Graphical abstract
Keywords: Mitral valve, Mitral regurgitation, Transcatheter edge-to-edge repair, Hospital safety
Highlights
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Transcatheter edge-to-edge repair (TEER) for mitral regurgitation has seen rapid advancements in recent years.
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This study examined 5,212 adult patients in the United States who underwent mitral TEER between 2016 and 2019.
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The study population was predominantly comprised of elderly patients with multiple comorbidities and cardiovascular risk factors.
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Advancements in technology and provider experience have made mitral TEER a safer and more efficient procedure.
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The study observed a significant reduction in hospital length of stay, adverse discharge outcomes and medical complications.
Abstract
Background
Transcatheter edge-to-edge repair (TEER) for mitral regurgitation has rapidly progressed. The MitraClip® system underwent stepwise improvements between 2016 and 2019 (second to fourth generation). However, real-world data on peri-procedural outcomes remain limited. We analyzed peri-procedural healthcare resource utilization and safety of TEER with the MitraClip® system in the U.S. between 2016 and 2019.
Methods
Primary outcomes (healthcare resource utilization) included hospital length of stay (LOS), adverse discharge to a short-term hospital or skilled nursing facility and hospital costs. Secondary outcomes (safety) were in-hospital mortality and post-procedural complications.
Results
A total of 5,212 adults underwent mitral TEER. Mean age was 77.7 (±10.1) years; 3,645 patients (69.9 %) were over 75 years. Median Charlson Comorbidity Index was 3 [IQR 1–4], number of cardiovascular risk factors 3 [2–4], CHA2DS2-VASc score 4 [3–5] and simplified HAS-BLED score 2 [2–3]. Most procedures were performed at large hospitals (76.0 %) and regional hubs on both U.S. coasts. Between 2016 and 2019, LOS decreased by 21 % (95 % CI 0.79–0.85), adverse discharges by 41 % (95 % CI 0.45–0.78) and hospital costs by 8 % (95 % CI 0.88–0.95). TEER showed favorable safety: vascular complications, ischemic strokes, cardiac arrests and tamponades each <1 %; mortality 1.6 %, bleeding 3.3 % and cardiogenic shock 4.5 %. The composite safety outcome declined by 27 % (95 % CI 0.59–0.91). All adverse outcomes increased linearly with increasing comorbidity burden (P for trend < 0.001).
Conclusion
Mitral TEER has become safer and more efficient due to technological advances, operator experience and centralized care. Caution is advised in highly comorbid patients.
1. Introduction
Mitral regurgitation (MR) is the second most common valvular heart disease and, if left untreated, associated with progressive heart failure and increased mortality risk.[1] Percutaneous transcatheter mitral valve repair (TMVr) has emerged as an important alternative to mitral valve surgery in both primary and secondary MR in patients judged inoperable or at high surgical risk.[2] TMVr includes mitral transcatheter edge-to-edge repair (TEER), mitral annuloplasty and chordal implantation, which might be safe and feasible alternatives to mitral valve surgery.[3].
Mitral TEER can be performed with the MitraClip® system (Abbott, Chicago, IL, USA) or PASCAL® system (Edwards Lifesciences, Irvine, CA, USA). The MitraClip® system received CE mark in 2008 and Food and Drug Administration (FDA) approval in 2013 and has been increasingly utilized since then. In 2015, the EVEREST II trial showed reduced efficacy in MR reduction but superior safety of the MitraClip® system compared to mitral valve surgery.[4] In 2018, two randomized controlled trials (RCTs) were published, MITRA-FR and COAPT, which compared the MitraClip® system to optimal medical therapy in patients with secondary MR.[5,6] The findings were conflicting due to different patient selection: while the MITRA-FR trial showed no benefits for the primary outcome after one and two years (i.e., mortality or heart failure hospitalization), the COAPT trial showed positive results for the primary outcome at two years (i.e., mortality or heart failure hospitalization). Recently, the five-year outcome data of the COAPT trial confirmed significantly improved quality of life after MitraClip® intervention and showed a high crossover rate from best medical care to intervention after two years. Notably, patients who crossed over to the interventional group had similar outcomes as patients who had initially been randomized to the intervention.[7] Very recently, the RESHAPE-HF2 trial, a large-scale RCT, was published, demonstrating benefits of MitraClip® interventions in patients with moderate to severe MR.[8] These findings further validate the outcomes previously observed in the COAPT trial. The MitraClip® system has undergone continuous developments between 2016 (second-generation model) and 2019 (fourth-generation model), including different clip sizes, gripper lines and controlled grasping angles.
Apart from the MitraClip® system, the PASCAL® system received CE mark approval in early 2019 and FDA approval in 2022. One-year outcomes of the CLASP study demonstrated a high survival rate of 92 %, as well as improvements in exercise capacity and quality of life.[9,10] Currently, the CLASP IID/IIF Pivotal Clinical Trial is comparing safety and efficacy outcomes between the PASCAL® and the MitraClip® system.[11].
However, outside of the aforementioned trials, real-world data on healthcare resource utilization and safety outcomes in patients undergoing mitral TEER are limited. Therefore, in a large United States (US) national database, comprising approximately one fifth of all annual hospitalizations, we sought to investigate the trends in healthcare resource utilization (primary outcomes) and safety (secondary outcomes) in patients undergoing TEER with the MitraClip® system between 2016 and 2019, which was the time period of continuous MitraClip® developments.[12].
2. Methods
2.1. Data source
The study was performed following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. Data were retrieved from the Healthcare Quality and Utilization Project National Inpatient Sample (HCUP NIS) which is an all-payer database of inpatient stays in the US that is made available by the Agency for Healthcare Research and Quality (AHRQ). An approval by the institutional review board was not mandated due to public availability of the de-identified data. HCUP NIS data covers hospital discharge-level data and represents an in-hospital sample of approximately 20 % of US hospitals. The sample is considered to be geographically dispersed and representative of all inpatient admissions in the US.[13].
The retrieved data included patient demographics (i.e., age, sex and ethnicity), primary payer status (i.e., public insurance by Medicare and Medicaid, private insurance, self-payment or other), patient diagnoses and procedures as well as hospital characteristics (i.e., year of admission, hospital length of stay [LOS], in-hospital mortality, hospital region, hospital location [urban or rural], teaching status, hospital size [small: 1–249 beds; medium: 250–449 beds; large: ≥450 beds], hospital costs and adverse discharge disposition). Patient diagnoses and procedures were retrieved from the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM), based on previously published ICD codes.[14] Deyo’s modification of the Charlson Comorbidity Index (CCI) was used to identify the level of patient comorbidities.[15] Additionally, the CHA2DS2-VASc-Score and a simplified form of the HAS-BLED score (criteria on International Normalized Ratio [INR] and antithrombotic medication not included) were calculated, based on previously published ICD codes.[[16], [17], [18]] Moreover, age groups were determined according to criteria of the CHA2DS2-VASc-Score: “young and middle-aged” (18–64 years), “senior” (65–74 years) and “gerontologic” patients (≥75 years). The patients’ cardiovascular risk burden was estimated on an ordinal scale by adding the number of cardiovascular risk factors for each patient. Risk factors included age (i.e., ≥55 years for males and ≥ 65 years for females),[19] hypertension, dyslipidemia, diabetes, peripheral vascular disease (PVD), as well as history of smoking, alcohol abuse or acute myocardial infarction.[20].
2.2. Study population
All hospitalized adult patients who underwent mitral TEER between 2016 and 2019 were included. The MitraClip® system underwent stepwise device improvements between 2016 and 2019.[12] Mitral TEER was selected based on the ICD code 02UG3JZ, as being previously published:[[21], [22], [23], [24]] Patients below the age of 18 and patients undergoing other heart valve procedures during the same hospitalization (i.e., transcatheter aortic valve replacement, tricuspid valve interventions or other mitral valve interventions or repairs) were excluded.
2.3. Outcomes
The primary outcomes were defined as healthcare resource utilization, including hospital LOS, adverse discharge disposition and hospital costs. Hospital LOS was defined as the number of days between hospital admission and discharge. Adverse discharge disposition was defined as discharge to a short-term hospital or skilled nursing facility (SNF).[25] Hospital costs were derived by converting hospital charges based on HCUP cost-to-charge-ratios. Hospital charges included the amounts that hospitals billed for services, while hospital costs included the actual expenses for hospital services (including wages, supplies and utilities).
Secondary outcomes were defined as safety outcomes, including in-hospital peri-procedural complications and in-hospital mortality. In-hospital complications were defined based on previously published ICD codes:[26] post-procedural bleeding, vascular complication, vascular complications requiring surgery, ischemic stroke, hemorrhagic stroke, transient ischemic attack, new pacemaker implantation, cardiogenic shock, cardiac arrest, acute renal failure, and pericardial tamponade. Additionally, one composite safety endpoint was included which was defined as the incidence of the aforementioned safety endpoints (i.e., in-hospital mortality and complications).
2.4. Statistical analysis
Data analyses were performed using R Core Team 2020 (Vienna, Austria). Normality was assessed using Shapiro-Wilk analysis. Categorical and continuous variables were compared using Chi-square tests and Student’s t-tests (normally distributed variables) or Fisher’s exact test and Wilcoxon-Mann-Whitney U test (non-normally distributed variables), respectively. Normally distributed continuous variables were expressed as mean (standard deviation, SD), non-normally distributed variables as median [interquartile range, IQR], and categorical variables as frequency (percentage). Results are presented as adjusted odds ratios (OR) or adjusted incidence rate ratios (IRR) with 95 % confidence intervals (CI) and P-values. A two-tailed P-value of less than 0.05 was considered statistically significant. Authors SB, DE and JMW had full access to all the data in the study and take responsibility for its integrity and the data analysis.
Logistic regression was used to analyze the effects of risk factors on medical complications, in-hospital mortality and adverse discharge disposition. Negative binomial regression was utilized to test risk factors of hospital LOS and costs. Regression models were adjusted for age groups, sex, ethnicity, CCI, cardiovascular risk burden, hospital admission year, insurance status, hospital size, hospital division, hospital teaching status, atrial fibrillation or flutter, rheumatic heart disease and MR.
2.5. Geographic analyses
To account for regional differences in healthcare, event rates for primary and secondary outcomes were examined for male and female patients across US regions and plotted on geographic maps.
2.6. Subgroup analysis
To assess outcomes after elective TEER of the mitral valve, the primary analyses were repeated in a subgroup after excluding patients with emergency or non-elective TEER.
3. Results
Between 2016 and 2019, 5,531 patients underwent mitral TEER. After excluding patients below the age of 18 or with any other additional valve intervention, 5,212 patients were included in the final study cohort (Table 1 and Fig. 1). There was an approximately threefold increase in mitral TEER cases from 2016 to 2019 (P < 0.001) (Table 1). In this study cohort, 2,787 patients (53.5 %) were male and 2,425 patients (46.5 %) were female. Most patients had a Caucasian ethnicity (4,191 patients [80.4 %]). The study population was relatively frail with an average age of 77.7 years (±10.1), average CCI of 3 [[1], [2], [3], [4]], average CHA2DS2-VASc-Score of 4 [[3], [4], [5]] and average simplified HAS-BLED score of 2 [2,3]. The patients had on average 3 [[2], [3], [4]] cardiovascular risk factors. Most mitral TEER cases (3,959 [76.0 %]) were performed in large hospitals and at US coastal regions, e.g. South Atlantic region (1,131 [21.7 %]) or Pacific region (896 [17.2 %]).
Table 1.
Characteristics of patients undergoing mitral TEER in the United States between 2016 and 2019.
| 2016 | 2017 | 2018 | 2019 | Total | |
|---|---|---|---|---|---|
| Patient characteristics | |||||
| Included number of patients | 792 | 1,059 | 1,354 | 2,007 | 5,212 |
| Age | 77.8 (10.6) | 78.6 (9.60) | 77.9 (9.74) | 77.1 (10.3) | 77.7 (10.1) |
| Age group | |||||
| ≥ 75 years | 555 (70.1 %) | 750 (70.8 %) | 969 (71.6 %) | 1,371 (68.3 %) | 3,645 (69.9 %) |
| ≥ 65 years | 141 (17.8 %) | 213 (20.1 %) | 237 (17.5 %) | 402 (20.0 %) | 993 (19.1 %) |
| ≤ 64 years | 96 (12.1 %) | 96 (9.1 %) | 148 (10.9 %) | 234 (11.7 %) | 574 (11.0 %) |
| Sex | |||||
| Male | 399 (50.4 %) | 552 (52.1 %) | 735 (54.3 %) | 1,101 (54.9 %) | 2,787 (53.5 %) |
| Female | 393 (49.6 %) | 507 (47.9 %) | 619 (45.7 %) | 906 (45.1 %) | 2,425 (46.5 %) |
| Ethnicity | |||||
| Caucasian | 633 (79.9 %) | 868 (82.0 %) | 1,092 (80.7 %) | 1,598 (79.6 %) | 4,191 (80.4 %) |
| Hispanic | 42 (5.3 %) | 69 (6.5 %) | 94 (6.9 %) | 113 (5.6 %) | 318 (6.1 %) |
| African American | 67 (8.5 %) | 75 (7.1 %) | 99 (7.3 %) | 192 (9.6 %) | 433 (8.3 %) |
| Other | 20 (2.5 %) | 22 (2.1 %) | 27 (2.0 %) | 44 (2.2 %) | 113 (2.2 %) |
| Asian/Pacific Island | 23 (2.9 %) | 22 (2.1 %) | 37 (2.7 %) | 53 (2.6 %) | 135 (2.6 %) |
| Native American | 7 (0.9 %) | 3 (0.3 %) | 5 (0.4 %) | 7 (0.3 %) | 22 (0.4 %) |
| Insurance type | |||||
| Public | 699 (88.3 %) | 956 (90.3 %) | 1,216 (89.8 %) | 1,757 (87.5 %) | 4,628 (88.8 %) |
| Other | 14 (1.8 %) | 12 (1.1 %) | 15 (1.1 %) | 39 (1.9 %) | 80 (1.5 %) |
| Private | 77 (9.7 %) | 89 (8.4 %) | 118 (8.7 %) | 201 (10.0 %) | 485 (9.3 %) |
| Self-payer | 2 (0.3 %) | 2 (0.2 %) | 5 (0.4 %) | 10 (0.5 %) | 19 (0.4 %) |
| Study outcomes | |||||
| Hospital length of stay (days) | 2.0 [1.0, 5.0] | 2.0 [1.0, 4.0] | 2.0 [1.0, 4.0] | 1.0 [1.0, 3.0] | 2.0 [1.0, 4.0] |
| Hospital costs | 44,000 [34,300, 59,900] | 43,000 [31,700, 56,400] | 40,300 [31,300, 55,800] | 40,500 [30,700, 55,000] | 41,500 [31,400, 56,200] |
| (US dollars) | |||||
| Adverse discharge disposition | 97 (12.2 %) | 107 (10.1 %) | 137 (10.1 %) | 167 (8.3 %) | 508 (9.7 %) |
| Hospital characteristics | |||||
| Hospital teaching status | |||||
| Rural | 2 (0.3 %) | 3 (0.3 %) | 5 (0.4 %) | 23 (1.1 %) | 33 (0.6 %) |
| Urban non-teaching | 54 (6.8 %) | 61 (5.8 %) | 123 (9.1 %) | 142 (7.1 %) | 380 (7.3 %) |
| Urban teaching | 736 (92.9 %) | 995 (94.0 %) | 1,226 (90.5 %) | 1,842 (91.8 %) | 4,799 (92.1 %) |
| Hospital bedsize | |||||
| Large (≥ 450) | 613 (77.4 %) | 795 (75.1 %) | 1,034 (76.4 %) | 1,517 (75.6 %) | 3,959 (76.0 %) |
| Medium (250–449) | 132 (16.7 %) | 207 (19.5 %) | 242 (17.9 %) | 348 (17.3 %) | 929 (17.8 %) |
| Small (≤ 249) | 47 (5.9 %) | 57 (5.4 %) | 78 (5.8 %) | 142 (7.1 %) | 324 (6.2 %) |
| Hospital division | |||||
| New England | 19 (2.4 %) | 39 (3.7 %) | 51 (3.8 %) | 87 (4.3 %) | 196 (3.8 %) |
| Middle Atlantic | 116 (14.6 %) | 153 (14.4 %) | 183 (13.5 %) | 297 (14.8 %) | 749 (14.4 %) |
| East North Central | 95 (12.0 %) | 131 (12.4 %) | 157 (11.6 %) | 245 (12.2 %) | 628 (12.0 %) |
| West North Central | 54 (6.8 %) | 73 (6.9 %) | 82 (6.1 %) | 155 (7.7 %) | 364 (7.0 %) |
| South Atlantic | 172 (21.7 %) | 241 (22.8 %) | 315 (23.3 %) | 403 (20.1 %) | 1,131 (21.7 %) |
| East South Central | 42 (5.3 %) | 59 (5.6 %) | 81 (6.0 %) | 125 (6.2 %) | 307 (5.9 %) |
| West South Central | 71 (9.0 %) | 85 (8.0 %) | 116 (8.6 %) | 167 (8.3 %) | 439 (8.4 %) |
| Mountain | 82 (10.4 %) | 87 (8.2 %) | 125 (9.2 %) | 208 (10.4 %) | 502 (9.6 %) |
| Pacific | 141 (17.8 %) | 191 (18.0 %) | 244 (18.0 %) | 320 (15.9 %) | 896 (17.2 %) |
| Patient comorbidities | |||||
| Charlson Comorbidity Index | 3.0 [1.0, 4.0] | 3.0 [1.0, 4.0] | 3.0 [1.0, 5.0] | 3.0 [2.0, 5.0] | 3.0 [1.0, 4.0] |
| Cardiovascular risk profile | 3.0 [2.0, 4.0] | 3.0 [2.0, 4.0] | 3.0 [2.0, 4.0] | 3.0 [2.0, 4.0] | 3.0 [2.0, 4.0] |
| 0 | 12 (1.5 %) | 7 (0.7 %) | 10 (0.7 %) | 16 (0.8 %) | 45 (0.9 %) |
| 1 | 102 (12.9 %) | 91 (8.6 %) | 116 (8.6 %) | 179 (8.9 %) | 488 (9.4 %) |
| 2 | 192 (24.2 %) | 222 (21.0 %) | 320 (23.6 %) | 469 (23.4 %) | 1,203 (23.1 %) |
| 3 | 285 (36.0 %) | 431 (40.7 %) | 509 (37.6 %) | 741 (36.9 %) | 1,966 (37.7 %) |
| 4 | 157 (19.8 %) | 246 (23.2 %) | 314 (23.2 %) | 468 (23.3 %) | 1,185 (22.7 %) |
| 5 | 38 (4.8 %) | 58 (5.5 %) | 80 (5.9 %) | 120 (6.0 %) | 296 (5.7 %) |
| 6 | 6 (0.8 %) | 4 (0.4 %) | 5 (0.4 %) | 14 (0.7 %) | 29 (0.6 %) |
| CHA2DS2-VASc score | 4.0 [3.0, 5.0 | 4.0 [4.0, 5.0] | 4.0 [3.0, 5.0] | 4.0 [4.0, 5.0] | 4.0 [3.0, 5.0] |
| 0 | 5 (0.6 %) | 5 (0.5 %) | 5 (0.4 %) | 8 (0.4 %) | 23 (0.4 %) |
| 1 | 17 (2.1 %) | 14 (1.3 %) | 17 (1.3 %) | 29 (1.4 %) | 77 (1.5 %) |
| 2 | 57 (7.2 %) | 59 (5.6 %) | 85 (6.3 %) | 120 (6.0 %) | 321 (6.2 %) |
| 3 | 148 (18.7 %) | 165 (15.6 %) | 235 (17.4 %) | 341 (17.0 %) | 889 (17.1 %) |
| 4 | 250 (31.6 %) | 348 (32.9 %) | 427 (31.5 %) | 653 (32.5 %) | 1,678 (32.2 %) |
| 5 | 233 (29.4 %) | 356 (33.6 %) | 420 (31.0 %) | 638 (31.8 %) | 1,647 (31.6 %) |
| 6 | 77 (9.7 %) | 95 (9.0 %) | 144 (10.6 %) | 185 (9.2 %) | 501 (9.6 %) |
| 7 | 5 (0.6 %) | 17 (1.6 %) | 21 (1.6 %) | 33 (1.6 %) | 76 (1.5 %) |
| Simplified HAS-BLED-Score | 2.0 [2.0, 3.0] | 2.0 [2.0, 3.0] | 2.0 [2.0, 3.0] | 2.0 [2.0, 3.0] | 2.0 [2.0, 3.0] |
| 0 | 22 (2.8 %) | 13 (1.2 %) | 23 (1.7 %) | 34 (1.7 %) | 92 (1.8 %) |
| 1 | 135 (17.0 %) | 151 (14.3 %) | 189 (14.0 %) | 282 (14.1 %) | 757 (14.5 %) |
| 2 | 376 (47.5 %) | 519 (49.0 %) | 666 (49.2 %) | 940 (46.8 %) | 2,501 (48.0 %) |
| 3 | 252 (31.8 %) | 369 (34.8 %) | 456 (33.7 %) | 734 (36.6 %) | 1,811 (34.7 %) |
| 4 | 7 (0.9 %) | 7 (0.7 %) | 20 (1.5 %) | 17 (0.8 %) | 51 (1.0 %) |
| Atrial fibrillation or flutter | 470 (59.3 %) | 666 (62.9 %) | 848 (62.6 %) | 1,214 (60.5 %) | 3,198 (61.4 %) |
| Medical complications | |||||
| In-hospital mortality | 13 (1.6 %) | 21 (2.0 %) | 28 (2.1 %) | 23 (1.1 %) | 85 (1.6 %) |
| Post-procedural bleeding | 33 (4.2 %) | 43 (4.1 %) | 40 (3.0 %) | 55 (2.7 %) | 171 (3.3 %) |
| Vascular complications | 1 (0.1 %) | 1 (0.1 %) | 1 (0.1 %) | 1 (0.0 %) | 4 (0.1 %) |
| Vascular complications requiring surgery | 0 (0 %) | 0 (0 %) | 2 (0.1 %) | 0 (0 %) | 2 (0.0 %) |
| Ischemic stroke | 8 (1.0 %) | 8 (0.8 %) | 13 (1.0 %) | 13 (0.6 %) | 42 (0.8 %) |
| Hemorrhagic stroke | 0 (0 %) | 0 (0 %) | 0 (0 %) | 2 (0.1 %) | 2 (0.0 %) |
| Transient ischemic attack | 3 (0.4 %) | 2 (0.2 %) | 2 (0.1 %) | 1 (0.0 %) | 8 (0.2 %) |
| New pacemaker implantation | 7 (0.9 %) | 8 (0.8 %) | 8 (0.6 %) | 12 (0.6 %) | 35 (0.7 %) |
| Cardiogenic shock | 32 (4.0 %) | 41 (3.9 %) | 72 (5.3 %) | 91 (4.5 %) | 236 (4.5 %) |
| Cardiac arrest | 8 (1.0 %) | 14 (1.3 %) | 13 (1.0 %) | 6 (0.3 %) | 41 (0.8 %) |
| Acute renal failure | 115 (14.5 %) | 147 (13.9 %) | 208 (15.4 %) | 286 (14.3 %) | 756 (14.5 %) |
| Cardiac tamponade | 1 (0.1 %) | 7 (0.7 %) | 3 (0.2 %) | 9 (0.4 %) | 20 (0.4 %) |
Values are displayed as mean (SD), median [ interquartile range].] or frequency (percent). TEER, transcatheter edge-to-edge repair.
Fig. 1.
Patient flow diagram. This figure displays the number of patients who underwent mitral transcatheter edge-to-edge repair with the MitraClip® system in the starting and final cohort after exclusion of patients below the age of 18 years, non-elective or emergency admissions, procedures on other cardiac valves and with missing values.
3.1. Primary outcomes: Healthcare resource utilization
Hospital length of stay. The average mitral TEER-related hospital LOS between 2016 and 2019 was 2 days [[1], [2], [3], [4]], with 2,321 (44.5 %) patients staying in the hospital overnight. Hospital LOS decreased incrementally by 21 % [95 % CI 0.74–0.85] between 2016 and 2019 (P < 0.001) (Table 2 and Fig. 2). A higher comorbidity level was also associated with an incremental increase in hospital LOS, e.g. by 142 % [95 % CI 1.60–3.80] in patients with CCI of 10 (P < 0.001). Results remained robust after excluding patients who died in the hospital (Sup. Table S1).
Table 2.
Outcomes of patients undergoing mitral TEER in the United States between 2016 and 2019 (N = 5,212).
| Outcomes | 2016 | 2017 | 2018 | 2019 |
|---|---|---|---|---|
| Healthcare resource utilization | ||||
| Hospital length of stay | 1 | 0.87 [0.80, 0.94] | 0.88 [0.82, 0.95] | 0.79 [0.74, 0.85] |
| Hospital costs | 1 | 0.95 [0.91, 0.99] | 0.94 [0.90, 0.98] | 0.92 [0.88, 0.95] |
| Adverse discharge | 1 | 0.75 [0.56, 1.02] | 0.75 [0.56, 1.0] | 0.59 [0.45, 0.78] |
| Safety endpoints | ||||
| Combined safety endpoint* | 1 | 0.86 [0.67, 1.09] | 0.90 [0.72, 1.13] | 0.73 [0.59, 0.91] |
| In-hospital mortality | 1 | 1.03 [0.49, 2.24] | 1.30 [0.67, 2.68] | 0.69 [0.34, 1.45] |
| Post-procedural bleeding | 1 | 0.98 [0.61, 1.58] | 0.66 [0.41, 1.08] | 0.59 [0.38, 0.94] |
| Vascular complications | 1 | 0.43 [0.01, 13.4] | 0.03 [0.0, 2.99] | 0.04 [0.0, 2.38] |
| Vascular complications requiring surgery | Omitted due to few event rates. | |||
| Ischemic stroke | 1 | 0.67 [0.23, 1.94] | 0.75 [0.30, 2.0] | 0.51 [0.20, 1.36] |
| Hemorrhagic stroke | Omitted due to few event rates. | |||
| Transient ischemic attack | 1 | 0.41 [0.04, 3.21] | 0.38 [0.04, 2.88] | 0.13 [0.01, 1.22] |
| New pacemaker implantation | 1 | 0.89 [0.31, 2.61] | 0.68 [0.24, 1.99] | 0.67 [0.26, 1.84] |
| Cardiogenic shock | 1 | 0.96 [0.59, 1.58] | 1.33 [0.86, 2.09] | 1.04 [0.69, 1.62] |
| Cardiac arrest | 1 | 1.34 [0.56, 3.48] | 0.91 [0.37, 2.37] | 0.27 [0.09, 0.81] |
| Acute renal failure | 1 | 0.90 [0.68, 1.18] | 0.98 [0.76, 1.28] | 0.87 [0.68, 1.12] |
| Cardiac tamponade | 1 | 5.92 [1.0, 113] | 1.49 [0.18, 30.8] | 3.82 [0.69, 71.5] |
Values are displayed as odds ratio (OR) or incidence rate ratio (IRR) [95% Confidence Interval]. Multivariable regression analyses were adjusted for 13 confounders. TEER, transcatheter edge-to-edge repair.
*Inclusion of all single safety endpoints.
Fig. 2.
Primary and secondary outcomes. Peri-procedural outcomes stratified by year of mitral transcatheter edge-to-edge repair with the MitraClip® system. Odds Ratios and Incidence Rate Ratios for primary (a-b) and secondary outcomes (c-e) are displayed for each year between 2016 and 2019.
Adverse discharge disposition. 4,704 (90.3 %) patients were successfully discharged home after mitral TEER. Adverse discharge rates after mitral TEER decreased by 41 % [95 % CI 0.45–0.78] from 12.2 % (97 out of 792 patients) in 2016 to 8.3 % (167 out of 2,007 patients) in 2019 (P < 0.001) (Table 1, Table 2 and Fig. 2). Compared to patients with successful home discharge, patients with an adverse discharge disposition were older (80.3 [±8.8] vs. 77.4 [±10.2] years) and more frequently female (55.3 % vs. 45.6 %), had a longer index hospital LOS (9 [[4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16]] vs. 2 [[1], [2], [3]] days), more frequently post-procedural bleedings (6.5 % vs. 2.9 %), ischemic strokes (4.5 % vs. 0.4 %), ICD implantations (3.1 % vs. 0.4 %), renal failures (40.4 % vs. 11.7 %), cardiac arrests (2.6 % vs. 0.6 %) and cardiogenic shocks (16.9 % vs. 3.2 %), and were less frequently privately insured (7.1 % vs. 9.5 %) (Table 3).
Table 3.
Characteristics of patients undergoing mitral TEER stratified by adverse discharge disposition.
| No adverse discharge |
Adverse discharge |
Total |
|
|---|---|---|---|
| (N = 4,704) | (N = 508) | (N = 5,212) | |
| Patient characteristics | |||
| Year | |||
| 2016 | 695 (14.8 %) | 97 (19.1 %) | 792 (15.2 %) |
| 2017 | 952 (20.2 %) | 107 (21.1 %) | 1,059 (20.3 %) |
| 2018 | 1,217 (25.9 %) | 137 (27.0 %) | 1,354 (26.0 %) |
| 2019 | 1,840 (39.1 %) | 167 (32.9 %) | 2,007 (38.5 %) |
| Age | 77.4 (10.2) | 80.3 (8.8) | 77.7 (10.1) |
| Age groups | |||
| ≥ 75 years | 3,244 (69.0 %) | 401 (78.9 %) | 3,645 (69.9 %) |
| ≥ 65 years | 913 (19.4 %) | 80 (15.7 %) | 993 (19.1 %) |
| ≤ 64 years | 547 (11.6 %) | 27 (5.3 %) | 574 (11.0 %) |
| Sex | |||
| Male | 2,560 (54.4 %) | 227 (44.7 %) | 2,787 (53.5 %) |
| Female | 2,144 (45.6 %) | 281 (55.3 %) | 2,425 (46.5 %) |
| Ethnicity | |||
| Caucasian | 3,776 (80.3 %) | 415 (81.7 %) | 4,191 (80.4 %) |
| Hispanic | 293 (6.2 %) | 25 (4.9 %) | 318 (6.1 %) |
| African American | 388 (8.2 %) | 45 (8.9 %) | 433 (8.3 %) |
| Other | 101 (2.1 %) | 12 (2.4 %) | 113 (2.2 %) |
| Asian/Pacific Island | 126 (2.7 %) | 9 (1.8 %) | 135 (2.6 %) |
| Native American | 20 (0.4 %) | 2 (0.4 %) | 22 (0.4 %) |
| Insurance type | |||
| Public | 4,161 (88.5 %) | 467 (91.9 %) | 4,628 (88.8 %) |
| Other | 77 (1.6 %) | 3 (0.6 %) | 80 (1.5 %) |
| Private | 449 (9.5 %) | 36 (7.1 %) | 485 (9.3 %) |
| Self-payer | 17 (0.4 %) | 2 (0.4 %) | 19 (0.4 %) |
| Healthcare resource utilization | |||
| Hospital length of stay (days) | 2.0 [1.0, 3.0] | 9.0 [4.0, 16.0] | 2.0 [1.0, 4.0] |
| Hospital costs | 40,400 [30,900, 53,900] | 58,400 [40,700, 83,700] | 41,500 [31,400, 56,200] |
| (US dollars) | |||
| Hospital characteristics | |||
| Hospital teaching status | |||
| Rural | 31 (0.7 %) | 2 (0.4 %) | 33 (0.6 %) |
| Urban nonteaching | 351 (7.5 %) | 29 (5.7 %) | 380 (7.3 %) |
| Urban teaching | 4,322 (91.9 %) | 477 (93.9 %) | 4,799 (92.1 %) |
| Hospital bedsize | |||
| Large (≥ 450) | 3,582 (76.1 %) | 377 (74.2 %) | 3,959 (76.0 %) |
| Medium (250–449) | 824 (17.5 %) | 105 (20.7 %) | 929 (17.8 %) |
| Small (≤ 249) | 298 (6.3 %) | 26 (5.1 %) | 324 (6.2 %) |
| Hospital division | |||
| New England | 156 (3.3 %) | 40 (7.9 %) | 196 (3.8 %) |
| Middle Atlantic | 656 (13.9 %) | 93 (18.3 %) | 749 (14.4 %) |
| East North Central | 559 (11.9 %) | 69 (13.6 %) | 628 (12.0 %) |
| West North Central | 327 (7.0 %) | 37 (7.3 %) | 364 (7.0 %) |
| South Atlantic | 1,030 (21.9 %) | 101 (19.9 %) | 1,131 (21.7 %) |
| East South Central | 284 (6.0 %) | 23 (4.5 %) | 307 (5.9 %) |
| West South Central | 401 (8.5 %) | 38 (7.5 %) | 439 (8.4 %) |
| Mountain | 466 (9.9 %) | 36 (7.1 %) | 502 (9.6 %) |
| Pacific | 825 (17.5 %) | 71 (14.0 %) | 896 (17.2 %) |
| Patient comorbidities | |||
| Charlson Comorbidity Index | 3.0 [1.0, 4.0] | 3.0 [2.0, 5.0] | 3.0 [1.0, 4.0] |
| 0 | 276 (5.9 %) | 9 (1.8 %) | 285 (5.5 %) |
| 1 | 996 (21.2 %) | 65 (12.8 %) | 1,061 (20.4 %) |
| 2 | 914 (19.4 %) | 72 (14.2 %) | 986 (18.9 %) |
| 3 | 823 (17.5 %) | 109 (21.5 %) | 932 (17.9 %) |
| 4 | 602 (12.8 %) | 73 (14.4 %) | 675 (13.0 %) |
| 5 | 494 (10.5 %) | 84 (16.5 %) | 578 (11.1 %) |
| 6 | 319 (6.8 %) | 49 (9.6 %) | 368 (7.1 %) |
| 7 | 164 (3.5 %) | 22 (4.3 %) | 186 (3.6 %) |
| 8 | 68 (1.4 %) | 17 (3.3 %) | 85 (1.6 %) |
| 9 | 26 (0.6 %) | 5 (1.0 %) | 31 (0.6 %) |
| 10 | 12 (0.3 %) | 1 (0.2 %) | 13 (0.2 %) |
| 11 | 4 (0.1 %) | 0 (0 %) | 4 (0.1 %) |
| 12 | 3 (0.1 %) | 1 (0.2 %) | 4 (0.1 %) |
| 13 | 2 (0.0 %) | 1 (0.2 %) | 3 (0.1 %) |
| 14 | 1 (0.0 %) | 0 (0 %) | 1 (0.0 %) |
| Cardiovascular risk profile | 3.0 [2.0, 4.0] | 3.0 [2.0, 4.0] | 3.0 [2.0, 4.0] |
| 0 | |||
| 1 | 42 (0.9 %) | 3 (0.6 %) | 45 (0.9 %) |
| 2 | 454 (9.7 %) | 34 (6.7 %) | 488 (9.4 %) |
| 3 | 1,086 (23.1 %) | 117 (23.0 %) | 1,203 (23.1 %) |
| 4 | 1,777 (37.8 %) | 189 (37.2 %) | 1,966 (37.7 %) |
| 5 | 1,068 (22.7 %) | 117 (23.0 %) | 1,185 (22.7 %) |
| 6 | 251 (5.3 %) | 45 (8.9 %) | 296 (5.7 %) |
| 26 (0.6 %) | 3 (0.6 %) | 29 (0.6 %) | |
| CHA2DS2-VASc score | 4.0 [3.0, 5.0] | 5.0 [4.0, 5.0] | 4.0 [3.0, 5.0] |
| 0 | 23 (0.5 %) | 0 (0 %) | 23 (0.4 %) |
| 1 | 77 (1.6 %) | 0 (0 %) | 77 (1.5 %) |
| 2 | 308 (6.5 %) | 13 (2.6 %) | 321 (6.2 %) |
| 3 | 833 (17.7 %) | 56 (11.0 %) | 889 (17.1 %) |
| 4 | 1,540 (32.7 %) | 138 (27.2 %) | 1,678 (32.2 %) |
| 5 | 1,444 (30.7 %) | 203 (40.0 %) | 1,647 (31.6 %) |
| 6 | 416 (8.8 %) | 85 (16.7 %) | 501 (9.6 %) |
| 7 | 63 (1.3 %) | 13 (2.6 %) | 76 (1.5 %) |
| HAS-BLED-Score | 2.0 [2.0, 3.0] | 3.0 [2.0, 3.0] | 2.0 [2.0, 3.0] |
| 0 | 90 (1.9 %) | 2 (0.4 %) | 92 (1.8 %) |
| 1 | 713 (15.2 %) | 44 (8.7 %) | 757 (14.5 %) |
| 2 | 2,317 (49.3 %) | 184 (36.2 %) | 2,501 (48.0 %) |
| 3 | 1,546 (32.9 %) | 265 (52.2 %) | 1,811 (34.7 %) |
| 4 | 38 (0.8 %) | 13 (2.6 %) | 51 (1.0 %) |
| Atrial fibrillation or flutter | 2,838 (60.3 %) | 360 (70.9 %) | 3,198 (61.4 %) |
| Post-procedural complications | |||
| In-hospital mortality | 85 (1.8 %) | 0 (0 %) | 85 (1.6 %) |
| Post-procedural bleeding | 138 (2.9 %) | 33 (6.5 %) | 171 (3.3 %) |
| Vascular complications | 3 (0.1 %) | 1 (0.2 %) | 4 (0.1 %) |
| Vascular complications requiring surgery | 2 (0.0 %) | 0 (0 %) | 2 (0.0 %) |
| Ischemic stroke | 19 (0.4 %) | 23 (4.5 %) | 42 (0.8 %) |
| Hemorrhagic stroke | 2 (0.0 %) | 0 (0 %) | 2 (0.0 %) |
| Transient ischemic attack | 6 (0.1 %) | 2 (0.4 %) | 8 (0.2 %) |
| New pacemaker implantation | 19 (0.4 %) | 16 (3.1 %) | 35 (0.7 %) |
| Cardiogenic shock | 150 (3.2 %) | 86 (16.9 %) | 236 (4.5 %) |
| Cardiac arrest | 28 (0.6 %) | 13 (2.6 %) | 41 (0.8 %) |
| Acute renal failure | 551 (11.7 %) | 205 (40.4 %) | 756 (14.5 %) |
| Pericardial tamponade | 15 (0.3 %) | 5 (1.0 %) | 20 (0.4 %) |
Values are displayed as frequency (percent), mean (standard deviation) and median [interquartile range]. TEER, transcatheter edge-to-edge repair.
*Inclusion of all single safety endpoints.
Hospital costs. The average costs for a mitral TEER-related hospital stay amounted to 41,500 US-$ [31,400–56,200] per patient between 2016 and 2019 (Table 1). Hospital costs were reduced by 8 % [95 % CI 0.88–0.95] between 2016 and 2019 (P < 0.001) (Table 2 and Fig. 2). Paralleling the pattern for LOS, hospital costs increased incrementally with patient comorbidity level, e.g. by 46 % [95 % CI 1.12–1.95], P = 0.007 in patients with a CCI of 10 compared to a CCI of 1.
3.2. Secondary outcomes: Safety
In-hospital mortality and peri-procedural complications were low in this patient population: 85 (1.6 %) patients died during hospitalization after mitral TEER, post-procedural bleeding occurred in 171 (3.3 %) patients, ischemic stroke in 42 (0.8 %) patients, cardiogenic shock in 236 (4.5 %) patients, cardiac arrest in 41 (0.8 %) patients, cardiac tamponade in 20 (0.4 %) patients and a new pacemaker was implanted in 35 (0.7 %) patients (Table 1).
Between 2016 and 2019, the composite safety outcome after mitral TEER improved by 27 % [95 % CI 0.59–0.91] (P = 0.005). Of note, within the study period, post-procedural bleeding and cardiac arrest were significantly reduced by 41 % [95 % CI 0.38–0.94], P = 0.022 and 73 % [95 % CI 0.09–0.81], P = 0.019, respectively (Table 2 and Fig. 2). The other safety endpoints showed decreasing numeric trends but no significant changes likely due to low general events rates.
There was a numeric decrease in in-hospital mortality from 1.6 % in 2016 to 1.1 % in 2019 (Table 1). Compared to survivors, the proportion of female (52.9 % vs. 46.4 %) and non-white patients (25.9 % vs. 19.5 %) was higher among deceased patients, while the proportion of privately insured patients was lower (3.5 % vs. 9.4 %). The hospital LOS for deceased patients was approximately six-fold longer (11 [[5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18]] days vs. 2 [[1], [2], [3], [4]] days) and the hospital expenditures were approximately two-fold higher (83,200 [56,400–133,000] US-$ vs. 41,200 [31,400–55,600] US-$). Expired patients were characterized by more comorbidities (CCI 4 vs. 3), had a higher stroke and bleeding risk (CHA2DS2-VASc score 5 vs. 4 and simplified HAS-BLED score 3 vs. 2), had more frequently post-procedural bleedings (15.3 % vs. 3.1 %), ischemic strokes (7.1 % vs. 0.7 %), renal failures (78.8 % vs. 13.4 %), cardiac arrests (17.6 % vs. 0.5 %) and cardiogenic shocks (55.3 % vs. 3.7 %) (Table 4).
Table 4.
Characteristics of patients undergoing mitral TEER stratified by survival status.
| Survived patients | Deceased patients | Total | |
|---|---|---|---|
| (N = 5,127) | (N = 85) | (N = 5,212) | |
| Patient characteristics | |||
| Year | |||
| 2016 | 779 (15.2 %) | 13 (15.3 %) | 792 (15.2 %) |
| 2017 | 1,038 (20.2 %) | 21 (24.7 %) | 1,059 (20.3 %) |
| 2018 | 1,326 (25.9 %) | 28 (32.9 %) | 1,354 (26.0 %) |
| 2019 | 1,984 (38.7 %) | 23 (27.1 %) | 2,007 (38.5 %) |
| Age | 77.7 (10.1) | 78.9 (8.0) | 77.7 (10.1) |
| Age group | |||
| ≥ 75 years | 3,583 (69.9 %) | 62 (72.9 %) | 3,645 (69.9 %) |
| ≥ 65 years | 975 (19.0 %) | 18 (21.2 %) | 993 (19.1 %) |
| ≤ 64 years | 569 (11.1 %) | 5 (5.9 %) | 574 (11.0 %) |
| Sex | |||
| Male | 2,747 (53.6 %) | 40 (47.1 %) | 2,787 (53.5 %) |
| Female | 2,380 (46.4 %) | 45 (52.9 %) | 2,425 (46.5 %) |
| Ethnicity | |||
| Caucasian | 4,128 (80.5 %) | 63 (74.1 %) | 4,191 (80.4 %) |
| Hispanic | 309 (6.0 %) | 9 (10.6 %) | 318 (6.1 %) |
| African American | 426 (8.3 %) | 7 (8.2 %) | 433 (8.3 %) |
| Other | 111 (2.2 %) | 2 (2.4 %) | 113 (2.2 %) |
| Asian/Pacific Island | 132 (2.6 %) | 3 (3.5 %) | 135 (2.6 %) |
| Native American | 21 (0.4 %) | 1 (1.2 %) | 22 (0.4 %) |
| Insurance type | |||
| Public | 4,546 (88.7 %) | 82 (96.5 %) | 4,628 (88.8 %) |
| Other | 80 (1.6 %) | 0 (0 %) | 80 (1.5 %) |
| Private | 482 (9.4 %) | 3 (3.5 %) | 485 (9.3 %) |
| Self-payer | 19 (0.4 %) | 0 (0 %) | 19 (0.4 %) |
| Healthcare resource utilization | |||
| Hospital length of stay (days) | 2.0 [1.0, 4.0] | 11.0 [5.0, 18.0] | 2.0 [1.0, 4.0] |
| Hospital costs | 41,200 [31,400, 55,600] | 83,200 [56,400, 133,000] | 41,500 [31,400, 56,200] |
| (US dollars) | |||
| Hospital characteristics | |||
| Hospital bedsize | |||
| Large (≥ 450) | 3,891 (75.9 %) | 68 (80.0 %) | 3,959 (76.0 %) |
| Medium (250–449) | 917 (17.9 %) | 12 (14.1 %) | 929 (17.8 %) |
| Small (≤ 249) | 319 (6.2 %) | 5 (5.9 %) | 324 (6.2 %) |
| Hospital division | |||
| New England | 193 (3.8 %) | 3 (3.5 %) | 196 (3.8 %) |
| Middle Atlantic | 734 (14.3 %) | 15 (17.6 %) | 749 (14.4 %) |
| East North Central | 622 (12.1 %) | 6 (7.1 %) | 628 (12.0 %) |
| West North Central | 358 (7.0 %) | 6 (7.1 %) | 364 (7.0 %) |
| South Atlantic | 1,112 (21.7 %) | 19 (22.4 %) | 1,131 (21.7 %) |
| East South Central | 300 (5.9 %) | 7 (8.2 %) | 307 (5.9 %) |
| West South Central | 435 (8.5 %) | 4 (4.7 %) | 439 (8.4 %) |
| Mountain | 492 (9.6 %) | 10 (11.8 %) | 502 (9.6 %) |
| Pacific | 881 (17.2 %) | 15 (17.6 %) | 896 (17.2 %) |
| Hospital teaching status | |||
| Rural | 33 (0.6 %) | 0 (0 %) | 33 (0.6 %) |
| Urban non-teaching | 370 (7.2 %) | 10 (11.8 %) | 380 (7.3 %) |
| Urban teaching | 4,724 (92.1 %) | 75 (88.2 %) | 4,799 (92.1 %) |
| Patient comorbidities | |||
| Charlson Comorbidity Index | 3.0 [1.0, 4.0] | 4.0 [3.0, 6.0] | 3.0 [1.0, 4.0] |
| 0 | 285 (5.6 %) | 0 (0 %) | 285 (5.5 %) |
| 1 | 1,048 (20.4 %) | 13 (15.3 %) | 1,061 (20.4 %) |
| 2 | 979 (19.1 %) | 7 (8.2 %) | 986 (18.9 %) |
| 3 | 911 (17.8 %) | 21 (24.7 %) | 932 (17.9 %) |
| 4 | 666 (13.0 %) | 9 (10.6 %) | 675 (13.0 %) |
| 5 | 565 (11.0 %) | 13 (15.3 %) | 578 (11.1 %) |
| 6 | 357 (7.0 %) | 11 (12.9 %) | 368 (7.1 %) |
| 7 | 183 (3.6 %) | 3 (3.5 %) | 186 (3.6 %) |
| 8 | 80 (1.6 %) | 5 (5.9 %) | 85 (1.6 %) |
| 9 | 29 (0.6 %) | 2 (2.4 %) | 31 (0.6 %) |
| 10 | 12 (0.2 %) | 1 (1.2 %) | 13 (0.2 %) |
| 11 | 4 (0.1 %) | 0 (0 %) | 4 (0.1 %) |
| 12 | 4 (0.1 %) | 0 (0 %) | 4 (0.1 %) |
| 13 | 3 (0.1 %) | 0 (0 %) | 3 (0.1 %) |
| 14 | 1 (0.0 %) | 0 (0 %) | 1 (0.0 %) |
| Cardiovascular risk profile | |||
| 3.0 [2.0, 4.0] | 3.0 [2.0, 4.0] | 3.0 [2.0, 4.0] | |
| 0 | 45 (0.9 %) | 0 (0 %) | 45 (0.9 %) |
| 1 | 481 (9.4 %) | 7 (8.2 %) | 488 (9.4 %) |
| 2 | 1,181 (23.0 %) | 22 (25.9 %) | 1,203 (23.1 %) |
| 3 | 1,936 (37.8 %) | 30 (35.3 %) | 1,966 (37.7 %) |
| 4 | 1,167 (22.8 %) | 18 (21.2 %) | 1,185 (22.7 %) |
| 5 | 289 (5.6 %) | 7 (8.2 %) | 296 (5.7 %) |
| 6 | 28 (0.5 %) | 1 (1.2 %) | 29 (0.6 %) |
| CHA2DS2-VASc score | 4.0 [3.0, 5.0] | 5.0 [4.0, 5.0] | 4.0 [3.0, 5.0] |
| 0 | 23 (0.4 %) | 0 (0 %) | 23 (0.4 %) |
| 1 | 76 (1.5 %) | 1 (1.2 %) | 77 (1.5 %) |
| 2 | 317 (6.2 %) | 4 (4.7 %) | 321 (6.2 %) |
| 3 | 880 (17.2 %) | 9 (10.6 %) | 889 (17.1 %) |
| 4 | 1,653 (32.2 %) | 25 (29.4 %) | 1,678 (32.2 %) |
| 5 | 1,620 (31.6 %) | 27 (31.8 %) | 1,647 (31.6 %) |
| 6 | 484 (9.4 %) | 17 (20.0 %) | 501 (9.6 %) |
| 7 | 74 (1.4 %) | 2 (2.4 %) | 76 (1.5 %) |
| HAS-BLED-Score | 2.0 [2.0, 3.0] | 3.0 [3.0, 3.0] | 2.0 [2.0, 3.0] |
| 0 | 92 (1.8 %) | 0 (0 %) | 92 (1.8 %) |
| 1 | 752 (14.7 %) | 5 (5.9 %) | 757 (14.5 %) |
| 2 | 2,489 (48.5 %) | 12 (14.1 %) | 2,501 (48.0 %) |
| 3 | 1,760 (34.3 %) | 51 (60.0 %) | 1,811 (34.7 %) |
| 4 | 34 (0.7 %) | 17 (20.0 %) | 51 (1.0 %) |
| Atrial fibrillation or flutter | 3,146 (61.4 %) | 52 (61.2 %) | 3,198 (61.4 %) |
| Post-procedural complications | |||
| Post-procedural bleeding | 158 (3.1 %) | 13 (15.3 %) | 171 (3.3 %) |
| Vascular complications | 4 (0.1 %) | 0 (0 %) | 4 (0.1 %) |
| Vascular complications requiring surgery | 2 (0.0 %) | 0 (0 %) | 2 (0.0 %) |
| Ischemic stroke | 36 (0.7 %) | 6 (7.1 %) | 42 (0.8 %) |
| Hemorrhagic stroke | 1 (0.0 %) | 1 (1.2 %) | 2 (0.0 %) |
| Transient ischemic attack | 7 (0.1 %) | 1 (1.2 %) | 8 (0.2 %) |
| New pacemaker implantation | 34 (0.7 %) | 1 (1.2 %) | 35 (0.7 %) |
| Cardiogenic shock | 189 (3.7 %) | 47 (55.3 %) | 236 (4.5 %) |
| Cardiac arrest | 26 (0.5 %) | 15 (17.6 %) | 41 (0.8 %) |
| Acute renal failure | 689 (13.4 %) | 67 (78.8 %) | 756 (14.5 %) |
| Pericardial tamponade | 18 (0.4 %) | 2 (2.4 %) | 20 (0.4 %) |
Values are displayed as frequency (percent), mean (standard deviation) and median [interquartile range]. TEER, transcatheter edge-to-edge repair.
3.3. Geographic analyses
With an exploratory intent, adverse discharge disposition and safety outcomes were analyzed across US states stratified by patient sex. The prevalence of in-hospital mortality, ischemic stroke, pacemaker implantation, cardiogenic shock and cardiac arrest varied strongly across US regions in male and female patients, while the other complications were more evenly distributed across the US (Fig. 3).
Fig. 3.
Outcomes across US regions stratified by patient sex. Peri-procedural in-hospital event rates stratified by female and male patients undergoing mitral transcatheter edge-to-edge repair with the MitraClip® system. This figure displays the event rates for peri-procedural outcomes (I-X) in female (a) and male (b) patients. Shades of blue color indicate lower event rates, while shades of red color indicate higher event rates. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
3.4. Exploratory analyses
4,020 patients received elective mitral TEER with increasing numbers between 2016 and 2019 (Sup. Table S2). The age, sex distribution, CCI, CHA2DS2-VASc-Score and simplified HAS-BLED score of patients undergoing elective mitral TEER were similar to the primary cohort. Though, compared to all cases, patients with elective cases had shorter hospital LOS with 1 [1,2] days (compared to 2 [[1], [2], [3], [4]] days), lower rates of adverse discharge with 6.2 % (compared to 9.7 %), in-hospital mortality with 0.8 % (compared to 1.6 %), cardiogenic shock with 1.6 % (compared to 4.5 %) and acute renal failure with 7.8 % (compared to 14.5 %), respectively. Primary results across the study period remained robust after excluding patients with non-elective or emergency mitral TEER (Sup. Table S3): Similar to the primary analyses, hospital LOS decreased by 22 % [95 % CI 0.73–0.83], adverse discharge disposition by 40 % [95 % CI 0.41–0.88], hospital costs by 6 % [95 % CI 0.90–0.98], the composite safety endpoint by 34 % [95 % CI 0.50–0.89], post-procedural bleeding by 55 % [95 % CI 0.27–0.76] and cardiac arrest by 87 % [95 % CI 0.02–0.61] between 2016 and 2019.
4. Discussion
Mitral TEER has become a safer and more efficient procedure with decreasing hospitalization length, adverse discharge rate, hospital costs and peri-procedural complications between 2016 and 2019. Careful considerations should be taken when performing the procedure in patients with multiple comorbidities.
The considerably improved efficiency and safety outcomes after mitral TEER within the study period might be explained by four reasons: Rapid technical improvement, patient-tailored heart team decision making, procedural learning curve and optimized anesthesia. First, mitral TEER is one of the rapidly evolving fields in interventional cardiology.[27] During the study period, new MitraClip® generations have been developed or were available for interventionalists, which allowed for patient-tailored leaflet repair based on etiology of MR, valve anatomy, valve lesion and condition of the patient to maximize patient outcome and reduce healthcare resource utilization. The MitraClip® system underwent continuous developments from NT (2016) and NTR / XTR models (2018) to the fourth-generation model (2019), including different clip sizes as well as improved gripper lines and controlled grasping angles.[12] Alternatively, the PASCAL® system – although not included in this study − might be applied in patients which do not fulfill the so-called EVEREST criteria for the MitraClip®, as the PASCAL® system has larger paddles, including a central spacer, to maximize grasping ability and leaflet coaptation, to allow for independent leaflet capture and precise leaflet positioning. Apart from novel device developments, procedural monitoring has improved, such as continuous intra-procedural left atrial pressure monitoring. Additionally, recently developed patients-specific simulation models on MitraClip® placement might help to identify optimal locations in patients.[28].
Second, based on guideline recommendations, the multidisciplinary heart team has gained increasing importance to evaluate the treatment strategy of severe valvular heart diseases over the past years.[2] Indeed, heart team decisions have been shown to improve peri-procedural outcomes after TMVr.[29] Given the broad spectrum of available mitral TEER devices, specific therapies and devices might be selected in a multidisciplinary manner to offer the best possible patient-tailored treatment to each individual type of MR.
Third, the operator and institutional experience were associated with less complications, shorter procedural duration and hospital LOS after TEER in Transcatheter Valve Therapy Registry data of the Society of Thoracic Surgeons and American College of Cardiology.[30,31] In this study, mitral TEER procedures have more than doubled from 594 cases in 2016 to 1,571 cases in 2019. Most mitral TEER procedures in this study were performed in large US hospitals (75.9 % of cases) and in regional “hubs” (such as in the South Atlantic and Pacific region). Smaller hospitals showed higher mortality rates than larger hospital in this study, reinforcing the importance of centralized care. To ensure peri-procedural quality, national societies proposed national standards on TMVr infrastructure and case volumes which are tied to case volumes of surgical mitral valve repair or replacement.[32] The findings in this study suggest that mitral TEER has been performed in fewer specialized centers of excellence with capacities for surgical valve repair or replacement, while smaller hospitals might not have been able to fulfill the national standards. Indeed, institutions which have incorporated TMVr programs have been shown to have reduced mortality rates on a long-term basis.[33] Nevertheless, increasing the threshold of surgical valve procedures of TMVr centers might disproportionately impact rural regions and smaller hospitals despite MR being one of the most frequent valvular heart disorders in the US.
Fourth, new forms of anesthesia, such as “monitored conscious sedation” (MCS) derived from the field of transcatheter aortic valve implantation, are considered to be a “minimalist approach” with good peri-procedural outcomes, including reduction in procedural duration and costs.[[34], [35], [36]] However, the type of anesthesia used could not be identified in this study.
Of note, although this study cohort was comprised of a frail patient population with high age, multiple comorbidities (CCI), high stroke risk (CHA2DS2-VASc score) and intermediate bleeding risk (HAS-BLED score), the peri-procedural complication rate was low. More than ten percent of hospitalized patients above the age of 75 years are expected to have substantial MR, while approximately 50 % of patients with substantial MR are not eligible for mitral valve surgery.[3,37] As surgical procedures are deemed high risk for these patients, percutaneous valve repair has emerged as a viable alternative in recent years, given the growing life expectancy in developed countries.[33] A recent analysis from the COAPT trial showed that elderly patients had reduced mortality and heart failure hospitalizations as well as improved quality of life after mitral TEER, compared to optimal medical therapy alone.[38] Furthermore, recent studies have confirmed safe and effective procedural outcomes after mitral TEER in elderly patients.[39,40] Therefore, as shown in this study, frail patients might rather benefit from mitral TEER as a lower risk treatment option than surgical treatment resulting in accelerated recovery and clinical improvement based on key considerations such as age, comorbidities, type of regurgitation, left ventricular dysfunction and valvular anatomy. Nevertheless, careful considerations should be taken when performing the procedure in patients with a high degree of comorbidities, who showed increased hospital LOS and costs, while elderly patients had more frequently adverse discharge dispositions.
Notably, there was not a strong sex difference in provision of mitral TEER in this study population (53.5 % male vs. 46.5 % female). Nevertheless, female patients were observed to have numerically higher rates of adverse discharge disposition and in-hospital mortality compared to male patients. Additionally, complications rates varied strongly across US regions for male and female patients. Interestingly, there were no sex-related differences reported in clinical outcomes at two years after TEER in the EuroSMR registry and the COAPT trial as well as in a recent meta-analysis.[[41], [42], [43]] However, it should be taken into account that anatomical and physiological sex-related differences exist. For example, female patients have smaller left atrial and ventricular volumes as well as absolute regurgitation.[44].
This study should be interpreted in the context of certain limitations: The HCUP NIS data did not include information on laboratory data, medication (e.g. antithrombotic or anti-coagulation therapy) or imaging (e.g. degree of MR reduction or mitral orifice area) reports. Due to the lack of echocardiographic and imaging data within the HCUP NIS database, a detailed classification of mitral regurgitation etiology (i.e., primary vs. secondary MR) and further subclassification of secondary MR into atrial or ventricular forms was not feasible. Given the retrospective design, selection bias or confounding by indication could not be ruled out, although the analyses were adjusted for multiple a priori defined patient- and hospital-specific confounders. State-level analyses were not performed as the NIS is not considered to be representative of each individual US state; analyses on US hospital regions (comprised of multiple states) were performed instead. Additionally, the analyses were restricted to short‐term in-hospital outcomes following mitral TEER. Nonetheless, this study enabled to analyze risk factors on healthcare resource utilization and safety outcomes in a large nationwide cohort of patients undergoing mitral TEER in a real-world setting and the results were based on as‐treated analyses.
5. Conclusions
In conclusion, TEER with the Mitraclip® system has become a more efficient and safer procedure. Importantly, patients with multiple comorbidities had worse outcomes, wherefore caution is warranted in these patients. Further studies are required to investigate differences in long‐term safety and healthcare resource utilization after mitral TEER.
Funding sources
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Data availability statement
The data underlying this article are available at the Healthcare Cost and Utilization Project National Inpatient Sample from https://hcup-us.ahrq.gov/nisoverview.jsp.
CRediT authorship contribution statement
Tharusan Thevathasan: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Sophie Berlinghof: Writing – review & editing, Visualization, Validation, Methodology, Investigation, Formal analysis, Data curation. Daniel Elschenbroich: Writing – review & editing, Visualization, Validation, Methodology, Investigation, Formal analysis. Julia M. Wiedenhofer: Writing – review & editing, Validation, Methodology, Investigation, Formal analysis. Sêhnou Degbeon: Writing – review & editing, Validation, Methodology, Investigation, Formal analysis. Luise Holzhauser: Writing – review & editing, Validation, Resources, Investigation, Data curation. Fabian Barbieri: Writing – review & editing, Validation, Investigation, Data curation. Mario Kasner: Writing – review & editing, Validation, Investigation. Anna Brand: Writing – review & editing, Validation, Investigation, Data curation. Henryk Dreger: Writing – review & editing, Validation, Investigation, Data curation. Steffen Desch: Writing – review & editing, Validation, Investigation, Data curation. Ulf Landmesser: Writing – review & editing, Validation, Project administration, Investigation, Data curation, Conceptualization. Markus Reinthaler: Writing – review & editing, Validation, Resources, Investigation, Data curation, Conceptualization. Carsten Skurk: Writing – review & editing, Validation, Project administration, Investigation, Data curation, Conceptualization.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
None declared.
Author contributions:
Tharusan Thevathasan: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing.
Sophie Berlinghof: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review and editing.
Daniel Elschenbroich: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review and editing.
Julia M. Wiedenhofer: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review and editing.
Sêhnou Degbeon: Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review and editing.
Luise Holzhauser: Data curation, Investigation, Methodology, Writing – review and editing.
Fabian Barbieri: Data curation, Investigation, Methodology, Writing – review and editing.
Mario Kasner: Data curation, Investigation, Methodology, Writing – review and editing.
Anna Brand: Data curation, Investigation, Methodology, Writing – review and editing.
Henryk Dreger: Data curation, Investigation, Methodology, Writing – review and editing.
Steffen Desch: Data curation, Investigation, Methodology, Writing – review and editing.
Ulf Landmesser: Data curation, Investigation, Methodology, Resources, Supervision, Writing – review and editing.
Markus Reinthaler: Data curation, Investigation, Methodology, Writing – review and editing.
Carsten Skurk: Conceptualization, Data curation, Investigation, Project administration, Resources, Supervision, Writing – original draft, Writing – review and editing.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.ijcha.2025.101696.
Contributor Information
Tharusan Thevathasan, Email: tharusan.thevathasan@dhzc-charite.de.
Carsten Skurk, Email: carsten.skurk@dhzc-charite.de.
Appendix A. Supplementary data
The following are the Supplementary data to this article:
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Supplementary Materials
Data Availability Statement
The data underlying this article are available at the Healthcare Cost and Utilization Project National Inpatient Sample from https://hcup-us.ahrq.gov/nisoverview.jsp.