Plasma volume status predicting clinical outcomes in patients undergoing transcatheter edge‐to‐edge mitral valve repair

Abstract

Aims

Plasma volume status (PVS) is recognized as a marker of systemic congestion, but its clinical utility in patients with mitral regurgitation (MR) undergoing transcatheter edge‐to‐edge mitral valve repair (M‐TEER) has not been well established. This study aimed to evaluate the prognostic significance of PVS in these patients.

Methods and results

Data from 3763 patients who underwent M‐TEER were analysed from a Japanese multicentre registry. Patients were classified into functional MR (FMR) and degenerative MR (DMR) according to MR aetiology, and the median PVS values for each were calculated (FMR 12.7, DMR 14.4). The median value was used as the cut‐off, stratifying the cohort into a high PVS group (n = 1882) and a low PVS group (n = 1881). All‐cause mortality, cardiovascular death, and heart failure (HF) hospitalization between these two groups were compared up to 3 years in the overall, FMR, and DMR populations. The cumulative incidence rates of all‐cause mortality, cardiovascular death, and HF hospitalization were higher in the high PVS group than in the low PVS group (47.0% vs. 22.2%, P < 0.001, 31.6% vs. 13.6%, P < 0.001, and 35.9% vs. 24.7%, P < 0.001, respectively). Similar trends in terms of all‐cause mortality, cardiovascular death, and HF hospitalization were observed in the FMR and DMR cohorts (all P < 0.05). In the multivariate Cox regression analysis, the high PVS compared with the low PVS group was independently associated with the increased risk of all‐cause death (hazard ratio [HR], 1.02; 95% confidence interval [CI], 1.01–1.03; P < 0.001), cardiovascular death (HR, 1.02; 95% CI, 1.01–1.03, P < 0.001) and HF hospitalization (HR, 1.02; 95% CI, 1.01–1.02, P < 0.001). An independent association between a high PVS and all‐cause death, cardiovascular death, and HF hospitalization was also found in FMR and DMR sub‐groups (all P < 0.05) while reducing MR severity to moderate or less after M‐TEER was associated with improved outcomes in both the high and low PVS groups.

Conclusions

Preoperative PVS is a strong independent prognostic marker in patients undergoing M‐TEER, correlating with increased risk of mortality and HF hospitalization. PVS may provide valuable clinical insights for patient stratification and management strategies in M‐TEER patients.

Introduction

With an increase in the number of patients with heart failure (HF) and mitral regurgitation (MR) in an aging society, mitral transcatheter edge‐to‐edge valve repair (M‐TEER) has emerged as a less invasive treatment option for reducing MR severity. ¹ , ² A recent pivotal randomized trial demonstrated a decreased risk of HF hospitalization and mortality in patients who underwent M‐TEER compared with patients treated with medical therapy alone. ³ , ⁴ However, our previous registry data revealed that 22% of patients died or were hospitalized for HF hospitalization within 1 year after M‐TEER. ⁵ Given the heterogeneity of the population and the complex nature of daily practice, risk stratification and detection better responders should be carefully screened before M‐TEER.

The total plasma volume (PV), reflecting cardiac congestion, can be directly estimated using an indicator dilution method, and the clinical relevance of its volume measurement has been demonstrated in patients with decompensated HF. ⁶ , ⁷ , ⁸ , ⁹ In contrast, most direct PV measurements are clinically impractical, with several limitations, such as cost and logistic constraints. ¹⁰ , ¹¹ A previous investigation demonstrated that the calculated PV, comprising an individual patient's body weight (BW), haematocrit, and sex difference, was closely associated with optimally measured PV values. ¹² In addition, many clinical analyses have confirmed that calculated PV status (PVS) as a marker of congestion strongly predicts morbidity and mortality in patients with HF after cardiac surgery or catheter interventions. ¹² , ¹³ , ¹⁴ , ¹⁵ In this context, the calculated PVS can be an adequate surrogate marker for predicting the major adverse cardiac events in patients undergoing M‐TEER. However, no data are available on the prognostic utility of PVS in this cohort. Therefore, this study aimed to investigate the prognostic value of calculated PVS in patients after M‐TEER using large‐scale multicenter registry data.

Methods

Study population and plasma volume status calculation

Data were extracted from the Optimized CathEter vAlvular iNtervention (OCEAN)‐Mitral registry, an ongoing multicentre registry comprising 21 Japanese medical centers. From April 2018 to June 2023, 3764 patients with significant MR underwent M‐TEER as eligible candidates by consensus through discussions among individual heat team members. Clinical findings, including blood test results, were obtained before the M‐TEER. BW was not calculated in only one patient, and the PVS of the remaining 3763 patients was obtained according to a previous formula. ¹² , ¹⁶ , ¹⁷ The PVS was calculated using the estimated and ideal PV levels. For calculating the estimated PV, the Kaplan–Hakim formula was adopted as follows: estimated PV = ([1 − haematocrit] × [a + (b × BW [kg])]), where a (1530 in men and 864 in women) and b (41 in men and 47.9 in women) were used as adjustment values. Ideal PV was calculated as c × BW (kg), where c = 39 in men and 40 in women. Finally, the estimated PVS was calculated as PVS = (estimated PV − ideal PV) × 100/ideal PV. In the population with 3763 PVS measurements available, 2637 patients had functional MR (FMR), and 1126 had degenerative MR (DMR). The median PVSs in FMR and DMR were 12.7 and 14.4, respectively. Based on these median values, the entire population was divided into two groups: a high PVS population (n = 1,882) and a low PVS population (n = 1881) (Figure 1 A,B ). All patients provided informed consent before undergoing M‐TEER, and the study protocol was approved by the institutional review board of each institution. This study was registered in the University Hospital Medical Information Network Clinical Trials Registry with the International Committee of Medical Journal Editors (UMIN000023653). The local institutional review board approved the study protocol. This study was conducted in accordance with the latest version of the Declaration of Helsinki and the guidelines for epidemiological studies issued by the Ministry of Health, Labour and Welfare of Japan.

Figure 1.

(A) Flowchart of the study design with patient distribution. (B) Distribution of plasma volume status (PVS) in the OCEAN‐Mitral registry cohort was divided into functional mitral regurgitation (FMR) and degenerative mitral regurgitation (DMR). (C) Kaplan–Meier curves showing cumulative all‐cause mortality, cardiovascular death, and heart failure hospitalization in patients with PVS stratified based on quartiles.

Procedural and clinical outcome measures

The indications and procedural definitions of M‐TEER followed the current recommendations and were previously mentioned in our studies. ¹⁸ , ¹⁹ The severity of the baseline MR (grade 0+, none/trivial; 1+, mild; 2+, moderate; 3+, moderate to severe; and 4+, severe) was defined according to the American Society of Echocardiography. ²⁰ During the follow‐up period, the MitraClip device (Abbott Vascular) was the only commercially available device for M‐TEER in Japan. From April 2018 to August 2020, a second‐generation (G2) system was used, and from September 2020 to June 2023, a G4 system was available. Post‐procedural MR ≤ 2+ is considered an acceptable MR reduction after M‐TEER. Baseline patient characteristics, laboratory data transthoracic echocardiography, transesophageal echocardiography, and procedural findings were examined at each centre. The patients were followed up at 1, 12, and every 12 months after M‐TEER through clinical visits or telephone consultations with the patients or their family members. The definition of death for cardiac and non‐cardiac profiles was determined based on the Mitral Valve Academic Research Consortium. ²¹ In brief, cardiac death included hospitalization for HF, myocardial infarction, stroke, cardiac arrhythmia, unknown causes including (sudden death), and any device‐related cause. In addition, the clinical outcomes were assessed between the median PVS value and the presence or absence of post‐MR ≥ 2+ after M‐TEER. The primary endpoints of this study were the event rates of all‐cause death, cardiac death, and HF hospitalization up to 3 years after M‐TEER. These endpoints were evaluated in overall, FMR, and DMR populations. To determine treatment efficacy in the high and low PVS population, we also added subgroup analyses by residual postoperative MR < 2+, optimized medical therapy as rate of fantastic 4 [angiotensin receptor blockers (ARBs), angiotensin‐converting enzyme inhibitors (ACEIs) or angiotensin receptor‐neprilysin inhibitors (ARNIs), beta‐blockers, mineralocorticoid receptor antagonists (MRAs), and sodium‐coupled glucose transporter 2 inhibitors (SGLT2Is)], and prescription of diuretics.

Statistical analysis

All statistical analyses were performed using the IBM SPSS software version 22 (IBM Corp., Armonk, NY, USA). Differences were considered statistically significant at a P value < 0.05, and 95% confidence intervals (CIs) were reported as appropriate. Continuous variables are expressed as means ± standard deviations or medians (interquartile ranges) according to the variable distributions. Categorical variables are expressed as percentages. The Kaplan–Meier method and log‐rank test were used to evaluate differences in mortality among the four groups. Univariate Cox regression analysis was performed to evaluate the associations between the clinical variables and all‐cause death, cardiac death, non‐cardiac death, and HF hospitalization following M‐TEER. Thereafter, multivariate analysis was performed using baseline clinical characteristics and variables (P < 0.05) in the univariate analysis to examine the independent associations between the calculated PVS and clinical endpoints after M‐TEER. Improvements in the predictive accuracy of the Geriatric Nutritional Risk Index compared with the conventional prediction of survival using the clinical model and basic components were determined by calculating the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) based on a logit model. ²²

Results

Baseline characteristics

The baseline patient characteristics are shown in Table 1 . Compared with the low PVS group, the high PVS group was older, had lower body surface area (BSA), and had higher prevalence of New York Heart Association (NYHA) class III/IV and Clinical Frailty Scale (CFS) ≥ 4 (all P < 0.05). Serum natrium (138.7 ± 3.9 mEq/L vs. 139.4 ± 3.5 mEq/L) and serum albumin (3.4 ± 0.5 g/dL vs. 3.8 ± 0.5 g/dL) levels, and estimated glomerular filtration rate (eGFR) (36.8 ± 19.6 mL/min/1.73 m² vs. 41.5 ± 18.9 mL/min/1.73 m²) were significantly lower in the high PVS group than in the low PVS group (all P < 0.05). B‐type natriuretic peptide (BNP) level > 200 pg/mL was more prevalent in the high PVS group than in the low PVS group (73.5% vs. 65.8%, P < 0.001).

Table 1.

Baseline patient characteristics high PVS versus low PVS

	Overall	High PVS	Low PVS
Patients, n	n = 3763	n = 1882	n = 1881	P value
Baseline clinical characteristics
Male, n	2066 (54.9%)	1071 (56.9%)	995 (52.9%)	0.01
Age, years	78.8 ± 9.6	81.1 ± 8.4	76.4 ± 10.2	<0.001
Weight, kg	52.6 ± 11.5	47.5 ± 9.1	57.7 ± 11.3	<0.001
Height, cm	156.9 ± 10.2	155.2 ± 10.0	158.7 ± 10.1	<0.001
BSA, m2	1.51 ± 0.19	1.43 ± 0.17	1.58 ± 0.19	<0.001
NYHA III/IV, n	2371 (63.0%)	1257 (66.8%)	1114 (59.2%)	<0.001
High CFS, n	1992 (52.9%)	1154 (63.3%)	838 (46.3%)	<0.001
Comorbidity
Hypertension, n	2451 (65.1%)	1205 (64.0%)	1246 (66.2%)	0.08
Dyslipidaemia, n	1817 (48.3%)	852 (45.3%)	965 (51.3%)	<0.001
Diabetes, n	988 (26.3%)	460 (24.4%)	528 (28.1%)	0.01
Atrial filiation, n	2323 (61.7%)	1149 (61.1%)	1174 (62.4%)	0.21
Coronary artery disease, n	1311 (34.8%)	697 (37.0%)	614 (32.6%)	0.003
Post open‐heart surgery	378 (10.0%)	190 (10.1%)	188 (10.0%)	0.48
Prior PMI/ICD/CRT, n	791 (21.0%)	395 (21.0%)	396 (21.1%)	0.50
Prior stroke, n	431 (11.5%)	232 (12.3%)	199 (10.6%)	0.051
Peripheral vascular disease, n	367 (9.8%)	207 (11.0%)	160 (8.5%)	0.01
Pulmonary disease, n	596 (15.8%)	310 (16.5%)	286 (15.2%)	0.15
Liver cirrhosis, n	62 (1.6%)	33 (1.8%)	29 (1.5%)	0.35
Pre‐procedural laboratory data
Serum natrium, mEq/L	139.0 ± 3.7	138.7 ± 3.9	139.4 ± 3.5	<0.001
Serum albumin, g/dL	3.6 ± 0.5	3.4 ± 0.5	3.8 ± 0.5	<0.001
eGFR, mL/min/1.73m2	39.2 ± 19.4	36.8 ± 19.6	41.5 ± 18.9	<0.001
BNP > 200 pg/mL, n	2621 (69.7%)	1384 (73.5%)	1237 (65.8%)	<0.001
Echocardiographic data
Prior LVEF, %	44.3 ± 16.3	45.9 ± 16.7	44.3 ± 16.6	0.003
LVDd, mm	56.6 ± 10.4	55.3 ± 9.9	58.0 ± 10.6	<0.001
LVDs, mm	43.9 ± 13.4	42.4 ± 12.6	45.4 ± 14.1	<0.001
LVEDV, mL	146.6 ± 69.7	141.0 ± 65.7	152.2 ± 73.2	<0.001
LVESV, mL	90.8 ± 62.9	85.9 ± 59.4	95.6 ± 65.9	<0.001
ERO, cm2	0.38 ± 0.20	0.38 ± 0.21	0.38 ± 0.19	0.95
Regurgitant volume, mL	56.0 ± 30.4	56.7 ± 32.4	55.4 ± 28.3	0.21
Regurgitant fraction, %	50.8 ± 16.9	51.0 ± 16.0	50.6 ± 17.7	0.50
Pre TR > moderate, n	386 (10.3%)	237 (12.6%)	149 (7.9%)	<0.001
Post‐procedural variable
Device time, min	63.9 ± 39.7	65.0 ± 41.3	62.8 ± 38.1	0.14
Procedure time, min	91.5 ± 46.7	92.0 ± 47.1	91.0 ± 46.3	0.53
Number of clips, n	1.28 ± 0.49	1.28 ± 0.49	1.28 ± 0.49	0.98
Acute procedural success, n	3578 (95.1%)	1770 (94.0%)	1808 (96.1%)	0.002
Functional MR (2637), n	2,543 (96.4%)	1,267 (95.9%)	1,276 (97.0%)	0.09
Degenerative MR (1126), n	1035 (91.9%)	503 (89.7%)	532 (94.2%)	0.004
Cardiac tamponade, n	16 (0.4%)	10 (0.5%)	6 (0.3%)	0.23
Access‐site‐related complication, n	63 (1.7%)	36 (1.9%)	27 (1.4%)	0.15
TEE‐related complication, n	31 (0.8%)	21 (1.1%)	10 (0.5%)	0.04
Pulmonary complication, n	23 (0.6%)	15 (0.8%)	8 (0.4%)	0.11
Acute kidney injury, n	78 (2.1%)	44 (2.3%)	34 (1.8%)	0.15
In‐hospital death, n	106 (2.8%)	75 (4.0%)	31 (1.6%)	<0.001
Post MR > moderate, n	138 (3.7%)	88 (4.7%)	50 (2.7%)	0.001

Values are numbers (%) or mean ± SD.

BNP, B‐type natriuretic peptide; BSA, body surface area; CFS, Clinical Frailty Scale; CRT, cardiac resynchronization therapy; eGFR, estimated glomerular filtration rate; ERO, effective regurgitant orifice; ICD, implantable cardioverter defibrillator; LVDd, left ventricular internal dimension in diastole; LVDs, left ventricular internal dimension in systole; LVEDV, left ventricular end‐diastolic volume; LVEF, left ventricle ejection fraction; LVESV, left ventricular end‐systolic volume; MR, mitral regurgitation; NYHA, New York Heart Association; PMI, pacemaker implantation; PVS, plasma volume status; TEE, transesophageal echocardiogram; TR, tricuspid regurgitation.

A comparison of the patient backgrounds between the FMR and DMR groups is summarized in Table 2 . There were many significant differences between the two groups with regard to the percentage of male, age, BSA, prevalence of NYHA class III/IV, and CFS ≥ 4 (all P < 0.05). Serum natrium level (138.7 ± 3.8 mEq/L vs. 139.8 ± 3.3 mEq/L, P < 0.001) and eGFR (37.5 ± 19.3 mL/min/1.73 m² vs. 43.0 ± 18.9 mL/min/1.73m², P < 0.001) were lower in the high PVS group than in the low PVS group, and BNP level > 200 pg/mL was more prevalent in the high PVS group than in the low PVS group (75.8% vs. 55.3%, P < 0.001). The FMR group was relatively young but had multiple comorbidities. In contrast, the patients in the DMR group were older and frail.

Table 2.

Baseline patient characteristics FMR versus DMR

	Overall	FMR	DMR
Patients, n	n = 3763	n = 2637	n = 1126	P value
Baseline clinical characteristics
Male, n	2066 (54.9%)	1,560 (59.2%)	506 (44.9%)	<0.001
Age, years	78.8 ± 9.6	77.0 ± 9.7	82.9 ± 8.1	<0.001
Weight, kg	52.6 ± 11.5	53.7 ± 11.6	49.9 ± 10.8	<0.001
Height, cm	156.9 ± 10.2	158.2 ± 9.9	154.0 ± 10.3	<0.001
BSA, m2	1.51 ± 0.19	1.53 ± 0.19	1.45 ± 0.19	<0.001
NYHA III/IV, n	2371 (63.0%)	1704 (64.6%)	667 (59.2%)	0.001
High CFS, n	1992 (52.9%)	1349 (53.1%)	643 (58.9%)	0.001
Comorbidity
Hypertension, n	2451 (65.1%)	1670 (63.3%)	781 (69.4%)	<0.001
Dyslipidaemia, n	1817 (48.3%)	1391 (52.7%)	426 (37.8%)	<0.001
Diabetes, n	988 (26.3%)	832 (31.6%)	156 (13.9%)	<00.01
Atrial fibrillation, n	2323 (61.7%)	1677 (63.6%)	646 (57.4%)	<0.001
Coronary artery disease, n	1311 (34.8%)	1093 (41.4%)	218 (19.4%)	<0.001
Post open‐heart surgery	378 (10.0%)	283 (10.7%)	95 (8.4%)	0.02
Prior PMI/ICD/CRT, n	791 (21.0%)	721 (27.3%)	70 (6.2%)	<0.001
Prior stroke, n	431 (11.5%)	302 (11.5%)	129 (11.5%)	0.52
Peripheral vascular disease, n	367 (9.8%)	277 (10.5%)	90 (8.0%)	0.01
Chronic kidney disease, n	3260 (86.6%)	2317 (87.9%)	943 (83.7%)	<0.001
Dialysis dependent, n	229 (6.1%)	143 (7.6%)	86 (4.6%)	<0.001
Pulmonary disease, n	596 (15.8%)	403 (15.3%)	193 (17.1%)	0.08
Liver cirrhosis, n	62 (1.6%)	46 (1.7%)	16 (1.4%)	0.29
Pre‐procedural laboratory data
Haemoglobin, g/dL	11.7 ± 1.8	11.7 ± 1.9	11.6 ± 1.7	0.20
Haematocrit, %	35.8 ± 5.4	35.8 ± 5.5	35.6 ± 5.0	0.17
Serum natrium, mEq/L	139.0 ± 3.7	138.7 ± 3.8	139.8 ± 3.3	<0.001
Serum albumin, g/dL	3.6 ± 0.5	3.6 ± 0.6	3.6 ± 0.5	0.01
eGFR, mL/min/1.73m2	39.2 ± 19.4	37.5 ± 19.3	43.0 ± 18.9	<0.001
BNP > 200 pg/mL, n	2621 (69.7%)	1998 (75.8%)	623 (55.3%)	<0.001
Echocardiographic data
Prior LVEF, %	44.3 ± 16.3	38.7 ± 14.2	60.1 ± 11.5	0.003
LVDd, mm	56.6 ± 10.4	59.1 ± 10.3	50.9 ± 7.8	<0.001
LVDs, mm	43.9 ± 13.4	48.3 ± 12.8	33.7 ± 8.6	<0.001
LVEDV, mL	146.6 ± 69.7	160.5 ± 73.4	113.6 ± 45.5	<0.001
LVESV, mL	90.8 ± 62.9	107.3 ± 64.5	49.0 ± 31.7	<0.001
ERO, cm2	0.38 ± 0.20	0.34 ± 0.16	0.49 ± 0.23	<0.001
Regurgitant volume, mL	56.0 ± 30.4	50.3 ± 27.4	69.4 ± 32.7	<0.001
Regurgitant fraction, %	50.8 ± 16.9	49.6 ± 17.5	53.6 ± 15.2	<0.001
Pre TR > moderate, n	386 (10.3%)	270 (10.2%)	116 (10.3%)	0.50
Post‐procedural variable
Device time, min	63.9 ± 39.7	62.0 ± 39.0	68.6 ± 41.2	<0.001
Procedure time, min	91.5 ± 46.7	89.9 ± 46.6	95.3 ± 46.5	0.022
Number of clips, n	1.28 ± 0.49	1.25 ± 0.47	1.35 ± 0.53	<0.001
Acute procedural success, n	3578 (95.1%)	2543 (96.4%)	1035 (91.9%)	0.002
Cardiac tamponade, n	16 (0.4%)	10 (0.4%)	6 (0.5%)	0.34
Access‐site‐related complication, n	63 (1.7%)	46 (1.7%)	17 (1.5%)	0.36
TEE‐related complication, n	31 (0.8%)	19 (0.7%)	12 (1.1%)	0.19
Pulmonary complication, n	23 (0.6%)	16 (0.6%)	7 (0.6%)	0.56
Acute kidney injury, n	78 (2.1%)	63 (2.4%)	15 (1.3%)	0.02
In‐hospital death, n	106 (2.8%)	85 (3.2%)	21 (1.9%)	0.01
Post MR > moderate, n	138 (3.7%)	68 (2.6%)	70 (6.3%)	<0.001

Values are numbers (%) or mean ± SD.

BNP, B‐type natriuretic peptide; BSA, body surface area; CFS, clinical frailty scale; CRT, cardiac resynchronization therapy; DMR, degenerative mitral regurgitation; eGFR, estimated glomerular filtration rate; ERO, effective regurgitant orifice; FMR, functional mitral regurgitation; ICD, implantable cardioverter defibrillator; LVDd, left ventricular internal dimension in diastole; LVDs, left ventricular internal dimension in systole; LVEDV, left ventricular end‐diastolic volume; LVEF, left ventricle ejection fraction; LVESV, left ventricular end‐systolic volume; MR, mitral regurgitation; NYHA, New York Heart Association; PMI, pacemaker implantation; TEE, transesophageal echocardiogram; TR, tricuspid regurgitation.

Association between calculated plasma volume status and outcomes in the mitral regurgitation undergoing transcatheter edge‐to‐edge mitral valve repair cohort

Cumulative mortality rates were compared between the high and low PVS groups with regard to all‐cause death, cardiovascular death, and HF hospitalization using Kaplan–Meier mortality curves (Figure 1 C ). A significantly higher all‐cause mortality at 3 years was found in the high PVS group than in the low PVS group (47.0% vs. 22.2%, log‐rank test: P < 0.001). In addition, the cardiovascular mortality and HF hospitalization rates were higher in the high PVS than in the low PVS group (cardiovascular death: 31.6% vs. 13.6%, P < 0.001; HF hospitalization: 35.9% vs. 24.7%, P < 0.001, respectively). These trends were similar when subdivided into the FMR and DMR cohorts (Figure  2 ).

Figure 2.

Kaplan–Meier curves showing the study endpoints in the plasma volume status (PVS) groups defined by two differential PVS classifications in functional mitral regurgitation (FMR) and degenerative mitral regurgitation (DMR) cohorts. (A) Kaplan–Meier curves showing cumulative all‐cause death in PVS stratified based on quartiles in the FMR cohort. (B) Kaplan–Meier curves showing cumulative cardiovascular death in PVS stratified based on quartiles in the FMR cohort. (C) Kaplan–Meier curves showing cumulative heart failure (HF) hospitalization in PVS stratified based on quartiles in the FMR cohort. (D) Kaplan–Meier curves showing cumulative all‐cause death in PVS stratified based on quartiles in the DMR cohort. (E) Kaplan–Meier curves showing cumulative cardiovascular death in PVS stratified based on quartiles in the DMR cohort. (F) Kaplan–Meier curves showing cumulative HF hospitalization in PVS stratified based on quartiles in the DMR cohort.

Independent associations of plasma volume status for predicting the clinical endpoints after mitral regurgitation undergoing transcatheter edge‐to‐edge mitral valve repair

The results of the Cox regression analysis are summarized in Figure 3 . The detailed information of the imputed clinical variables is provided in Data S1 . In the overall cohort, univariate Cox regression showed that all‐cause death (hazard ratio [HR], 1.04; 95% CI, 1.04–1.05; P < 0.001), cardiovascular death (HR, 1.04; 95% CI, 1.03–1.05; P < 0.001), and HF hospitalization (HR, 1.02; 95% CI, 1.02–1.03; P < 0.001) were significantly higher in patients with high PVS compared with that of those with low PVS. The multivariate model for all‐cause death in the overall cohort was adjusted for the following: age, sex, BSA, NYHA functional class III or IV, CFS ≥ 4, eGFR, albumin level, natrium level, BNP level > 200 pg/mL, atrial fibrillation (AF), coronary artery disease (CAD), prior stroke, peripheral vascular disease (PAD), liver cirrhosis (LC), FMR, left ventricular ejection fraction (LVEF), and pre‐tricuspid regurgitation (TR) grade 3 or 4. Compared with the low PVS group, the high PVS was independently associated with the increased risk of all‐cause death after M‐TEER (HR, 1.02; 95% CI, 1.01–1.02; P < 0.001). An independent association between a high PVS and all‐cause death was also found in the FMR and DMR sub‐groups. The multivariate model for cardiovascular death in the overall cohort was adjusted for the following: age, sex, BSA, NYHA functional class III or IV, CFS ≥ 4, eGFR, albumin level, natrium level, BNP level > 200 pg/mL, AF, prior stroke, PAD, LC, FMR, LVEF, and pre‐TR grade 3 or 4. The multivariate model for HF hospitalization in the overall cohort was adjusted for the following: age, sex, NYHA functional class III or IV, CFS ≥ 4, eGFR, albumin level, natrium level, BNP level > 200 pg/mL, AF, CAD, FMR, LVEF, and pre‐TR grade 3 or 4. The high PVS was significantly related to the increased risk of cardiovascular death (HR, 1.02; 95% CI, 1.01–1.03; P < 0.001) and HF hospitalization (HR, 1.02; 95% CI, 1.01–1.02; P < 0.001). These trends were similar when the patients were divided into the FMR and DMR cohorts.

Figure 3.

Results of multivariate Cox regression analysis in terms of all‐cause mortality, cardiovascular death, and heart failure (HF) hospitalization by overall, functional mitral regurgitation (FMR), and degenerative mitral regurgitation (DMR) cohorts.

Ability of plasma volume status for predicting clinical outcomes after mitral regurgitation undergoing transcatheter edge‐to‐edge mitral valve repair

Table 3 shows the results of the NRI and IDI analysis of the predictive model and the incremental value of adding the PVS to the basic component. NRI and IDI showed a significant increase in all‐cause mortality when PVS was combined with a clinical model consisting of age, sex, and other independent predictors of mortality (NRI, 0.320; 95% CI, 0.242–0.398; P < 0.001; IDI, 0.028; 95% CI, 0.022–0.034; P < 0.001). Furthermore, the predictive model consisting of the clinical model and PVS was superior to the model consisting of the clinical model and basic components, such as eGFR, natrium, and BNP levels, but the clinical model and albumin did not show significant differences.

Table 3.

Net reclassification improvement and integrated discrimination improvement for comparison among basic components

	NRI	95% CI	P value	IDI	95% CI	P value
Clinical model	Reference			Reference
Clinical model + PVS	0.320	0.242–0.398	<0.001	0.028	0.022–0.034	<0.001
Clinical model + eGFR	0.268	0.191–0.346	<0.001	0.012	0.008–0.016	<0.001
Clinical model + albumin	0.227	0.148–0.305	<0.001	0.020	0.015–0.025	<0.001
Clinical model + natrium	0.274	0.196–0.353	<0.001	0.015	0.010–0.020	<0.001
Clinical model + BNP > 200 pg/ml	0.205	0.138–0.272	<0.001	0.005	0.003–0.008	<0.001
Clinical model + eGFR	Reference			Reference
Clinical model + PVS	0.192	0.113–0.270	<0.001	0.016	0.010–0.023	<0.001
Clinical model + albumin	Reference			Reference
Clinical model + PVS	0.061	0.018–0.140	0.130	0.008	0.002–0.015	0.014
Clinical model + natrium	Reference			Reference
Clinical model + PVS	0.154	0.076–0.233	<0.001	0.013	0.006–0.021	0.001
Clinical model + BNP > 200 pg/mL	Reference			Reference
Clinical model + PVS	0.235	0.157–0.314	<0.001	0.023	0.017–0.029	<0.001
Clinical model + eGFR	Reference			Reference
Clinical model + eGFR + PVS	0.304	0.226–0.382	<0.001	0.023	0.018–0.029	<0.001
Clinical model + albumin	Reference			Reference
Clinical model + albumin + PVS	0.252	0.174–0.330	<0.001	0.015	0.011–0.020	<0.001
Clinical model + natrium	Reference			Reference
Clinical model + natrium + PVS	0.332	0.254–0.410	<0.001	0.026	0.020–0.032	<0.001
Clinical model + BNP > 200 pg/mL	Reference			Reference
Clinical model + BNP > 200 pg/ml + PVS	0.309	0.231–0.387	<0.001	0.026	0.021–0.032	<0.001

Clinical model: age, sex, body surface area, Clinical Frail Scale ≥4, New York Heart Association functional class III or IV, atrial fibrillation, coronary artery disease, prior stroke, peripheral vascular disease, liver cirrhosis, functional mitral regurgitation, left ventricle ejection fraction, pre tricuspid regurgitation grade 3 or 4.

BNP, B‐type natriuretic peptide; eGFR, estimated glomerular filtration rate; IDI, integrated discrimination improvement; NRI, net reclassification improvement; PVS, plasma volume status.

Clinical impact of subgroup analysis of mitral regurgitation reduction and preoperative medications in patients between high plasma volume status and low plasma volume status

The effects of residual MR after M‐TEER on all‐cause death are shown using Kaplan–Meier mortality curves in Figure 4 A . In the high PVS group, the mortality rate was significantly increased in the overall cohort for all‐cause mortality when MR remained equal or more than moderate. In patients with a low PVS, residual MR also significantly increased the risk of all‐cause death. In addition, the impact of preoperative medications on mortality after M‐TEER was analysed. Comparisons were made between two groups of patients those taking two or more of the following medications before M‐TEER and those taking one or none: ARBs, ACEIs, or ARNIs, beta‐blockers, MRAs, and SGLT2Is. There was no significant difference in all‐cause mortality between the two groups, whether in the high PVS or low PVS group (Figure 4B). Similar comparisons were made between the two groups of patients with and without preoperative use of loop diuretics, thiazide diuretics, MRAs, and tolvaptans, but there were no significant differences in all‐cause death regardless of high or low PVS (Figure 4 C ).

Figure 4.

Kaplan–Meier curves of all‐cause death showing in the plasma volume status (PVS) groups defined by two differential PVS classifications in clinical variables. (A) Kaplan–Meier curves showing cumulative all‐cause death in postprocedural residual mitral regurgitation (MR) ≥ +2 stratified based on quartiles in the high and low PVS cohort. (B) Kaplan–Meier curves showing cumulative all‐cause death in following preoperative number of medications. (C) Kaplan–Meier curves showing cumulative all‐cause death in preoperative diuretics stratified based on quartiles in the high and low PVS cohort.

Discussion

The results of this study demonstrated that the PVS value measured preoperatively stratified the risk of all‐cause death, cardiac death, non‐cardiac death, and HF hospitalization after TEER. In particular, PVS was found to be an independent risk factor, even after adjusting for considerable adjustment factors for all‐cause death, cardiovascular death, and HF hospitalization events. The mean values of PVS were 12.7 in FMR and 14.4 in DMR, with DMR showing significantly higher values than FMR. In particular, there were numerous differences in baseline patient background between the FMR and DMR groups. Patients with FMR are considered a high‐risk population for developing HF because of poor cardiac function, an enlarged left ventricle, and increased BNP levels. In contrast, patients with DMR were older and comprised a relatively frail subset in our cohort. However, the results of our study showed that consistent prognostic stratification in death and HF hospitalization was possible using PVS in both the FMR and DMR cohorts. Assessing PVS in patients scheduled to undergo M‐TEER may be useful for predicting the pathway of clinical progress.

Controlling circulating plasma volume is important for the treatment of HF; however, no simple method for assessing circulating plasma volume has yet been established. ¹⁰ , ¹¹ PVS is calculated using a conversion formula that assesses the patient's haematocrit value and BW and is differentiated between males and females. ¹² The median PVS in this study was also different in the DMR population, which is mainly older, and in the FMR population, which is relatively young but has a low LVEF with advanced‐stage HF. PVS is affected by differences in disease and population. In Western observational studies on HF, the median PVS was lower than that in our study. ¹³ , ¹⁵ This may be partly because the population that underwent M‐TEER was older with multiple comorbidities. In addition, because in the ideal PV, the denominator in the PVS formula is BW, it is possible that a small underweight Japanese population tends to have a higher PVS. ¹² Although the universal evaluation of PVS by absolute values is important, appropriate cut‐offs may need to be established in disease groups and patients for whom PVS is evaluated. Patients with higher PVS have poorer prognosis, and the fact that PVS proved to be an excellent marker for prognostic stratification in this special M‐TEER population is of clinical significance.

Serum albumin and natrium concentrations, fluid balance indicators, and nutritional status were independent prognostic factors for all‐cause and cardiovascular mortality in this study. The NRI and IDI analyses provided a better predictive ability of all‐cause death for PVS than previous traditional biomarkers. In addition, these indices were not significant predictors of HF rehospitalization, leaving only PVS as a marker for HF prediction. A sub‐analysis of the COAPT trial also revealed that serum albumin level was a predictor of all‐cause death, but not HF rehospitalization. ²³ In our study, which focused on the FMR cohort, the predictive ability of albumin level was largely consistent with the results of the CAOPT sub‐study. Moreover, the PVS was a useful indicator of HF hospitalization not only for FMR but also for DMR. BNP is also a useful marker for estimating cardiac events among patients with HF. ²⁴ , ²⁵ The presence of elevated BNP level was also associated with elevated all‐cause death and cardiac death in this study, but it was not a predictor of HF hospitalization after adjusting for factors, including PVS. PVS may be a more reliable predictor of all‐cause death and HF hospitalization than other markers that reflect fluid balance and nutritional status.

The most important point was to establish a method for the clinical application of PVS in patients undergoing M‐TEER. Patients who fail to achieve postoperative MR < 2+ have poor prognosis after M‐TEER, regardless of whether the PVS is high or low. Regarding residual MR, this study also showed that mild MR had a better prognosis than moderate MR residual. On the other hand, although medical therapies have been found to be effective in the treatment of HF with reduced LVFE, ²⁶ , ²⁷ these pre‐procedural medications had no significant effect on all‐cause death after M‐TEER, regardless of high or low PVS. A similar analysis was performed for diuretics, which are directly involved in controlling circulating volume, and there were no significant differences in all‐cause death after M‐TEER. These results were not changed when focused on the medical therapies at discharge (data not shown). Future studies are needed to determine how to treat PVS, a useful prognostic indicator, in terms of peri‐ or post‐procedural medical therapies.

Because MR reduction is a possible modifiable factor in M‐TEER, heart team members should concentrate on minimizing the residual MR. The situation may change in conjunction with device improvements and/or the introduction of new devices for M‐TEER. In addition, other options, such as a left ventricular assist device or heart transplantation, may be considered in cases where the expected mortality rate is significantly high or the effect of M‐TEER is expected to be limited. However, PVS may be clinically useful in making such decisions, as it is a sensitive predictor of cardiovascular death and HF hospitalization.

Limitations

This study has some limitations. First, the OCEAN‐Mitral registry comprises non‐randomized, real‐world, observational, and unblinded data from Japan. Therefore, selection bias is inevitable. Second, the results of this study are consistent with those of a single Japanese population. Reflecting the small BW in the Japanese cohort, the PVS value seemed to be relatively higher than that in the Western data. However, global competency remains unclear. Third, the echo evaluation was not performed by the central core laboratory. However, the facilities enrolled in the registry have sufficient experience, and documents with echo definitions, including guidelines, are shared in advance. Finally, clinical variables in the multivariate analysis were considered important, whereas the existence of other missing or uncaptured findings that were not included in this study could not be ruled out.

Conclusions

The PVS value measured preoperatively stratified the risk of all‐cause death, cardiac death, and HF hospitalization after M‐TEER. The current results also indicated that PVS might be superior to traditional parameters that predict clinical outcomes following M‐TEER. Importantly, patients who fail to achieve postoperative MR < 2+ have poor prognosis after M‐TEER, regardless of whether the PVS is high or low. Future studies are expected to examine how this indicator can be used in clinical practice.

Funding

The OCEAN‐Mitral registry is supported by Edwards Lifesciences, Medtronic, Boston Scientific, Abbott Medical, and Daiichi‐Sankyo Company.

Conflict of interest

Drs Yamamoto, Kagase, Kubo, Saji, Izumi, Asami, Izumo, Watanabe, Ohno, Hachinohe, Enta, Shirai, Mizuno, Boda, Kodama, Amaki, and Hayashida are clinical proctors of transcatheter edge‐to‐edge repair for Abbott Medical and have received lecture/consultant fees from Abbott Medical. Dr J. Yamaguchi is a clinical proctor of transcatheter edge‐to‐edge repair for Abbott Medical and has received a lecture fee and a scholarship donation from Abbott Medical. The remaining authors have no disclosures to report.

Supporting information

Data S1. Supplementary Information.

Kagase, A. , Yamamoto, M. , Tokuda, T. , Kawahata, R. , Nishio, H. , Shimura, T. , Yamaguchi, R. , Sago, M. , Izumi, Y. , Saji, M. , Asami, M. , Enta, Y. , Nakashima, M. , Shirai, S. , Izumo, M. , Mizuno, S. , Watanabe, Y. , Amaki, M. , Kodama, K. , Yamaguchi, J. , Naganuma, T. , Bouta, H. , Ohno, Y. , Yamawaki, M. , Ueno, H. , Mizutani, K. , Hachinohe, D. , Otsuka, T. , Kubo, S. , Hayashida, K. , and OCEAN‐Mitral Investigators (2025) Plasma volume status predicting clinical outcomes in patients undergoing transcatheter edge‐to‐edge mitral valve repair. ESC Heart Failure, 12: 2855–2865. 10.1002/ehf2.15295.