Association of Valve Size and Hemodynamic Performance With Clinical Outcomes in Aortic Valve Replacement　― A Long-Term Follow-up in an Asian Population ―

Yi Yen; Kuo-Chun Hung; Yi-Hsin Chan; Victor Chien-Chia Wu; Yu-Ting Cheng; Chia-Pin Lin; Jih-Kai Yeh; Pao-Hsien Chu; Shao-Wei Chen

doi:10.1253/circj.CJ-22-0718

Abstract

Background: Studies of the influence of smaller body type on the severity of prosthesis-patient mismatch (PPM) after small-sized surgical aortic valve replacement (SAVR) are few, but the issue is particularly relevant for Asian patients.

Methods and Results: 695 patients who underwent SAVR with bioprosthetic valves had their hemodynamic valve performance analyzed at 3 months, 1 year, 3 years, and 5 years after operation, and clinical outcomes were assessed. The patients were stratified into 3 valve size groups: 19/21, 23, and 25/27 mm. A smaller valve was associated with higher mean pressure gradients at the 4 time points after operation (P trend <0.05). However, the 3 valve size groups demonstrated no significant differences in the risk of clinical events. At none of the time points did patients with projected PPM show increased mean pressure gradients (P>0.05), whereas patients with measured PPM did (P<0.05). Compared with patients with projected PPM, those with measured PPM demonstrated higher rates of infective endocarditis readmission (adjusted hazard ratio [aHR] 3.31, 95% confidence interval [CI] 1.06–10.39) and a higher risk of composite outcomes (aHR 1.45, 95% CI 0.95–2.22, P=0.087).

Conclusions: Relative to those receiving larger valves, patients receiving small bioprosthetic valves had poorer hemodynamic performance but did not demonstrate differences in clinical events in long-term follow-up.

Aortic valve stenosis (AS) is the most common valve disease,¹ with a prevalence of 2% among populations older than 65 years.² The guidelines of the American College of Cardiology and the American Heart Association³ recommend aortic valve replacement (AVR) for severe cases of AS. Surgical AVR (SAVR), especially stented tissue valve replacement, is a common treatment for AS, and SAVR is the only treatment for aortic regurgitation. Bovine pericardial valve replacement is generally superior to porcine valve replacement because bovine pericardial valve is associated with a lower pressure gradient (PG), larger indexed effective orifice area (EOAi), fewer cases of prosthesis-patient mismatch (PPM), and a lower complication rate.⁴^,⁵ Furthermore, studies have demonstrated that transcatheter AVR (TAVR) may be more advantageous because is less invasive and can achieve more favorable hemodynamic performance after replacement.⁶^,⁷ However, long-term follow-up data for TAVR are lacking, and it is therefore generally not recommended for young patients.⁸^,⁹

PPM can be defined as a lower EOAi after AVR and is believed to cause an elevated PG and poorer prognoses, such as an increased risk of valve degeneration, readmission, and death.¹⁰^–¹⁴ EOAi is calculated using the Dubois formula, in which the EOA is divided by the body surface area (BSA).¹⁵ According to the European Association of Cardiovascular Imaging, 0.85 ≥ EOAi > 0.65 cm²/m² is classified as moderate PPM, and EOAi ≤0.65 cm²/m² is classified as severe PPM.¹⁶ EOAi charts have been developed to predict PPM before an operation, but whether the predicted PPM supports the echocardiographic findings or matches clinical outcomes remains unclear,¹⁷^,¹⁸ and long-term follow-up studies investigating the topic are lacking. In addition, the associations among PPMs, hemodynamic performance, and clinical outcome after small-sized AVR (i.e., 19 or 21 mm) remain unclear. Because small valves are generally used in patients with smaller body types, this topic is especially relevant to Asian populations.¹⁹

For SAVR, few studies have reported on the direct correlations among projected PPM from EOAi charts, echocardiogram-measured PPM after surgery, hemodynamic performance, and long-term clinical outcomes. In addition, studies of the influence of the smaller body type of Asian patients on the severity of PPM and postoperative performance after small-size valve implantation are few. In this study, we analyzed a large Asian cohort with long-term follow-up hemodynamic and clinical outcome data after SAVR to validate the roles of PPMs and valve size.

Methods

Data Source

For this retrospective cohort study, data were retrieved from the Chang Gung Research Database (CGRD), which mainly contains data on Taiwanese patients. The CGRD includes de-identified medical records from the Chang Gung Memorial Hospital system, which has 21.2% outpatient and 12.4% inpatient nationwide coverage.²⁰ The database contains data on medications, vital signs, laboratory tests, operation notes, and discharge notes. Further details on the CGRD have been provided in previous reports.²⁰^,²¹ Before 2015, diseases were classified using the “International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM)” diagnostic codes, and after 2016, both the ICD-9-CM and ICD-10-CM were used. The requirement for written informed consent was waived because of the de-identification of the data in the database. This study was approved by the Chang Gung Medical Foundation Institutional Review Board on April 22, 2019 (IRB No. 201900585B0).

Study Patients

Patients who had undergone AVR with bioprosthetic valves between January 1, 2001, and December 31, 2018, were identified in the CGRD. If the patient had undergone ≥2 AVR surgeries during the study period, the first AVR was selected as the index surgery. Use of AVR with bioprosthetic valves was verified by reviewing the operation notes. Patients who died during admission, were <20 years old, did not undergo echocardiography after surgery, or did not have information available on valve size, etiology, and brand were excluded. Use of AVR and the details of the surgery and echocardiography were verified by the 2 principal investigators (Y.Y. and S.-W.C.).

Variables of Interest

This study had 2 variables of primary interest: the valve size and PPM. The valve size information was extracted from the operation notes by the 2 principal investigators. Patients were stratified into 3 groups according to valve size: small (19 and 21 mm), medium (23 mm), and large (25 and 27 mm).²² PPM was defined based on the projected EOAi and the postoperative measured EOAi. The projected EOAi was calculated using EOAi charts, and the measured EOAi was calculated using the postoperative echocardiograms. The severity of PPM was graded using the criteria of the European Association of Cardiovascular Imaging.¹⁶ The patients were stratified into 3 groups (no PPM, moderate PPM, and severe PPM) and 2 groups (no PPM and PPM).

Outcomes

Two outcomes were investigated: echocardiographic reports and clinical events during follow-up. The echocardiographic reports included left ventricular ejection fraction, maximum aortic velocity, mean PG, and maximum PG. The echocardiographic information was extracted at 3 months, 1 year, 3 years, and 5 years after the index surgery. The mean PG was of particular interest. The clinical events were all-cause death, redo AVR, all-cause readmission, infective endocarditis (IE) requiring hospitalization, heart failure (HF) readmission, and the composite of these events (with the exception of all-cause readmission). The occurrence of redo AVR was verified using the operation notes. The other clinical events were identified from the inpatient claims data in the CGRD. For the analysis of clinical events, the patients were followed up from discharge after the index surgery to the date of outcome occurrence, the date of death or December 31, 2018, whichever occurred first.

Covariates

The covariates were demographics (sex, age, height, weight, body mass index, BSA, and smoking habit), valvular diseases, comorbidities, history of clinical events, medications at baseline, preoperative laboratory data, etiology of valve surgery, concomitant surgeries, and operation time. Data regarding the valvular diseases, etiology of valve surgery, concomitant surgeries, and operation time were extracted from the operation notes. Comorbidity was defined as having at ≥2 outpatient diagnoses or any inpatient diagnosis prior to the index AVR surgery. Historical events were defined as having a record of hospitalization prior to the index AVR surgery. The medications at baseline and preoperative laboratory data were also available in the CGRD.

Statistical Analysis

The characteristics of the patients with different valve sizes (19/21 vs. 23 vs. 25/27) were compared using independent sample t tests for continuous variables and chi-square tests for categorical variables. The pairwise comparison was performed using the Bonferroni adjustment. The trend of the mean PG across the ordinal groups of valve size (19/21 vs. 23 vs. 25/27) and PPM (no PPM vs. moderate vs. severe) was tested using a linear contrast in a general linear model. The mean PG of the patients with and without PPM was compared using an independent sample t test. The associations between valve size, PPM status, and the risk of clinical events were analyzed using a Cox proportional hazards model. In the Cox models, the following potential confounding factors were adjusted for: age, sex, and BSA and presence of diabetes, hypertension, coronary artery disease, atrial fibrillation, chronic obstructive pulmonary disease, chronic kidney disease, and previous HF hospitalization. A two-sided P value <0.05 was considered significant. All analyses were conducted using SAS 9.4 (SAS Institute, Cary, NC, USA).

Results

Patients’ Characteristics

All patients included in the CGRD who had undergone bioprosthetic valve AVR surgery between January 1, 2001, and December 31, 2018, were identified. After the exclusion criteria were applied, 695 patients were included for analysis (Figure 1). Their baseline characteristics, stratified by valve size, are listed in Supplementary Table 1, and the surgical characteristics and preoperative echocardiography characteristics stratified by valve size are presented in Supplementary Table 2. The mean age of the patients was 66.8±12.6 years, and 61% (424) of them were male. The patients with larger valve sizes were generally younger, male, had bigger body size, less aortic stenosis, more aortic regurgitation, less prevalence of diabetes and hyperlipidemia, and had a higher prevalence of gout, intracranial hemorrhage, or major bleeding. The follow-up duration was comparable among the 3 groups (Supplementary Table 1). Patients with larger valve sizes had a higher prevalence of aortic aneurysm or dissection, lower prevalence of degeneration, longer operation times, and lower preoperative maximum aortic velocity. The mean preoperative PGs were comparable among the 3 groups (Supplementary Table 2).

Figure 1.

Patient inclusion and exclusion flowchart. AVR, aortic valve replacement.

Echocardiographic Results

Mean PGs were recorded in 186, 129, 170, and 122 patients at 3-month, 1-year, 3-year, and 5-year postoperative echocardiographic follow-up, respectively. Among the 3 groups stratified by valve size (19/21, 23, and 25/27), a trend of smaller valve size when mean PGs were higher after surgery was observed for every time point of the echocardiographic records. As detailed in Supplementary Table 3 and Figure 2A, the P trends were <0.001, 0.006, >0.001, and 0.019 at 3 months, 1 year, 3 years, and 5 years after operation, respectively.

Figure 2.

Mean pressure gradients at 3 months, 1 year, 3 years, and 5 years after surgery (Post-OP) in patients with (A) different replaced valve sizes, and (B) binary groups of projected indexed effective orifice area.

The hemodynamic performance results after operation, grouped according to projected EOAi and measured EOAi, are presented in Supplementary Table 4. When PPM was calculated using the projected EOAi, the hemodynamic performance of the patients with PPM did not differ from the results for those without PPM for any of the recorded periods, as illustrated in Figure 2B (P values were 0.088, 0.972, 0.299, and 0.646 at 3 months, 1 year, 3 years, and 5 years after operation, respectively). However, when hemodynamic performance was calculated using the measured EOAi, patients with PPM had considerably higher mean PGs than patients without PPM did for every time period, as presented in Supplementary Figure 1A (P values were <0.001, 0.001, 0.033, and 0.025 at 3 months, 1 year, 3 years, and 5 years after operation, respectively). As indicated in Supplementary Figure 1B, a trend of more severe PPM occurring when the mean PG after surgery was higher was noted at 3 months, 1 year, 3 years, and 5 years after surgery, with P values of <0.001, 0.002, 0.036, and 0.106, respectively. An association between measured PPM and an increase in PG was noted; however, the trend weakened over time. In addition, the relationship between measured and projected iEOA was low (r=0.31) (Supplementary Figure 2).

Clinical Events

Data for the clinical events in each valve size group are presented in Table 1, with the data revealing no significant differences in the risk of all clinical events among the 19/21, 23, and 25/27 groups when adjusted for covariates.

Table 1. Clinical Events During Follow-up According to Different Aortic Valve Sizes

Outcome/aortic valve size	No. of events (%)	Univariate analysis		Multivariable analysis
Outcome/aortic valve size	No. of events (%)	Crude HR (95% CI)	P value	Adjusted HR (95% CI)*	P value
All-cause death
19 mm/21 mm	48 (15.4)	Ref.		Ref.
23 mm	34 (14.3)	0.92 (0.59–1.43)	0.704	1.02 (0.62–1.68)	0.929
25 mm/27 mm	11 (7.6)	0.47 (0.24–0.90)	0.024	0.61 (0.30–1.26)	0.182
Redo AVR
19 mm/21 mm	11 (3.5)	Ref.		Ref.
23 mm	11 (4.6)	1.23 (0.53–2.84)	0.627	1.17 (0.45–3.07)	0.744
25 mm/27 mm	4 (2.8)	0.75 (0.24–2.37)	0.625	0.37 (0.10–1.42)	0.146
All-cause readmission
19 mm/21 mm	177 (56.7)	Ref.		Ref.
23 mm	151 (63.4)	1.19 (0.95–1.48)	0.123	1.14 (0.89–1.45)	0.294
25 mm/27 mm	85 (58.6)	0.99 (0.76–1.28)	0.936	0.99 (0.73–1.33)	0.941
IE hospitalization
19 mm/21 mm	17 (5.4)	Ref.		Ref.
23 mm	13 (5.5)	0.97 (0.47–2.01)	0.943	0.73 (0.33–1.59)	0.422
25 mm/27 mm	7 (4.8)	0.84 (0.35–2.03)	0.704	0.47 (0.17–1.29)	0.141
HF readmission
19 mm/21 mm	62 (19.9)	Ref.		Ref.
23 mm	56 (23.5)	1.21 (0.84–1.74)	0.299	1.35 (0.90–2.02)	0.152
25 mm/27 mm	28 (19.3)	0.89 (0.57–1.39)	0.606	1.14 (0.68–1.90)	0.623
Composite outcome^†
19 mm/21 mm	98 (31.4)	Ref.		Ref.
23 mm	83 (34.9)	1.13 (0.84–1.51)	0.415	1.14 (0.82–1.59)	0.422
25 mm/27 mm	40 (27.6)	0.82 (0.56–1.18)	0.278	0.87 (0.57–1.33)	0.525

*Adjusted for age, sex, body surface area, diabetes, hypertension, coronary artery disease, atrial fibrillation, COPD, chronic kidney disease, and previous HF hospitalization. ^†Included all-cause death, redo AVR, IE hospitalization and HF readmission. AVR, aortic valve replacement; CI, confidence interval; COPD, chronic obstructive pulmonary disease; HF, heart failure; HR, hazard ratio; IE, infective endocarditis.

Table 2 details the comparison of clinical events in patients with different grades of PPM calculated from the measured EOAi and projected EOAi separately. When the projected PPM was used for calculation, no significant difference was observed between patient with PPM and those without for all-cause death, redo AVR, all-cause readmission, IE readmission, HF readmission, and the composite outcome. However, compared with patients with no measured PPM, those with measured PPM exhibited a significantly higher risk of IE readmission (adjusted hazard ratio [aHR] 3.31, 95% confidence interval [CI] 1.06–10.39), and they also exhibited a trend of higher risk in the composite outcome (aHR 1.45, 95% CI 0.95–2.22, P=0.087).

Table 2. Clinical Events During Follow-up According to iEOA’s PPM Status

Outcome/EOA/PPM status	No. of events (%)	Univariate analysis		Multivariable analysis
Outcome/EOA/PPM status	No. of events (%)	Crude HR (95% CI)	P value	Adjusted HR (95% CI)*	P value
All-cause death
Projected iEOA
No PPM	65 (13.0)	Ref.		Ref.
Moderate/severe PPM	24 (16.0)	1.13 (0.70–1.80)	0.619	1.15 (0.66–1.99)	0.623
Measured iEOA
No PPM	16 (9.6)	Ref.		Ref.
Moderate PPM	15 (17.0)	1.44 (0.71–2.92)	0.313	1.20 (0.57–2.50)	0.632
Severe PPM	10 (14.3)	1.24 (0.56–2.74)	0.593	1.23 (0.53–2.86)	0.636
Measured iEOA
No PPM	16 (9.6)	Ref.		Ref.
Moderate/severe PPM	25 (15.8)	1.35 (0.72–2.54)	0.348	1.21 (0.62–2.35)	0.577
Redo AVR
Projected iEOA
No PPM	19 (3.8)	Ref.		Ref.
Moderate/severe PPM	6 (4.0)	0.95 (0.38–2.38)	0.913	0.62 (0.21–1.82)	0.385
Measured iEOA
No PPM	5 (3.0)	Ref.		Ref.
Moderate PPM	4 (4.5)	1.10 (0.29–4.13)	0.888	1.18 (0.28–4.97)	0.824
Severe PPM	3 (4.3)	1.24 (0.30–5.21)	0.766	2.08 (0.37–11.72)	0.408
Measured iEOA
No PPM	5 (3.0)	Ref.		Ref.
Moderate/severe PPM	7 (4.4)	1.16 (0.37–3.66)	0.804	1.40 (0.39–5.09)	0.605
All-cause readmission
Projected iEOA
No PPM	297 (59.4)	Ref.		Ref.
Moderate/severe PPM	100 (66.7)	1.10 (0.88–1.38)	0.402	1.01 (0.78–1.31)	0.944
Measured iEOA
No PPM	86 (51.8)	Ref.		Ref.
Moderate PPM	56 (63.6)	1.21 (0.86–1.70)	0.266	1.13 (0.80–1.61)	0.481
Severe PPM	50 (71.4)	1.68 (1.18–2.38)	0.004	1.53 (1.05–2.21)	0.025
Measured iEOA
No PPM	86 (51.8)	Ref.		Ref.
Moderate/severe PPM	106 (67.1)	1.39 (1.05–1.85)	0.022	1.29 (0.95–1.74)	0.104
IE hospitalization
Projected iEOA
No PPM	26 (5.2)	Ref.		Ref.
Moderate/severe PPM	11 (7.3)	1.33 (0.66–2.69)	0.432	1.22 (0.54–2.75)	0.626
Measured iEOA
No PPM	4 (2.4)	Ref.		Ref.
Moderate PPM	7 (8.0)	3.02 (0.88–10.34)	0.079	3.31 (0.94–11.62)	0.062
Severe PPM	7 (10.0)	3.73 (1.09–12.78)	0.036	3.31 (0.90–12.15)	0.071
Measured iEOA
No PPM	4 (2.4)	Ref.		Ref.
Moderate/severe PPM	14 (8.9)	3.34 (1.10–10.16)	0.034	3.31 (1.06–10.39)	0.040
HF readmission
Projected iEOA
No PPM	106 (21.2)	Ref.		Ref.
Moderate/severe PPM	34 (22.7)	0.95 (0.64–1.40)	0.787	0.81 (0.52–1.27)	0.363
Measured iEOA
No PPM	24 (14.5)	Ref.		Ref.
Moderate PPM	21 (23.9)	1.44 (0.80–2.59)	0.225	1.37 (0.74–2.54)	0.320
Severe PPM	19 (27.1)	1.75 (0.96–3.19)	0.069	1.76 (0.92–3.38)	0.090
Measured iEOA
No PPM	24 (14.5)	Ref.		Ref.
Moderate/severe PPM	40 (25.3)	1.57 (0.95–2.61)	0.081	1.52 (0.89–2.62)	0.129
Composite outcome^†
Projected iEOA
No PPM	156 (31.2)	Ref.		Ref.
Moderate/severe PPM	56 (37.3)	1.07 (0.79–1.46)	0.649	0.94 (0.65–1.34)	0.727
Measured iEOA
No PPM	38 (22.9)	Ref.		Ref.
Moderate PPM	32 (36.4)	1.45 (0.91–2.33)	0.121	1.29 (0.79–2.11)	0.312
Severe PPM	31 (44.3)	1.88 (1.17–3.03)	0.009	1.68 (1.01–2.80)	0.044
Measured iEOA
No PPM	38 (22.9)	Ref.		Ref.
Moderate/severe PPM	63 (39.9)	1.64 (1.09–2.45)	0.017	1.45 (0.95–2.22)	0.087

*Adjusted for age, sex, body surface area, diabetes, hypertension, coronary artery disease, atrial fibrillation, COPD, chronic kidney disease, and previous HF hospitalization. ^†Included all-cause death, redo AVR, IE hospitalization and HF readmission. iEOA, index effective orifice area; PPM, prosthesis-patient mismatch. Other abbreviations as in Table 1.

Compared with patients with no measured PPM, those with severe measured PPM had a significantly higher risk of all-cause readmission (aHR 1.53, 95% CI 1.05–2.21) and the composite outcome (aHR 1.68, 95% CI 1.01–2.80); trends of a higher risk for IE readmission (aHR 3.31, 95% CI 0.90–12.15, P=0.071) and HF admission (aHR 1.76, 95% CI 0.92–3.38, P=0.087) were also observed. As Figure 3 demonstrates, compared with projected EOAi, the measured EOAi exhibited a stronger association with postoperative clinical events, including associations with redo AVR, all-cause readmission, IE readmission, HF readmission, and the composite outcome.

Figure 3.

Adjusted association between projected indexed effective orifice area (EOAi), measured EOAi, and risk of clinical events. CI, confidence interval; HR, hazard ratio; PPM, prosthesis-patient mismatch.

Subgroup Analysis by Valve Type

We additionally compared outcomes (PPM and late outcomes) between the bovine pericardial and porcine valves. The bovine pericardial valves included Trifecta, Perimount, and Magna Ease in our study. The results showed that PPM was more common in patients receiving porcine valves than those receiving bovine valves in either definition by projected iEOA (odds ratio 11.86, 95% CI 2.87–49.00) or measured iEOA (odds ratio 2.42, 95% CI 1.11–5.28). However, the risk of follow-up late outcome was not significantly different between the 2 valve types (Supplementary Table 5).

Discussion

Our data demonstrated that the mean PG after operation was higher in patients who received smaller bioprosthetic valves, a result that was observed in both the short-term and the long-term follow-up of 5 years. The difference in hemodynamic performance was more pronounced when the smaller valves were compared with the larger ones (25 and 27 mm). The rates of PPM for each valve size group were comparable. Compared with patients receiving bovine pericardial valves, we found patients receiving porcine valves showed greater risk for developing both projected PPM and measured PPM, which is consistent with former research.⁴^,⁵ PPM is the foremost factor when selecting a valve size;²³^,²⁴ however, our results indicated that, relative to those with larger valves, patients with smaller valve implants had a higher risk of poor hemodynamic performance regardless of whether they had PPM. Similar to another study,²⁵ we discovered that valve size was not associated with a higher risk of death or readmission. Patients with smaller body size, such as Asian women,²⁶ who required smaller valves, were more likely to have elevated PGs, but this did not affect the mortality rate.

Root enlargement procedures, including the Manouguian,²⁷ Nicks,²⁸ and Konno²⁹ procedures, may be an option for patients with smaller body sizes because these procedures enable implantation of larger bioprosthetic valves, even when the PPM risk is low. Although such procedures can improve hemodynamic performance, they do not improve long-term clinical events,²² and increase the risks of postoperative mortality and morbidity.³⁰ TAVR has been associated with better hemodynamic performance;³¹ therefore, surgeons should consider implanting larger valves to increase the EOA and decrease the PG when using SAVR as treatment. Root enlargement can be performed in high-volume centers to improve patients’ hemodynamic performance, although the long-term outcomes of these procedures require further investigation.

PPM was introduced as a conceptby Rahimtoola in 1978,¹¹ and has since become a key tool for evaluating valve size. However, whether EOAi and PPM are used before an operation is influenced by various assumptions, including that the projected PPM will be similar to the measured PPM, and thus related to hemodynamic performance, such as mean PG, and then to clinical events.³² Although numerous studies have discussed the associations among PPM, hemodynamic performance, and clinical events,²⁴^,³³ the accuracy of the projected EOA provided by the relevant valve manufacturers,³⁴ which is not measured in vivo, is questionable. Our data indicated that the projected PPM was not associated with the mean PG at follow-up from 3 months to 5 years after surgery and that the projected PPM was not associated with clinical events, such as all-cause death and readmission. Therefore, our data indicated that the projected EOAi is not an appropriate predictor of valve performance after AVR because the assumed association between projected PPM and clinical performance is invalid.

According to our results, measured PPM calculated using measured EOA can be used to predict the mean PG. Our study not only revealed that individuals with measured PPM were more likely to have a higher PG but also demonstrated that the severity of the measured PPM can predict mean PG elevation. The association between the measured PPM and mean PG weakened by the 5-year follow-up, so the measured PPM may be a useful indicator of mean PG for 3 months to 5 years after an operation; however, the association over longer periods remains unclear. Moreover, our results revealed an association between measured PPM and clinical events. Groups with measured PPM demonstrated higher rates of IE readmission. Groups with severe measured PPM demonstrated higher rates of all-cause readmission and composite outcomes. Among the groups, the group with PPM did not differ significantly from the group without PPM in the composite outcome after adjustment, which was likely due to the smaller population. The group with severe PPM did not differ significantly from the group without PPM for IE readmission and HF readmission, although trends were observed. The possible relationship between PPM and IE may be associated with increased turbulent shear stress, which can be caused by PPM and lead to a higher risk of IE and structural valve deterioration.³⁵ Moreover, the correlation of IE and structural valve deterioration has been observed in other studies.³⁶

Our results and those of other studies³⁷^,³⁸ have demonstrated that the cascade of prediction for measured PPM, hemodynamic performance, and clinical events is valid. However, the cascade is not useful for projected PPM. Our data on the clinical events demonstrated several differences in measured PPM but no significant difference in all-cause death.

In conclusion, Asian patients who receive small bioprosthetic valves, relative to those who receive larger valves, generally have less favorable hemodynamic performance but do not demonstrate differences in clinical events in long-term follow-up. Nevertheless, hemodynamic performance after small-sized SAVR should be improved. Under the challenges of TAVR, root enlargement can be performed in some patients during SAVR to improve their hemodynamic performance, although the short-term risks of root enlargement procedures should be carefully considered. In addition, although projected PPM is not an effective predictor of hemodynamic performance or clinical events, measured PPM may be an effective indicator.

Study Limitations

This was a nonrandomized retrospective study. Because we retrieved patients’ data from a large clinical database, several patients had missing data, including incomplete echocardiographic reports and missing bioprosthetic valve information. However, we have no reason to believe that those data led to substantial bias in our analyses. Furthermore, because the patients in this study were of a single race, the result may not be generalizable to other ethnicities.

Acknowledgments

This study was based on data from the CGRD provided by the Chang Gung Memorial Hospital administration. However, the interpretation and conclusions in this study belong to the authors. The authors thank the Maintenance Project of the Center for Big Data Analytics and Statistics (Grant CLRPG3D0049) at Chang Gung Memorial Hospital for statistical consultation and data analysis. The authors also thank Alfred Hsing-Fen Lin and Bing-Yu Chen for their assistance with the statistical analysis. This manuscript was edited by Wallace Academic Editing.

Funding

This work was supported by a grant from Chang Gung Memorial Hospital, Taiwan (CFRPG3M0011, CMRPG3L0101-2, BMRPD95 (SWC)). This work was also supported by the Ministry of Science and Technology grant [(MOST-110-2314-B-182A-114 (SWC)].

Disclosures

The authors declare that there are no conflicts of interest.

IRB Information

This study was approved by the Chang Gung Medical Foundation Institutional Review Board on April 22, 2019 (IRB No. 201900585B0).

Supplementary Files

Please find supplementary file(s);

https://doi.org/10.1253/circj.CJ-22-0718

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