Temporal Trends and Early Outcomes of Transcatheter versus Surgical Mitral Valve Repair in Atrial Fibrillation Patients

Zhou, Chi; Tan, Kai; Liu, Weili; Li, Shaohua; Xia, Zongyi; Song, Yanxu; Lian, Zhexun

doi:https://doi.org/10.1155/2023/4332684

Journal of Interventional Cardiology

On this page

Abstract Introduction Methods Discussion Conclusion Data Availability Conflicts of Interest Supplementary Materials References Copyright Related Articles

Research Article | Open Access

Volume 2023 | Article ID 4332684 | https://doi.org/10.1155/2023/4332684

Temporal Trends and Early Outcomes of Transcatheter versus Surgical Mitral Valve Repair in Atrial Fibrillation Patients

Chi Zhou,¹Kai Tan,¹Weili Liu,²Shaohua Li,¹Zongyi Xia,¹Yanxu Song,¹and Zhexun Lian¹

Academic Editor: Yuli Huang

Received27 Oct 2022

Revised21 Aug 2023

Accepted03 Oct 2023

Published12 Oct 2023

Abstract

Objectives. To study trends of utilization, in-hospital outcomes, and short outcomes in patients undergoing transcatheter mitral valve repair (TMVR) vs. surgical mitral valve repair (SMVR) in atrial fibrillation (AF). Background. TMVR is a treatment option in inoperable or high-risk patients with mitral regurgitation (MR). AF is a common comorbidity of MR. Data comparing between TMVR and SMVR in MR patients with AF is lacking. Methods. The National Readmission Database from 2016 to 2019 was utilized to identify hospitalizations undergoing TMVR or SMVR with AF. Outcomes of interest included mortality, postoperative complications, length of stay, and 30-day readmission rate. Results. A total of 9,195 patients underwent TMVR and 16,972 patients underwent SMVR with AF; the number of AF undergoing TMVR was increasing from 1,342 in 2016 to 4,215 in 2019 and SMVR. The incidence of in-hospital mortality decreased from 2.6% in 2016 to 1.8% in 2019. We identified length of stay>5 days, dyslipidemia, cerebrovascular disease, heart failure with reduced ejection fraction, and urgent/emergent admissions as independent risk factors for in-hospital mortality. After matching, we included 4,680 patients in each group; the in-hospital death, transfusion, acute kidney injury, sepsis, stroke, and mechanical ventilation were lower in TMVR compared with SMVR. TMVR was associated with a similar rate of all-cause readmission at 30 days compared with SMVR. Conclusion. Patients with AF receiving TMVR have been increasing along with progressive improvement in in-hospital death and length of stay. Compared to SMVR, AF patients receiving TMVR had a lower rate of in-hospital death and postoperative complications.

1. Introduction

Mitral regurgitation (MR) is a common heart valve disease that affects approximately 10% of people over the age of 75 in the general population [1]. Severe MR can lead to left ventricular failure, pulmonary hypertension, atrial fibrillation, and even death, and in patients with a New York Heart Association (NYHA) class III or IV, the mortality rate is 34% yearly [2]. Surgical mitral valve repair (SMVR) used to be the only treatment option for patients with MR that was poorly controlled by medications [3, 4]. In 2003, the first MitraClip procedure was performed and received European CE certification in 2008. Based on the results of the EVEREST II and COAPT clinical trials, transcatheter mitral valve repair (TMVR) for primary and secondary MR has been updated to class 2a in the latest guidelines.

Atrial fibrillation (AF) is often associated with valvular heart disease (VHD), and up to 60% of the patients with AF have some form of valvular abnormality [5]. Previous research has revealed poor outcomes in AF patients treated with SMVR [6]. Patients with AF who undergo TMVR have higher risks of postoperative bleeding and stroke as well as a higher risk of mortality during follow-up. As TMVR is being increasingly performed, its safety in specific patient populations needs further clarification. However, there is very little published research specifically comparing the outcomes of TMVR and SMVR in AF patients [7]. This study compared utilization trends and outcomes of TMVR and SMVR using nationally representative real-world population data.

2. Methods

2.1. Data Source

The National Readmission Database (NRD) from January 2016 to December 2019 was used for this analysis. The NRD is a part of administrative databases developed by federal support of Healthcare Research and Quality (AHRQ) agency. The NRD has over 16 million admissions, which represents a 57% stratified sample of all discharges from community hospitals in the United States excluding rehabilitation and long-term acute care hospitals [8]. As an administrative database, the NRD used the International Classification of Diseases, 10th Revision (ICD-10) code, to identify patient diagnosis and operation. This article was approved by the Ethics Committee of the Affiliated Hospital of Qingdao University (ethics number: QYFY WZLL 27354).

2.2. Study Design and Data Selection

We searched the 2016–2019 NRD for patients with AF who underwent SMVR or TMVR using the ICD-10 (TMVR: 02UG3JZ; SMVR: 02QG0ZE or 02QG0ZZ). Patients with less than 18 -year-old and missing data were excluded. Meanwhile, we also excluded patients with CABG to reduce the likelihood of selection in favor of SMVR. To calculate the estimated cost of hospitalization, the NRD data were merged with cost-to-charge ratios available from the Healthcare Cost and Utilization Project. We estimated the cost of each inpatient stay by multiplying the total hospital charge with cost-to-charge ratios. Cost was also adjusted for inflation (December 2021).

2.3. Outcomes

Our study’s primary outcome was in-hospital outcomes including the in-hospital death, length of stay, cost, transfusion, acute kidney injury, sepsis, mechanical ventilation, and stroke. The secondary outcomes were the 30-day outcomes including all-cause readmission, cardiovascular (CV) readmission, and heart failure readmission. CV readmission was defined as hospitalization due to myocardial infarction, heart failure, or arrhythmia. The primary diagnosis in the first readmission after TMVR or SMVR was a reason for readmission. In the case of multiple postoperative readmissions, only the first hospitalization after admission was counted. All ICD-10 codes used for cohort screening, baseline characteristics, and outcomes are presented in Supplementary Table 1.

3. Statistical Analysis

Normally distributed measures are expressed as the mean ± variance using Student’s t test; nonnormally distributed measures are expressed as the median (interquartile range (IQR)) using the Wilcoxon rank-sum test. Categorical variables are expressed as percentages, and comparisons between the groups were made using the X² test or the Fisher’s exact test. A nearest neighbor 1 : 1 variable ratio, parallel, balanced, propensity-matching model was made using a caliper width of 0.2. The Cochran–Armitage trend test was used for categorical variables and linear regression for continuous ones’ trend analysis. We entered variables with < 0.05 in the univariate analysis into a multivariate regression model and selected the entry method to identify independent predictors of in-hospital death and 30-day readmission and compute the odds ratio (OR) and 95% confidence interval (CI).

We chose two sides’ value of <0.05 as statistically significant. We used univariate Cox proportional hazards regression for the 30-day outcomes to calculate the hazard ratio (HR) and 95% CI. Kaplan‒Meier curves for 30-day all-cause readmissions were constructed. Statistical analyses and propensity-matched analysis were performed using R version 3.5.

4. Result

4.1. Population Characteristics and Outcomes

There were 26,037 patients of TMVR and 45,619 patients of SMVR performed in the NRD between 2016 and 2019. After screening, we finally included 9,195 patients of TMVR and 16,972 patients of SMVR. Figure 1 illustrates the patient selection process. Before matching, patients in the TMVR group were older (mean age of 79.3 years vs. 66.6 years; < 0.001) and had more women (44.7 vs. 41.2%; < 0.001) compared with those in the SMVR group. The TMVR group associated more comorbidities including the prior PCI, prior CABG, smoke, myocardial infarction, congestive heart failure, chronic pulmonary disease, diabetes, renal disease, cerebrovascular disease, peripheral vascular disease, and metastatic solid tumor compared with the SMVR group. Conversely, more obesity was associated in the SMVR group. The detailed differences between TMVR and SMVR are summarized in Table 1.

4.2. Temporal Trends

Over the study period, the number of AF undergoing TMVR was increasing from 1,342 in 2016 to 4,215 in 2019 ( = 0.049 for trend) and with SMVR remained unchanged from 4,323 in 2016 to 4,084 in 2019. In the TMVR group, we reported the in-hospital mortality in the range of 2% (2.6 vs. 1.8%; = 0.049 for trend), while in SAVR, the mortality rate also declined (2.2 vs. 1.7%; = 0.037 for trend). In terms of postoperative complications in the SMVR group, transfusion, sepsis, acute kidney injury, mechanical ventilation, and stroke all remained unchanged. However, in the TMVR group, the sepsis rate declined (2.7 vs. 1.0%; = 0.037 for trend) and transfusion, acute kidney injury, mechanical ventilation, and stroke all remained unchanged.

In the 30-day readmission rate, the all-cause and CV reason remained stable, but there was a trend towards a decreased admissions for heart failure (2.7 vs. 1.0%; = 0.037 for trend) in the TMVR group. However, in the SMVR group, the all-cause, CV, and heart failure reason rate all declined during 2016–2019. The TMVR and SMVR groups’ temporal trends between 2016 and 2019 patients are summarized in Tables 2 and 3.

4.3. Multivariate Predictors of In-Hospital Death and 30-Day Readmission

In the TMVR group, among the univariate logistic regression analyses of risk factors for in-hospital mortality, we determined that length of stay (LOS) >5 days, dyslipidemia, cerebrovascular disease, heart failure with reduced ejection fraction, urgent/emergent admission, heart failure with preserved ejection fraction, renal disease, smoke, Charlson comorbidity index, paraplegia, and myocardial infarction had statistically significant differences. After adjusting for these confounding factors, we identified LOS >5 days, dyslipidemia, cerebrovascular disease, heart failure with reduced ejection fraction, and urgent/emergent admission as risk factors for in-hospital mortality.

In the TMVR group, among the univariate logistic regression analyses of risk factors for 30-day readmission, we determined that LOS >5 days, female, chronic pulmonary disease, dementia, heart failure with reduced ejection fraction, renal disease, urgent/emergent admission, heart failure with preserved ejection fraction, and Charlson comorbidity index had statistically significant differences. After adjusting for these confounding factors, we identified LOS >5 days, female, chronic pulmonary disease, dementia, heart failure with reduced ejection fraction, and renal disease as a risk factor for 30-day readmission. Tables 4 and 5 summarize the odds ratio and 95% CI both the univariate and multivariate logistic regression.

4.4. Outcomes in Matching Cohort

The variables used in the matching model are shown in the Supplementary Table 2. We have also shown the data distribution before and after propensity matching in the Supplementary Figure 1.

After matching, a total of 4,680 TMVR patients were matched with 4,680 SMVR patients with AF. All the baseline characters were equally balanced between the two groups (Table 1). TMVR was associated with a lower risk in the hospital death (2.3 vs. 3.3%; OR: 0.69; 95% CI: 0.53–0.88; = 0.003). Meanwhile, TMVR had fewer surgical complications, including transfusion, acute kidney injury, sepsis, stroke, and mechanical ventilation. The TMVR group had shorter hospital stay and less cost. All the matching cohort outcomes are detailed in Tables 6 and 7.

4.5. 30-Day Outcomes

Patients undergoing TMVR had no difference in 30-day all-cause readmission (HR: 0.93; 95% CI: 0.84–1.03; = 0.139), CV readmission (HR: 0.99; 95% CI: 0.75–1.02; = 0.053), and heart failure readmission (HR: 0.88; 95% CI: 0.70–1.13; = 0.89) compared with SMVR patients. Figure 2 shows the 30-day all-cause readmission Kaplan–Meier curve. All the 30-day outcomes are detailed in Table 6.

4.6. Subgroup Analysis

According to the AF type, we divided the patients into paroxysmal AF and nonparoxysmal AF groups in the matching cohort. In the paroxysmal AF group, TMVR and SMVR had the similar risk in the hospital death and stroke. TMVR was associated with a lower rate in the transfusion, acute kidney injury, sepsis, and mechanical ventilation.

In the nonparoxysmal AF group, the TMVR and SMVR had the similar risk in sepsis and stroke. TMVR was associated with a lower rate in the hospital death, transfusion, acute kidney injury, and mechanical ventilation.. The paroxysmal AF detail outcomes are shown in Table 8, and the nonparoxysmal AF group outcomes are shown in Table 9.

4.7. MR Etiology

According to the different causes of mitral regurgitation, we classify them into rheumatic mitral valve, mitral valve prolapse, congenital heart disease, and other cause groups. In the rheumatic mitral valve group, TMVR and SMVR had the similar risk in the hospital death, sepsis, cardiogenic shock, and stroke. TMVR was associated with a lower rate in transfusion, acute kidney injury, and mechanical ventilation.

In the mitral prolapse group, TMVR and SMVR had the similar risk in the hospital death, mechanical ventilation, acute kidney injury, sepsis, and stroke. TMVR was associated with a lower rate in transfusion and cardiogenic shock.

In the congenital valvular heart disease group, TMVR and SMVR had the similar risk in the hospital death, mechanical ventilation, acute kidney injury, sepsis, transfusion, and cardiogenic shock.

In the other reason group, TMVR was associated with a lower rate in hospital death, mechanical ventilation, acute kidney injury, sepsis, transfusion, and cardiogenic shock. The different etiologies of mitral regurgitation outcomes are shown in Table 10.

5. Discussion

We report the following main findings in our contemporary real-world population study of TMVR and SMVR outcomes in patients with AF. (1) Patients with AF receiving TMVR have been increasing since 2016 and SMVR has remained stable. (2) The incidence of in-hospital mortality decreased from 2.6% in 2016 to 1.8% in 2019, and 30-day all-cause readmission remains stable in the TMVR group. (3) In AF receiving TMVR, LOS>5 days, dyslipidemia, cerebrovascular disease, heart failure with reduced ejection fraction, and urgent/emergent admission were associated with in-hospital mortality. LOS >5 days, female, chronic pulmonary disease, dementia, heart failure with reduced ejection fraction, and renal disease were associated with 30-day readmission. (4) In the matching cohort, compared to SMVR, AF patients receiving TMVR had a lower rate of in-hospital death, transfusion, acute kidney injury, sepsis, stroke, and mechanical ventilation. (4) In the subgroup analysis, in the paroxysmal AF group, TMVR and SMVR had the similar risk in hospital death, but in the nonparoxysmal AF group, TMVR was associated with a lower rate in hospital death. (5) In the 30-day outcomes, TMVR and SMVR had a similar result in all-cause readmission, heart failure readmission, and CV readmission.

TMVR is being increasingly performed because of its expanding real-world application and growing popularity. MR and AF are closely related. MR can lead to atrial enlargement, possibly resulting in an increased incidence of AF [9]. In a retrospective study in which echocardiographic characteristics were collected, researchers observed that the annual incidence of new-onset AF was approximately 5% in primary MR patients [10]. In previous trials and registry studies in which NRD was consulted, approximately 32 to 68% of AF patients underwent TMVR [11–14]. Using NRD, we identified in the real world about 57.1% of patients with MR who underwent mitral valve repair coexisting with AF. We identified independent risk factors for in-hospital mortality in patients with atrial fibrillation receiving TMVR, including the importance of urgent/emergent admissions and prior cardiovascular events. AF is an important risk factor for ischemic stroke, and these patients tend to have higher rates of embolism and bleeding. These patients tend to have a higher rate of perioperative bleeding. So, enhanced management of anticoagulants in patients with AF helps reduce in-hospital mortality in those patients receiving TMVR.

Similar to previous studies, our TMVR cohort was older (mean age 79.4) and had a higher prevalence of pre-existing comorbidities. Before matching, the patients in the TMVR group were generally in poor condition and the in-hospital mortality was slightly higher comparing the SMVR group, but not statistically different. After matching, TMVR demonstrated a lower in-hospital death and multiple in-hospital outcomes, as shown in the current study, including blood transfusion, acute kidney injury, sepsis, mechanical ventilation, cardiogenic shock, and stroke. This result is probably related to the fact that transcatheter manipulation is less invasive to the body. Fewer in-hospital complications were also reflected in the lower length of stay and cost of hospitalization in the TMVR group.

During the study period, we reported that the in-hospital mortality rate was 2% in AF patients who underwent TMVR. The in-hospital mortality rate found in our study was similar to that found in Alkhouli et al.’s study, which reported an in-hospital mortality of 2.47% for patients who underwent TMVR and were identified using the NRD database from 2014 to 2018 [15]. Although the difference in the incidence of postoperative complications was not significant, the gradual decrease in incidence indicates a gradual improvement in the safety of TMVR. This improvement in the safety of TMVR is also reflected in a gradual decrease in the length of stay over the study period. By using the STS/ACC TVT Registry, we found that as TMVR became more frequently performed and as operators became more experienced in performing TMVR, the procedural success improved and the complication rate decreased [16, 17]. Early all-cause readmission correlates to a poor prognosis. AF patients who underwent TMVR had a high 30-day readmission rate.

Previous studies have shown that heart failure is the most common reason for readmission of TMVR patients [18]. We found that the 30-day readmission heart failure rate declined from 2016 to 2019 in AF patients who underwent TMVR. This decreased rate is associated with reduced mitral regurgitation and relief of heart failure symptoms in AF patients with TMVR. However, we also note that the heart failure rate did not change significantly from 2017 to 2019. Whether this is related to the loose extension of TMVR indications to patients with functional MR, especially atrial functional MR, still needs further investigation in the future.

Whether AF has adverse effects on patients receiving mitral valve repair remains unclear. Alexiou et al.’s and Kessler et al.’s studies concluded that AF has a major negative impact in the long-term follow-up in patients undergoing SMVR [5, 6]. However, other reports have shown that the outcomes of SMVR are similar in patients with AF and those without AF [19, 20]. For patients who underwent TMVR, AF was not an independent risk factor for in-hospital death [21, 22], but it was an independent risk factor for 30-day readmission [18]. Therefore, it is important to identify risk factors for readmission of AF patients to reduce readmission after TMVR. The longer length of stay may be associated with the patients’ poorer general condition, more comorbidities, and a higher probability of in-hospital complications, which are also associated with an increased 30-day readmission rate [23]. Strategies such as increased collaboration between pulmonologists and nephrologists, multidisciplinary evaluation of TMVR patients, and early discharge may help to reduce the rate of readmission of AF patients.

According to the well-known EVEREST II trial subgroup analysis, the AF patients in the TMVR and SMVR groups had similar in-hospital death rates and 1-year survival outcomes [24]. Our results were consistent with those of previous studies, and no significant differences were observed between TMVR and SMVR in terms of 30-day readmission after matching. However, before matching, the SMVR group had a lower 30-day readmission rate. In fact, after matching, the SMVR patients we matched were older, frailer, and had more comorbidities. As a result, the prognosis of SMVR was poorer.

We evaluated the impact of different AF types on outcomes, and we found that the paroxysmal AF group had similar risk in hospital death compared to SMVR, but the nonparoxysmal AF group had a lower in-hospital mortality rate. Generally, the prognosis of patients with paroxysmal AF tends to be positively correlated with the presentation of the frequency of AF.

Patients with nonparoxysmal AF have worsening heart failure symptoms, frailty, and a higher burden of noncardiovascular disease. This is also reflected in a meta-analysis by Ganesan et al. including approximately 100,000 patients receiving SMVR, where all-cause mortality was higher in nonparoxysmal AF than in paroxysmal AF [25]. However, in our univariate logistic regression analyses, the paroxysmal AF is not a protective factor for in-hospital death in AF patients undergoing TMVR and this is consistent with Gangani et al.’s study [26]. Also, in our subgroup analysis, we found that in the nonparoxysmal AF patients, TMVR appears to be more beneficial for patients compared to SMVR. However, this result still needs to be further demonstrated in a randomized trial. In a subgroup analysis by etiology, we found no significant difference in in-hospital death between the two groups in the comparison of rheumatic mitral valve, mitral valve prolapse, and congenital heart disease. We found that TMVR was more favorable than SMVR in patients with mitral regurgitation due to other causes (including left atrium enlargement for various reasons and mitral valve degeneration). We think that this is due to part of the group of small sample size.

5.1. Limitations

Our study has the following limitations. NRD used for this analysis is an administrative database, and we used the ICD-10 code to identify the patients and outcomes, so it may suffer from coding errors. However, the procedure code was used to recognize our cohort, and we expect the errors in the coding to be negligible. Meanwhile, our study cannot calculate the Society of Thoracic Surgeons (STS) score. However, in our study, we found that the TMVR group had a high burden of comorbidity; it reflects the current guideline that TMVR patients are at intermediate or high surgical risk. Whether the STS score can be an indicator of patient prognosis factor is unclear. Meanwhile, the RCT study should be conducted to analyze whether there is a difference between TMVR and SMVR in intermediate or high surgical risk patients in the future.

Second, although we performed subgroup analyses based on different MR causes, including rheumatic heart disease, congenital valvular heart disease, and mitral valve prolapse, other causes including the search for secondary mitral regurgitation due to enlargement cannot be analyzed. Meanwhile, we also can get the echocardiography data (including the effective aortic valve orifice area, ejection fraction, pulmonary artery pressure, left ventricular diameter, left ventricular end-diastolic volume, and MR degree). These unmeasured factors may influence the results of the analysis as confounding factors.

Third, our study is a retrospective analysis with the inherent disadvantages of retrospective analysis. However, randomized grouping cannot be done as in randomized controlled studies although we used propensity score matching to reduce the difference between the two groups.

Fourth, the NRD database does not include emergency and out-of-hospital deaths. It can only count patients admitted to the hospital in the same state. However, we expect such readmissions to be uncommon in patients undergoing aortic valve replacement. Meanwhile, we used the ICD-10 code to identify outcomes, like others studies used [27, 28]. The possibility exists that some patients were coded incorrectly; however, the frequency of a given outcome being miscoded is similar in a particular group. The strength of this study is the large sample and the multicenter retrospective study.

6. Conclusion

We report real-world data on in-hospital outcomes of TMVR and SMVR in AF patient. The number of AF undergoing TMVR was increasing. We also found that the incidence of in-hospital mortality and sepsis decreased but the 30-day all-cause readmission remained stable. LOS >5 days, cerebrovascular disease, urgent/emergent admission, prior stroke, and smoke were considered as risk factors for in-hospital mortality; female, chronic pulmonary disease, and renal disease were considered as risk factors for 30-day readmission. After matching, TMVR had a low risk in hospital death, transfusion, acute kidney injury, sepsis, stroke, and mechanical ventilation. However, TMVR had a similar 30-day all-cause readmission incidence compared to SMVR in AF patients.

Data Availability

The data used to support the findings of this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

Supplementary Materials

Supplement Table 1: list of ICD-10 used in this article. Supplement Table 2: variables used in propensity-match analysis. Supplementary Figure 1: data distribution before and after propensity matching. (Supplementary Materials)

References

V. T. Nkomo, J. M. Gardin, Skelton et al., “Burden of valvular heart diseases: a population-based study,” Lancet (London, England), vol. 368, no. 9540, pp. 1005–1011, 2006.
View at: Google Scholar
L. H. Ling, M. Enriquez-Sarano, J. B. Seward et al., “Clinical outcome of mitral regurgitation due to flail leaflet,” New England Journal of Medicine, vol. 335, no. 19, pp. 1417–1423, 1996.
View at: Google Scholar
C. M. Otto, Nishimura, A. Rick et al., “ACC/AHA guideline for the management of patients with valvular heart disease: executive summary: a report of the American college of cardiology/American heart association joint committee on clinical practice guidelines,” Journal of the American College of Cardiology, vol. 77, no. 4, pp. 450–500, 2021.
View at: Google Scholar
G. W. Stone, J. Lindenfeld, W. T. Abraham et al., “Transcatheter mitral-valve repair in patients with heart failure,” New England Journal of Medicine, vol. 379, no. 24, pp. 2307–2318, 2018.
View at: Google Scholar
M. Keßler, A. Pott, E. Mammadova et al., “Atrial fibrillation predicts long-term outcome after transcatheter edge-to-edge mitral valve repair by MitraClip implantation,” Biomolecules, vol. 8, no. 4, 2018.
View at: Google Scholar
Alexiou, D. Christos, O. George et al., “The effect of preoperative atrial fibrillation on survival following mitral valve repair for degenerative mitral regurgitation,” European Journal of Cardio-Thoracic Surgery: Official Journal of the European Association for Cardio-Thoracic Surgery, vol. 31, no. 4, pp. 586–591, 2007.
View at: Google Scholar
A. S. Nathan, L. Yang, J. Elias et al., “Oral anticoagulant use in patients with atrial fibrillation and mitral valve repair,” American Heart Journal, vol. 232, pp. 1–9, 2021.
View at: Google Scholar
M. D. Rockville, “Hcup-US database,” 2018, https://hcup-us.ahrq.gov/tech_assist/centdist.jsp.
View at: Google Scholar
R. S. Vasan, M. G. Larson, D. Levy, J. C. Evans, and E. J. Benjamin, “Distribution and categorization of echocardiographic measurements in relation to reference limits: the Framingham Heart Study: formulation of a height- and sex-specific classification and its prospective validation,” Circulation, vol. 96, no. 6, pp. 1863–1873, 1997.
View at: Google Scholar
F. Grigioni, H. Avierinos, C. G. Scott et al., “Atrial fibrillation complicating the course of degenerative mitral regurgitation: determinants and long-term outcome,” Journal of the American College of Cardiology, vol. 40, no. 1, pp. 84–92, 2002.
View at: Google Scholar
M. Puls, E. Lubos, P. Boekstegers et al., “One-year outcomes and predictors of mortality after MitraClip therapy in contemporary clinical practice: results from the German transcatheter mitral valve interventions registry,” European Heart Journal, vol. 37, no. 8, pp. 703–712, 2016.
View at: Google Scholar
T. Feldman, S. C. Smart, A. Trento et al., “Randomized comparison of percutaneous repair and surgery for mitral regurgitation: 5-year results of EVEREST II,” Journal of the American College of Cardiology, vol. 66, no. 25, pp. 2844–2854, 2015.
View at: Google Scholar
F. F. Maisano, B. Olaf, S. Stephan et al., “Percutaneous mitral valve interventions in the real world: early and 1-year results from the ACCESS-EU, a prospective, multicenter, nonrandomized post-approval study of the MitraClip therapy in Europe,” Journal of the American College of Cardiology, vol. 62, no. 12, pp. 1052–1061, 2013.
View at: Google Scholar
G. Nickenig, Estevez-Loureiro, F. Rodrigo et al., “Percutaneous mitral valve edge-to-edge repair: in-hospital results and 1-year follow-up of 628 patients of the 2011-2012 Pilot European Sentinel Registry,” Journal of the American College of Cardiology, vol. 64, no. 9, pp. 875–884, 2014.
View at: Google Scholar
Alkhouli, S. Mohamad, Samian, M. Osman, El Shaer, and M. Ahmed, “Abdulah Amer, and Kawsara, Akram: trends in outcomes, cost, and readmissions of transcatheter edge to edge repair in the United States (2014-2018),” Catheterization and Cardiovascular Interventions, vol. 99, no. 3, pp. 949–955, 2022.
View at: Google Scholar
A. Chhatriwalla, S. Sreekanth, K. Molly et al., “Operator experience and outcomes of transcatheter mitral valve repair in the United States,” Journal of the American College of Cardiology, vol. 74, no. 24, pp. 2955–2965, 2019.
View at: Google Scholar
A. K. Chhatriwalla, S. Vemulapalli, D. R. Holmes et al., “Institutional experience with transcatheter mitral valve repair and clinical outcomes: insights from the TVT registry,” JACC: Cardiovascular Interventions, vol. 12, no. 14, pp. 1342–1352, 2019.
View at: Google Scholar
B. Tripathi, A. C. Sawant, P. Sharma et al., “Short term outcomes after transcatheter mitral valve repair,” International Journal of Cardiology, vol. 327, pp. 163–169, 2021.
View at: Google Scholar
E. Lim, C. W. Barlow, A. R. Hosseinpour et al., “Influence of atrial fibrillation on outcome following mitral valve repair,” Circulation, vol. 104, no. 1, pp. I59–I63, 2001.
View at: Google Scholar
A. Jabs, von Bardeleben, S. Ralph et al., “Effects of atrial fibrillation and heart rate on percutaneous mitral valve repair with MitraClip: results from the TRAnscatheter Mitral valve Interventions (TRAMI) registry, EuroIntervention,” Journal of EuroPCR in Collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology, vol. 12, no. 14, pp. 1697–1705, 2017.
View at: Google Scholar
R. S. von Bardeleben, L. Hobohm, F. Kreidel et al., “Incidence and in-hospital safety outcomes of patients undergoing percutaneous mitral valve edge-to-edge repair using MitraClip: five-year German national patient sample including 13,575 implants,” EuroIntervention: Journal of EuroPCR in Collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology, vol. 14, no. 17, pp. 1725–1732, 2019.
View at: Google Scholar
J. F. Velu, F. A. Kortlandt, T. Hendriks et al., “Comparison of outcome after percutaneous mitral valve repair with the MitraClip in patients with versus without atrial fibrillation,” The American Journal of Cardiology, vol. 120, no. 11, pp. 2035–2040, 2017.
View at: Google Scholar
D. H. Lee, K. J. Buth, B.-J. Martin, Yip, M. Alexandra, and G. M. Hirsch, “Frail patients are at increased risk for mortality and prolonged institutional care after cardiac surgery,” Circulation, vol. 121, no. 8, pp. 973–978, 2010.
View at: Google Scholar
E. Frank, S. E. Wiegers, Y. Woo et al., “Effects of atrial fibrillation on treatment of mitral regurgitation in the EVEREST II (Endovascular Valve Edge-to-Edge Repair Study) randomized trial,” Journal of the American College of Cardiology, vol. 59, no. 14, pp. 1312–1319, 2012.
View at: Google Scholar
A. N. Ganesan, D. P. Chew, T. Hartshorne et al., “The impact of atrial fibrillation type on the risk of thromboembolism, mortality, and bleeding: a systematic review and meta-analysis,” European Heart Journal, vol. 37, no. 20, pp. 1591–1602, 2016.
View at: Google Scholar
K. Gangani, H. Alkhaimy, N. Patil et al., “Impact of paroxysmal versus non-paroxysmal atrial fibrillation on outcomes in patients undergoing transcatheter mitral valve repair,” Cardiovascular Diagnosis and Therapy, vol. 10, no. 1, pp. 31–35, 2020.
View at: Google Scholar
R. B. Houchens, D. Ross, and A. Elixhauser, “National inpatient sample (NIS),” Tech. Rep., U.S. Agency for Healthcare Research and Quality, ML, USA, 2012, HCUP Method Series Report # 2015-04.
View at: Google Scholar
Elbadawi, Ayman, A. Albaeni et al., “Transcatheter versus surgical aortic valve replacement in patients with prior mediastinal radiation,” JACC: Cardiovascular Interventions, vol. 13, no. 22, pp. 2658–2666, 2020.
View at: Google Scholar

Copyright

Copyright © 2023 Chi Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

209

Downloads

287

Citations