- Academic Editor
†These authors contributed equally.
Background: The population of adults with congenital heart defects
(ACHD) is growing. The leading cause of premature death in these patients is
heart failure (HF). However, there is still limited information on the predictive
factors for HF in ACHD patients. Objectives: This study re-examined a
group of patients with repaired or palliated congenital heart defects (CHD) that
were initially studied in 2003. A follow-up period of 15 years has allowed us to
identify and evaluate predictors for the development of HF in ACHD.
Methods: All patients with repaired or palliated CHD who participated in
the initial study (n = 364) were invited for a follow-up examination. The effects
of maximum oxygen uptake (VO
The prevalence of congenital heart defect (CHD) in newborns is approximately 1% [1]. Improvements in diagnostics and in surgical and catheter interventions over the last 40 years have significantly prolonged life expectancy. As a consequence, the population of adults with congenital heart defects (ACHD) has surpassed the number of children with CHD [2] and continues to increase. However, ACHD experience residual effects and sequelae that require regular surveillance throughout their lifespan [3], including heart failure (HF) and arrhythmias [4].
HF is the leading cause of premature death in ACHD [5]. The identification of surrogate parameters for HF in ACHD and the development of predictive models should lead to earlier identification of high-risk patients, thereby enabling timely intervention and preventive measures.
Although several studies have described prediction models and risk factors for HF in patients without CHD, there is still very little data on predictors for HF in ACHD [6, 7]. The focus of published literature is primarily on the evaluation of a single clinical parameter for predicting long-term outcomes in ACHD, such as N-terminal pro brain natriuretic peptide (NT-proBNP), cardiopulmonary exercise testing, QRS duration, fractional shortening, and ejection fraction [8, 9, 10, 11]. Gaps remain in our understanding of the predictors for HF in ACHD, including the utility of combining various parameters, and whether the available clinical variables can predict HF at an early stage.
To fill this knowledge gap, the aim of the current study was to determine whether a combination of clinical parameters can identify ACHD patients who are at increased risk of HF, therefore requiring more intensive follow-up care and early preventive interventions.
A previous study from 2003–2004 entitled Life Chances 1 (LC1) investigated 364 patients with various types of repaired or palliated CHD [12]. These patients were treated by surgical or interventional procedures at the University Hospital of Goettingen, Germany, and then followed up in our ACHD clinic. The LC1 study included patients aged 13–50 years (median age, 26.4 years). Patients had undergone a medical history review, physical examination, electrocardiography (ECG), 2D-echocardiogram, blood sampling, metabolic exercise testing, and assessment of their psychological and socioeconomic status.
The present study is entitled Life Chances 2 (LC2). In 2017, all patients who had participated in LC1 were invited by phone, mail, or their family physician to attend the ACHD clinic for a follow-up examination [13].
The severity of CHD was assessed according to the 2020 European Society of Cardiology (ESC) Guidelines for the management of ACHD [14]. Patients were categorized into three groups: mild, moderate, or complex CHD. In patients with multiple cardiac lesions, the lesion with the highest complexity was used to assign the patient.
HF is not a single pathological diagnosis, but rather a clinical syndrome consisting of cardinal symptoms such as breathlessness, ankle swelling, and fatigue. For the purpose of this study, patients were classified as having developed HF if at least one of the following criteria was fulfilled:
(1) Patient had not been taking any HF medication (e.g., diuretic, beta blocker, ACE inhibitor, etc.) during LC1, but then started taking HF medication between LC1 and LC2. Although in a small number of patients these medications might have been used to treat hypertension, this condition could be considered a precursor for HF.
(2) Patient who required a surgical/interventional procedure for their underlying CHD, or had been admitted to a hospital for HF between LC1 and LC2.
(3) Patient who had died of HF between LC1 and LC2.
Only patients who had participated in the LC1 study were eligible for inclusion in LC2. Patients who were pregnant during the enrollment period for LC2 were excluded.
All patients provided written informed consent. The first part of this study was reviewed and approved by the ethics committee of Hannover Medical School under no. 3710 (date: 04-10-2004) and by the University Medical Center Goettingen under no. 10/2/01 (date: 01-03-2001). The second part was reviewed and approved by the ethics committee of the University Medical Center Goettingen under no. 15/8/14.
All patients underwent physical examination and measurement of heart rate, blood pressure, body weight, height, and standard 12-lead ECG.
Exercise testing for LC2 was performed on an upright bicycle ergometer and began
with 2 minutes of unloaded peddling, followed by cycling against increasing
resistance until exhaustion (RAMP protocol), and concluding with 3 to 5 minutes
of cycling with minimal resistance. The choice of ramp protocol steepness was
tailored to the patient’s exercise tolerance based on previous exercise tests,
gender and weight. The aim was for a test duration ranging between 8 and 12
minutes. Oxygen uptake was measured using breath-by-breath analysis (Oxycon pro,
Jaeger Company, Hoechberg, Germany) throughout the exercise procedure. All
patients exercised to maximum exercise capability, and peak oxygen consumption
(VO
Peripheral venous blood samples were obtained from all patients after resting
for at least 15 minutes and prior to exercise testing. The blood samples were
immediately placed on ice and centrifuged at 5000 rpm for 10 minutes. Plasma and
serum aliquots were stored at –80 °C until further analysis. NT-proBNP
for the LC2 study was measured via Alere NT-proBNP for ARCHITECT Assay
(Axis-Shield Diagnostics Limited, Dundee, United Kingdom). This is a
Chemiluminescence-Microparticle-Immunoassay (CMIA) in which values
For the LC1 study, NT-proBNP was measured by immunoassay (Elecsys 2010, Roche,
Diagnostics GmbH, Mannheim, Germany). The mean NT–proBNP value for 100 age- and
gender-matched healthy blood donors was used as a reference for the LC1 patient
data (mean
Two-dimensional transthoracic echocardiography was performed in all patients using EPIQ 7 (Philips, Amsterdam, Netherlands). It was decided not to include echocardiography data in the present analysis because of the heterogeneous cardiac morphology in the complex ACHD group. This often limits the interpretation of cardiac function and makes it partly subjective, especially in patients with systemic right ventricle or single ventricle physiology [17].
Continuous variables were summarized with means and standard deviations.
Categorical variables were summarized using frequencies and percentages. Receiver
operating characteristic (ROC) curves were constructed for variables of interest,
and areas-under-the-curve (AUC) were calculated to identify cut-off values based
on the highest levels of sensitivity and specificity for predicting HF, with an
AUC
Of the initial 364 patients in LC1, a total of 249 patients (68%, 134 male and 115 female) were recruited to participate in LC2. The remaining 115/364 (32%) patients did not participate in LC2 for the following reasons: patient could not be reached or was lost to follow-up (48/364, 13%), patient declined to participate (45/364, 12%), or patient had died (22/364, 6%). Two other patients died shortly after inclusion in LC2.
The distribution of CHD severity between the LC1 and LC2 participants did not differ significantly. CHD severity in the 364 patients (58% male, 42% female) from LC1 was mild (81, 22%), moderate (199, 55%), and severe (84, 23%), while in the 249 patients (58% male, 42% female) from LC2 it was mild (52, 21%), moderate (150, 60%), and severe (47, 19%).
Patients were further classified according to their diagnosis and lesion complexity. Table 1 shows patient classification based on diagnosis, as well as the patient demographics and prevalence of HF at initial assessment (LC1-HF), and in patients who developed HF by the start of LC2 (LC2-HF). A total of 57 patients (23%) had already developed HF at LC1, while another 67 of the remaining 192 patients (35%) developed HF during the follow-up period. Of note, patients with ventricular septal defect (VSD) closure had the lowest risk of developing HF (10%), whereas all patients with single ventricle physiology (Fontan) had developed HF by LC2.
Type of heart defect | N (female) | LC1-HF (female) % | Age-LC2 (mean |
LC2-HF (female) | New HF % | p |
Atrial septal defect | 15 (9) | 1 (0) {4} | 36 (8) | 2 (1) | 14 | 0.30 |
Ventricular septal defect | 21 (9) | 1 (0) {3} | 39 (9) | 2 (1) | 10 | 0.28 |
AV septal defect | 12 (7) | 2 (1) {13} | 40 (8) | 3 (2) | 30 | 0.43 |
Pulmonary valve disease | 14 (6) | 2 (1) {11} | 40 (10) | 3 (2) | 25 | 0.44 |
Aortic valve disease | 27 (4) | 8 (0) {22} | 42 (9) | 11 (2) | 58 | 0.10 |
Coarctation of the aorta | 38 (16) | 13 (5) {27} | 39 (7) | 8 (2) | 32 | 0.10 |
D-TGA | 19 (5) | 3 (0) {9} | 36 (5) | 9 (2) | 56 | 0.001 |
Tetralogy of Fallot | 51(22) | 11 (6) {12} | 45 (9) | 17 (6) | 43 | 0.01 |
Fontan procedure | 9 (5) | 4 (2) {24} | 40 (8) | 5 (3) | 100 | 0.11 |
Miscellaneous | 43 (22) | 12 (6) {18} | 38 (7) | 7 (4) | 23 | 0.78 |
Total | 249 (105) | 57 (21) {16} | 67 (25) | 35 (67 of 192) | 0.0009 | |
AV Septal defect, Atrioventricular septal defect; D-TGA, dextro-Transposition of the great arteries after surgical procedure except arterial switch; HF%, patients who developed HF from LC1 to LC2 in relation to the patients who did not have HF within this time frame; LC1-HF, number of patients who were on heart failure medication at LC1; LC2-HF, number of patients who developed HF between LC1 and LC2; SD, standard deviation. p indicates LC1-HF vs. LC2-HF. |
Table 2 (Ref. [18]) shows the classification of patients according to lesion severity, as outlined by the 2020 ESC Guidelines for the management of ACHD [14]. Fifty-two (21%) had mild CHD, 150 (60%) had moderate CHD, and 47 (19%) had complex CHD. Patient demographics at the time of clinical work-up for LC1 and LC2 are also shown in Table 2. There was no significant difference in mean age between the three ACHD groups (p = 0.160).
Mild-CHD | Moderate-CHD | Complex-CHD | |
LC2 (LC1) {%} | LC2 (LC1) {%} | LC2 (LC1) {%} | |
Number of patients | 52 (81) {64%} | 150 (199) {75%} | 47 (84) {56%} |
Male/female (LC2) | 27/25 | 87/63 | 30/17 |
Age (years) | 39 |
41 |
38 |
VO |
85 |
86 |
72 |
NT-proBNP (pg/mL) | 142 |
182 |
560 |
QRS (ms) | 112 |
132 |
130 |
Patients with HF at LC1 | 6 of 52 | 35 of 150 | 17 of 47 |
Patients without HF at LC2 | 38 | 73 | 13 |
Patients with new HF at LC2 (%) | 8 of 46 {17%} | 42 of 115 {37%} | 17 of 30 {57%} |
Data are displayed as the mean |
As stated above, 67 of the 192 patients (35%) who did not have HF at LC1 later developed HF during the follow-up in LC2.
Table 2 shows the distribution of new HF cases according to lesion complexity.
Of note, the percentage of patients with new HF increased as the lesion
complexity increased (mild CHD: 17%, moderate CHD: 37%, complex CHD: 57%).
Significant differences (p
Table 2 and Fig. 1A,B show the levels of NT-proBNP in the three ACHD groups at
LC1 and LC2, respectively. Significant increases in NT-proBNP were observed in
all three groups at LC2 compared to LC1. Differences between the three groups at
LC2 remained significant (mean complex ACHD = 560 pg/mL, mean moderate CHD = 182
pg/mL, and mean mild CHD = 142 pg/mL; p

NT-proBNP levels (pg/mL) for mild, moderate, and severe CHD at
LC1 (A) and LC2 (B). Mean
Table 3 shows the NT-proBNP levels at LC1 in patients who later developed HF in LC2. These were already significantly higher compared to patients who did not develop HF.
HF patients | Non-HF patients | p | |
Number of patients | 67 | 125 | |
VO |
74 |
80 |
0.03 |
NT-proBNP (pg/mL) | 126 |
88 |
0.03 |
QRS (ms) | 121 |
110 |
0.10 |
VO |
Table 2 and Fig. 2A,B show the percentage of predicted VO

VO
Table 2 and Fig. 3A,B show the QRS duration in all three groups at LC1 and LC2, respectively. In LC1 there was no significant difference in mean QRS duration between patients with moderate and complex ACHD (121 vs. 115 ms, respectively; p = 0.4). However, the QRS complexes of these patients was significantly longer compared to that of mild ACHD patients (103 ms; p = 0.002). In LC2, the mean QRS duration in all three groups was significantly longer compared to the equivalent group from LC1: 112 ms for mild (p = 0.03), 130 ms for moderate (p = 0.0001), and 132 ms for complex CHD (p = 0.001). The QRS duration of LC2 patients with mild CHD was shorter than that of the other two groups (p = 0.001), but there was no significant difference between the moderate and complex CHD patients (p = 0.99).

QRS duration (ms) for mild, moderate, and severe CHD (mean
The following parameters were found to be the best predictors for the
development of HF between LC1 and LC2: NT-proBNP
Parameter | Patient group | AUC | Sensitivity | Specificity |
---|---|---|---|---|
NT-proBNP | All Patients | 0.71 | 0.64 | 0.67 |
Only mild + moderate | 0.66 | 0.63 | 0.63 | |
VO |
All Patients | 0.64 | 0.56 | 0.67 |
Only mild + moderate | 0.62 | 0.60 | 0.50 | |
QRS | All Patients | 0.65 | 0.56 | 0.69 |
Only mild + moderate | 0.68 | 0.60 | 0.68 | |
NT-proBNP + VO |
All Patients | 0.71 | 0.63 | 0.67 |
Only mild + moderate | 0.68 | 0.56 | 0.70 | |
NT-proBNP + QRS | All Patients | 0.71 | 0.69 | 0.68 |
Only mild + moderate | 0.71 | 0.63 | 0.71 | |
VO |
All Patients | 0.66 | 0.77 | 0.52 |
Only mild + moderate | 0.67 | 0.76 | 0.53 | |
NT-proBNP + VO |
All Patients | 0.75 | 0.75 | 0.63 |
Only mild + moderate | 0.75 | 0.73 | 0.66 | |
The following parameters were included for this calculation: NT-proBNP greater
than 1.7 times the upper normal limit ( |

Results of AUC, sensitivity, and specificity analyses for the
development of HF in all three ACHD groups for individual parameters, and in
combination. No statistically significant differences were found between results
for the combined parameters and the individual parameters of NT-proBNP
(p = 0.630), VO
The timely identification of patients who are at risk of developing HF is critical to improving their outcome through appropriate therapeutic intervention. Several international HF societies and associations recently published a consensus statement that emphasizes the importance of adding objective parameters to the clinical findings in order to establish a universal definition and classification of HF [19]. HF poses a major challenge for the management of ACHD patients, including its definition, pathophysiologic understanding, healthcare planning, and the provision of evidence-based medical therapies to improve outcomes [20]. The current study provides long-term follow-up data of previously described ACHD patients with mild, moderate, and complex CHD. We were able to identify objective and easily reproduceable parameters to predict the development of HF in this patient cohort over a 15-year interval.
Biomarkers have major significance for the diagnosis of HF. Giannokoulas
et al. [8] reported that elevated BNP levels (
VO
Patients in LC1 with complex ACHD already had significantly reduced VO
Widening of the QRS complex has been identified as an independent predictor of
adverse outcomes in ACHD [10, 27]. Müller et al. [28] conducted a
multicenter retrospective investigation on 875 patients with tetralogy of Fallot.
These authors reported that patients with a QRS duration of
In adults without CHD, QRS prolongation
The progression of QRS complex duration in our patients (mainly in the moderate and complex CHD groups) from LC1 to LC2 is assumed to reflect decreasing cardiac function as a pattern of electro-mechanical interaction. In patients without CHD, progressive increases in QRS duration were shown to predispose HF patients to an increased risk of ventricular tachyarrhythmias [32, 33].
In order to identify surrogate parameters for predicting the development of HF,
we applied logistic regression models to combinations of the top-performing
variables of interest. Regardless of the severity of the underlying HF, the best
result was found to be a combination of three parameters: NT-proBNP,
VO
Our findings indicate that assessment of these parameters in ACHD patients could provide predictive information on patients who are at high risk of developing HF. These parameters have the advantage of being investigator-independent and of not requiring a deep knowledge of CHD. Hence, they might be a useful screening tool to indicate the need for referral to large ACHD centers.
To the best of our knowledge, this study is unique as it analyzes a large cohort of ACHD patients with a wide variety of CHD over a 15-year period. This allowed us to identify robust parameters for predicting the development of HF. It is important to note that these parameters can be applied for risk stratification of all ACHD patients, regardless of the type and complexity of their underlying CHD. Presently, HF is often not identified promptly in patients with ACHD. The increasing number of hospitalizations of ACHD patients, particularly due to HF, is a growing burden on the healthcare system [34, 35]. The present study found that investigator-independent parameters consisting of a laboratory test, exercise test and ECG can be used to construct prediction models that help to identify ACHD patients who are at high risk of developing HF. These patients may benefit from early referral and close follow-up by ACHD specialists, thereby allowing sophisticated monitoring and timely interventions.
Although the number of patients from the LC1 study who were lost to follow-up
was quite low (13%), 32% of the original cohort did not participate in the
current study. This may have affected the results, since the prevalence of HF in
patients with ACHD is unknown [13]. Notably, more patients with mild CHD were
lost to follow-up than patients with moderate or complex CHD. Multiple factors
could have contributed to this, including the patients’ belief that further
cardiological follow-up was not required, refusal to accept CHD as a life-long
issue, moving to an area without a known ACHD specialist, or simply changing the
place of residence. Another limitation was the different immunoassays used during
the LC1 and LC2 studies. The NT-proBNP immunoassays used in LC1 were different
to those used in LC2. However, the value of
ACHD, Adult Congenital Heart Defect; CHD, Congenital Heart Defect; HF, Heart
Failure; LC1, Life chances 1: Assessment of patients between 2003 and 2004; LC2,
Life chances 2: Assessment of patients between 2018 and 2019; NT-proBNP,
N-terminal pro Brain Natriuretic Peptide; VO
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
KN, TP, CD and SG conceived the study. CD and MJM initiate the recruitment, coordinated and supervised patients’ examinations. CD, MJM and JB performed testing and acquired the data. KN, SG, CX and MRM performed data analysis and statistics. All authors contributed significantly to the preparation of manuscript and its’ internal revisions. All authors have read and agreed to the published version of the manuscript.
The first part of this study was reviewed and approved by the ethics committee of Hannover Medical School under no. 3710 (date: 04-10-2004) and by the University Medical Center Goettingen under no. 10/2/01 (date: 01-03-2001). The second part was reviewed and approved by the ethics committee of the University Medical Center Goettingen under no. 15/8/14. All patients provided written informed consent.
We greatly acknowledge the excellent work from Iris Bolle (Dept. of Pediatric Cardiology, University Clinic of Göttingen) for contacting the patients and organizing follow-up appointments.
This manuscript is based on two research projects: the first was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft DFG; grant numbers WE 2670/1–1 and GE1167/2–1. The follow-up study was funded by Stiftung Kinderherzen, grant number W-GÖ-014/2016 (URL: https://www.kinderherzen.de).
The authors declare no conflict of interest.
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