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01.12.2019 | Research | Ausgabe 1/2019 Open Access

Cardiovascular Ultrasound 1/2019

Comparison of the prognostic values of three calculation methods for echocardiographic relative wall thickness in acute decompensated heart failure

Zeitschrift:
Cardiovascular Ultrasound > Ausgabe 1/2019
Autoren:
Satoshi Yamaguchi, Michio Shimabukuro, Masami Abe, Tomohiro Arakaki, Osamu Arasaki, Shinichiro Ueda
Wichtige Hinweise

Supplementary information

Supplementary information accompanies this paper at https://​doi.​org/​10.​1186/​s12947-019-0179-6.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Introduction

A concentric left ventricular (LV) structure is the result of remodeling that occurs with LV wall thickening relative to the LV cavity to compensate for pressure overload [ 1, 2]. A concentric LV structure is a risk factor for cardiovascular events in hypertensive patients [ 3, 4]. Furthermore, we previously reported that a concentric LV structure evaluated by transthoracic echocardiography (TTE) was associated with poor survival in patients with acute decompensated heart failure (ADHF) [ 5].
Relative wall thickness (RWT) is an index of LV concentricity. RWT is the ratio of LV wall thickness to the LV internal dimension at end diastole (LVDd) [ 6]. LV wall thickness, which can be measured in a parasternal long-axis view by TTE, is represented by the Interventricular septum wall thickness (IVSth) and the posterior wall thickness (PWth) [ 6]. Therefore, there are three methods to calculate the RWT: RWT PW = 2 × PWth/LVDd; RWT IVS + PW = (IVSth + PWth) LVDd; and RWT IVS = 2 × IVSth/LVDd. The American Society of Echocardiography (ASE) recommends RWT PW for calculating RWT [ 6]. However, some studies found that RWT IVS + PW had clinical significance [ 7, 8]. The difference in clinical significance among the three methods of measuring RWT is unclear.
To compare the clinical significance of RWT PW, RWT IVS + PW, and RWT IVS, the prognostic values of the RWTs were examined and compared in patients with ADHF.

Materials and methods

Participants

This was a single-center, retrospective, observational study conducted at a Japanese community hospital. In total, 426 consecutive patients admitted due to ADHF through the clinic or emergency room were recruited between June 2014 and April 2016 and followed-up from June 2014 to September 2016. A total of 41 patients were excluded for any of the following reasons: no TTE on admission ( n = 35); and RWT not measured ( n = 6). Finally, 385 patients were eligible for the analysis (Fig.  1). We previously documented the enrolled patients in detail [ 5].
The present study followed the tenets of the Declaration of Helsinki and the Ethical Guidelines for Medical and Health Research Involving Human Subjects proposed by the Ministry of Health and Welfare in Japan. The institutional ethics committee at Tomishiro Central Hospital approved the present study and waived informed consent because of the observational nature of the study.

Transthoracic echocardiography

Comprehensive TTE (Vivid 7 ultrasound system, GE Vingmed Ultrasound, Horten, Norway) was performed during hospital admission by four medical technicians who had at least 5 years of experience performing TTE. Their measurements followed established and standardized methods recommended by the ASE and the European Society of Cardiology. At least two attending cardiologists certified by the Japanese Circulation Society and an experienced sonographer reviewed the echocardiography reports immediately after comprehensive TTE. LV geometry, including PWth, IVSth, and LVDd, was measured in M-mode in a parasternal long-axis view [ 6]. All measurements were performed from the leading edge to the leading edge [ 6]. RWTs were calculated by the three measurement methods and defined as follows: RWT PW = 2 × PWth/LVDd; RWT IVS + PW = (IVSth + PWth)/LVDd; and RWT IVS = 2 × IVSth/LVDd. The patients were divided into two groups based on the median RWT PW (low- and high-RWT PW), median RWT IVS + PW (low- and high-RWT IVS + PW), or median RWT IVS (low- and high-RWT IVS).
Left ventricular ejection fraction (LVEF) was assessed using the biplane Simpson’s method [ 6]. Heart failure with preserved ejection fraction (HFpEF) was defined as an ejection fraction ≥50% [ 9]. LV mass was computed by the Cube formula [ 6]. LV end-diastolic volume (LVEDVI) was estimated by the Teichholz equation [ 10]. Peak transmitral early diastolic wave (E wave) velocity, atrial contraction wave (A wave) velocity, and deceleration time (DCT) were measured by the pulse wave Doppler signals of the mitral inflow in the apical four-chamber view [ 11]. Valvular diseases were evaluated using a semiquantitative 4-grade scale (none, mild, moderate, and severe ) [ 12].

Data collection

Cardiologists followed the patients at Tomishiro Central Hospital Clinic every 1–3 months after hospital discharge. Medical clerks confirmed the patients’ condition if the patients canceled the appointment.
Patients’ medical charts were reviewed to collect their demographic characteristics and clinical data, including medications, laboratory tests, and hemodynamic data on hospital admission. The primary outcome was all-cause death. Death was confirmed by the medical chart, telephone call with a patient’s family, or obituary in local newspapers.

Statistical analysis

Continuous variables with normal and skewed distributions are presented as means (SD) and medians [25th, 75th percentiles], respectively. Categorical variables are presented as numbers with a percentage.
In two-group comparisons, Student’s t-test and the Mann-Whitney U test were used to compare normally distributed and non-normally distributed continuous variables, respectively. Fisher’s exact test was used for categorical variables.

Survival analysis

During follow-up (235 [92, 425] days), 95/385 (25%) patients died. Survival analysis for all-cause death was performed. Kaplan-Meier curves were stratified by RWT PW, RWT IVS + PW, and RWT IVS. The log-rank test was used to compare survival curves. High-RWT PW, high-RWT IVS + PW, and high-RWT IVS were examined by univariate Cox proportional hazard models and a Cox proportional hazard model adjusted by the Get With The Guideline score (GWTG) [ 13, 14], an established risk score for mortality in patients with acute heart failure, to obtain hazard ratios (HRs) and 95% confidence intervals (95% CIs).

Logistic regression model for 90-day mortality

A total of 48 patients who were lost to follow-up were excluded to evaluate the risk of 90-day mortality. Logistic regression models were used to obtain the odds ratios (ORs) of 90-day mortality and 95% CIs. High-RWT PW, high-RWT IVS + PW, and high-RWT IVS were examined in univariate logistic regression models and a logistic regression model adjusted by GWTG.

Receiver operating curves for 90-day mortality

Receiver operating curves for 90-day mortality were drawn using RWT PW, RWT IVS + PW, and RWT IVS to obtain c-statistics, and the best RWT cut-off values were determined by the maximum Youden index [ 15].

Sensitivity analysis of the survival analysis by stratified RWTs by the best cut-off

To confirm the consistency of the survival analysis, the participants were divided based on the best RWT cut-off value derived from the Youden index.
Survival analysis was performed to compare low and high-RWTs. High-RWT PW, high-RWT IVS + PW, and high-RWT IVS were also examined with univariate and adjusted proportional Cox hazard models.

Relationships between RWTs and clinical characteristics

Spearman’s correlation coefficient (ρ) was used to identify significant associations between RWTs and clinical characteristics: age, the natural logarithm of brain natriuretic peptide (logBNP), LVEF, LVEDV, and systolic blood pressure (SBP).

Reliability of measurement of PWth and IVSth

The reliabilities of the TTE measurements of PWth, IVSth, and LVDd were examined in 25 patients whose TTE image quality was good, and all of the patients underwent TTE performed by the same one of four medical technicians. The medical technician and two other examiners re-measured PWth and IVSth in the TTE image stored in the local server on hospital admission, using an off-line image analysis system (Nahri Aqua, Mehergen Group, Fukuoka, Japan). Comparing every two examiners’ measurements, Bland-Altman plots were used to assess the agreement between the measurement by the same examiner and different examiners [ 16]. The inter-class coefficient (ICC) was computed to assess agreement [ 17].
The reliabilities of RWT PW, RWT IVS + PW, and RWT IVS were also examined. RWTs were computed using PWth, IVSth, and LVDd measured by three examiners. Bland-Altman plots were drawn, and the ICC and P values were calculated.

Software

The statistical software used was R 3.4.3 (R Foundation for Statistical Computing, Vienna, Australia). All reported P values are two-tailed, and a P value < 0.05 was considered significant.

Results

Participants

The participants’ median age was 81 years, and there were 181/385 (47%) men in the overall population. Comparing low- and high-RWT PW, high-RWT PW had more elderly patients and more females, whereas in comparisons between low- and high-RWT IVS + PW and between low- and high-RWT IVS, there were no significant differences in baseline characteristics (Table  1).
Table 1
Demographic data and echocardiographic parameters
 
Overall
RWT PW b
RWT IVS + PW b
RWT IVS b
Low
High
P value
Low
High
P value
Low
High
P value
n = 385
n = 193
n = 192
n = 193
n = 192
n = 193
n = 192
Age, y
81 [70, 88]
80 [68, 87]
83 [73, 89]
0.021
80 [69, 87]
83 [73, 89]
0.067
80 [69, 87]
83 [73, 88]
0.082
Mele, n (%)
181/385 (47)
104/193 (54)
77/192 (40)
0.008
99/193 (51)
82/192 (43)
0.1
98/193 (51)
83/192 (43)
0.15
Height, cm
154 ± 10
156 ± 9.7
153 ± 9.9
0.002
155 ± 10
153 ± 10
0.048
155 ± 10
153 ± 10
0.15
Body weight., kg
60 ± 16
60 ± 15
60 ± 17
0.95
61 ± 15
59 ± 17
0.45
60 ± 16
59 ± 16
0.59
Body mass index, kg/m 2
22.8 ± 4.6
22.6 ± 4.5
23.0 ± 4.8
0.42
22.8 ± 4.6
22.8 ± 4.7
0.99
22.9 ± 4.7
22.8 ± 4.6
0.87
Body surface area, m 2
1.51 ± 0.22
1.53 ± 0.22
1.49 ± 0.23
0.11
1.53 ± 0.22
1.50 ± 0.23
0.2
1.52 ± 0.22
1.50 ± 0.22
0.3
Get With The Guideline score
38 ± 7
38 ± 6
38 ± 8
0.99
38 ± 7
38 ± 8
0.55
38 ± 7
38 ± 8
0.86
Hospital stay, days
13 [8, 20]
13 [8, 21]
12 [8, 19]
0.55
13 [8, 21]
12 [8, 19]
0.35
13 [8, 20]
12 [8, 19]
0.76
Past medical history, n (%)
 Hypertension
187/385 (49)
92/193 (48)
95/192 (50)
0.76
92/193 (48)
95/192 (50)
0.76
93/193 (48)
94/192 (49)
0.92
 Diabetes mellitus
132/385 (34)
68/193 (35)
64/192 (33)
0.75
75/193 (39)
57/192 (30)
0.068
80/193 (42)
52/192 (27)
0.004
 Chronic obstructive pulmonary disease
18/385 (4.7)
7/193 (3.6)
11/192 (5.7)
0.35
7/193 (3.6)
11/192 (5.7)
0.35
8/193 (4.1)
10/192 (5.2)
0.64
 Old myocardial infarction
62/385 (16)
37/193 (19)
25/192 (13)
0.13
35/193 (18)
27/192 (14)
0.33
34/193 (18)
28/192 (15)
0.49
Echocardiographic parameters
 RWT PW a
0.36 ± 0.12
0.28 ± 0.05
0.45 ± 0.12
<  0.001
0.28 ± 0.05
0.44 ± 0.12
<  0.001
0.30 ± 0.07
0.43 ± 0.13
<  0.001
 RWT IVS + PW a
0.37 ± 0.13
0.29 ± 0.06
0.45 ± 0.12
<  0.001
0.28 ± 0.05
0.46 ± 0.12
<  0.001
0.29 ± 0.06
0.46 ± 0.12
<  0.001
 RWT IVS a
0.38 ± 0.14
0.30 ± 0.09
0.46 ± 0.15
<  0.001
0.29 ± 0.06
0.48 ± 0.14
<  0.001
0.28 ± 0.06
0.48 ± 0.13
<  0.001
 IVSth, mm
9.4 ± 2.4
8.5 ± 2.0
10.4 ± 2.4
<  0.001
8.1 ± 1.8
10.7 ± 2.2
<  0.001
7.9 ± 1.5
11.0 ± 2.1
<  0.001
 PWth, mm
9.0 ± 2.1
7.8 ± 1.3
10.3 ± 2.0
<  0.001
8.1 ± 1.4
10 ± 2.2
<  0.001
8.3 ± 1.6
9.8 ± 2.3
<  0.001
 LVDd, mm
52 ± 9.7
57.1 ± 8.8
46.8 ± 7.8
<  0.001
57.7 ± 8.2
46.2 ± 7.6
<  0.001
57 ± 8.8
46.8 ± 7.8
<  0.001
 LVEF, (%)
47 ± 17
41 ± 16
51 ± 16
<  0.001
39 ± 16
52 ± 16
<  0.001
40 ± 16
51 ± 16
<  0.001
 HFpEF (LVEF ≥ 50%), n (%)
157/383 (41)
56/193 (29)
101/190 (53)
<  0.001
47/193 (24)
110/190 (58)
<  0.001
50/193 (26)
107/190 (56)
<  0.001
 LVM, g
168 [131, 211]
173 [135, 211]
164 [132, 208]
0.51
174 [138, 211]
164 [123, 208]
0.18
170 [135, 207]
166 [130, 212]
0.9
 LVEDV, mL
130 [92, 167]
160 [130, 194]
102 [79, 126]
<  0.001
160 [130, 194]
97 [74, 124]
<  0.001
160 [124, 194]
102 [79, 130]
<  0.001
 LVM/LVEDV
1.43 ± 0.56
1.10 ± 0.23
1.75 ± 0.61
<  0.001
1.08 ± 0.20
1.77 ± 0.59
<  0.001
1.09 ± 0.21
1.76 ± 0.6
<  0.001
 E wave, cm/sec
97 ± 29
97 ± 30
97 ± 28
0.94
95 ± 28
99 ± 29
0.37
98 ± 30
96 ± 28
0.58
 A wave, cm/sec
76 ± 32
70 ± 29
82 ± 34
0.011
73 ± 29
79 ± 34
0.13
74 ± 30
77 ± 33
0.57
 E/A
1.21 [0.84, 1.83]
1.29 [0.89, 2.04]
1.15 [0.82, 1.68]
0.18
1.21 [0.84, 1.84]
1.21 [0.86, 1.81]
0.81
1.22 [0.84, 1.83]
1.17 [0.85, 1.83]
0.6
 Deceleration time, ms
150 [123, 195]
150 [121, 196]
150 [128, 192]
0.49
149 [119, 185]
150 [129, 200]
0.043
147 [118, 181]
152 [129, 201]
0.013
 Aortic valve stenosis, n (%)
29/385 (7.5)
7/193 (3.6)
22/192 (12)
0.004
8/193 (4.1)
21/192 (11)
0.012
8/193 (4.1)
21/192 (11)
0.012
 Aortic valve regurgitation, n (%)
24/385 (6.2)
14/193 (7.3)
10/192 (5.2)
0.53
14/193 (7.3)
10/192 (5.2)
0.53
11/193 (5.7)
13/192 (6.8)
0.68
 Mitral valve regurgitation, n (%)
59/385 (15)
39/193 (20)
20/192 (10)
0.01
40/193 (21)
19/192 (9.9)
0.004
41/193 (21)
18/192 (9.4)
0.002
Laboratory data
 Blood urea nitrogen, mg/dL
24 [17, 35]
24 [17, 34]
24 [17, 36]
0.77
24 [17, 35]
24 [17, 35]
0.67
24 [17, 36]
23 [17, 35]
0.76
 Creatinine, mg/dL
1.14 [0.81, 1.52]
1.15 [0.83, 1.54]
1.09 [0.79, 1.51]
0.31
1.18 [0.83, 1.56]
1.09 [0.79, 1.50]
0.22
1.17 [0.83, 1.55]
1.07 [0.79, 1.50]
0.19
 Hemoglobin, g/dL
12.0 ± 2.4
12.0 ± 2.4
11.9 ± 2.4
0.84
11.9 ± 2.4
12.0 ± 2.4
0.78
11.9 ± 2.5
12 ± 2.3
0.68
 Brain natriuretic peptide, pg/mL
666 [427, 1266]
737 [449, 1376]
638 [403, 1155]
0.056
765 [472, 1376]
636 [401, 1092]
0.026
683 [437, 1349]
645 [413, 1190]
0.28
Medication, n (%)
 ACE-I and/or ARB
124/285 (32)
71/193 (37)
53/192 (28)
0.069
67/193 (35)
57/192 (30)
0.34
66/193 (34)
58/192 (30)
0.47
 Beta blocker
153/385 (40)
78/193 (40)
75/192 (39)
0.069
75/193 (39)
78/192 (41)
0.8
74/193 (38)
79/192 (41)
0.65
Hemodynamic data
 Systolic blood pressure, mmHg
132 ± 26
128 ± 24
135 ± 29
0.006
131 ± 24
133 ± 29
0.35
130 ± 24
134 ± 29
0.13
 Diastolic blood pressure, mmHg
78 ± 21
75 ± 19
73 ± 17
0.009
74 ± 18
77 ± 21
0.17
74 ± 18
77 ± 21
0.1
 Heart rate, bpm
84 ± 21
83 ± 21
84 ± 21
0.81
83 ± 19
84 ± 22
0.64
83 ± 19
83 ± 22
0.78
A wave, late mitral valve inflow velocity; ACE-I angiotensin converting enzyme inhibitor; ARB angiotensin receptor blocker; E wave, early mitral valve inflow velocity; IVSth interventricular septum thickness; LVEDV left ventricular end diastolic volume; LVDd left ventricular internal dimension at end-diastole; LVEF left ventricular ejection fraction;  LVM left ventricular mass; PWth posterior wall thickness; RWT relative wall thickness
aRWT was the ratio of left ventricular wall thickness to LVDd. Left ventricular wall thickness was measured at interventricular septum as IVSth and posterior wall as PWth. Three measurement methods to compute RWT were as follows; RWT PW = 2 × PWth/LVDd, RWT IVS + PW = (PWth + IVSth)/LVDd, and RWT IVS = 2 × IVSth/LVDd
bThe patients were divided into two groups based on the median of RWT PW, RWT IVS + PW, and RWT IVS

Transthoracic echocardiography

The mean RWT PW, RWT IVS + PW, and RWT IVS values in the overall population were 0.36 ± 0.12, 0.37 ± 0.13, and 0.38 ± 0.14, respectively.
On comparing the three RWTs (low- vs. high- RWT PW, RWT IVS + PW, RWT IVS), high-RWTs had thicker IVSth and PWth, smaller LVDd, greater LVEF, smaller LV end-diastolic volume, high LVM/LVEDV, and less severe mitral regurgitation than low-RWTs (Table 1).

Survival analysis

During follow-up (235 [92, 425] days), 95/385 (25%) patients died in the overall population.
Comparing low- and high-RWT PW, there was a significant difference in the incidence of all-cause death (low 36/193 (19%) vs. high-RWT PW 59/192 (31%), P = 0.007). Kaplan-Meier curves showed that high-RWT PW had worse survival than low-RWT PW ( P for log-rank test = 0.009; Fig.  2a).
Comparing low- and high-RWT IVS + PW, there was no significant difference in all-cause death (low 40/193 (21%) vs. high-RWT PW 55/192 (29%), P = 0.077) or survival ( P for log-rank test = 0.074; Fig. 2b).
In a comparison between low- and high-RWT IVS, there was no significant difference in all-cause death (low 42/193 (22%) vs. high-RWT IVS 53/192 (28%), P incidence = 0.2) or survival ( P for log-rank test = 0.19; Fig. 2c).

Cox proportional hazard models for all-cause death

In the unadjusted and adjusted Cox proportional hazard models, high-RWT PW was a significant risk factor for all-cause death (unadjusted Cox model, HR (95% CI), 1.72 (1.41–2.61), P = 0.01; adjusted Cox model, 1.95 (1.28–2.98), P = 0.02; Table  2).
Table 2
Cox proportional hazard model for evaluate the risk of RWTs for all-cause mortality
Calculate method and factor
Unadjusted
Adjusted by GWTG
Event/cases
HR
95% CI
P value
Event/cases a
HR
95% CI
P value
High- to low-RWT PW
95/385
1.72
1.14
2.61
0.01
93/380
1.95
1.28
2.98
0.002
High- to low-RWT IVS + PW
95/385
1.45
0.96
2.17
0.075
93/380
1.53
1.01
2.32
0.045
High- to low-RWT IVS
95/385
1.31
0.87
1.96
0.19
93/380
1.36
0.9
2.06
0.14
CI confidence interval; GWTG Get With The Guideline score; HR hazard ratio; RWT relative wall thickness
a5 cases were removed because of GWTG missing
High-RWT IVS + PW was not a significant risk factor for all-cause death in the unadjusted Cox proportional model (unadjusted Cox model, HR, 1.45 (0.96–2.17), P = 0.075), but it was in the adjusted Cox proportional hazard model (adjusted Cox model, 1.53 (1.01–2.32), P = 0.045; Table  2).
High-RWT IVS was not a significant factor in either the unadjusted or the adjusted Cox proportional hazard model (Table  2).

Logistic regression models for 90-day mortality

The OR of high- to low-RWT PW was significant (univariate, OR, 2.19, 95%CI, 1.15–2.19, P = 0.017; adjusted, OR, 2.26, 95%CI, 1.16–4.4, P = 0.017) on univariate analysis and the adjusted logistic regression model (Table  3). In contrast, the OR of neither high to low-RWT IVS + PW nor RWT IVS was significant on univariate analysis or the adjusted logistic regression models.
Table 3
Logistic models for evaluating the risk of 90 days mortality
Calculate method and factor
Unadjusted
Adjusted by GWTG
Event/cases
OR
95% CI
P value
Event/cases
OR
95% CI
P value
High- to low-RWT PW
48/337
2.19
1.15
2.19
0.017
48/337
2.26
1.16
4.4
0.017
High- to low-RWT IVS + PW
48/337
1.26
0.68
1.26
0.46
48/337
1.19
0.63
2.25
0.6
High- to low-RWT IVS
48/337
0.86
0.47
0.86
0.64
48/337
0.8
0.42
1.52
0.5
CI confidence interval; GWTG Get With The Guideline score, OR odds ratio; RWT relative wall thickness

Receiver operating curves for 90-day mortality

A total of 48 (13%) patients died within 90 days from hospital admission. Figure  3 shows the receiver operating characteristic (ROC) curves for 90-day mortality using the RWTs. The c-statistic of the ROC curve using RWT PW was 62.6%, and the best cut-off value was 0.35. The c-statistic of the ROC curve using RWT IVS + PW was 59.7%, and the best cut-off value was 0.55. The c-statistic of the ROC curve using RWT IVS was 43.1%, and the best cut-off value was 0.36.

Sensitivity analysis of the survival analysis by stratified RWTs by the best cut-off

Additional file 1: Table S1 shows the demographic data and echocardiographic data with stratification by the best RWT cut-off. High-RWT PW had worse survival than low-RWT PW ( P for log-rank test = 0.03; Additional file  2: Figure S1a). High-RWT IVS + PW also had a worse prognosis than low-RWT IVS + PW ( P for log-rank test < 0.001; Additional file 2: Figure S1b). In contrast, there was no significant difference in survival between low- and high-RWT IVS ( P for log-rank test = 0.077; Additional file 2: Figure S1c).
In the unadjusted and adjusted Cox proportional hazard models, high-RWT PW and high-RWT IVS + PW were associated with mortality (high-RWT PW, unadjusted Cox model, HR (95% CI), 1.55 (1.04–2.33), P = 0.033; adjusted Cox model, 1.72 (1.14–2.59), P = 0.01; high-RWT IVS + PW, unadjusted Cox model, HR (95% CI), 3.88 (2.34–6.43), P <  0.001; adjusted Cox model, 3.42 (2.04–5.72), P <  0.001; Additional file  3: Table S2). High-RWT IVS was not a significant risk factor in the unadjusted and adjusted Cox proportional hazard models.

Relationship between RWTs and clinical characteristics

There were significant positive correlations between the three RWTs and age and LVEF, and negative correlations between the RWTs and LogBNP and LVEDV (Table  4). RWT IVS + PW and RWTI VS did not have significant correlations with systolic blood pressure, but RWT PW did (ρ = 0.15, P = 0.004).
Table 4
Relationship between RWTs and clinical characteristics
 
RWT PW
RWT IVS + PW
RWT IVS
ρ
P value
ρ
P value
ρ
P value
Age, y
0.15
0.003
0.17
0.003
0.17
0.001
LogBNP, log (pg/mL)
−0.2
<  0.001
−0.15
0.003
−0.11
0.039
LVEF, %
0.42
<  0.001
0.47
<  0.001
0.43
<  0.001
LVEDV, mL
−0.67
<  0.001
−0.74
<  0.001
− 0.69
<  0.001
Systolic blood pressure, mmHg
0.15
0.004
0.094
0.065
0.063
0.22
LogBNP logarithmed brain natriuretic peptide; LVEDV left ventricular end-diastolic volume; LVEF left ventricular ejection fraction; ρ, Spearman’s correlation coefficient

Reliability of TTE measurement of PWth, IVSth, and LVDd

Intra-observer agreement of TTE measurement of PWth was significant (ICC = 0.73, P <  0.001; Fig.  4a). Inter-observer agreements of TTE measurement of PWth were also significant (observer 1 vs. 2, ICC = 0.76, P <  0.001; observer 1 vs. 3, ICC = 0.6, P <  0.001; observer 2 vs. 3, ICC = 0.7, P <  0.001; Fig.  3a). There were no systematic biases in the intra- and inter-observer agreements in PWth measurement (Fig. 4a).
Intra-observer agreement of TTE measurement of IVSth was significant (ICC = 0.88, P <  0.001; Fig. 4b). Inter-observer agreements of TTE measurement of IVSth were also significant (observer 1 vs. 2, ICC = 0.81, P <  0.001; observer 1 vs. 3, ICC = 0.77, P <  0.001; observer 2 vs. 3, ICC = 0.73, P <  0.001; Fig. 4b). There were no systematic biases in the intra- and inter-observer agreements in IVSth measurement (Fig. 4b).
Intra-observer agreement of TTE measurement of LVDd was significant (ICC = 0.94, P <  0.001; Fig. 4c). Inter-observer agreements of TTE measurement of LVDd were also significant (observer 1 vs. 2, ICC = 0.71, P <  0.001; observer 1 vs. 3, ICC = 0.92, P <  0.001; observer 2 vs. 3, ICC = 0.65, P <  0.001; Fig. 4c). There were no systematic biases in the intra- and inter-observer agreements in LVDd measurement (Fig. 4c).

Reliability of RWTs obtained from TTE measurement

Intra-observer agreement of RWT PW was significant (ICC = 0.77, P <  0.001; Fig.  5a). Inter-observer agreements of RWT PW were significant (observer 1 vs. 2, ICC = 0.74, P <  0.001; observer 1 vs. 3, ICC = 0.63, P <  0.001; observer 2 vs. 3, ICC = 0.8, P <  0.001). There were no systematic biases in the intra- and inter-observer agreements in RWT PW.
Intra-observer agreement of RWT IVS + PW was significant (ICC = 0.89, P <  0.001; Fig. 5b). Inter-observer agreements of RWT PW were also significant (observer 1 vs. 2, ICC = 0.82, P <  0.001; observer 1 vs. 3, ICC = 0.74, P <  0.001; observer 2 vs. 3, ICC = 0.83, P <  0.001). There were no systematic biases in the intra- and inter-observer agreements in RWT IVS + PW.
Intra-observer agreement of RWT IVS was significant (ICC = 0.84, P <  0.001; Fig. 5c). Inter-observer agreements of RWT IVS were also significant (observer 1 vs. 2, ICC = 0.77, P <  0.001; observer 1 vs. 3, ICC = 0.75, P <  0.001; observer 2 vs. 3, ICC = 0.72, P <  0.001). There were no systematic biases in the intra- and inter-observer agreements in RWT IVS.

Discussion

To the best of our knowledge, this is the first study to show the difference in the clinical significance of the three RWTs. The present study demonstrated that, compared to RWT IVS + PW and RWT IVS, RWT PW is the best to stratify the risk for all-cause death in ADHF patients. This may be consistently supported by three findings. First, high-RWT PW had a significantly worse prognosis than low-RWT PW. In contrast, on survival analysis, there was no significant difference between high- and low-RWT IVS + PW or RWT IVS. Second, in the logistic regression model for 90-day mortality, only high-RWT PW was significant among the three RWTs (Table  3). Third, ROC for 90-day all-cause death using RWT PW had the highest c-statistic among the three ROCs.

Explanations of the differences in the prognostic values among the three RWTs

High-RWT PW was associated with a poor prognosis on survival analysis and Cox proportional hazard models (Fig. 2a; Table  2). High-RWT IVS + PW was not associated with poor survival on survival analysis (Fig. 1b), whereas high-RWT IVS + PW was a significant risk only in the Cox proportional hazard model adjusted by GWTG, not in the unadjusted model (Table  2). High-RWT IVS did not show worse survival than low-RWT IVS (Fig. 1c; Table 2). The equations of RWT PW and RWT IVS + PW contain PWth. PWth or the ratio of PWth to LVDd, therefore, may represent the LV remodeling related to a worse prognosis better than IVSth or IVSth to LVDd in patients with ADHF. Patients with high-RWT PW had higher systolic blood pressure than those with low-RWT PW (Table 1), while there was no such difference either between low- and high-RWT IVS + PW or between low- and high-RWT IVS. RWT PW had a positive correlation with systolic blood pressure (Table  4), while either RWT IVS + PW or RWT IVS did not. This may suggest that thickening of PWth, rather than IVSth, is likely to counterbalance pressure overload and may lead to LV diastolic dysfunction leading to a poor prognosis. A higher A wave in high RWT pw patients than in low RWT pw patients may support this assumption (Table 1).
In terms of methodological validity, there were no differences in inter- and intra-observer agreements for each RWT. Given that fairly good reproducibility was observed in all measurements, differences in prognostic values among the three RWTs may not result from technical aspects of TTE.
Paradoxically, high-RWT PW patients had lower BNP than low-RWT PW patients (Table 1). High-RWT PW included 101 (53%) patients with HFpEF. Generally, BNP increases modestly in HFpEF [ 18]. Furthermore, the prognostic value of BNP has not been confirmed in patients with HFpEF [ 19]. High RWT PW might be of clinically utility, especially, in patients with HFpEF.

Limitations

The present study had several limitations. The present study did not have pressure data such as LV end-diastolic pressure or pulmonary artery wedge pressure. LV wall thickness was not evaluated by other modalities, such as magnetic resonance imaging or computed tomography. Patients having valvular diseases with various etiologies were included, which might affect the prognostic value of RWTs.
In conclusion, high-RWT PW had a higher systolic pressure and A wave than low-RWT PW. This finding was not observed in the comparison between low- and high-RWT IVS + PW or between low-and high-RWT IVS. PWth may represent pressure overload better than IVSth. When calculating RWT, RWT PW should be recommended for evaluating the mortality risk in ADHF.

Supplementary information

Supplementary information accompanies this paper at https://​doi.​org/​10.​1186/​s12947-019-0179-6.

Acknowledgements

The authors are grateful to Yoji Takami, Shimon Toma, Chio Iseki, and Kunitoshi Iseki for assistance with data collection and management.
The authors also appreciate the dedicated work of the sonographers, Masako Noborikawa, Naoko Sakugawa, Kazue Kudaka, and Yayoi Taira.
The authors would also like to thank Masanori Kakazu, Masahiro Tamashiro, Toshiya Chinen, Akihiko Yamauchi, Masaki Tabuchi, Hideki Takayasu, and Hideki Sonoi for heart failure patient enrollment and clinical data capture.
Finally, the authors would like to thank Yumi Ikehara and Sachiko Nakaima for manuscript assistance.

Ethics approval and consent to participate

The institutional ethics committee at Tomishiro Central Hospital approved the present study and waived informed consent because of the observational nature of the study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.

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