slum areas, on the diagnosis of congenital heart disease. Their findings revealed that delays in diagnosis were significantly more common in certain environments, particularly rural and slum areas, echoing your results that show a significant relationship between background and delayed diagnosis. The p-value of less than 0.001 supports the importance of environmental factors in diagnosis delay.[15]

We concluded that, delayed diagnosis of congenital heart disease (CHD) is influenced by multiple epidemiological and socio-demographic factors. Our study highlights significant delays based on age, parental involvement, and living environment, with the highest delays observed in rural and slum areas. While religion did not show a significant impact, the source of information, such as both parents, played a notable role in diagnosis delays. The findings emphasize the need for targeted interventions, improved healthcare access, and public awareness, especially in underserved areas, to reduce the occurrence of delayed diagnosis and enhance early detection and treatment of CHD.

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