Abstract
As more patients undergo transcatheter aortic valve implantation (TAVI), knowledge of 1-year mortality and associated factors becomes increasingly important. After other cardiac procedures, discharge location has been shown to be associated with 1-year mortality. We examined outcomes of TAVI patients discharged home vs an extended care facility (ECF). All TAVI patients from January 1, 2012, to December 31, 2017, were evaluated. Cox proportional hazard regression models with cubic splines were used to estimate the adjusted effect of discharge to ECF on 1-year mortality. A total of 957 (85.6%) patients discharged home were compared to 160 (14.3%) discharged to ECF. On univariate analysis, patients discharged home were younger and had a lower Society of Thoracic Surgeons Predicted Risk of Mortality, higher albumin, and fewer vascular complications and strokes. Patients discharged to ECF had a higher 30-day mortality (3.8% vs. 0.5%, P = 0.001) and 1-year mortality (25.7% vs. 8.3%, P < 0.001). Cox proportional hazard regression models showed increased risk of 1-year mortality for patients discharged to ECF. In conclusion, patients discharged to ECF had a higher 30-day and 1-year mortality. The strongest predictor of 1-year mortality was discharge to ECF. Society of Thoracic Surgeons Predicted Risk of Mortality score was not a predictor of 1-year mortality.
Keywords: Extended care facility, non-home discharge, quality of life, TAVI
Transcatheter aortic valve implantation (TAVI) has become an acceptable alternative to surgical aortic valve replacement.1,2 As more patients become candidates for TAVI, knowledge of long-term outcomes becomes increasingly important. Several risk scores have been developed to predict 30-day and 1-year mortality following the procedure.3–5 Although the Society of Thoracic Surgeons Predicted Risk of Mortality (STS-PROM) is often used as a predictor of TAVI outcomes, it was developed for a surgical population and its use in this transcatheter procedure has not been validated. Discharge to an extended care facility (ECF) has been shown to be associated with both decreased quality of life6–9 and increased 1-year mortality10,11 after other cardiac surgical procedures. However, current literature demonstrating outcomes for patients discharged to an ECF following TAVI is limited. We have shown in previous work that non-home discharge is associated with increased mortality in cardiac surgical patients.12–14 Therefore, we hypothesized that discharge to ECF may also be associated with increased short- and long-term mortality in these transcatheter patients.
METHODS
Patients who underwent TAVI at a single center from January 1, 2012, through December 31, 2017, and were discharged alive were included in the study. Patient data was collected from a local institutional TAVI registry, the American College of Cardiology Transcatheter Valve Therapy Registry, and the Society of Thoracic Surgeons (STS) database. Discharge location and 1-year survival status were assessed using a previously described systematic review protocol and were known in 100% of cases.12 This study was approved by the institutional review board of Baylor Scott and White Medical Center (#014-209, June 2018), which waived the requirement for informed consent due to the retrospective nature of the study. We examined the outcomes of discharge location treated as a dichotomous variable. Patients discharged to an ECF, which included long-term acute care facilities, rehabilitation facilities, and skilled nursing facilities, were compared to patients discharged home. We have previously used this variable.13,14 The primary outcome was all-cause mortality at 1 year.
Analyses were performed using SAS 9.4 (SAS Institute, Cary, NC). Categorical variables were presented as proportions and continuous variables as mean ± standard deviation or median (range) as appropriate. Difference in characteristics between patients who were discharged home and to ECF were compared using a chi-square/Fisher’s exact test for proportions and Student’s t test/Wilcoxon rank sum test for continuous variables, as applicable. Similarly, demographic and baseline characteristics were compared between those who were alive and dead at 1 year.
Cox proportional hazard regression models were fitted to assess the adjusted effect of discharge to ECF on 1-year mortality. Two separate models were considered: Model 1 included race and STS risk score as independent predictors, while Model 2 included race, STS risk score, and postoperative variables (postoperative length of stay, vascular complications, and postoperative stroke/transient ischemic attack). These complications were included because they impart persistent debilitations that can affect 1-year mortality. More minor complications such as bleeding generally do not affect 1-year mortality, but may contribute to a longer length of stay. This was already accounted for in Model 2. Continuous risk factors were fitted with restricted cubic splines with 5 knots to avoid categorization or assumption of a linear relationship between continuous variables and the outcome and to prevent biased estimates. The concordance and R-square statistics were used to assess quality of the model fit. The concordance statistics for both of our models was 0.65, which is within the common range of 0.6 to 0.7 for survival models.
RESULTS
A total of 1117 patients were included in the study. Characteristics of the study population are presented in Table 1. The mean age was 82.3 ± 8.2 years, and 512 patients (45.8%) were women. In this cohort, 957 (85.7%) patients were discharged home compared to 160 (14.3%) discharged to an ECF. The mean STS-PROM was 6.9 ± 3.6 and the overall median length of stay was 3 days (range, 0–82). The median length of stay and percent of patients discharged to ECF both decreased over the study period (Table 2). By univariate analysis, patients discharged home were younger and had a lower STS-PROM, higher serum albumin, fewer vascular complications, and fewer neurologic events. Patients discharged to an ECF had a higher 30-day mortality (3.8% vs. 0.5%, P < 0.001) and 1-year mortality (25.6% vs. 8.3%, P < 0.001) (Figure 1). There was no difference in rate of readmissions (discharge to home, 12.2%; discharge to ECF, 15.6%; P = 0.23) (Table 1).
Table 1.
Patient characteristics and outcomes by discharge status
| Variable | Discharged to home (N = 957) | Discharged to facility (N = 160) | P value |
|---|---|---|---|
| Age (years): mean (SD) | 79.9 (8.7) | 83.0 (7.0) | <0.001 |
| Male sex | 533 (55.7%) | 72 (45.0%) | 0.012 |
| White, non-Hispanic | 843 (92.4%) | 126 (93.3%) | 0.710 |
| BMI (kg/m2): mean (SD) | 28.3 (6.5) | 27.7 (6.6) | 0.336 |
| STS PROM: mean (SD) | 6.5 (3.8) | 7.4 (3.5) | 0.009 |
| Serum albumin (g/dL): mean (SD) | 3.6 (0.4) | 3.5 (0.4) | 0.010 |
| Diabetes | 333 (46.1%) | 44 (37.0%) | 0.063 |
| Hypertension | 685 (94.9%) | 113 (95.0%) | 0.970 |
| Dialysis | 9 (1.3%) | 3 (2.5%) | 0.275 |
| Lung disease | 338 (47.1%) | 53 (45.3%) | 0.721 |
| Immunocompromised | 35 (13.6%) | 3 (4.8%) | 0.055 |
| Peripheral vascular disease | 255 (35.4%) | 54 (45.8%) | 0.031 |
| Coronary artery disease | 224 (31.2%) | 45 (38.1%) | 0.132 |
| Previous CABG | 253 (37.5%) | 40 (35.1%) | 0.625 |
| Previous MI | 179 (25.0%) | 27 (22.9%) | 0.627 |
| NYHA III/IV | 642 (67.1%) | 105 (65.6%) | 0.717 |
| Prior PPM | 184 (19.2%) | 33 (20.6%) | 0.679 |
| Postop LOS: median (range) | 2.0 (1.0, 4.0) | 7.0 (5.0, 10.0) | <0.001 |
| Stroke/TIA postprocedure | 14 (1.5%) | 15 (9.4%) | <0.001 |
| Vascular complications | 88 (9.2%) | 26 (16.2%) | 0.006 |
| Mortality (30-day) | 5 (0.5%) | 6 (3.8%) | <0.001 |
| Mortality (1-year) | 79 (8.3%) | 41 (25.6%) | <0.001 |
| Readmission in 30 days | 117 (12.2%) | 25 (15.6%) | 0.232 |
BMI indicates body mass index; CABG, coronary artery bypass graft; LOS, length of stay; MI, myocardial infarction; NYHA, New York Heart Association; PPM, permanent pacemaker; SD, standard deviation; STS-PROM, Society of Thoracic Surgeons Predicted Risk of Mortality; TIA, transient ischemic attack.
Table 2.
Length of stay and discharge to extended care facility
| 2012 (N = 52) | 2013 (N = 119) | 2014 (N = 156) | 2015 (N = 225) | 2016 (N = 247) | 2017 (N = 318) | P value | |
|---|---|---|---|---|---|---|---|
| Postop LOS (days): median (range) | 6.0 (4.0, 8.2) |
5.0 (3.0, 7.0) |
3.0 (2.0, 5.0) |
3.0 (2.0, 5.0) |
1.0 (1.0, 3.0) |
1.0 (1.0, 2.0) |
<0.001 |
| LOS (days): median (range) | 7.0 (5.8, 10.0) |
6.0 (4.0, 8.0) |
3.0 (2.0, 5.2) |
3.0 (2.0, 5.0) |
1.0 (1.0, 3.0) |
1.0 (1.0, 2.0) |
<0.001 |
| Discharge to ECF | 21 (40.4%) |
29 (24.4%) |
29 (18.6%) |
35 (15.6%) |
16 (6.5%) |
30 (9.4%) |
<0.001 |
ECF indicates extended care facility; LOS, length of stay.
Figure 1.
One-year mortality by discharge location.
A univariate analysis of 30-day and 1-year mortality is presented in Table 3. Unadjusted and adjusted hazard ratios (HR) for 1-year mortality are provided in Table 4. Prior to adjusting, discharge to ECF conferred a HR for 1-year mortality of 3.19. After adjusting the study population for baseline variables, discharge to ECF remained significant with a HR of 3.19 (Table 4, Model 1). Even after adjustment for both baseline characteristics and postoperative complications, discharge to ECF still carried a significant and essentially unchanged risk for 1-year mortality (HR 2.23, P = 0.0001; Table 4, Model 2). The adjusted effect of STS risk score on 1-year mortality was relatively constant for STS < 10 and STS > 10, but increased for a STS risk score of 5 to 10 (Figure 2a). In general, an increase in postoperative length of stay was associated with increased risk of mortality (Figure 2b).
Table 3.
Univariate analysis: 30-day and 1-year mortality
| Variable | 30-day mortality |
1-year mortality |
||||
|---|---|---|---|---|---|---|
| Alive (N = 1106) | Died (N = 11) | P value | Alive (N = 997) | Died (N = 120) | P value | |
| Age (years): mean (SD) | 80.3 (8.5) | 84.7 (8.8) | 0.088 | 80.2 (8.6) | 81.2 (8.1) | 0.223 |
| Men | 599 (54.2%) | 6 (54.5%) | 0.980 | 529 (53.1%) | 76 (63.3%) | 0.033 |
| White, non-Hispanic | 960 (92.5%) | 9 (100.0%) | 0.393 | 864 (92.1%) | 105 (96.3%) | 0.112 |
| BMI: mean (SD) | 28.3 (6.5) | 27.2 (8.1) | 0.635 | 28.5 (6.6) | 26.3 (5.4) | 0.001 |
| STS-PROM: mean (SD) | 6.6 (3.7) | 8.4 (4.8) | 0.123 | 6.6 (3.7) | 7.2 (3.7) | 0.078 |
| Albumin (g/dL): mean (SD) | 3.6 (0.4) | 3.5 (0.5) | 0.375 | 3.6 (0.4) | 3.5 (0.4) | 0.006 |
| Diabetes mellitus | 376 (45.2%) | 1 (11.1%) | 0.041 | 339 (45.4%) | 38 (40.4%) | 0.363 |
| Hypertension | 790 (95.0%) | 8 (88.9%) | 0.411 | 710 (95.0%) | 88 (93.6%) | 0.553 |
| Dialysis | 11 (1.3%) | 1 (11.1%) | 0.014 | 9 (1.2%) | 3 (3.2%) | 0.129 |
| Lung disease | 389 (47.1%) | 2 (22.2%) | 0.137 | 351 (47.4%) | 40 (42.6%) | 0.378 |
| Immunocompromised | 37 (11.8%) | 1 (16.7%) | 0.717 | 34 (12.2%) | 4 (10.0%) | 0.690 |
| Peripheral vascular disease | 305 (36.8%) | 4 (44.4%) | 0.636 | 270 (36.3%) | 39 (41.5%) | 0.325 |
| Coronary artery disease | 264 (31.9%) | 5 (55.6%) | 0.130 | 227 (30.6%) | 42 (44.7%) | 0.006 |
| Previous CABG | 291 (37.3%) | 2 (22.2%) | 0.352 | 265 (37.9%) | 28 (31.5%) | 0.239 |
| Previous MI | 204 (24.7%) | 2 (22.2%) | 0.864 | 184 (24.8%) | 22 (23.4%) | 0.762 |
| NYHA III/IV | 739 (66.8%) | 8 (72.7%) | 0.679 | 665 (66.7%) | 82 (68.3%) | 0.719 |
| Prior PPM | 217 (19.6%) | 0 (0.0%) | 0.102 | 188 (18.9%) | 29 (24.2%) | 0.165 |
| Postop LOS: median (range) | 2.0 (1.0, 5.0) | 7.0 (1.5, 7.5) | 0.037 | 2.0 (1.0, 5.0) | 4.0 (1.0, 8.0) | <0.001 |
| Stroke/TIA postprocedure | 29 (2.6%) | 0 (0.0%) | 0.586 | 25 (2.5%) | 4 (3.3%) | 0.591 |
| Vascular complications | 111 (10.0%) | 3 (27.3%) | 0.060 | 102 (10.2%) | 12 (10.0%) | 0.937 |
| Discharge to ECF | 154 (96.4%) | 6 (0.04%) | <0.001 | 119 (74.4%) | 41 (25.6%) | <0.001 |
BMI indicates body mass index; CABG, coronary artery bypass graft; ECF, extended care facility; LOS, length of stay; MI, myocardial infarction; NYHA, New York Heart Association; PPM, permanent pacemaker; SD, standard deviation; STS-PROM, Society of Thoracic Surgeons Predicted Risk of Mortality; TIA, transient ischemic attack.
Table 4.
Unadjusted and risk-adjusted Cox proportion hazard ratio of 1-year mortality
| Risk factor | Hazard ratio (95% confidence interval) |
||
|---|---|---|---|
| Unadjusted | Model 1: Adjusted for baseline variables | Model 2: Adjusted for baseline and postop variables | |
| Extended care facility | 3.19 (2.19, 6.25) (P < 0.0001) |
3.19 (2.16, 4.71) (P < 0.0001) |
2.23 (1.39, 3.59) (P = 0.001) |
| Race | |||
| White | Reference | Reference | Reference |
| Black | 0.77 (0.24, 2.41) (P = 0.65) |
0.66 (0.21, 2.08) (P = 0.47) |
0.66 (0.21, 2.10) (P = 0.44) |
| Other | 0.88 (0.48, 1.60) (P = 0.68) |
0.74 (0.39, 1.39) (P = 0.35) |
0.55 (0.28, 1.07) (P = 0.08) |
| STS risk | Cubic spline | Cubic spline | Cubic spline |
| Postoperative LOS | Cubic spline | – | Cubic spline |
| Vascular complications | 0.92 (0.51, 1.68) (P = 0.79) |
– | 0.70 (0.38, 1.30) (P = 0.27) |
| Postoperative stroke/TIA | 1.49 (0.55, 4.04) (P = 0.43) |
– | 0.83 (0.30, 2.30) (P = 0.67) |
| Model fitness | |||
| Concordance | 0.642 | 0.652 | |
| R-square | 0.042 | 0.055 | |
LOS indicates length of stay; STS, Society of Thoracic Surgeons risk score; TIA, transient ischemic attack.
Figure 2.
Restricted cubic spline with 5 knots showing relationship between risk factors for continuous variables and relative hazard of mortality in 1 year. (a) The adjusted effect of Society of Thoracic Surgeons (STS) risk score on 1-year mortality was relatively constant for STS < 10 and STS > 10, but increased for a STS risk score of 5 to 10. (b) In general, the increase in postoperative length of stay was associated with increased risk of mortality.
DISCUSSION
Nearly 15% of patients were discharged to ECF after TAVI. This is comparable to our previously published rate of 16% in our general open cardiac surgery population.14 Though we demonstrated discharge to an ECF to be a significant predictor of 1-year mortality, the likelihood of being discharged to such is not readily apparent prior to TAVI. Many studies have instead examined baseline factors predictive of 1-year mortality. As these baseline characteristics often affect the decision to discharge to an ECF, we created a model to assess the adjusted effect of discharge to ECF on 1-year mortality. Even after adjusting for both baseline characteristics and postoperative complications, the risk of 1-year mortality was more than twice as high for patients discharged to an ECF compared to home. This demonstrates that it is not simply the occurrence of complications driving discharge to ECF and 1-year mortality.
Though extensive work has been put into the development of TAVI-specific risk scores to predict mortality, none have included discharge location in their algorithm.3,4 The use of the STS-PROM, which was developed and validated in a surgical population, as a surrogate score is controversial. A large study by Holmes et al analyzed over 12,000 patients for factors associated with 1-year mortality.15 Discharge location was not included in the analysis. The STS-PROM was found to be associated with increased mortality when treated as a binary variable. We believe it is more appropriate to analyze STS-PROM as a continuous variable, and in our study, it was not a predictor of 1-year mortality. Greason et al also did not find STS-PROM to be predictive of 1-year mortality.16 Hermiller et al found the STS-PROM to be predictive of 1-year mortality, but also treated it as a binary variable.4 Discharge to assisted living was noted to be a predictor of 30-day mortality, but it fell out as a predictor at 1 year. In our analysis, it remained significant at 1 year.
Recent studies have explored the association between discharge location and long-term outcomes following TAVI. In a study by Okoh et al, 36% of TAVI patients were discharged to an ECF compared to our 14.3%.17 They found that patients discharged to an ECF had a significantly higher 30-day, 1-year, and 2-year mortality rate than their propensity-matched counterparts. The comparison of this study with our own suggests that even when the threshold for use of ECF is twice as liberal as ours, discharge to ECF is still predictive of higher mortality. This argues for the generalizability of our results. Their study was also limited to patients admitted from home. While our study lacked information on preoperative residence, the persistence of this finding in the Okoh study supports our findings. The results of our study suggest that an anticipated need for discharge to an ECF should be considered in the development of risk-assessment tools.
We have shown a strong association between discharge to ECF and increased mortality independent of postoperative complications. We stress that this is a correlation but not a causal relationship. Nevertheless, awareness of these data may aid the clinician in appropriate candidate selection for TAVI and improve the ability to obtain truly informed consent. In frail or debilitated patients, prehabilitation efforts can be made to avoid discharge to ECF. Awareness of the effect of discharge to an ECF on 1-year mortality can help drive postoperative management. For instance, patients teetering between discharge to home vs ECF could be maintained as an inpatient to gain strength if this would allow them to forgo discharge to an ECF.
Interpretation of the results of this study should be considered with the following limitations. First, the retrospective nature of a single institutional study may limit the generalizability of our results. Regional differences in practice may alter the threshold for utilizing ECF and influence the impact of non-home discharge.18 Second, we did not have data on patient residence at time of admission. The implications of discharge to an ECF may be lessened if some patients were already residing in an ECF and were simply discharged back to their residence. We also lacked data on duration of stay in an ECF and what proportion were successfully discharged to home from ECF. Days alive and out of facility are an important component of patient quality of life and are the subject of future investigation.18 Third, we know that the type of ECF impacts mortality in the surgical population.14 However, as the Transcatheter Valve Therapy Registry database does not delineate the type of ECF, we were unable to separately analyze discharge to rehabilitation, skilled nursing, and long-term acute care facilities. In this study, we sought to examine whether discharge to any ECF was predictive of mortality. Having established this relationship, future work may now investigate whether the type of ECF predicts mortality in the TAVI population. Fourth, the reason for discharge to ECF may impact the long-term findings. A discharge to ECF because the patient lacks family and needs temporary support likely differs from a discharge to ECF due to debilitation. Again, this represents an opportunity for future investigation. Finally, our study population includes medium- to high-risk patients undergoing TAVI and the results may not be applicable to low-risk patients. However, it is in these higher-risk patients that the clinician may anticipate the need for discharge to ECF, and our results may help guide decision-making in those situations. This final point on how to use these data is critical. These data should facilitate the process of shared decision-making and not be construed as indications for exclusion from intervention.
In conclusion, 14.3% of patients in this study were discharged to ECF after TAVI. These patients had a higher 30-day and 1-year mortality than patients discharged home. The strongest predictor of 1-year mortality was discharge to ECF. In contrast to previous reports, STS-PROM was not a predictor of 1-year mortality.
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