Abstract
Background
Hypertrophic cardiomyopathy (HCM) involves left atrial remodeling linked to adverse outcomes such as death, heart failure, and atrial fibrillation (AF). The left atrioventricular coupling index (LACI) reflects atrial–ventricular interaction, but its prognostic role in HCM is unclear. The objective of this study is to evaluate the prognostic value of cardiac magnetic resonance imaging (CMR)-derived LACI and identify optimal cut-offs for predicting adverse outcomes in HCM.
Methods
This retrospective cohort study included HCM patients who underwent CMR with at least 1 year of follow-up. LACI was calculated as the ratio of left atrial to left ventricular end-diastolic volume. Associations between LACI and outcomes were analyzed using Cox regression. The primary outcome was a composite endpoint of all-cause death and hospitalization for heart failure (HHF). Secondary outcomes included all-cause death, HHF, and new-onset AF. Receiver operating characteristic (ROC) analysis determined optimal LACI cut-offs.
Results
Among 183 patients (median age 61 years; 59 % male) followed for 4.2 years, 53 (29 %) reached the primary endpoint. Elevated LACI independently predicted the primary composite endpoint (≥0.41: aHR 2.24, 95 %CI: 1.19, 4.24, p = 0.013), HHF (≥0.44: aHR 4.54, 95 %CI: 1.69, 12.19, p = 0.003), and new-onset AF (≥0.44: aHR 3.06, 95 %CI: 1.26, 7.43, p = 0.003) but not all-cause death.
Conclusion
CMR-derived LACI independently predicted adverse outcomes in HCM, offering a reproducible marker for improved risk stratification.
Keywords: Left atrioventricular coupling index, Hypertrophic cardiomyopathy, All-cause mortality, Heart failure, Atrial fibrillation
Graphical abstract
Highlights
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CMR-derived LACI independently predicts outcomes in hypertrophic cardiomyopathy.
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Elevated LACI (≥0.41) predicts death and heart failure hospitalization.
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LACI (≥0.44) also predicts new-onset atrial fibrillation in HCM.
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LACI outperforms conventional LA parameters for prognostic assessment.
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LACI offers a reproducible marker of atrioventricular coupling and diastolic function.
1. Introduction
Hypertrophic cardiomyopathy (HCM) is a primary myocardial disease characterized by left ventricular (LV) hypertrophy unexplained by abnormal loading conditions [1]. This pathological thickening is often accompanied by impaired diastolic function and abnormal coupling between the left atrium (LA) and LV [2,3]. HCM carries substantial clinical importance due to its association with heart failure, ventricular arrhythmia, atrial fibrillation (AF), and stroke, which contribute to significant morbidity and mortality [4,5].
Despite advances in risk prediction, reliable markers for adverse outcomes in HCM remain limited. Existing prognostic models, such as the HCM Risk–Sudden Cardiac Death (SCD) score, integrate conventional parameters including LV wall thickness, LA diameter, and ventricular arrhythmias to estimate SCD risk [[6], [7], [8], [9], [10], [11], [12], [13]]. However, many adverse events occur in patients classified as low risk by these models, highlighting the need for additional indices to improve risk stratification [10].
The left atrioventricular coupling index (LACI) has recently emerged as a novel parameter that reflects the interaction between LA and LV functions. Defined as the ratio of left atrial end-diastolic volume (LAEDV) to left ventricular end-diastolic volume (LVEDV), LACI provides a dynamic measure of diastolic coupling and atrioventricular interaction [14]. Studies in non-HCM populations have shown that elevated LACI independently predicts major adverse cardiac events and AF [14,15]. Moreover, in acute myocardial infarction, cardiac magnetic resonance (CMR)–derived LACI demonstrated superior prognostic performance compared with traditional measures such as LV ejection fraction (LVEF) [15]. Elevated LACI has been shown to predict new-onset AF and is also associated with composite adverse outcomes in HCM; however, data on its prognostic performance remain limited and require further validation [16,17].
This study aims to evaluate the prognostic significance of CMR-derived LACI in predicting adverse clinical outcomes in HCM and to identify optimal LACI cut-offs for clinical applications.
2. Methods
This retrospective cohort study included adult patients (≥18 years) with HCM who underwent CMR imaging between January 2015 and October 2023 and had at least 1 year of clinical follow-up. HCM was diagnosed according to the 2023 European Society of Cardiology guidelines, defined by a LV wall thickness ≥15 mm in any myocardial segment unexplained by loading conditions. For cases with borderline hypertrophy (13–14 mm), additional features, such as family history, genetic findings, or electrocardiographic abnormalities, were required for diagnosis [6]. Patients were excluded if they had known mitochondrial, metabolic, or neuromuscular diseases; malformation syndromes (e.g., Noonan syndrome); cardiac amyloidosis; or abnormal cardiac loading conditions (e.g., severe aortic stenosis or poorly controlled hypertension). Those with inadequate CMR image quality were also excluded.
Clinical and imaging data were obtained from hospital electronic medical records. For patients with multiple CMR studies, only the first examination was analyzed. The study was approved by the Institutional Review Board of the Faculty of Medicine, Chulalongkorn University (IRB No. 0320/67; Certificate of Approval No. 0861/2024), with informed consent waived due to its retrospective design using anonymized data. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki as reflected in a priori approval by the institution's human research committee.
2.1. CMR protocol and analysis
CMR imaging was performed using 3.0 T scanners (Magnetom Skyra and Magnetom Vida, Siemens Healthineers, Erlangen, Germany) equipped with an 18-channel phased-array cardiac coil. The protocol included cardiac localizers, cine imaging, first-pass perfusion, long inversion time sequences, inversion time scout, and late gadolinium enhancement (LGE) imaging, obtained 5–10 min after contrast administration. Cine images were acquired using a steady-state free precession sequence in long-axis (2-, 3-, and 4-chamber) and contiguous short-axis views (8-mm slices without inter-slice gaps) covering the entire ventricles.
Image post-processing was performed using Syngo.via (Siemens Healthineers, Erlangen, Germany). The software automatically quantified LVEDV, LV end-systolic volume (LVESV), and LV mass, with manual adjustments as needed. LA volumes were measured at ventricular end-diastole (LAEDV) and end-systole (LAESV) using the biplane area-length method: LA volume = [8 x (A1 x A2)]/3πL, where A1 and A2 are LA areas from the 2- and 4-chamber views, and L is the shortest distance from the mitral annulus plane to the LA roof. Pulmonary veins and the LA appendage were excluded.
The LACI was calculated as LAEDV/LVEDV. Inter- and intra-observer reliability were assessed by two independent cardiovascular imaging specialists, with repeat LACI measurements performed one month apart.
2.2. Outcomes
The primary outcome was a composite endpoint of all-cause death and hospitalization for heart failure (HHF). Secondary outcomes included individual components of the primary composite endpoint and the incidence of new-onset AF, which was defined as the first episode of AF or atrial flutter, lasting longer than 30 s. Participants with pre-existing AF were excluded from the analysis of the new-onset AF.
2.3. Statistical analysis
The estimated annual incidence of adverse cardiac outcomes among patients with HCM in Thailand is approximately 5 % [18]. However, the incidence of major adverse cardiac events stratified by LACI has not been previously reported in this population. Prior studies have shown that patients with elevated LACI experience roughly twice the event rate of those with lower values [14,15]. Accordingly, we assumed an event rate of 7 % in the high-LACI group and 4 % in the low-LACI group. In HCM, an elevated LACI (≥40 %) has been observed in approximately 46 % of patients [17]. With a two-tailed alpha of 0.05 and 80 % power, the required sample size to detect a significant difference between groups was estimated at 110 patients [19].
Descriptive statistics summarized baseline characteristics. Continuous variables were expressed as medians with interquartile ranges (IQR). Categorical variables were summarized as counts and percentages. Group comparisons used Mann-Whitney U tests for continuous data and chi-square tests for categorical data. The optimal LACI cut-off for predicting the primary composite endpoint was identified using Youden's index from receiver operating characteristic (ROC) analysis.
Cox proportional hazards regression models evaluated the prognostic value of LACI, adjusting for confounders with p < 0.1 in univariate analysis. Kaplan–Meier survival analysis with log-rank testing compared event-free survival by LACI group. Inter- and intra-observer reliability were assessed using intraclass correlation coefficients (ICC), with values > 0.90 indicating excellent agreement. Statistical significance was defined as p < 0.05. Analyses were performed using SPSS version 29.0.1 (IBM Corp., Armonk, NY, USA).
3. Results
3.1. Baseline characteristics
Of the 227 CMR scans performed in patients with HCM between January 2015 to October 2023, 193 met the inclusion criteria after excluding 14 duplicate scans from the same patients, 12 scans from individuals aged <18 years, and 8 scans with <1 year of follow-up. Ten additional patients were excluded (6 with alternative diagnoses and 4 with inadequate image quality), resulting in 183 participants included in the final analysis. The median age was 61 years (IQR 51–73), and 59 % were male. Over a median follow-up of 4.2 years, 53 participants (29.0 %) experienced the primary composite outcome of all-cause death or HHF [Supplementary Fig. 1].
Participants who developed events were significantly older [69 years (IQR 56–80) vs. 60 years (IQR 51–69), p = 0.002] and had lower body mass index [23.5 kg/m2 (IQR 21.5–26.3) vs. 25.2 kg/m2 (IQR 23.3–28.2), p = 0.045]. The event group had a higher proportion of males (64.6 % vs. 45.3 %, p = 0.016) and a greater prevalence of atrial fibrillation (25.0 % vs. 9.2 %, p = 0.005). Other comorbidities, including diabetes, hypertension, coronary artery disease, cerebrovascular disease, and prior heart failure, did not differ significantly. Patients with events also demonstrated a trend toward worse New York Heart Association (NYHA) functional class [Table 1].
Table 1.
Baseline characteristics of the participants.
| Total (N = 183) | Event (N = 53) | No Event (N = 130) | p-value∗ | |
|---|---|---|---|---|
| Age, years | 61 (51, 73) | 69 (56, 80) | 60 (51, 69) | 0.002 |
| Males | 108 (59.0 %) | 24 (45.3 %) | 84 (64.6 %) | 0.016 |
| BMI, kg/m2 | 25.0 (22.1, 27.9) | 23.5 (21.5, 26.3) | 25.2 (23.3, 28.2) | 0.045 |
| Co-morbidities | ||||
| Diabetes | 45 (24.9 %) | 10 (19.2 %) | 35 (27.1 %) | 0.266 |
| Hypertension | 100 (55.2 %) | 32 (61.5 %) | 68 (52.7 %) | 0.240 |
| Dyslipidemia | 99 (54.7 %) | 32 (61.5 %) | 67 (51.9 %) | 0.429 |
| Cerebrovascular disease | 19 (10.6 %) | 7 (13.5 %) | 12 (9.4 %) | 0.361 |
| Coronary artery disease | 17 (9.4 %) | 7 (13.5 %) | 10 (7.8 %) | 0.233 |
| History of heart failure | 7 (3.9 %) | 3 (5.8 %) | 4 (3.1 %) | 0.400 |
| History of AF | 25 (13.7 %) | 13 (25.0 %) | 12 (9.2 %) | 0.005 |
| NYHA functional class | ||||
| NYHA class I | 102 (56.4 %) | 18 (34.6 %) | 84 (65.1 %) | <0.001 |
| NYHA class II | 68 (37.6 %) | 28 (53.8 %) | 40 (31.0 %) | 0.004 |
| NYHA class III | 10 (5.5 %) | 6 (11.5 %) | 4 (3.1 %) | 0.025 |
| NYHA class IV | 0 | 0 | 0 | N/A |
| Clinical presentations | ||||
| Asymptomatic | 64 (35.0 %) | 22 (41.5 %) | 42 (32.3 %) | 0.908 |
| Dyspnea | 29 (15.8 %) | 6 (11.3 %) | 23 (17.7 %) | 0.236 |
| Angina | 17 (9.3 %) | 3 (5.7 %) | 14 (10.8 %) | 0.284 |
| Syncope | 173 (94.5 %) | 47 (88.7 %) | 126 (96.9 %) | 0.280 |
| Heart failure | 9 (4.9 %) | 1 (1.9 %) | 8 (6.2 %) | 0.026 |
| Stroke | 64 (35.0 %) | 22 (41.5 %) | 42 (32.3 %) | 0.226 |
| HCM subtypes | ||||
| Asymmetrical septal | 110 (60.1 %) | 35 (66.0 %) | 75 (57.7 %) | 0.296 |
| Apical | 56 (30.6 %) | 9 (17.0 %) | 47 (36.2 %) | 0.011 |
| Mid cavity | 5 (2.7 %) | 1 (1.9 %) | 4 (3.1 %) | 0.654 |
| Concentric | 20 (10.9 %) | 10 (18.9 %) | 10 (7.7 %) | 0.028 |
| Localized | 1 (0.5 %) | 0 (0.0 %) | 1 (0.8 %) | 0.522 |
| Echocardiogram parameters | ||||
| LVEF, % | 71.0 (64.0, 78.0) | 66.5 (59.0, 77.0) | 72.5 (65.0, 78.0) | 0.041 |
| LVOT pressure gradient | 8.0 (4.0, 30.0) | 8.4 (4.0, 39.0) | 8.0 (4.0, 26.0) | 0.518 |
| LA diameter, mm | 41.0 (36.0, 46.0) | 42.0 (37.0, 47.0) | 40.0 (36.0, 45.0) | 0.318 |
| Maximal wall thickness, mm | 17.0 (14.0, 21.0) | 18.0 (14.0, 22.0) | 17.0 (14.0, 20.0) | 0.471 |
| CMR parameters | ||||
| Maximal wall thickness, mm | 76.9 (67.2, 87.5) | 81.7 (65.2, 95.6) | 74.6 (67.3, 86.1) | 0.069 |
| LVEDVI, ml/m2 | 25.9 (19.9, 32.1) | 27.4 (20.8, 38.9) | 25.2 (19.9, 30.6) | 0.075 |
| LVESVI, ml/m2 | 67.0 (61.0, 71.0) | 66.0 (57.0, 69.0) | 68.0 (62.0, 72.0) | 0.044 |
| LVEF, % | 87.5 (67.0, 108.0) | 84.3 (66.0, 108.0) | 89.9 (68.0, 108.0) | 0.636 |
| LV mass index, g/m2 | 76.9 (67.2, 87.5) | 81.7 (65.2, 95.6) | 74.6 (67.3, 86.1) | 0.069 |
| LV apical aneurysm | 3 (1.6 %) | 0 (0.0 %) | 3 (2.3 %) | 0.265 |
| LV LGE | 159 (86.9 %) | 48 (90.6 %) | 111 (85.4 %) | 0.346 |
| LA diameter, mm | 40.0 (34.0, 44.0) | 40.0 (38.0, 49.0) | 38.5 (32.0, 43.0) | <0.001 |
| LAEDVI, ml/m2 | 30.7 (20.4, 50.0) | 41.0 (27.6, 66.6) | 28.4 (19.7, 41.6) | <0.001 |
| LAESVI, ml/m2 | 49.8 (36.4, 64.5) | 58.7 (46.3, 80.2) | 45.5 (34.8, 60.4) | <0.001 |
| LAEF (%) | 35.0 (22.8, 43.7) | 29.6 (16.4, 39.2) | 37.9 (26.7, 44.4) | 0.003 |
| LACI | 39.4 (28.8, 61.0) | 47.0 (35.5, 77.5) | 36.1 (26.4, 54.6) | 0.002 |
Continuous data was presented as a median with an interquartile range.
∗ The Mann-Whitney U test was used to compare continuous, non-normally distributed data between two independent groups. The chi-square test was used to compare categorical data.
AF, atrial fibrillation; BMI, body mass index; LA, left atrium; LAEDVI, left atrial end-diastolic volume index; LAEF, left atrial ejection fraction; LACI, left atrioventricular coupling index; LGE, late gadolinium enhancement; LVEF, left ventricular ejection fraction; LVEDVI, left ventricular end-diastolic volume index; LVESVI, Left ventricular end-systolic volume index; LVESVI, left atrial end-systolic volume index; LVOT, left ventricular outflow tract; NYHA, New York Heart Association functional class.
Among CMR parameters, LACI was significantly higher in those with the primary outcome [0.47 (IQR 0.36–0.78) vs. 0.36 (IQR 0.26–0.55), p = 0.002]. LAESV index [58.7 mL/m2 (IQR 46.3–80.2) vs. 45.5 mL/m2 (IQR 34.8–60.5), p < 0.001] and LAEDV index [41.0 mL/m2 (IQR 27.6–66.6) vs. 28.4 mL/m2 (IQR 19.7–41.6), p < 0.001] were also greater, whereas LA ejection fraction (LAEF) was lower [28 % (IQR 15–39) vs. 36 % (IQR 25–44), p = 0.012]. No significant differences were observed in the LV parameters, including maximal wall thickness, LVEDV index, LVEF, LV mass index, or LV LGE, except for a modest difference in LVESV index [66.0 mL/m2 (IQR: 57.0, 69.0) vs. 68.0 mL/m2 (IQR: 62.0, 72.0), p = 0.044].
3.2. Optimal LACI cut-off
ROC analysis identified a LACI cut-off of 0.41 as optimal for predicting the primary composite endpoint, yielding an area under the curve (AUC) of 0.654, sensitivity of 74 %, specificity of 60 %, and the best Youden's index of 0.332. LACI showed the highest predictive accuracy (AUC 0.662) compared with LA diameter (0.627), maximal wall thickness (0.531), LVOT gradient (0.500), LVEF (0.408), and LAEF (0.367) [Fig. 1]. The optimal LACI cut-offs for predicting all-cause death, HHF, and new-onset AF were 0.37 (AUC 0.560), 0.44 (AUC 0.784), and 0.44 (AUC 0.659), respectively, as shown in Supplementary Fig. 2–4.
Fig. 1.
Receiver operating characteristic curve of LACI and other parameters predicting primary composite endpoints of all-cause mortality and heart failure hospitalization LA, left atrium; LACI, left atrioventricular coupling index; LAEF, left atrial ejection fraction; LVEF, left ventricular ejection fraction; LVOT, left ventricular outflow tract.
3.3. Adverse outcomes and survival analysis
During a median follow-up of 4.2 years, 53 participants (29.0 %) experienced the primary composite outcome. All-cause death, HHF, and new-onset AF occurred in 30 (16.4 %), 30 (16.4 %), and 27 (13.1 %) patients, respectively. Participants with elevated LACI above the defined cut-offs had a significantly higher incidence of the primary composite endpoint, HHF, and new-onset AF [Table 2].
Table 2.
Incidence of primary and secondary outcomes.
| Total | LACI ≥ cut-offs∗ | LACI < cut-offs∗ | P-value | |
|---|---|---|---|---|
| Primary outcome | 53 (29.0 %) | 36 (40.9 %) | 17 (17.9 %) | <0.001 |
| Secondary outcomes | ||||
| All-cause death | 30 (16.4 %) | 17 (19.3 %) | 13 (13.7 %) | 0.304 |
| Hospitalization for heart failure | 30 (16.4 %) | 25 (28.4 %) | 5 (5.3 %) | <0.001 |
| New-onset atrial fibrillation | 27 (14.8 %) | 20 (22.7 %) | 7 (7.4 %) | 0.003 |
∗ LACI cut-off was 0.41 for the primary outcome, 0.37 for all-cause death, 0.44 for hospitalization for heart failure, and 0.44 for new-onset atrial fibrillation.
LACI, left atrioventricular coupling index.
In univariate Cox regression analysis for the primary outcome, age (HR 1.04, 95 % CI: 1.02, 1.06, p < 0.001), male sex (HR 1.98, 95 % CI: 1.07, 3.65, p = 0.03), apical subtype (HR 0.44, 95 % CI: 0.20, 0.99, p = 0.049), LVEF (HR 0.96, 95 % CI: 0.93, 0.98; p = 0.002), and LACI ≥0.41 (HR 2.59, 95 % CI: 1.45, 4.63, p < 0.001) were significantly associated with the composite endpoint. After adjustment, age (adjusted hazard ratio (aHR) 1.03, 95 % CI: 1.01, 1.05, p = 0.003), LVEF (aHR 0.97, 95 % CI: 0.95, 0.99; p = 0.012), and LACI ≥0.41 (aHR 2.24, 95 % CI: 1.19, 4.24, p = 0.013) remained independent predictors [Table 3].
Table 3.
Univariate and multivariate Cox regression analysis for the primary composite outcome.
| Univariate analysis | p-value | Multivariate analysis | p-value | |
|---|---|---|---|---|
| Age, years | 1.04 (1.02, 1.06) | < 0.001 | 1.03 (1.01, 1.05) | 0.003 |
| Males | 1.98 (1.07, 3.65) | 0.030 | 1.37 (0.75, 2.48) | 0.308 |
| BMI, kg/m2 | 0.96 (0.89, 1.03) | 0.231 | ||
| HCM subtypes | ||||
| Asymmetrical septal | 1.36 (0.72, 2.55) | 0.346 | ||
| Apical | 0.44 (0.20, 0.99) | 0.049 | 0.82 (0.38, 1.78) | 0.619 |
| Others | 1.52 (0.73, 3.12 | 0.267 | ||
| Echocardiogram parameters | ||||
| LVOT pressure gradient | 1.00 (0.99, 1.01) | 0.378 | ||
| CMR parameters | ||||
| Maximal wall thickness, mm | 0.99 (0.94, 1.03) | 0.653 | ||
| LVEF, % | 0.96 (0.93, 0.98) | 0.002 | 0.97 (0.95, 0.99) | 0.012 |
| LV mass index, g/m2 | 1.00 (0.99, 1.00) | 0.463 | ||
| LV LGE | 1.91 (0.76, 4.82) | 0.171 | ||
| LACI ≥0.41 | 2.59 (1.45, 4.63) | <0.001 | 2.24 (1.19, 4.24) | 0.013 |
BMI, body mass index; CMR, cardiac magnetic resonance; HCM, hypertrophic cardiomyopathy; LACI, left atrioventricular coupling index; LGE, late gadolinium enhancement; LVEF, left ventricular ejection fraction; LVOT, left ventricular outflow tract.
For secondary outcomes, elevated LACI (≥0.44) independently predicted HHF (aHR 4.54, 95 % CI 1.69–12.19, p = 0.003) and new-onset AF (aHR 3.24, 95 % CI 1.37–7.68, p = 0.003), but not all-cause death [Supplementary Tables 1–3]. Kaplan–Meier curves stratified by LACI cut-offs are shown in Fig. 2.
Fig. 2.
Kaplan-Meier curves demonstrate cumulative hazard for the primary composite outcome (A), all-cause death (B), hospitalization for heart failure (C), and new-onset atrial fibrillation (D) stratified by LACI cut-off. aHR, adjusted hazard ratio; LACI, left atrioventricular coupling index.
3.4. Intra- and inter-observer variation
Inter- and intra-observer reliability were excellent, with ICCs of 0.908 (95 % CI 0.876–0.954, p < 0.001) and 0.962 (95 % CI 0.920–0.989, p < 0.001), respectively, indicating outstanding measurement consistency.
4. Discussion
This study demonstrates that the CMR-derived LACI is a powerful prognostic marker in HCM. An elevated LACI (≥0.41) was independently associated with a more than twofold increased risk of the composite outcome of all-cause death and HHF, even after adjusting for age, sex, HCM subtype, and LVEF. These findings underscore the prognostic significance of atrioventricular coupling in the disease continuum of HCM.
4.1. Pathophysiologic insights
The association between elevated LACI and adverse outcomes likely reflects the underlying pathophysiology of HCM, in which LA remodeling and functional impairment serve as key markers of disease severity. LACI, defined as the ratio of LAEDV to LVEDV, provides an integrative assessment of atrioventricular coupling and diastolic function that extends beyond isolated chamber metrics. By quantifying the imbalance between atrial reservoir capacity and ventricular filling, LACI captures the hemodynamic consequence of LV stiffness and elevated filling pressures, hallmark features of HCM. Backhaus et al. demonstrated that LACI measured during rest and exercise stress CMR sensitively detects diastolic dysfunction in heart failure with preserved ejection fraction [20]. In HCM, reduced LV compliance and disproportionate LA enlargement amplify atrioventricular uncoupling, making LACI particularly relevant in this population. The predominance of HHF in our composite endpoint supports that elevated LACI reflects impaired atrial contractile reserve and increased intracardiac pressures leading to congestion. The lack of association with all-cause mortality may indicate that atrioventricular uncoupling contributes mainly to morbidity. Moreover, prominent LA enlargement relative to LV size underscores HCM's distinct pathophysiology, highlighting the superior utility of LACI in this cohort [21,22].
Elevated LACI could serve as a critical surrogate for chronically elevated filling pressures and the maladaptive atrial remodeling that predisposes patients to arrhythmias. Prior work investigating predictive parameters for recurrence in patients undergoing electrical cardioversion has demonstrated that increased LA dimensions are strongly associated with arrhythmia recurrence, reflecting a more advanced state of atrial myopathy [23]. This structural remodeling has direct therapeutic implications for early rhythm control strategies [24,25]. Consequently, an elevated LACI should prompt consideration for early catheter ablation rather than a deferral of therapy. Meta-analytic data indicate that catheter ablation is superior to medical treatment in reducing mortality and improving quality of life, even in heart failure populations [26]; therefore, early rhythm control should be prioritized in HCM patients with significant atrioventricular uncoupling to prevent irreversible remodeling.
4.2. Comparison with previous studies
Previous studies have shown that LA dysfunction, typically assessed by LA diameter or volume, is associated with adverse events such as SCD in HCM. However, these conventional indices primarily reflect structural remodeling and do not capture the dynamic atrioventricular interaction that characterizes disease progression. Furthermore, earlier studies did not establish strong associations with composite outcomes such as HHF or mortality [14]. In patients with acute myocardial infarction, CMR-derived LACI independently predicted major adverse cardiac events beyond LVEF [15]. This aligns with our findings, underscoring the prognostic utility of LACI in identifying high-risk patients across diverse cardiac pathologies.
The most comprehensive CMR-based study of LACI in HCM to date included 206 patients with a median follow-up of 60 months [16]. That study demonstrated that elevated LACI independently predicted composite adverse outcomes, including death, heart failure, and arrhythmia-related events (HR 1.054, 95 % CI 1.037–1.071, p < 0.001), with an optimal cut-off of 40.1 %. This threshold closely parallels our study's optimal value of 0.41 for predicting the composite outcome of all-cause death and HHF. Both studies consistently identified elevated LACI as a strong prognostic marker, suggesting that a threshold near 0.40 is robust across different populations and clinical endpoints. Several differences are noteworthy. The prior study used a broader composite outcome encompassing heart failure and arrhythmia-related events, whereas our study focused specifically on death and HHF. Moreover, we demonstrated that LACI ≥0.44 independently predicted new-onset AF, extending its prognostic relevance beyond heart failure and ventricular arrhythmia to atrial arrhythmic risk.
Consistent with earlier echocardiographic studies, elevated LACI (>0.40) has been linked to new-onset AF and stroke. Our findings corroborate these observations, showing that participants with LACI ≥0.44 had a threefold higher risk of AF (aHR 3.24, 95 % CI 1.37–7.68, p = 0.003) [17,27].
Emerging evidence indicates that LACI serves as a robust prognostic marker across diverse populations and cardiac pathologies beyond HCM. In older adults without baseline cardiovascular disease, elevated LACI has been shown to predict mortality independently of traditional LV functional parameters [28]. Similarly, in patients with heart failure, LACI outperforms LA volume alone in identifying high-risk phenotypes [29], and it provides powerful independent prognostic value in infiltrative diseases such as light-chain amyloidosis [30]. These data support the concept that LACI integrates atrial-ventricular interaction more effectively than isolated chamber indices across the spectrum of myocardial diseases.
Taken together, these results establish LACI as a reproducible and physiologically grounded biomarker of atrioventricular uncoupling and diastolic dysfunction. The consistent prognostic thresholds around 0.40 across imaging modalities and cardiac conditions support its robustness and clinical applicability [14,16,17,31].
4.3. Limitations
This study has several limitations. First, its retrospective, single-center design may introduce selection and information bias, limiting causal inference. Second, all-cause mortality was used as an endpoint rather than cardiovascular-specific death, which may have diluted associations with LACI due to the inclusion of non-cardiac deaths. Third, myocardial tissue characterization (e.g., T1 mapping, extracellular volume, T2-based imaging, or perfusion studies) and biomarkers of inflammation or ischemia, which were reported as significant prognostic factors in HCM patients, were not evaluated, precluding assessment of their additive prognostic value [[32], [33], [34]]. Fourth, external validation in multicenter and ethnically diverse cohorts is warranted to confirm the generalizability and refine the clinical cut-off for LACI. Lastly, considering the heterogeneity and complexity of HCM, current risk markers and risk stratification models may not fully capture interactions between risk factors and outcomes. Machine-learning-based models may significantly enhance predictive precision by integrating multifaceted clinical variables [35]. Future studies could similarly employ machine learning algorithms to incorporate LACI into a more dynamic and personalized risk prediction framework for HCM patients.
5. Conclusion
CMR-derived LACI is an independent prognostic marker in HCM. An elevated LACI (≥0.41) is associated with a higher risk of the composite outcome of all-cause death and HHF, and it also predicts new-onset AF. LACI provides an integrative and reproducible measure of atrioventricular interaction that enhances risk stratification beyond conventional parameters.
CRediT authorship contribution statement
Sittinop Titichoatrattana: Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Ing-orn Arunakul: Writing – review & editing, Supervision, Methodology, Conceptualization. Paisit Kosum: Methodology, Data curation. Aree Maitaothong: Visualization, Investigation, Data curation. Em-on Puripun: Methodology, Investigation. Monravee Tumkosit: Visualization, Supervision, Investigation. Yongkasem Vorasettakarnkij: Supervision, Methodology, Conceptualization. Pairoj Chattranukulchai: Writing – review & editing, Visualization, Resources, Investigation, Conceptualization. Nonthikorn Theerasuwipakorn: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.
Disclosure
None.
Sources of funding
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
Acknowledgement
The authors acknowledge the support for article processing provided by the Cardiac Center, King Chulalongkorn Memorial Hospital, Bangkok, Thailand.
Footnotes
This author takes responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.
Supplementary data to this article can be found online at https://doi.org/10.1016/j.ijcrp.2025.200566.
Appendix A. Supplementary data
The following is the Supplementary data to this article:
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