Body Mass Index in Adult Congenital Heart Disease Patients: Distribution, Association with Exercise Capacity and Prognostic Implication.

Margarita Brida MD 2,3, Konstantinos Dimopoulos MD PhD MSc 1,2, Alexander Kempny MD 1,2, Em-

manouil Liodakis MD 1, Lorna Swan MD 1,2, Anselm Uebing MD PhD 1,2, Helmut Baumgartner MD 3,

Michael A Gatzoulis MD PhD 1,2, Gerhard-Paul Diller MD PhD MSc 1-3,

(1) Adult Congenital Heart Centre and Centre for Pulmonary Hypertension, NIHR Cardiovascular and Respiratory Biomedical Research Unit, Royal Brompton Hospital, London, UK (2) National Heart and Lung Institute, Imperial College London, London, UK (3) Division of Adult Congenital and Valvular Heart Disease, Department of Cardiovascular Medicine, University Hospital Muenster, Muenster, Germany.

This study was supported by a research grant from the EMAH Stiftung Karla Voellm, Krefeld, Germany. G-P.D., A.K., K.D. M.G. and the Adult Congenital Heart Centre and Centre for Pulmonary Hypertension, Royal Brompton Hospital, London, UK have received support by Actelion UK, Pfizer UK, GSK UK, the British Heart Foundation and the NIHR Cardiovascular and Respiratory Biomedical Research Units

Correspondence to:Gerhard-Paul Diller MD PhD National Heart and Lung Institute, Imperial College London, Dovehouse StreetLondon SW3 6LY United KingdomTel: +44 207 351 8127Email: gerhard.diller@gmail.com

Manuscript word count: 3895

Background:

Abnormal body mass index (BMI) is associated with increased mortality in various

cardiovascular cohorts. Increasing rates of obesity raised concerns on the prognostic

implications of a high BMI in adults with congenital heart disease (ACHD). We aimed to

assess the distribution of BMI and its association with symptoms, exercise capacity and

survival in this population.

Methods and Results:

We included 3,069 ACHD patients (median age 32.6 years) under follow-up at our institution

between 2001 and 2015. Patients were classified based on BMI as underweight (<18.5),

normal weight (18.5-25), overweight (25-30) or obese (>30) and symptoms and objective

exercise capacity were assessed. Overall, 6.2% of patients were underweight , 28.2%

overweight and 14.6% obese. A lower BMI was associated with more symptoms and lower

absolute and percentage predicted peak oxygen uptake (p<0.05 for both). Moreover, higher

BMI values were associated with lower all-cause and cardiac mortality on univariable Cox

analysis and this effect persisted after adjustment for age, defect complexity, cyanosis and

objective exercise capacity. In patients with a complex cardiac defect who had repeated

weight measurements, weight loss was also associated with a worse survival (HR 1.82, 95%

CI 1.02-3.24, P=0.04).

Conclusions:

ACHD patients with a higher BMI were less symptomatic and had a higher objective exercise

capacity and lower mortality. The association between BMI and mortality was especially

pronounced in symptomatic patients with complex underlying cardiac defects, suggesting that

cardiac cachexia may play a role. Indeed, weight loss was linked to an even higher mortality

in complex ACHD.

Abstract - word count: 250

The number of adults with congenital heart disease (ACHD) has markedly increased

over the past few decades.1, 2 Although most ACHD patients undergo surgical intervention in

childhood, this is not curative and life-long follow-up is required due to a high incidence of

long-term complications.3 Exercise intolerance is not uncommon in ACHD and is in part

secondary to chronic detraining. From early age, many patients have been advised against

certain types of physical activity. Furthermore, physicians have historically focused on

encouraging weight gain, particularly in early childhood, when failure to thrive is often

encountered and long term eating habits begin to develop.4 As a consequence, restricted

exercise and increased food intake could predispose to obesity.

Obesity is emerging as a global epidemic and its prevalence has increased at an alarming rate

in the last few decades worldwide.5 While numerous studies have established that obesity

increases the risk of premature mortality and predisposes to diseases such as diabetes,

hypertension, or cardiovascular disease in the general population,6-9 its impact in chronic life-

long conditions is less clear. In contrast to the widely held public belief that obesity invariably

shortens life expectancy, there is recent evidence that the optimal body size may be differ

between normal individuals and those with long-standing chronic disease, in whom a higher

body mass index (BMI) may be associated with a better outcome. This so-called “obesity

paradox”10 has linked higher BMI to better survival in a variety of chronic diseases, such as

chronic heart failure,11, 12 kidney disease and chronic obstructive pulmonary disease.13

Body mass index, the index of “weight-for-height” (kg/m²), is the metric recommended by the

World Health Organization (WHO) to define underweight, normal weight, overweight and

obesity. The cut-offs used are based on data from healthy populations in which there appears

to be a U-shaped relationship with mortality. Underweight and cachexia on one side and

obesity, particularly morbid obesity (> 40 kg/m²), on the other side have been shown to be

associated with increased mortality relative to the normal weight category in primary

prevention, general population studies.9, 14-16

Limited and conflicting data on the prevalence of obesity in ACHD exist and the association

between BMI and outcome has not yet been established.17-19 The aim of our study was to

establish the distribution of BMI and its association with symptoms, objective exercise

capacity and outcome in a large contemporary cohort of ACHD patients.

Patients and Methods

We retrospectively reviewed data on all patients with congenital heart disease under

active follow-up at the Royal Brompton Hospital, London between 2001 and 2015, based on

available administrative and clinical databases. All patients older than 14 years of age in

whom data on height and weight were electronically available were included. Whenever

possible, data collected at the time of cardiopulmonary testing was favoured over other data

sources to allow accounting for physical fitness. In patients with more than one exercise test

during the study timeframe, information from the last test was used for analysis. Data

containing information on diagnosis, age, gender, height, weight, NYHA functional class,

blood pressure and arterial oxygen saturation were collected. In patients undergoing

cardiopulmonary exercise testing (87.6% of the population), data on peak oxygen

consumption, VE/VCO2 slope and blood pressure / heart rate response to exercise were

included. Patients underwent exercise testing on a treadmill using a modified Bruce protocol

as previously published.20, 21 The severity of the cardiac defect was categorized based on the

Bethesda system as “simple”, “moderate” or “complex”.22 Patients with multiple defects but

without Eisenmenger syndrome were classified as complex. Body mass index was calculated

as body weight (in kg) divided by squared height (in metres). As recommended by the World

Health Organization (WHO), patients were classified based on BMI as underweight (< 18.5

kg/m²), normal weight (18.5–24.9 kg/m²), overweight (≥ 25–29.9 kg/m²) and obese (≥ 30

kg/m²).23

In addition, if more than one weight recording over time was available in a patient, the two

most recent values were used to calculate temporal weight/BMI changes. Data on overall

mortality were retrieved from the Office for National Statistics, which registers all United

Kingdom deaths. The cause of death was established from medical records and death

certificates by one investigator (G-P.D.). As this was a retrospective analysis based on data

collected for routine clinical care and administrative purposes (UK National Research Ethics

Service guidance), individual informed consent was not required.

Statistical Analysis

Data are presented as numbers / percentages for categorical variables, while

mean±standard deviation values or median and interquartile ranges (IQR) are given for

continuous variables depending on data distribution. In addition to rank correlation (providing

Spearman's ρ), quantile regression analysis was used to account for non-linear associations

between BMI and exercise parameters. The latter describes the relationship between a

response and predictor variables, by providing estimates for more than a single slope.24 The

association between BMI and mortality was assessed with the use of uni- and multivariable

Cox proportional hazards regression analysis. The proportional hazards assumption was

verified using generalized linear regression analysis, testing for a non-zero slope of the scaled

Schoenfeld residuals in addition to visual inspection of the graphs of the regression. Relevant

clinical parameters were tested for significance on univariable analysis. Parameters

significantly predicting prognosis on univariable analysis were subsequently included in

multivariable time dependent models. For all analyses, a 2-tailed p-value <0.05 was used as

the criterion for statistical significance. Analyses were performed with the use of R version

3.1.0 (R Foundation for Statistical Computing).

Results

Overall, 3,086 patients were included in the current analysis. As illustrated in Table 1,

48% of patients were female and the median age of the study group was 32.6 years. The

majority of patients had normal weight (51.1%), while 6.2% of patients were underweight and

14.6% of the population was classified as obese based on BMI. Obese patients were

significantly older (41.1 [IQR: 27.8-50.5] vs. 31.9 [23.4-43.5] years; p<0.0001) and had

higher systolic and diastolic blood pressure values compared to non-obese subjects (125 [115

– 136] vs. 118 [108 – 125] mmHg and 80 [70 – 85] vs. 74 [67 – 80] mmHg; p<0.0001 for

both). In contrast, underweight subjects were more likely to be cyanotic (13.1 vs. 6.5%;

p=0.0009), have complex cardiac disease (33.9 vs. 22.4%; p=0.0005) or be more symptomatic

(46.3 vs. 34.5% NYHA class ≥ 3; p=0.003) compared to the remaining patients. In addition, a

higher BMI was directly correlated with age (=0.27; p<0.0001), systolic (=0.27; p<0.0001)

and diastolic blood pressure (=0.31; p<0.0001).

A small minority of patients had underlying syndromes (Down syndrome 1.1%; Di George

0.7%, Noonan or Turner syndrome 0.1%). These patients had significantly lower body weight

(60.8 [55.3 – 73.4] vs. 70.1 [60.1 – 82.3] kg; p<0.0001) and height (160 [148 – 168] vs. 170

[163 – 178] cm; p<0.0001) but similar BMI values (25.2 [21.3 – 27.7] vs. 24.0 [21.4 – 27.5]

kg/m²; p=0.27) compared to the remainder.

The highest proportion of underweight patients was observed in Eisenmenger syndrome

(16.0%), followed by patients with a Fontan palliation (12.0%), patients after arterial switch

operation for transposition of the great arteries (9.2%) and other complex cardiac defects

(8.7%). In contrast, the highest rate of obese patients was seen in patients with atrial septal

defect (19.1%), followed by atrioventricular septal defect (18.0%), valve/outflow tract disease

(17.4%) and tetralogy of Fallot (15.1%).

Association between BMI, symptoms and exercise capacity

As illustrated in Table 1, the majority of patients were in NYHA class I (64.8%). However,

significantly fewer underweight patients were asymptomatic compared to non-underweight

patients (53.7 % vs. 66.3%; p=0.004). In contrast, no significant difference in the proportion

of asymptomatic patients was found between normal weight/overweight and obese patients

(66.3 % vs. 61.7 %; p=0.12). As illustrated in Figure 1A, the proportion of symptomatic and

severely symptomatic patients was higher in underweight patients, but also amongst obese

patients with the highest BMI (> 35 kg/m², severe/morbid obesity).

On quantile regression analysis, a non-linear but positive association between BMI and

absolute peak oxygen consumption was found (Figure 1 B, =0.20; p<0.0001). In addition, a

modest positive association between peak oxygen consumption in percent of predicted value

and BMI was evident (=0.07; p=0.0006). Furthermore, a negative association with lower

VE/VCO2-slope values at higher BMI levels was found (= - 0.11; p<0.0001).

Association between weight, BMI and mortality

Over a median follow-up period of 2.54 years (IQR 0.65-5.31 years) 178 patients (5.8%) died.

The majority of patients died due to cardiac causes (n=121), while the leading non-cardiac

causes of death were pneumonia (n=10), hemorrhage (n=10), cancer (n=7), sepsis (n=7) and

cerebrovascular accidents (n=5). On univariate Cox-proportional-hazards analysis, a higher

patient weight (hazard ratio [HR] 0.984 [95% CI 0.975 – 0.993]/kg; p=0.0007) and a higher

BMI (HR 0.963 [95% CI 0.933-0.994]/kg/m²; p=0.02) were associated with better outcome.

Closer inspection of the association between BMI and outcome revealed a non-linear, U-

shaped relationship. The lowest risk of mortality was formally observed at a BMI of 34.1

kg/m². When the median BMI of 24 kg/m² was used as a reference value, the relative hazard

of death was increased for BMI values below this threshold but was lower for patients with a

BMI between 24 kg/m² and approx. 40. Only, severely obese patients (BMI>40 kg/m²) had

higher relative risk compared to those with a median BMI.

A higher BMI was associated with lower all-cause mortality in symptomatic patients (i.e.

NYHA 2 and above) and in those with complex underlying congenital cardiac defect (Figure

4). A trend towards lower mortality at higher BMI values was seen in cyanotic patients and

those with medium complexity cardiac defects. High and medium complexity cardiac defects

tended to be associated with better prognosis at higher BMI levels (Figure 4), while no such

association was seen in patients with simple defects such as valvular heart disease and VSDs

or atrioventricular septal defects (whether or not Down patients were included).

In addition to weight and BMI, age, disease complexity, cyanosis, higher NYHA functional

class, peak oxygen uptake (both absolute and percentage predicted) and VE/VCO2 slope were

significantly associated with all-cause mortality on univariable Cox analysis in the study

population (Table 2).

On multivariable analysis, BMI emerged as a significant predictor of outcome independently

of age, complexity, cyanosis, NYHA class and peak oxygen uptake as shown in Table 3.

Similarly to all-cause mortality, a higher BMI was associated with lower cardiac mortality on

univariable (HR 0.958 [95% CI 0.922-0.996]/ kg/m²; p=0.03) and multivariable (HR 0.953

[95% CI 0.908-0.999]/ kg/m²; p=0.047) Cox-proportional-hazards analysis.

Association between weight changes and mortality

Repeated weight measures were available in 1,519 patients. The median time between weight

measurements was 2.87 years (IQR 1.36 – 4.40 years). The median change in weight between

the two most recent weight measurements was +0.31 kg/year of follow-up (IQR -0.40 – 1.46

kg/year of follow-up). As illustrated in Figure 5, weight loss was associated with a

significantly higher mortality in patients with complex underlying cardiac defects (HR 1.82,

95% CI 1.02-3.24; p=0.04). In contrast, no association between weight loss and outcome

could be established in patients with cardiac defects of simple or moderate complexity

(p=0.89 and p=0.29, respectively).

Discussion

To our knowledge, this is the first report investigating the association between BMI and out-

come in ACHD patients. Including more than 3,000 patients followed at a single tertiary

ACHD center, we found that higher BMI was associated with a lower mortality, especially in

symptomatic ACHD patients and in those with complex underlying heart defects, while un-

derweight patients had a worse outcome. This association was independent of patient age,

symptoms, cardiopulmonary exercise capacity and defect complexity. In addition, using re-

peated weight measurements in a subgroup of patients we show that weight loss was related to

an increased risk of death in patients with complex cardiac defects.

The increasing prevalence of obesity from early age is a recognized problem in most western

societies.25 Obesity is risk factor for the development of cardiovascular disease, including

coronary artery disease25 and heart failure.6 Alarmingly, ACHD patients share the hallmarks

of heart failure in general, including exercise intolerance, increased levels of neurohormones

and inflammatory markers.26-28 Furthermore, heart failure remains a leading cause of death in

ACHD patients with its impact on mortality continuing to increase.29 This is due to an aging

population with increasingly complex congenital heart disease accompanied by the lack of ef-

fective heart failure treatment options. Although, rare below 40 years of age, coronary heart

disease is emerging as an important cardiac co-morbidity in elderly ACHD patients and may

also contribute to increased morbidity and mortality.30, 31 As a consequence, it appears prudent

and timely to be concerned about the potential detrimental impact of overweight/obesity on

cardiac function and late outcome, especially in the sickest patient sub-groups with congenital

heart disease. This includes, for example, the Fontan population, with recent reports suggest-

ing an increasing proportion of obese Fontan patients.32-34 It has been suggested that these

vulnerable patients with limited ventricular reserve may be negatively affected by obesity due

to higher metabolic demands during exercise and increased afterload.32 On the other hand,

higher BMI values have been consistently linked to superior outcome in the setting of heart

failure due to acquired heart disease.10, 14, 35 Against this background, the current study clarifies

the prognostic impact of BMI in ACHD and challenges - in part - the dogma of a clear detri-

mental association between overweight / obesity and poor outcome during short and mid-term

follow-up. It rather raises the question of optimal weight management in the setting of

ACHD, suggesting that the weight associated with lowest mortality may be dependent on the

type and severity of underlying heart disease. It appears, from the presented data, that an un-

critical extrapolation from healthy cohorts may be inappropriate in ACHD.

While asymptomatic ACHD patients and those with simple congenital heart defects seem to

resemble the general (primary prevention) population, potentially benefiting from lower body

weight, it appears that complex, symptomatic ACHD patients may fare better when maintain-

ing a higher BMI similarly to patients with heart failure due to acquired heart disease. The

reasons for this association are not clear but may be linked to a higher metabolic reserve in the

setting of consuming chronic disease. Furthermore, adipose tissue has been demonstrated to

be a source of various progenitor cells and this could have beneficial impact in a subset of pa-

tients.36 We have previously demonstrated that ACHD patients with complex, cyanotic dis-

ease have reduced levels of endothelial progenitor cells.37 Based on our results, we do not ad-

vocate active weight gain or unhealthy life style in ACHD patients but rather aim to draw at-

tention to the counterintuitive association between higher BMI and better outcome especially

in the most vulnerable groups of patients with complex, symptomatic and cyanotic disease. In

addition, all ACHD patients should be advised to remain physically active as higher peak oxy-

gen uptake is related to improved outcome independently of complexity of disease.20, 21 Fur-

thermore, the association between BMI and outcome was independent of peak oxygen uptake

in the current study, suggesting that mildly overweight patients with preserved exercise capac-

ity may in fact have the best prognosis in the setting of ACHD.

The association between underweight or cachexia and poor outcome have long been estab-

lished as a risk factor for mortality in patients with chronic disease and heart failure14, 38 and

are, thus, not entirely surprising in the setting of ACHD. It is also plausible that patients at the

highest end of the BMI spectrum (i.e. morbid obesity) have poor survival prospects. Inspect-

ing the resulting U-shaped relationship between BMI and all-cause mortality, however, re-

veals a remarkably high BMI value associated with lowest overall mortality. This value

should be interpreted with care, especially in asymptomatic patients with corrected simple un-

derlying defects as mentioned above. Of course, morbidly obese patients require special atten-

tion as they may benefit from specific interventention such as bariatric surgery to avoid meta-

bolic syndrome and higher complication risks during required cardiac interventions and

surgery.39 Overall, genetic aspects may also require further attention as it has been reported

that body mass index is highly determined by genetic factors, with a reported heritability of

up 70%.40 Therefore, it is possible – although speculative – that similar genes modify the

propensity for obesity and act as protective factors in the setting of congenital heart disease.

Assessing the association between BMI and symptoms or objective exercise capacity, we

could not confirm a clear association between higher BMI (with the possible exception of

more than moderate obesity) and symptoms or exercise intolerance. Indeed, underweight pa-

tients tended to be more symptomatic and have lower absolute and relative exercise capacity.

These findings should caution physicians against taking an undifferentiated approach and at-

tributing symptoms directly to body weight without excluding other possible cardiovascular

causes. While overweight increases the metabolic demands during exercise, it also represents

a training stimulus, especially for the antigravity muscles, and is associated with increased ab-

solute maximal skeletal muscle strength compared to individuals with normal weight.41 On the

other hand, pronounced obesity has been linked to functional limitations in muscle perfor-

mance and higher rates of functional disability in general, and this should be considered when

advising ACHD patients.41

The association between weight loss and worse survival in patients with complex heart dis-

ease is especially intriguing. This is because, unlike the cross-sectional association between

BMI and outcome, it illustrates that temporal changes in body weight may also provide prog-

nostic information. This finding is consistent with previous studies in the setting of heart fail-

ure. Wasting and cardiac cachexia have long been recognized as detrimental signs in the set-

ting of chronic disease and this is confirmed in ACHD patients.

Limitations

Despite the large patient population, including follow-up times of up to 15 years, the median

follow-up time was too short to comment on the possible association between adiposity and

late sequelae, such as coronary heart disease and ischemic stroke, that may manifest at an

older age. We are, thus, careful to comment on long term impacts of BMI in this patient popu-

lationwith a median age of 32.6 years. We found higher blood pressure values in

overweight/obese patients, although - on average - these patient groups did not meet the crite-

ria for arterial hypertension. However, it has been reported that risk factors for cardiovascular

disease commonly cluster in overweight/obese patients.43 As a consequence, although not as-

sessed as part of the current study, it appears possible that overweight/obese patients had a

higher prevalence of additional non assessed risk factors compared to non-overweight individ-

uals. Further long term studies are therefore required to elucidate the association between

body weight and atherosclerotic complications in ACHD patients.

While BMI is the most widely used and accepted measure of obesity, it does not account for

the wide variation in body fat distribution, body composition and may not reflect the

associated health risk in different individuals and populations.23 As no further data on fat free

mass or other measurements such as skin fold thickness or modalities such as dual energy X-

ray absorptiometry were available to us, we cannot comment on the confounding effect of

muscle mass on BMI and outcome. Further prospective studies using these techniques are

required to differentiate a high BMI due to a large muscle mass (albeit unlikely in the

majority of ACHD patients with defects of moderate or severe complexity) from a high BMI

due to adipose tissue. Fat distribution (e.g. abdominal fat being prognostically more adverse)

and especially the association between waist circumference and outcome in ACHD requires

further attention.6, 15

The results of the current study are robust to sensitivity analyses excluding patients with

syndromes such as Down syndrome but, due to limited number of events, we were unable to

study the prognostic impact of BMI on outcome specifically in patients with genetic

syndromes or severe learning difficulties. As a consequence, it remains unclear whether these

findings apply to this subpopulation. Outcome was based on mortality in this study, while

morbidity was not assessedwhich may be increased in overweight patients despite a better

survival. In fact, a recent study suggested that obese patients undergoing pulmonary valve

replacement had longer hospital stays and more postoperative arrhythmias compared to the

non-obese, albeit with identical mortality risk.39

Finally, although our results were robust to adjustment for symptoms, disease complexity,

cyanosis and cardiopulmonary exercise capacity, we cannot exclude the possibility that

reverse causation plays a role in this setting. One may argue that patients with less severe

disease could have a higher potential for weight gain, while patients with severe heart failure

or consuming disease may be predisposed for cachexia. However, this is unlikely to affect the

main result of this study, namely the positive association between body mass and better

prognosis, but rather provide a different interpretation for the findings.

Conclusions

A higher BMI was associated with less symptoms, higher objective exercise capacity and

lower mortality in the current study. The association between BMI and outcome was espe-

cially pronounced in symptomatic patients with complex underlying cardiac defects. Further-

more, weight loss in this ACHD subgroup was linked to an even higher risk of mortality. De-

pending on the underlying cardiac defect, symptoms and factors that remain to be assessed

(e.g. genetic predisposition), the optimal BMI may differ in individual ACHD patients. Al-

though a multitude of reasons may prompt patients towards losing weight or maintaining a

normal body weight, including individual wellbeing and aesthetic considerations, an uncritical

approach advising ACHD to lose weight simply to prolong survival is not supported by the

current data.

Parameter All BMI<18.5 kg/m² BMI 18.5-25 kg/m² BMI 25-30 kg/m² BMI >30 kg/m² p-value

n 3086 191 (6.2 %) 1576 (51.1 %) 869 (28.2 %) 450 (14.6 %)

Age 32.6 [23.9 - 44.7] 24.7 [19.8 - 32.0] 30.8 [23.0 - 41.5] 35.1 [26.4 - 48.1] 41.1 [27.8- 50.5] <0.0001Gender (% female) 47.7 % 55.0 % 49.8 % 38.9 % 54.0 % <0.0001

Height (cm) 170.0 [162.5 - 178.0] 168.0 [159.0 - 176.0] 170.0 [163.0 - 178.0] 172.0 [164.0 - 179.0] 168.0 [160.0 - 175.0] <0.0001Weight (kg) 70.0 [60.0 - 82.0] 48.4 [43.9 - 53.0] 63.8 [57.0 - 70.0] 79.0 [71.7 - 86.8] 94.6 [85.5 - 104.5] <0.0001IMD Score (lower more affluent) 15.17 [8.73 - 24.85] 19.99 [10.91 - 28.73] 14.48 [8.44 - 24.09] 14.74 [8.61 - 24.16] 16.81 [9.55 - 27.19] <0.0001

Cyanosis (%) 6.9 % 13.1 % 8.3 % 4.5 % 4.0 % <0.0001

Systolic blood pressure (mmHg) 118 [110 - 128] 110 [100 - 116] 115 [105 - 124] 120 [110 - 130] 125 [115 - 136] <0.0001Diastolic blood pressure (mmHg) 75 [68 - 80] 70 [62 - 78] 70 [65 - 80] 78 [70 - 80] 80 [70 - 85] <0.0001

Complexity

Simple defect 33.3 % 27.4 % 30.8 % 36.4 % 38.6 % <0.0001Medium complexity 43.6 % 38.7 % 42.8 % 45.2 % 45.4 %Complex disease 23.1 % 33.9 % 26.4 % 18.5 % 15.9 %

NYHA class

Class I 64.8 % 53.7 % 66.2 % 66.4 % 61.7 % <0.0001Class II 30.0 % 38.2 % 28.6 % 29.5 % 32.0 %Class III 5.1 % 7.4 % 5.1 % 4.1 % 6.3 %Class IV 0.9 % 0.7% 0.1 % 0.0 % 0.0 %

Diagnoses

ASD 7.7 % 7.9 % 6.5 % 8.4 % 10.0 % <0.0001VSD 6.1 % 5.2 % 6.6 % 5.5 % 6.0 %PDA 0.6 % 0.5 % 0.6 % 0.9 % 0.2 %Valve/outflow tract disease 17.7 % 13.6 % 15.8 % 20.3 % 21.1 %Coarctation 10.0 % 6.8 % 10.0 % 10.6 % 10.2 %AVSD 3.2 % 2.1 % 3.2 % 3.2 % 4.0 %Tetralogy of Fallot 22.4 % 21.5 % 21.5 % 23.7 % 23.1 %TGA atrial switch 4.3 % 3.1 % 4.1 % 4.7 % 4.9 %TGA arterial switch 3.2 % 4.7 % 3.7 % 2.2 % 2.4 %Congenitally corrected TGA 2.9 % 2.1 % 3.0 % 3.1 % 2.2 %Ebstein anomaly 3.5 % 1.6 % 3.5 % 4.1 % 3.1 %Complex 6.4 % 8.9 % 8.0 % 4.4 % 3.3 %Fontan palliation 4.3 % 8.4 % 5.2 % 2.9 % 2.2 %Eisenmenger physiology 3.4 % 8.9 % 4.1 % 1.7 % 2.0 %Other 4.4 % 4.7 % 4.2 % 4.3 % 5.1 %

Exercise Testing

peak VO2 (ml/min) 1763 [1272 - 2321] 1195 [846 - 1788] 1705 [1248 - 2264] 1919 [1416 - 2490] 1847 [1388 - 2373] <0.0001peak VO2 (ml/kg/min) 25.0 [18.7 - 31.8] 24.9 [18.2 - 33.8] 27.3 [20.5 - 33.9] 24.6 [18.9 - 30.2] 19.8 [15.5 - 24.0] <0.0001% predicted peak VO2 (%) 73.0 [57.5 - 87.8] 62.8 [46.0 - 79.4] 73.7 [57.5 - 89.0] 72.7 [59.2 - 86.8] 74.9 [59.8 - 89.9] <0.0001VE/VCO2-slope 31.0 [27.0 - 35.5] 32.3 [28.0 - 42.0] 31.0 [27.0 - 37.0] 30.0 [27.0 - 34.0] 30.0 [27.0 - 34.0] <0.0001Peak heart rate (bpm) 166 [140 - 180] 165 [133 - 182] 169 [144 - 184] 166 [142 - 181] 155 [130 - 176] <0.0001

Table 1. Demographics and baseline characteristics of the study population. P-values refer to

differences between the groups. ASD=atrial septal defect; AVSD=atrioventricular septal defect;

BMI=body mass index (kg/m²); PDA=patent arterial duct; peak VO2 = peak oxygen consumption;

TGA=transposition of the great arteries; VSD=ventricular septal defect.

Variable Hazard Ratio 95% CI P -value

Age (per decade) 1.278 1.167 - 1.399 <0.0001Gender (female) 0.967 0.720-1.300 0.82IMD score 1.000 0.985-1.015 0.99Complexity (at least moderate) 2.521 1.701-3.737 <0.0001Cyanosis 3.059 2.155-4.342 <0.0001

NYHA class (>1) 4.311 2.976-6.245 <0.0001Systolic blood pressure 0.993 0.984-1.002 0.14Diastolic blood pressure 0.986 0.972-1.000 0.057

Peak oxygen uptake (100 ml/min) 0.859 0.832-0.887 <0.0001Perc. pred peak VO2 (/10%) 0.650 0.599-0.705 <0.0001VE/VCO2 slope 1.209 1.170-1.250 <0.0001

Weight (kg) 0.984 0.975-0.993 <0.0001Body mass index 0.963 0.933-0.994 0.02

Table 2. Univariable predictors of all-cause mortality.

95% CI = 95% confidence interval, NYHA = New York Heart Association functional class.

Variable Hazard Ratio 95% CI P -value

Age (per decade) 1.152 1.004-1.322 0.04Complexity (moderate) 1.340 0.728-2.465 0.35Complexity (severe) 2.719 1.493-4.954 0.001Cyanosis 0.676 0.417-1.095 0.11

NYHA class 2 1.288 0.808-2.053 0.29NYHA class 3 0.931 0.465-1.862 0.84NYHA class 4 23.654 5.169-108.249 <0.0001

Peak oxygen uptake (100 ml/min) 0.906 0.877-0.936 <0.0001

Body mass index 0.947 0.909-0.986 0.008

Table 3. Multivariable predictors of all-cause mortality.

95% CI = 95% confidence interval, NYHA = New York Heart Association functional class.

Figure 1.

A) Association between body mass index (BMI; kg/m²) and New York Heart Asssociation (NYHA) functional class. The percentage distribution for various ranges of BMI are presented. B) Quantile regression illustrating the association between BMI and peak oxygen consumption (peak VO2; ml/min). The median, 10th, 25th, 75th and 90th percentile of the regression line. The regression coefficient () and the p-value are based on non-parametric Spearman rank correlation. C) Quantile regression illustrating the association between BMI and percentage predicted peak oxygen consumption (peak VO2; %). The median, 10th, 25th, 75th and 90th percentile of the regression line. The regression coefficient () and the p-value are based on non-parametric Spearman rank correlation.

Figure 2.

A) Hazard ratio of death (all-cause mortality) for various body mass index (BMI; kg/m2) ranges illustrating the lowest hazard for BMI ranges between 30 and 40 kg/m². B) Association between hazard ratio of death and BMI as a continuous variable, illustrating excess mortality in underweight and severely obese patients. The median BMI of the population (24 kg/m²) was set as the reference value.

Figure 3.

Survival by body mass index (BMI; kg/m²) based on the results of the Cox analysis.

Compared to normal weight patients (i.e. BMI 18.5-25 kg/m²), underweight patients tended to

have worse outcome, while overweight/obese patients as a group had on average a

significantly superior prognosis.

Figure 4.

Hazard ratios of death (all-cause mortality) stratified by underlying diagnosis, the presence of cyanosis, complexity of heart disease and NYHA functional class. Hazard ratios with 95% confidence intervals are presented. Only diagnostic subgroups with at least five deaths during follow-up were included. ASD=atrial septal defects, AVSD=atrioventricular septal defect, CoA=aortic coarctation, RV=right ventricle, ToF=tetralogy of Fallot, VSD=ventricular septal defect.

Figure 5.

Survival of patient with repeated weight measurements stratified by complexity of underlying heart disease modelled based on the results of Cox proportional hazards analysis. Patients were split by those with and without weight loss between repeated measurements. Hazard ratios and 95% confidence intervals are provided.

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