Introduction: Heart failure (HF) is difficult to diagnose in obese patients because of cardiovascular and pulmonary comorbidities associated with physical deconditioning, all of which lead to dyspnea. Methods: The OLECOEUR study is a prospective screening for HF using systematic brain natriuretic peptide (BNP) measurement in ambulatory patients with obesity from a department of Nutrition (Paris, France). Clinical, biological, and echocardiographic data were extracted from electronic medical records. Results: We included 1,506 patients middle-aged (mean age: 47.2 ± 14.6 years old) with severe obesity (mean body mass index: 40.4 ± 6.6 kg/m2). Patients with BNP ≥35 pg/mL had left heart remodeling including thicker interventricular septum (10.4 ± 2.0 vs. 9.6 ± 1.8 mm; p = 0.0008), higher left ventricular mass (89.9 ± 24.3 vs. 77.2 ± 20.0 g/m2; p = 0.0009), and significant changes in both left and right atria consistent with a higher proportion of prior atrial fibrillation. Markers of right heart remodeling on echocardiography were also significantly higher (pulmonary artery systolic pressure: 33.3 ± 17.3 vs. 24.5 ± 6.3 mm Hg; p = 0.0002). Conclusion: The OLECOEUR study shows left and right subclinical cardiac remodeling in obese patients screened for HF with systematic dosing of BNP with usual cut-off of 35 pg/mL.

Heart failure (HF) is a common, costly and potentially fatal syndrome in adults that causes substantial morbidity and mortality worldwide [1]. Several risk factors can increase the likelihood of developing HF, one of which is obesity. Regardless of age, a body mass index (BMI) of ≥30 kg/m2 doubles the risk of developing HF [2]. Obesity induces hemodynamic stress that may contribute to changes in cardiac morphology and ventricular function, ultimately increasing the risk of developing HF. This association may also be related to the fact that metabolically healthy obese individuals progressively transition over time to a metabolically unhealthy phenotype with a higher risk of HF [3]. Recent data have shown that the burden of HF is increasing in younger populations due to the increasing prevalence of obesity and its associated comorbidities, including hypertension and type 2 diabetes [4, 5]. Indeed, obesity is also a major global health problem. In France, recent epidemiological data showed a prevalence of 17% in the adult population [6]. Importantly, the increase in BMI precedes the development of HF suggesting a causal relationship [7], but also opportunities for earlier detection to prevent the development of HF.

The latest ACC/AHA guidelines for the management of HF [8] recommend that patients at risk for HF (i.e., stage A of HF) be screened with brain natriuretic peptide (BNP) or NT-proBNP measurement, followed by team-based care involving a cardiovascular specialist, in order to prevent the development of left ventricular (LV) dysfunction or new-onset HF. However, the value of natriuretic peptide measurements in obesity clinics remains to be determined, as these measurements are neither routinely performed nor recommended [9‒11]. In ambulatory patients, BNP levels above 35 pg/mL (compared with 100 pg/mL in hospitalized/decompensated patients) are suggestive of HF [12]. The diagnosis of HF may be difficult in obese patients because of the higher prevalence of multiple cardiovascular and pulmonary diseases associated with physical deconditioning, all of which may lead to symptoms such dyspnea unrelated to HF. In addition, patients with obesity have lower natriuretic peptide levels than those without obesity, but no guideline suggests a different threshold for HF diagnosis in this particular population. Furthermore, obesity can lead to serious technical limitations in echocardiography [13, 14]. For all these reasons, we decided to screen for HF using systematic BNP measurement in ambulatory patients referred for obesity management without known HF.

Patients

The OLECOEUR study is a monocenter prospective observational study conducted in the Nutrition department of the Georges Pompidou European Hospital (Paris, France). Our department is a reference center for the management of patients with severe obesity (class II and III according to WHO). Since 2018, we have added systematic BNP dosage to routine blood measurements during 1-day hospitalizations. Patients were assessed for eligibility from the Inpatient Clinical Data Warehouse from January 2018 to December 2020 (n = 1,989). Duplicates were removed (n = 50). Clinical, biological, and echocardiographic data were extracted from electronic medical records. Patients with BMI <30 kg/m2 were excluded (n = 405). Two investigators (D.O.-B. and M.H.) manually reviewed all medical charts to verify and collect missing data. Patients were manually excluded if they had a known history of heart disease (such as hypertrophic cardiomyopathy or dilated cardiomyopathy) or a known history of hospitalization for HF (n = 28).

Data Collection

Clinical and biological variables extracted for analysis were age and sex, BMI, cardiovascular risk factors (hypertension, dyslipidemia, diabetes), cardiovascular history (atrial fibrillation, venous thromboembolic disease, acute HF, chronic kidney disease), and blood biological data (BNP, glucose, creatinine, glomerular filtration rate according to the MDRD equation, cholesterol, triglyceride, HDL, and LDL cholesterol).

Transthoracic Echocardiographic Data

Echocardiographic data were considered eligible if they were performed within 1 year before or after the date of the 1-day hospitalization. Echocardiographic variables were extracted for analysis as exhaustively as possible, i.e., LV end diastolic diameter (mm), LV end systolic diameter (mm), interventricular septum (mm), LV posterior wall (mm), LV mass (i) (g/m2), LV ejection fraction (%), left atria (LA) diameter (mm), LA surface (cm2), LA volume indexed to body surface area (i) (mL/m2), left ventricle diastolic function (mitral inflow velocities [cm/s] [E, A, and E/A]), tissue Doppler with lateral e’ and E/E’ ratio, right ventricle parameters (S wave, tricuspid annular plane systolic excursion), right atria surface (cm2), and systolic pulmonary artery pressure (mm Hg) estimated from peak tricuspid regurgitation velocity.

Statistical Analysis

Patients were categorized according to BNP level (group 1: BNP <35 pg/mL and group 2: BNP ≥35 pg/mL). Continuous variables were reported as mean +/− standard deviation (SD) or medians +/− interquartile range (IQR) when appropriate. Discrete variables were reported as counts and percentages. Groups were compared using the Wilcoxon rank test or t test for continuous variables and Fisher’s exact test or χ2 for discrete variables, as appropriate. For all analyses, p values <0.05 were considered significant. Logistic regression was performed in a multivariate model including variables selected with a p threshold below 0.05. Statistics were performed using NCSS 2021 (G Hintze, Kaysville, UT, USA).

Between 2018 and 2020, a total of 1,939 patients were referred to the Nutrition Department and were eligible to participate in the study (Fig. 1). Among these patients, 433 were excluded because of a BMI <30 kg/m2 (n = 405) or a previous diagnosis of HF or cardiomyopathy (n = 28). Finally, we analyzed clinical and biological data from 1,506 patients who were further categorized according to their BNP level: 1,059 patients (70.3%) had BNP <35 pg/mL (group 1) and 447 patients (29.7%) had BNP ≥35 pg/mL (group 2).

Fig. 1.

Flowchart of the OLECOEUR study.

Fig. 1.

Flowchart of the OLECOEUR study.

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Clinical Characteristics

Table 1 shows the main clinical characteristics of the 1,506 participants. Patients were predominantly women (71.6%), middle-aged (mean age: 47.2 ± 14.6 years), and with severe obesity (mean BMI: 40.4 ± 6.6 kg/m2). None of these patients had a known history of HF. Comparing the two groups after categorization by BNP level, patients with BNP ≥35 pg/mL were significantly older (54.9 ± 14.1 vs. 43.9 ± 13.5 years old; p < 0.0001) and had higher rates of hypertension (58.6 vs. 30.9%; p < 0.0001) and diabetes (31.8 vs. 21.9%; p < 0.0001) than patients with normal BNP. Patients with BNP ≥35 pg/mL had a higher prevalence of prior atrial fibrillation (7.8 vs. 1.5%; p < 0.0001), coronary artery disease (8.7 vs. 0.7%; p < 0.0001), pulmonary embolism (4.9 vs. 2.4%; p = 0.009), chronic kidney disease (19.0 vs. 3.5%; p < 0.0001), and sleep obstructive apnea (39.6 vs. 30.1%; p = 0.0004). However, there was no significant difference in BMI between the two groups (p = 0.17). Multivariate analysis confirmed that patients with BNP ≥35 ng/mL were more likely to have a history of atrial fibrillation (OR 7.95 [3.32–19.0]), renal insufficiency (OR 3.34 [2.11–5.28], coronary artery disease (OR 3.07 [1.53–6.14]), or hypertension (OR 1.75 [1.31–2.35]) (Table 2).

Table 1.

Clinical and biological characteristics of the patients included in the OLECOEUR study (i.e., patients with systematic BNP dosage and obesity)

PopulationTotal (n = 1,506)Group 1 BNP <35 pg/mL (n = 1,059)Group 2 BNP ≥35 pg/mL (n = 447)p value (group 2 vs. group 1)
Age, mean±SD, years 47.2±14.6 43.9±13.5 54.9±14.1 <0.0001 
Men, n (%) 427 (28.4) 316 (29.8) 111 (24.8) 0.04 
Weight, mean±SD, kg 113.2±23.3 113.4±21.5 112.8±27.0 0.65 
BMI, mean±SD, kg/m2 40.4±6.6 40.2±6.2 40.8±7.6 0.17 
BMI 30–34.9 kg/m2, n (%) 190 (17.9) 98 (21.9) 288 (19.1) 
BMI 35–35.9 kg/m2, n (%) 377 (35.6) 139 (31.1) 516 (34.2) 0.10 
BMI ≥40 kg/m2, n (%) 492 (46.5) 210 (47.0) 702 (46.6) 
Cardiovascular risk factors, n (%) 
 Diabetes 373 (24.8) 232 (21.9) 141 (31.8) <0.0001 
 Hypertension 589 (39.1) 327 (30.9) 262 (58.6) <0.0001 
 Dyslipidemia 952 (63.3) 689 (65.1) 263 (59.0) 0.02 
Medical history, n (%) 
 Atrial fibrillation 46 (3.0) 7 (0.7) 39 (8.7) <0.0001 
 Coronary artery disease 51 (3.4) 16 (1.5) 35 (7.8) <0.0001 
 Pulmonary embolism 47 (3.1) 25 (2.4) 22 (4.9) 0.009 
 Obstructive sleep apnea 496 (32.9) 319 (30.1) 177 (39.6) 0.0004 
 Renal insufficiency 122 (8.1) 37 (3.5) 85 (19.0) <0.0001 
Biological data 
 BNP, median [IQR], pg/mL 20 [12–40] 15 [10–22] 56 [42–80] <0.0001 
 Creatinine, median [IQR], µmol/L 67 [58–77] 66 [57–75] 70 [60.7–88.2] <0.0001 
 MDRD-GFR, median [IQR], mL/min 90 [76–107] 93 [79–109.5] 81 [64–96] <0.0001 
 LDL cholesterol, median [IQR], mM/L 3.3 [2.6–3.9] 3.36 [2.70–3.97] 3.18 [2.48–3.81] 0.001 
 Triglyceride, median [IQR], mM/L 1.29 [0.94–1.79] 1.30 [0.91–1.80] 1.27 [0.98–1.75] 0.46 
PopulationTotal (n = 1,506)Group 1 BNP <35 pg/mL (n = 1,059)Group 2 BNP ≥35 pg/mL (n = 447)p value (group 2 vs. group 1)
Age, mean±SD, years 47.2±14.6 43.9±13.5 54.9±14.1 <0.0001 
Men, n (%) 427 (28.4) 316 (29.8) 111 (24.8) 0.04 
Weight, mean±SD, kg 113.2±23.3 113.4±21.5 112.8±27.0 0.65 
BMI, mean±SD, kg/m2 40.4±6.6 40.2±6.2 40.8±7.6 0.17 
BMI 30–34.9 kg/m2, n (%) 190 (17.9) 98 (21.9) 288 (19.1) 
BMI 35–35.9 kg/m2, n (%) 377 (35.6) 139 (31.1) 516 (34.2) 0.10 
BMI ≥40 kg/m2, n (%) 492 (46.5) 210 (47.0) 702 (46.6) 
Cardiovascular risk factors, n (%) 
 Diabetes 373 (24.8) 232 (21.9) 141 (31.8) <0.0001 
 Hypertension 589 (39.1) 327 (30.9) 262 (58.6) <0.0001 
 Dyslipidemia 952 (63.3) 689 (65.1) 263 (59.0) 0.02 
Medical history, n (%) 
 Atrial fibrillation 46 (3.0) 7 (0.7) 39 (8.7) <0.0001 
 Coronary artery disease 51 (3.4) 16 (1.5) 35 (7.8) <0.0001 
 Pulmonary embolism 47 (3.1) 25 (2.4) 22 (4.9) 0.009 
 Obstructive sleep apnea 496 (32.9) 319 (30.1) 177 (39.6) 0.0004 
 Renal insufficiency 122 (8.1) 37 (3.5) 85 (19.0) <0.0001 
Biological data 
 BNP, median [IQR], pg/mL 20 [12–40] 15 [10–22] 56 [42–80] <0.0001 
 Creatinine, median [IQR], µmol/L 67 [58–77] 66 [57–75] 70 [60.7–88.2] <0.0001 
 MDRD-GFR, median [IQR], mL/min 90 [76–107] 93 [79–109.5] 81 [64–96] <0.0001 
 LDL cholesterol, median [IQR], mM/L 3.3 [2.6–3.9] 3.36 [2.70–3.97] 3.18 [2.48–3.81] 0.001 
 Triglyceride, median [IQR], mM/L 1.29 [0.94–1.79] 1.30 [0.91–1.80] 1.27 [0.98–1.75] 0.46 

GFR, glomerular filtration rate.

Table 2.

Multivariate analysis looking for factors associated with higher BNP, comparing patients with BNP ≥35 ng/mL to those with normal BNP level

CovariatesOdds ratio95% CIp value
Age 1.04 (1.03–1.05) <0.0001 
Sex 0.46 (0.34–0.64) <0.0001 
Hypertension 1.75 (1.31–2.35) 0.0001 
Renal insufficiency 3.34 (2.11–5.28) <0.0001 
Atrial fibrillation 7.95 (3.32–19.0) <0.0001 
Dyslipidemia 0.65 (0.50–0.85) 0.001 
Coronary artery disease 3.07 (1.53–6.14) 0.001 
Sleep obstructive apnea 0.89 (0.67–1.18) 0.43 
Type 2 diabetes 0.74 (0.54–1.01) 0.06 
BMI 35–40, kg/m2 0.85 (0.59–1.20) 0.36 
BMI >40, kg/m2 1.09 (0.77–1.54) 0.60 
Pulmonary embolism 1.13 (0.57–2.19) 0.72 
CovariatesOdds ratio95% CIp value
Age 1.04 (1.03–1.05) <0.0001 
Sex 0.46 (0.34–0.64) <0.0001 
Hypertension 1.75 (1.31–2.35) 0.0001 
Renal insufficiency 3.34 (2.11–5.28) <0.0001 
Atrial fibrillation 7.95 (3.32–19.0) <0.0001 
Dyslipidemia 0.65 (0.50–0.85) 0.001 
Coronary artery disease 3.07 (1.53–6.14) 0.001 
Sleep obstructive apnea 0.89 (0.67–1.18) 0.43 
Type 2 diabetes 0.74 (0.54–1.01) 0.06 
BMI 35–40, kg/m2 0.85 (0.59–1.20) 0.36 
BMI >40, kg/m2 1.09 (0.77–1.54) 0.60 
Pulmonary embolism 1.13 (0.57–2.19) 0.72 

Echocardiographic Data

The available echocardiographic data of 273 patients were then evaluated and analyzed: 148 patients (13.9%) for group 1 (BNP <35 pg/mL) and 125 patients (27.9%) for group 2 (BNP ≥35 pg/mL). The clinical and biological characteristics of these 2 subgroups of patients are shown in Table 3, and their echocardiographic results are shown in Table 4. Comparing these two subgroups, patients with BNP ≥35 pg/mL had a higher prevalence of hypertension (69.6 vs. 33.1%; p < 0.0001) and had a higher cardiac hypertrophic remodeling on echocardiography, including thicker interventricular septum (10.4 ± 2.0 vs. 9.6 ± 1.8 mm; p = 0.0008) and higher LV mass (89.9 ± 24.3 vs. 77.2 ± 20.0 g/m2; p = 0.0009). However, LV ejection fraction remained similar and within the normal range in both subgroups (61.4 ± 6.3 vs. 62.6 ± 7.0%; p = 0.17). Patients with BNP ≥35 pg/mL showed significant changes in both the left and right atria, consistent with a higher proportion of prior atrial fibrillation (15/125 vs. 1/148; p = 0.0001). Left atrial volume and surface area were significantly increased (33.0 ± 11.4 vs. 24.5 ± 7.1 mL/m2 and 23.0 ± 6.4 vs. 18.9 ± 4.2 cm2, respectively; p < 0.0001). The mitral velocity profile was similar between the two groups, but patients with BNP ≥35 pg/mL had a higher E/E′ ratio in (9.1 ± 3.0 vs. 7.6 ± 2.0; p = 0.004). Finally, markers of right heart remodeling were significantly higher in patients with BNP ≥35 pg/mL (i.e., pulmonary artery systolic pressure: 33.3 ± 17.3 vs. 24.5 ± 6.3 mm Hg; p = 0.0002) who were also more likely to have obstructive sleep apnea (58/125 vs. 42/148; p = 0.002). In contrast to the overall study population, there was no significant difference in the history of pulmonary embolism in the 2 subgroups of patients with echocardiography (9/125 vs. 4/148: p = 0.09).

Table 3.

Clinical and biological characteristics of the patients with both BNP systematic dosage and concomitant cardiac echography

PopulationSubgroup 1 BNP <35 pg/mL (n = 148)Subgroup 2 BNP ≥35 pg/mL (n = 125)p value
Age, mean±SD, years 43.4±12.6 55.6±13.4 <0.0001 
Men, n (%) 48 (32.4) 29 (23.2) 0.09 
Weight, mean±SD, kg 116.8±21.4 116.0±32.3 0.81 
BMI, mean±SD, kg/m2 41.0±5.8 41.4±97.2 0.63 
Cardiovascular risk factors, n (%) 
 Diabetes 34 (23.0) 44 (35.5) 0.02 
 Hypertension 49 (33.1) 87 (69.6) <0.0001 
 Dyslipidemia 98 (66.2) 70 (56.0) 0.08 
Medical history, n (%) 
 Atrial fibrillation 1 (0.7) 15 (12.0) 0.0001 
 Coronary artery disease 3 (2.0) 7 (5.6) 0.19 
 Pulmonary embolism 4 (2.7) 9 (7.2) 0.09 
 Obstructive sleep apnea 42 (28.4) 58 (46.4) 0.002 
 Renal insufficiency 4 (2.7) 23 (18.4) <0.0001 
Biological data 
 BNP, median [IQR], pg/mL 15 [10–22] 56 [45–79.5] <0.0001 
 Creatinine, median [IQR], µmol/L 67 [57–78] 69 [58–85] 0.19 
 MDRD-GFR, median [IQR], mL/min 91 [78–108] 83 [65–97] 0.0003 
 LDL cholesterol, median [IQR], mM/L 3.32 [2.7–3.9] 3.18 [2.5–3.9] 0.13 
 Triglyceride, median [IQR], mM/L 1.35 [0.98–2.10] 1.26 [0.96–1.69] 0.31 
PopulationSubgroup 1 BNP <35 pg/mL (n = 148)Subgroup 2 BNP ≥35 pg/mL (n = 125)p value
Age, mean±SD, years 43.4±12.6 55.6±13.4 <0.0001 
Men, n (%) 48 (32.4) 29 (23.2) 0.09 
Weight, mean±SD, kg 116.8±21.4 116.0±32.3 0.81 
BMI, mean±SD, kg/m2 41.0±5.8 41.4±97.2 0.63 
Cardiovascular risk factors, n (%) 
 Diabetes 34 (23.0) 44 (35.5) 0.02 
 Hypertension 49 (33.1) 87 (69.6) <0.0001 
 Dyslipidemia 98 (66.2) 70 (56.0) 0.08 
Medical history, n (%) 
 Atrial fibrillation 1 (0.7) 15 (12.0) 0.0001 
 Coronary artery disease 3 (2.0) 7 (5.6) 0.19 
 Pulmonary embolism 4 (2.7) 9 (7.2) 0.09 
 Obstructive sleep apnea 42 (28.4) 58 (46.4) 0.002 
 Renal insufficiency 4 (2.7) 23 (18.4) <0.0001 
Biological data 
 BNP, median [IQR], pg/mL 15 [10–22] 56 [45–79.5] <0.0001 
 Creatinine, median [IQR], µmol/L 67 [57–78] 69 [58–85] 0.19 
 MDRD-GFR, median [IQR], mL/min 91 [78–108] 83 [65–97] 0.0003 
 LDL cholesterol, median [IQR], mM/L 3.32 [2.7–3.9] 3.18 [2.5–3.9] 0.13 
 Triglyceride, median [IQR], mM/L 1.35 [0.98–2.10] 1.26 [0.96–1.69] 0.31 
Table 4.

Results of the transthoracic cardiac echography

PopulationSubgroup 1 BNP <35 pg/mL (n = 148)Subgroup 2 BNP ≥35 pg/mL (n = 125)p value
Left ventricle (LV) 
 LV end diastole diameter, mean±SD, mm 48.6±6.1, n = 143 (97%) 48.9±7.3, n = 119 (95%) 0.67 
 LV end systole diameter, mean±SD, mm 31.3±8.2, n = 93 (63%) 31.2±6.6, n = 72 (58%) 0.99 
 Interventricular septum, mean±SD, mm 9.6±1.8, n = 141 (95%) 10.4±2.0, n = 119 (95%) 0.0008 
 LV posterior wall, mean±SD, mm 9.3±1.5, n = 140 (95%) 9.9±2.1, n = 119 (95%) 0.02 
 LV mass (i), mean±SD, g/m2 77.2±20.0, n = 80 (54%) 89.9±24.3, n = 62 (50%) 0.0009 
 LV hypertrophy, n (%) 9 (11.25), n = 80 (54) 16 (25.8), n = 62 (50) 0.02 
 LV ejection fraction, mean±SD, % 62.6±7.0, n = 133 (90%) 61.4±6.3, n = 123 (98%) 0.17 
Left atrium (LA) 
 LA diameter, mean±SD, mm 33.4±7.6, n = 51 (34%) 41.0±6.5, n = 42 (33%) 0.002 
 LA surface, mean±SD, cm2 18.9±4.2, n = 104 (70%) 23.0±6.4, n = 96 (76%) <0.0001 
 LA volume (i), mean±SD, mL/m2 24.5±7.1, n = 67 (45%) 33.0±11.4, n = 51 (41%) <0.0001 
Mitral velocity profile 
 E wave, mean±SD, cm/s 77.0±16.0, n = 111 (75%) 80.3±20.0, n = 90 (72%) 0.19 
 A wave, mean±SD, cm/s 71.9±18.5, n = 92 (62%) 76.5±20.9, n = 76 (61%) 0.13 
 E/A ratio, mean±SD 1.11±0.33, n = 118 (80%) 1.13±0.64, n = 97 (77%) 0.85 
 E’septal, mean±SD, cm/s 9.4±2.1, n = 48 (32%) 8.7±3.2, n = 43 (34%) 0.20 
 E’Lateral, mean±SD, cm/s 12.2±3.3, n = 96 (65%) 10.6±3.6, n = 69 (55%) 0.004 
 E/E′, mean±SD 7.6±2.0, n = 45 (30%) 9.1±3.0, n = 41 (33ù) 0.004 
Right atrium (RA) and right ventricle (RV) 
 S wave, mean±SD, cm/s 13.8±2.7, n = 103 (70%) 12.6±2.7, n = 84 (67%) 0.002 
 Tricuspid annular plane systolic excursion, mean±SD, mm 23.6±4.4, n = 129 (87%) 22.8±5.9, n = 103 (82%) 0.22 
 RA surface, mean±SD, cm2 15.7±3.7, n = 66 (45%) 17.4±5.1, n = 55 (44%) 0.04 
 Pulmonary artery systolic pressure, mean±SD, mm Hg 24.5±6.3, n = 67 (45%) 33.3±17.3, n = 68 (54%) 0.0002 
PopulationSubgroup 1 BNP <35 pg/mL (n = 148)Subgroup 2 BNP ≥35 pg/mL (n = 125)p value
Left ventricle (LV) 
 LV end diastole diameter, mean±SD, mm 48.6±6.1, n = 143 (97%) 48.9±7.3, n = 119 (95%) 0.67 
 LV end systole diameter, mean±SD, mm 31.3±8.2, n = 93 (63%) 31.2±6.6, n = 72 (58%) 0.99 
 Interventricular septum, mean±SD, mm 9.6±1.8, n = 141 (95%) 10.4±2.0, n = 119 (95%) 0.0008 
 LV posterior wall, mean±SD, mm 9.3±1.5, n = 140 (95%) 9.9±2.1, n = 119 (95%) 0.02 
 LV mass (i), mean±SD, g/m2 77.2±20.0, n = 80 (54%) 89.9±24.3, n = 62 (50%) 0.0009 
 LV hypertrophy, n (%) 9 (11.25), n = 80 (54) 16 (25.8), n = 62 (50) 0.02 
 LV ejection fraction, mean±SD, % 62.6±7.0, n = 133 (90%) 61.4±6.3, n = 123 (98%) 0.17 
Left atrium (LA) 
 LA diameter, mean±SD, mm 33.4±7.6, n = 51 (34%) 41.0±6.5, n = 42 (33%) 0.002 
 LA surface, mean±SD, cm2 18.9±4.2, n = 104 (70%) 23.0±6.4, n = 96 (76%) <0.0001 
 LA volume (i), mean±SD, mL/m2 24.5±7.1, n = 67 (45%) 33.0±11.4, n = 51 (41%) <0.0001 
Mitral velocity profile 
 E wave, mean±SD, cm/s 77.0±16.0, n = 111 (75%) 80.3±20.0, n = 90 (72%) 0.19 
 A wave, mean±SD, cm/s 71.9±18.5, n = 92 (62%) 76.5±20.9, n = 76 (61%) 0.13 
 E/A ratio, mean±SD 1.11±0.33, n = 118 (80%) 1.13±0.64, n = 97 (77%) 0.85 
 E’septal, mean±SD, cm/s 9.4±2.1, n = 48 (32%) 8.7±3.2, n = 43 (34%) 0.20 
 E’Lateral, mean±SD, cm/s 12.2±3.3, n = 96 (65%) 10.6±3.6, n = 69 (55%) 0.004 
 E/E′, mean±SD 7.6±2.0, n = 45 (30%) 9.1±3.0, n = 41 (33ù) 0.004 
Right atrium (RA) and right ventricle (RV) 
 S wave, mean±SD, cm/s 13.8±2.7, n = 103 (70%) 12.6±2.7, n = 84 (67%) 0.002 
 Tricuspid annular plane systolic excursion, mean±SD, mm 23.6±4.4, n = 129 (87%) 22.8±5.9, n = 103 (82%) 0.22 
 RA surface, mean±SD, cm2 15.7±3.7, n = 66 (45%) 17.4±5.1, n = 55 (44%) 0.04 
 Pulmonary artery systolic pressure, mean±SD, mm Hg 24.5±6.3, n = 67 (45%) 33.3±17.3, n = 68 (54%) 0.0002 

The OLECOEUR study aimed to assess the value of routine BNP measurement in a population of patients seen in a specialized ambulatory Nutrition Department dedicated to managing severe obesity. More than a quarter of the patients (29.7%) had a BNP level above 35 pg/mL. None of them had known HF and most were middle-aged women. Patients with high BNP levels did not differ from those with normal BNP levels in terms of BMI. However, they had higher rates of other HF risk factors (hypertension and diabetes) and comorbidities (atrial fibrillation, coronary artery disease, pulmonary embolism, obstructive sleep apnea, and chronic kidney disease). Consistent with this, echocardiography showed evidence of structural heart disease (in particular LV hypertrophy, left atrial dilatation and increased E/E′ ratio), suggesting the presence of pre-HF (or stage B HF) in these patients with BNP ≥35 pg/mL and severe obesity.

For example, LV mass was significantly increased (mean 90 g/m2) with more LV hypertrophy (n = 16/62 vs. 9/80, p = 0.02). However, most of the echocardiographic changes found to be significant were mildly abnormal and remained below the upper limit of normal.

This suggests that a BNP elevation above 35 pg/mL in a general population of severely obese patients is sensitive enough to detect early signs of structural heart disease and help identify those at higher risk of developing HF. The population included is typically a population of patients with stage A HF who have severe obesity, a high level of other HF risk factors (including hypertension) but no history or symptoms of HF. Importantly, the population studied has undergone HF screening at a very young age (45–50 years old) as compared to the typical average age of HF patients (around 70 years old in France).

Another important finding in our study relates to the significant abnormalities in the right ventricle. We found higher pulmonary artery systolic pressures in patients with high BNP, who also had higher rates of obstructive sleep apnea and, in particular, a history of pulmonary embolism (although this last association was not significant in subgroups of patients who underwent cardiac echography). Finally, right heart abnormalities are not uncommon in our population with severe obesity and high BNP levels.

Our observational study has some important limitations. Although BNP was measured systematically performed in all patients referred to the Nutrition Department, echocardiography was prescribed at the discretion of the physician. However, the subgroups of patients who underwent echocardiography were representative of the total population. In addition, the performance of echocardiography in obese patients may have been limited, resulting in missing data for several cardiac parameters that reflect real-world experience.

The OLECOEUR study shows subclinical left and right cardiac remodeling on echocardiography in patients with obesity who are screened for HF with a systematic dosage of BNP. Interestingly, the usual cut-off of 35 pg/mL may be helpful in identifying at-risk patients who should be offered an echocardiogram.

We conducted a prospective observational study using data collected during routine medical care. Our hospital uses an authorized clinical data warehouse using an i2b2 platform [15]. All patients are informed that health data collected during routine medical care may be reused for clinical research purposes, unless they object. The data collected were retrospective, aggregated, and no longer related to identifiable individuals. For all these reasons, and in accordance with French law n°2012-300, the study was formally exempted from ethical approval on the advice of the Local Ethics Committee (CERAPHP.Centre #00011928), and no written consent was required to participate in this study.

Claire Carette reported personal fees from Ipsen Pharma, Pfizer, AstraZeneca, Novo Nordisk, Lilly, Vitalaire, and Merck France outside the submitted work. Claire Rives-Lange reported personal fees from Nestlé Health Science. Sebastien Czernichow reported participation fees from MyGoodlife, and personal fees from Novo Nordisk, Fresenius, Lilly, Janssen, Bristol Myers Squibb, and other fees from Jellynov outside the submitted work. Jean-Sébastien Hulot has received speaker, advisory board, or consultancy fees from Alnylam, Amgen, AstraZeneca, Bayer, Bioserenity, Boehringer Ingelheim, MSD, Novartis, Novo Nordisk, Vifor Pharma. The APHP, which employs Pr. Hulot, has received research grants from Bioserenity, Pliant Thx, Sanofi, Servier, and Novo Nordisk. Other authors have nothing to declare.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Claire Carette, Diana Okamba-Belle, Antoine Fayol, Anne-Sophie Jannot, and Jean-Sébastien Hulot designed the study, analyzed the data, and wrote the manuscript. Diana Okamba-Belle and Mélanie Hirlemann collected the data. Maxime Wack and Anne-Sophie Jannot did the extraction from the Inpatient Clinical Patient Warehouse. Antoine Fayol and Jean-Sébastien Hulot did the statistics. Sébastien Czernichow, Orianne Domenge, and Claire Rives-Lange revised the manuscript.

Materials described in the manuscript, including all relevant raw data, will be freely available to any researcher wishing to use them for noncommercial purposes, without breaching participant confidentiality. Data are not available due to ethical reasons. Further inquiries can be directed to the corresponding author.

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