Abstract
Objectives
Frailty is increasingly recognized as a key determinant in predicting postoperative outcomes. Centers that see more frail patients may not be captured in risk adjustment, potentially accounting for poorer outcomes in hospital comparisons. We aimed to 1) determine the effect of frailty on long-term mortality in patients undergoing elective abdominal aortic aneurysm (AAA) repair and 2) evaluate the variability in frailty burden among centers in the Vascular Quality Initiative (VQI) database.
Methods
Patients undergoing elective open and endovascular AAA repair (2003–2017) were identified and those with complete data on component variables of the VQI-derived Risk Analysis Index (VQI-RAI) and centers with ≥ 10 AAA repairs were included. VQI-RAI characteristics are: sex, age, body mass index, renal failure, congestive heart failure, dyspnea, preoperative ambulation and functional status. Frailty was defined as VQI-RAI ≥ 35 based on prior work in surgical patients using other quality improvement databases. This corresponds to the top 12% of patients at-risk in the VQI. Center-level VQI-RAI differences were assessed by Analysis of Variance (ANOVA) test. Relationships between frailty and survival were compared by Kaplan-Meier analysis and log-rank test for open and endovascular procedures. Multivariable hierarchical Cox proportional hazards regression models were calculated with random intercepts for center, controlling for frailty, race, insurance, AAA diameter, procedure type, AAA case-mix, and year.
Results
A total of 15,803 patients from 185 centers were included. VQI-RAI scores ranged from 4 to 56 (mean 27.6, SD 5.9) and varied significantly across centers (F=2.41, p<0.001). The percentage of frail patients per center ranged from 0–40.0%. In multivariable analysis, frailty was independently associated with long-term mortality (hazard ratio 2.88, 95% CI 2.6–3.2) after accounting for covariates and center-level variance. Open AAA repair was not associated with long-term mortality after adjusting for frailty (hazard ratio 0.98, 0.86–1.13). There was a statistically significant difference in the percentage of frail patients compared to non-frail patients who were discharged to a rehabilitation facility or nursing home following both open (40.5% vs. 17.8%, p<0.0001) and endovascular repair (17.7% vs. 4.6%, p<0.0001).
Conclusions
There is considerable variability of preoperative frailty among VQI centers performing elective AAA repair. Adjusting for center-level variation, frailty but not procedure type had a significant association with long-term mortality; however, both frailty and procedure type were associated with non-home discharge. Routine measurement of frailty preoperatively by centers to identify high-risk patients may help mitigate procedural and long-term outcomes and improve shared-decision making regarding AAA repair.
Keywords: Frailty, Risk Analysis Index, open abdominal aortic aneurysm repair, endovascular abdominal aortic aneurysm repair, non-home discharge
Table of Contents Summary:
This VQI study of 15,803 patients undergoing elective open and endovascular abdominal aortic aneurysm (AAA) repair found that frailty varied significantly across centers and that it predicted long-term mortality. Routine pre-operative screening to identify high-risk patients may help mitigate procedural complications and long-term mortality.
Introduction
The introduction of endovascular techniques has allowed us to offer a wider array of interventions to patients who would have otherwise been considered poor candidates for open repair. Frailty is a biological syndrome reflecting limited reserve across a number of physiologic systems which culminates in decreased ability to withstand stressors and increased vulnerability to adverse outcomes.(1) Different methods to quantify frailty have been described, including multiple frailty scores, sarcopenia, and questionnaire-based scales. Regardless of the measure, frailty has been shown to be an independent risk factor for poor outcomes across surgical specialties, including vascular surgery.(2–13)
In 2014, in the United States alone, abdominal aortic aneurysms (AAA) were directly responsible for approximately 9,900 deaths and ~120,000 AAA repairs were performed to prevent subsequent rupture.(14) Independent of other co-morbidities, increased frailty has been found to predict higher 30-day mortality, morbidity, and failure to rescue following both open AAA repair (OAR) and endovascular AAA repair (EVAR); however, the impact of frailty on long-term survival after elective AAA repair has not been examined.(15)
The aim of our study is to determine the effect of frailty (as measured by an adaptation of the Risk Analysis Index (RAI) derived from variables contained within the Vascular Quality Initiative (VQI) database) on long-term mortality after elective AAA repair. We plan to investigate the distribution of frailty across centers performing AAA repair, and our hypothesis is that frailty will be a predictor of long-term survival following OAR and EVAR when adjusting for center-level variance.
Methods
Patients undergoing OAR and EVAR in the VQI database from 2003–2017 were identified. We elected to crosswalk a prospectively validated frailty screening tool, the RAI, to the VQI to create the VQI-derived RAI (VQI-RAI).(16) The instrument is an adaptation of the Minimum Data Set Mortality Risk Index-Revised and based on the deficit accumulation model of frailty by Rockwood et al.(10,17–20) The validity and utility of the original RAI has been discussed in depth previously, but in brief, the instrument was developed and validated in the veteran population and is associated with short and long-term mortality.(16,21) The RAI has two versions: 1) a prospective survey (RAI-C) administered pre-operatively by clinic staff or providers, and 2) a retrospective, objective calculation (RAI-A) of frailty based on chart review. The RAI-A (from which the VQI-RAI is derived) is used to test associations between frailty and surgical outcomes in larger databases and the RAI-C is intended for prospective screening with a high correlation between the two versions.(16)
Cohort Selection
This study was deemed exempt from review by Stanford University’s Institutional Review Board. Patients undergoing both straightforward and complex infrarenal AAA repair were retrospectively identified in the de-identified VQI database (n=40,254) at a total of 246 different centers. Patients with “ruptured” or “symptomatic” AAA were excluded (n=7,180). Further exclusions included age <18 (n=7), incomplete VQI-RAI data (n=16,845), insufficient long-term mortality data (n=7), AAA diameters outside of the VQI’s parameters (<20mm or > 150mm) or missing AAA diameter data (n=363). For patients listed with more than one discrete AAA operation (n=88), only the first AAA encounter was included. Similar to the Society for Vascular Surgery (SVS) Clinical Practice Guidelines, centers with very low case volume (< 10 total cases) were excluded (n=46 centers, n=163 patients).(22) The final cohort included 15,803 patients from 185 centers (Supplemental Figure 1). Supplemental Table I is a comparison of the included and excluded cohorts and confirms that our sample was an accurate representation of patients in the VQI.
Variables
The dependent variable, survival time, is defined as the difference between the procedure date and the last date of contact or death. Death is determined by the VQI using either procedural or follow-up data and is updated with the Social Security Death Index semi-annually. The primary independent variable was frailty as measured by the VQI-RAI using the following characteristics: sex, age, body mass index (BMI), renal failure, congestive heart failure (CHF), dyspnea, residence other than independent living, preoperative ambulation, and functional status (Supplemental Figure 2). Renal failure was defined as Cr > 1.78 mg/dL or on dialysis, consistent with previous frailty research in the VQI.(17) An activities of daily living (ADL) score was determined by assessing a patient’s preoperative ambulation and functional status. To adjust the nutritional domain of the RAI for the available VQI variables, we employed BMI as a measure of frailty. Literature from Hubbard et al. suggests frailty is increased among those with very low (underweight <20 kg/m2) and very high (morbidly obese ≥ 35 kg/m2) BMIs, and we chose to incorporate both extremes.(23) Previous studies using the RAI included three other variables, weight loss, cognitive status, and cancer diagnosis; however, these are not available within the VQI registry. Weighted indicator variables for each component were summed as a continuous composite VQI-RAI score (total scale range: 0–72). The cut-off to dichotomize frail versus non-frail patients was chosen as a VQI-RAI score ≥ 35 based on prior research.(16,21) Covariates included in the analysis for adjustment were procedure type, race, maximum AAA diameter, insurance provider, surgery year, and proportion of OAR cases by center.
Statistics
Frail and non-frail patients in each procedure subtype were compared by t-test or chi-square test for differences in VQI-RAI characteristics and covariates. The average VQI-RAI per center was used to create center-level quintiles. These were then evaluated for trends in VQI-RAI characteristics, frailty, and OAR case proportion using nonparametric Spearman rank correlation. Center-level VQI-RAI differences were assessed by global F test of center ID fixed effects in ANOVA. Relationships between frailty and survival were compared by Kaplan-Meier analysis for OAR and EVAR until 10% of the cohort remained in the sample (four years). A multivariable Cox proportional hazard center-level random intercept model was calculated to evaluate differences in survival time by frailty status adjusted for the aforementioned covariates. Differences in postoperative discharge destination were evaluated with Fisher’s exact tests. Statistical significance was assessed at an alpha level of 0.05. All statistical analyses were performed using SAS version 9.4 (Cary, NC, USA).
Results
VQI-derived RAI scores were calculated for each of the 15,803 patients that received either elective OAR or EVAR. The overall mean VQI-RAI score was 27.6 (SD 5.9, range 4 – 56), the mean EVAR VQI-RAI score was 28.3 (SD 5.9, range 4–54), and the mean OAR VQI-RAI score was 25.6 (SD 5.4, range 4 – 56) [p<0.001]. The majority of patients (74.0%) underwent EVAR, and a greater proportion of frail patients received EVAR (85.4%) compared to non-frail patients (72.3%, p<0.001).
In both procedure groups, there were significant differences between frail and non-frail patients [Table I]. For OAR, there were statistically significant differences (p<0.05) between frail and non-frail patients for all VQI-RAI components, in addition to insurance and AAA diameter (p<0.001). For EVAR, there were significant differences for all VQI-RAI components with the exception of gender (0.091), and for race, insurance, and AAA diameter.
Table I.
Baseline demographic, Vascular Quality Initiative-derived Risk Analysis Index (VQI-RAI) characteristics, and model covariates of patients undergoing elective abdominal aortic aneurysm repair stratified first by type of repair [open (OAR) versus endovascular (EVAR)] and then by frailty status [frail (VQI-RAI score > 35) versus non-frail)]. Continuous variables are expressed as mean ± standard deviation and categorical variables are reported in total number of observations with associated percentage (%). [N=15,803]
| OAR* (n=4109) | EVAR^ (n=11694) | OAR Frail vs. EVAR Frail | |||
|---|---|---|---|---|---|
| Characteristic | Frail (n=293) | Non-Frail (n=3816) | Frail (n=1717) | Non-Frail (n=9977) | p-value |
| VQI-RAI components | |||||
| Age, Mean (SD) | 76.1 (6.4) | 68.9 (8.1) | 80.1 (6.6) | 73.0 (8.4) | <0.0001 |
| Age, Range | 54.−90.0 | 21.0−90.0 | 56.0−90.0 | 20.0–90.0 | |
| Nutrition Score – underweight or morbidly obese, n (%) | 159 (54.3) | 407 (10.7) | 806 (46.9) | 1007 (10.1) | 0.0204 |
| Renal Failure - Cr > 1.78 or on dialysis, n (%) | 120 (41.0) | 104 (2.7) | 477 (27.8) | 198 (2.0) | <0.0001 |
| Congestive Heart Failure, n (%) | 90 (30.7) | 230 (6.0) | 611 (35.6) | 821 (8.2) | 0.1061 |
| Dyspnea, n (%) | 28 (9.6) | 71 (1.9) | 253 (14.7) | 368 (3.7) | 0.0181 |
| Living status – not living independently, n (%) | 5 (1.7) | 19 (0.5) | 128 (7.5) | 88 (0.9) | <0.0001# |
| ADL score, n (%) | 0.0067# | ||||
| Totally Independent | 190 (64.9) | 3685 (96.6) | 1069 (62.3) | 9657 (96.8) | |
| Partially Dependent | 102 (34.8) | 131 (3.4) | 630 (36.7) | 320 (3.2) | |
| Totally Dependent | 1 (0.3) | 0 (0.0) | 18 (1.1) | 0 (0.0) | |
| Male sex, n (%) | 235 (80.2) | 2819 (73.9) | 1415 (82.4) | 8049 (80.7) | 0.3626 |
| Covariates | |||||
| Race, n (%) | 0.0002# | ||||
| Caucasian | 252 (86.0) | 3372 (88.4) | 1519 (88.5) | 8998 (90.2) | |
| African American | 22 (7.5) | 160 (4.2) | 99 (5.8) | 411 (4.1) | |
| Hispanic | 6 (2.1) | 98 (2.6) | 41 (2.4) | 253 (2.5) | |
| Asian | 4 (1.4) | 52 (1.4) | 18 (1.1) | 130 (1.3) | |
| Not reported/Other | 9 (3.1) | 134 (3.5) | 40 (2.3) | 185 (1.9) | |
| Insurance, n (%) | <0.0001# | ||||
| Medicare | 206 (70.3) | 1998 (52.4) | 1241 (72.3) | 6312 (63.3) | |
| Medicaid | 9 (3.1) | 124 (3.3) | 20 (1.2) | 169 (1.7) | |
| Commercial | 63 (21.5) | 1395 (36.6) | 390 (22.7) | 3106 (31.1) | |
| Not reported/Other | 15 (5.1) | 299 (7.8) | 66 (3.8) | 390 (3.9) | |
| AAA diameter, n (%) | <0.0001 | ||||
| Less than 4.50cm | 14 (4.8) | 263 (6.9) | 110 (6.4) | 834 (8.4) | |
| 4.50 – 5.49cm | 51 (17.4) | 1133 (29.7) | 501 (29.2) | 4203 (42.1) | |
| 5.50 – 6.49cm | 126 (43.0) | 1492 (39.1) | 746 (43.5) | 3576 (35.8) | |
| 6.50 – 7.49cm | 61 (20.8) | 490 (12.8) | 223 (13.0) | 865 (8.7) | |
| 7.50cm or larger | 41 (14.0) | 438 (11.5) | 137 (8.0) | 499 (5.0) | |
OAR: All comparisons between frail and non-frail groups showed statistically significant differences (p < 0.05) between the groups with the exception of race, p=0.118.
EVAR: All comparisons between frail and non-frail groups showed statistically significant differences (p < 0.05) between the groups with the exception of sex, p = 0.091.
p-values were calculated with Fisher’s exact test
AAA: Abdominal aortic aneurysm; ADL: Activities of Daily Living; EVAR: Endovascular aortic aneurysm repair; OAR: Open aortic aneurysm repair; RAI: Risk Analysis Index; VQI: Vascular Quality Initiative
Variable components of the VQI-RAI significantly differed between frail OAR and frail EVAR patients, with the exception of CHF (p = 0.11) and gender (p=0.36). Frail EVAR patients were significantly older than frail OAR patients (mean age 80.1 vs. 76.1, p < 0.001) and experienced dyspnea (14.7% vs. 9.6%, p = 0.018). In contrast, a larger percentage of frail OAR patients had renal failure compared to the frail EVAR subgroup (41.0% vs. 27.8%, p < 0.001) and had an extremely low or high BMI (54.3% vs. 46.9%, p=0.020). There was also significantly greater functional dependence among frail patients who underwent EVAR (partially dependent 36.7% and totally dependent 1.1%) compared to OAR (partially dependent 34.8% and totally dependent 0.3%, p=0.007).
Frail patients undergoing OAR tended to have proportionately larger aneurysms at the time of repair; 34.8% frail OAR patients compared to 21.0% frail EVAR patients had AAA diameters > 6.5cm (p<0.001). Overall, 45.0% of patients underwent elective AAA repair for aneurysms measuring less than 5.5cm, with the overwhelming majority (84.5%) of those repairs being EVARs. Of those patients who had their aneurysms repaired at a diameter < 5.5cm, 9.5% of those patients were frail. Overall, 5.2% of EVARs and 1.6% of OARs were performed on frail patients with aneurysms measuring < 5.5cm.
The mean VQI-RAI score varied significantly across centers, with mean scores ranging from 21.9 in the lowest quintile to 31.8 in the highest quintile (F=2.41, p<0.001, [Figure 1]). Table II evaluates in greater granularity how the components of the VQI-RAI vary across the center-level quintiles. In the highest quintile with the largest frailty burden (quintile 5), 20.1% were frail whereas in the lowest quintile with the smallest frailty burden (quintile 1) only 7.8% of patients were frail. The percentage of patients who were partially or totally dependent more than tripled for quintile 5 (14.5%) compared to quintile 1 (4.5%). Interestingly, there was an inverse relationship across the quintiles between the proportion of OAR cases and the percentage of frail patients; quintile 5 had 12% OAR cases per center while quintile 1 had on average 40.7% OARs per center.
Figure 1.
Variation in center-level frailty burden arranged by quintile based on the average Vascular Quality Initiative-derived Risk Analysis Index (VQI-RAI) score of patients treated at those centers from smallest to largest (N=185 centers). Center-level VQI-RAI differences were assessed by Analysis of Variance (ANOVA) test.
Table II.
Comparison of individual Vascular Quality Initiative-derived Risk Analysis Index (VQI-RAI) components, percentage of frail patients, and average proportion of open abdominal aortic aneurysm repairs (OAR) across quintiles grouped by mean VQI-RAI score. Note the inverse relationship between frailty burden and proportion of OAR performed within each quintile. [N=185 centers and 15,803 patients]
| Center-level Quintile | 1 | 2 | 3 | 4 | 5 | p- |
|---|---|---|---|---|---|---|
| Number of Centers within each Quantile | 37 | 37 | 37 | 37 | 37 | value* |
| Patients within Center-level Quantile, n (% total patients) | n=2642 (16.7) | n=3347 (21.2) | n=4342 (27.5) | n=3668 (23.2) | n=1804 (11.4) | |
| VQI-RAI components | ||||||
| Age, mean (SD) | 70.9 (8.6) | 72.3 (8.4) | 72.9 (8.7) | 73.9 (8.6) | 74.4 (8.8) | <0.001 |
| Underweight or morbidly obese, n (%) | 343 (13.0) | 486 (14.5) | 637 (14.7) | 597 (16.3) | 316 (17.5) | <0.001 |
| Renal Failure - Cr > 1.78 or on dialysis, n (%) | 139 (5.3) | 158 (4.7) | 241 (5.6) | 229 (6.2) | 132 (7.3) | <0.001 |
| Congestive Heart Failure, n (%) | 196 (7.4) | 339 (10.1) | 539 (12.4) | 373 (10.2) | 305 (16.9) | <0.001 |
| Dyspnea, n (%) | 93 (3.5) | 163 (4.9) | 172 (4.0) | 198 (5.4) | 94 (5.2) | 0.003 |
| Residence other than independent living, n (%) | 26 (1.0) | 45 (1.3) | 56 (1.3) | 65 (1.8) | 48 (2.7) | <0.001 |
| ADL Partially/Totally Dependent, n (%) | 118 (4.5) | 182 (5.4) | 341 (7.9) | 299 (8.2) | 262 (14.5) | <0.001 |
| Male sex, n (%) | 2098 | 2630 | 3487 | 2910 | 1393 | 0.431 |
| (79.4) | (78.6) | (80.3) | (79.3) | (77.2) | ||
| Frail, n (%) | 205 (7.8) | 345 (10.3) | 551 (12.7) | 546 (14.9) | 363 (20.1) | <0.001 |
| Proportion OAR, n (%) | 1075 (40.7) | 1036 (31.0) | 1046 (24.1) | 735 (20.0) | 217 (12.0) | <0.001 |
p-values were calculated by Spearman nonparametric tests for trend
OAR: Open abdominal aortic aneurysm repair; RAI: Risk Analysis Index; VQI: Vascular Quality Initiative
In Kaplan-Meier analysis, significant differences were observed in survival curves by frailty and procedure groups (p<0.001, [Figure 2]). Most of the mortality risk varied during the first postoperative year as the curves plateaued over time. As expected, non-frail EVAR patients had the best initial survival outcomes with 98.6% alive at 3 months, 97.7% at 6 months, 95.9% at 1 year, and 92.9% at 2 years post-operatively. Non-frail OAR patients had similar long-term outcomes with 96.4% survival to 3 months, 95.6% to 6 months, 94.6% to 1 year, and 93.6% to 2 years post-operatively. Survival in the frail subgroups was markedly worse. In the frail OAR subgroup 85.6% survived to 3 months and 83.4% to 6 months, but this proportion dropped to 78.2% alive at 1 year and 74.3% at 2 years post-operatively. The frail EVAR subgroup experienced a similar decline but to a lesser degree with 93.6% alive at 3 months, 90.8% at 6 months, 86.0% at 1 year, and 80.0% alive at 2 years post-operatively.
Figure 2.
Kaplan-Meier adjusted analysis of the impact of frailty (Vascular Quality Initiative-derived Risk Analysis Index (VQI-RAI) score > 35) on long-term survival of patients undergoing open or endovascular AAA repair in the VQI database from 2003–2017. Subgroup survival differences were plotted until 10% of the cohort remained in the sample, which was at four years follow-up.
Frailty was associated with increased hazard of long-term mortality (HR 2.88, 95% CI 2.57–3.21, p < 0.001) after adjusting for center-level variance and covariates [Table III]. Notably, there was no increased hazard of mortality in patients who underwent OAR compared to EVAR (HR 0.98, 95% CI 0.86–1.13, p=0.780), and there were no differences in mortality hazard among centers when stratified by percentage of OARs performed. Patients of Hispanic background had significantly lower mortality risk than Caucasian patients (HR 0.54, 95% CI 0.35–0.83, p = 0.006). Compared to commercial insurance, Medicare was associated with increased mortality hazard (HR 1.37, 95% CI 1.21–1.54, p < 0.001); however, Medicaid was not (HR 1.35, 95% CI 0.93–1.95). AAA diameter greater than 5.5 cm was associated with increased long-term mortality (p<0.0001).
Table III.
Multivariable Cox proportional hazard center-level random intercept model to evaluate differences in survival time by frailty status and procedure type [open (OAR) versus endovascular (EVAR) abdominal aortic aneurysm (AAA) repair]. The model was adjusted for procedure type, race, insurance, AAA diameter, surgery year, and proportion of open cases by center [N=15,772].
| Hazard Ratio (95% CI) | p-value | |
|---|---|---|
| Frailty | 2.88 (2.57, 3.21) | < 0.0001 |
| Procedure Type | ||
| EVAR | Referent | |
| OAR | 0.98 (0.86, 1.13) | 0.780 |
| Race | ||
| Caucasian | Reference | |
| African American | 0.94 (0.74, 1.20) | 0.633 |
| Hispanic | 0.54 (0.35, 1.37) | 0.006 |
| Asian | 0.84 (0.52, 1.37) | 0.478 |
| Not reported/Other | 0.65 (0.43, 0.98) | 0.041 |
| Insurance | ||
| Commercial | Referent | |
| Medicaid | 1.35 (0.93, 1.95) | 0.117 |
| Medicare | 1.37 (1.21, 1.54) | <0.0001 |
| Not reported/Other | 1.14 (0.81, 1.62) | 0.447 |
| AAA Diameter | ||
| Less than 4.50cm | 1.05 (0.84, 1.30) | 0.684 |
| 4.50 − 5.49cm | Referent | |
| 5.50 − 6.49cm | 1.35 (1.20, 1.53) | <0.0001 |
| 6.50 − 7.40cm | 1.95 (1.67, 2.27) | <0.0001 |
| 7.50cm or larger | 1.88 (1.56, 2.25) | <0.0001 |
| Proportion OAR Quartile | ||
| 0 − 9.31% | Referent | |
| 9.32 − 0 20.94% | 1.08 (0.83, 1.41) | 0.572 |
| 20.95 − 33.89% | 1.04 (0.79, 1.35) | 0.798 |
| 33.90 − 100% | 0.81 (0.61, 1.08) | 0.149 |
| Surgery Year | ||
| 2003 − 2011 | Referent | |
| 2012 | 1.08 (0.73, 1.58) | 0.713 |
| 2013 | 1.12 (0.76, 1.64) | 0.562 |
| 2014 | 0.92 (0.63, 1.36) | 0.685 |
| 2015 | 1.09 (0.72, 1.63) | 0.696 |
| 2016 | 0.80 (0.52, 1.25) | 0.334 |
| 2017 | 1.04 (0.50, 2.17) | 0.911 |
In a post-hoc analysis of discharge destination, there were significant differences in the percentage of prior home-dwelling frail patients discharged to either a rehabilitation facility or nursing home following both OAR (40.5% vs. 17.8%, p<0.0001) and EVAR (17.7% vs. 4.6%, p<0.0001) [Table IV]. Overall, just under a fifth (19.3%) of elective OAR patients were discharged to a rehab or nursing facility as were 6.5% of elective EVAR patients. Amongst patients with non-home discharge, long-term mortality was twice that of patients who were discharged home (17.64% vs. 8.37%, p<0.0001).
Table IV.
Post-hoc analysis examining the discharge destination of patients undergoing elective abdominal aortic aneurysm repair stratified by frailty status and procedure type. Discharges to an acute/subacute rehab facility or skilled/regular nursing home reported in the Vascular Quality Initiative (VQI) are new following surgery as the VQI defines discharge “home” as inclusive of patients who returned to their pre-operative level of care [N=15,064].
| Discharge Destination | |||||
|---|---|---|---|---|---|
| Home | Rehab facility | Nursing home | Transfer to another hospital | p-value* | |
| EVAR Non-Frail, n (%) | 9453 (95.1) | 249 (2.5) | 204 (2.1) | 29 (0.3) | <0.0001 |
| OAR Non-Frail, n (%) | 3014 (81.2) | 427 (11.5) | 232 (6.3) | 38 (1.0) | |
| EVAR Frail, n (%) | 1383 (81.6) | 139 (8.2) | 161 (9.5) | 11 (0.6) | <0.0001 |
| OAR Frail, n (%) | 148 (56.1) | 63 (23.9) | 44 (16.7) | 9 (3.4) | |
p-value calculated by Fisher’s exact test
EVAR: Endovascular abdominal aortic aneurysm repair; OAR: open abdominal aortic aneurysm repair
Discussion
This is the first study to use the VQI-derived RAI to look at the distribution of frailty across VQI centers and evaluate its impact on survival in elective AAA patients. We found that frailty in patients undergoing elective AAA repair varied significantly across centers. Increased long-term mortality following AAA repair was significantly associated with patient frailty (HR 2.88), and although procedure type did not impact long-term mortality, both procedure type and frailty were associated with increased non-home discharge.
Prior studies in AAA patients have demonstrated frailty to be associated with short-term mortality, but this is the first study to examine the impact of frailty on long-term mortality following elective AAA repair.(15) Mortality diverged significantly in frail and non-frail patients within the first year of surgery. EVAR in frail patients did not confer survival advantage beyond the post-operative period. The frail OAR survival curve plateaus beyond two years while the frail EVAR survival curve continues its downward slope to result in the poorest long-term survival outcomes, potentially reflecting the inherent lack of physiologic reserve that may have influenced initial selection of operative approach. Interestingly, non-frail patients who underwent either OAR or EVAR had similar long-term survival. Around the 1.5-year mark the survival curves cross, and the non-frail OAR curve plateaus while the non-frail EVAR curve continues to have a slightly downward slope. These findings echo randomized control trial data from the DREAM, EVAR-1, and OVER trials where there was an early survival advantage of EVAR compared to OAR, but this advantage was not sustained long-term and EVAR was ultimately associated with increased secondary interventions.(24–27) There has been a rapid uptake of EVAR in elective and emergency surgeries in the United States, so it is not surprising that a larger percentage of frail patients underwent EVAR compared to OAR.(28) However, open surgery had equivalent long-term survival results for non-frail patients, and thus OAR should remain an option for patients based on quality of life preferences and need for surveillance and secondary interventions.(24) In our analysis, 1-year mortality for frail patients undergoing EVAR and OAR was high (~15–20%). The EVAR-2 trial randomly assigned patients physically ineligible for OAR to either EVAR or no repair. Although aneurysm-related mortality was lower following EVAR, overall mortality was the same and EVAR provided no additional mortality benefit.(29) Given these results, it is of utmost importance that long-term survival data be included as part of the shared-decision making process when offering patients elective AAA repair.
Our analysis revealed that 45.0% of patients underwent elective AAA repair below the 5.5cm diameter threshold. In frail patients, 35.6% underwent EVAR and 22.2% underwent OAR with aneurysms measuring less than 5.5cm. The SVS Clinical Practice Guidelines recommend elective repair for patients at low or acceptable surgical risk with a fusiform AAA that is > 5.5cm.(22) This recommendation is based on trials such as the Aneurysm Detection and Management (ADAM) trial where the rupture risk for those unfit for repair was less than 1.0% per year for patients with aortic diameters less than 5.5cm, 9.4% between 5.5 and 5.9 cm, 10.2% between 6.0 and 6.9 cm, and 32.5% for those >7.0 cm.(30,31) A more recent pooled analysis suggested that the current rupture risk may be much lower: 5.3% per year for AAAs between 5.5 and 7.0 cm in diameter and 6.3% per year for AAAs >7.0 cm.(32) Similar to the EVAR-2 trial, the risk of death from causes other than AAA was higher than the risk of death from aneurysm rupture.(29,32)
This raises the important question whether there should be a different size threshold for AAA repair in frail patients. Comparing published data to our Kaplan-Meier survival curves, we suggest that elective aneurysm repair in frail patients be performed only for AAA diameters > 7.0cm as 1-year survival following surgery in frail patients was 86.0% for EVAR and 78.2% for OAR. Future research is required to substantiate the need and threshold for repair as AAA repair clearly sends frail patients down a very different survival trajectory than what may have befallen them without intervention(33). Development of medical therapies for slowing AAA growth, such as the ongoing work in doxycycline and metformin, also has the potential to produce a paradigm shift in our management of AAAs, especially for frail patients.(34,35)
Although age and co-morbidities are associated with poor outcomes, they are not useful as tools for determining candidacy for surgery given the heterogeneity of outcomes.(36,37) Frailty, however, has consistently been shown to predict poor outcomes and more evidence continues to accumulate that frailty is multidimensional and goes beyond merely comorbidities and functional status. The advantage of the RAI is the capture of five domains of frailty; namely, functional, physical, social, cognitive, and nutritional. A prospective version of the RAI has been developed and validated in surgical populations [Supplemental Figure 3].(16) The ease of administration and granular detail provided by the RAI makes it an ideal tool for frailty screening in the vascular surgical population to identify high-risk patients and improve patient selection.(38) It also provides a structured opportunity to elicit patient preferences and incorporate quality of life considerations into the treatment plan.
In the context of AAA repair, frailty could influence the decision between elective surgery versus ongoing surveillance and between possible versus no intervention in case of aneurysm size progression or rupture. Furthermore, we found 40.5% of frail OAR patients and 17.7% of frail EVAR patients were discharged to either a rehab facility or nursing home. Frail home-dwelling patients undergoing elective vascular procedures are at high risk of not returning home after surgery.(39) However, even in the absence of frailty, discussions regarding post-surgery discharge expectations are important because overall 1 in 5 elective OAR and 1 in 15 elective EVAR patients were discharged to locations other than home. In a study by Edgerton et al., only half of the cardiac surgery patients discharged to an extended care facility return to independent living, thus highlighting that discharge to a rehabilitation facility is not a “benign” event and can lead to prolonged or permanent stay away from home.(40)
There is considerable variability of preoperative frailty among centers performing AAA repair. For some centers, almost a third of their patients qualified as being frail. Establishing a screening program to identify potentially frail patients may allow them to decrease procedural and long-term morbidity and mortality through the implementation of preoperative interventions such as pre-habilitation with exercise. (41) Furthermore, it can help hospitals direct their resources to the highest risk strata to anticipate rehabilitation and discharge needs and include families/caregivers in the process. process. The variability of patient frailty could have a dramatic impact on an individual center’s reporting of surgical outcomes and has implications for ensuring proper hospital quality comparisons. Over the past two decades, authorities such as the Centers for Medicare and Medicaid Services have increased the transparency of reporting hospital quality of care. Understanding that different centers will bear a higher burden of frailty over time will help develop better normalizing methodologies for more appropriate head-to-head hospital comparisons.
There are several limitations to our study, some of which are inherent to the VQI dataset. First, there is a selection bias manifest in the data collection itself as institutions and providers voluntarily submit self-reported data and not all institutions or providers participate in all aspects of the registry. Second, this is a retrospective analysis of prospectively collected data and we are therefore limited in our ability to draw conclusions about causality and the analyses may be subject to residual confounding. Third, variables such as ambulation and functional status are prone to individual interpretation and as a result may introduce unintentional bias. Finally, the VQI database differs from the original RAI dataset, notably missing data on cognition and malignancy. Functional status and cognition are typically recorded in the original RAI as a composite sub-score (ADL*cognition) as cognitive and physical decline often go hand in hand.(42) Since there is no variable available for capturing cognition in the VQI, we assumed the absence of cognitive deficits or dementia and ascribed all the weight for the original ADL*cognition sub-score to the ADL domain in the VQI-RAI. Similarly, the cancer variable is part of a composite sub-score (age*cancer) in the original RAI due to an interaction between age and cancer. In younger patients, frailty is mostly due to the presence of disseminated or poor prognosis malignancies. Since our population’s mean age is > 65 years old, we ascribed all the weight for the original age*cancer sub-score to the age criteria and assumed no active malignancy in VQI patients. Statistically speaking, these assumptions will bias our association results towards the null. If the VQI were to capture the presence of cognitive decline or cancer, we hypothesize more patients would be classified as frail.
The prevalence of cognitive impairment among older patients presenting for vascular surgery is high; 68% in one study and previously unrecognized in 88.3% of those patients.(43) In a recent systematic review, patients deemed frail with cognitive deficits were at higher risk for mortality, morbidity, functional decline, and major adverse events following cardiac surgery.(44,45) Patients with mild cognitive impairment or dementia are at two-fold higher risk of developing postoperative delirium as well as other adverse outcomes.(42,46) Therefore, we believe cognitive status to be a critical component of any preoperative evaluation, and based on our analysis we recommend more granular data regarding cognition be included in VQI data collection to help preoperative assessment and future quality improvement efforts.
Conclusion
Frailty has a significant association with long-term mortality after AAA repair after adjusting for operative approach and variance across centers while operative approach did not influence long-term mortality. There is considerable variability of preoperative frailty among centers, and this may have implications for making accurate hospital comparisons regarding surgical outcomes. Routine measurement of frailty preoperatively by centers to identify high-risk patients and implementation of perioperative interventions may help improve shared-decision making regarding AAA repair and possibly mitigate procedural and long-term mortality.
Supplementary Material
Highlights:
Type of Research:
Retrospective review of prospectively collected Vascular Quality Initiative (VQI) data Key Findings: In 15,803 patients undergoing elective open abdominal aortic aneurysm repair (OAR) or endovascular abdominal aortic aneurysm repair (EVAR) frailty, as measured by the VQI-derived Risk Analysis Index (VQI-RAI), was independently associated with long-term mortality [HR 2.88, (2.6, 3.2)] and non-home discharge. OAR was associated with non-home discharge. Frailty varied significantly across centers (F=2.41, p<0.001). Take Home Message: Routine measurement of frailty preoperatively to identify high-risk patients and implementation of perioperative interventions may help mitigate procedural and long-term outcomes and improve shared-decision making regarding AAA repair.
Footnotes
Presented at the 33rd Annual Western Vascular Society Meeting held September 22–25th, 2018 in Santa Fe, New Mexico.
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Conflicts of Interest: There are no relevant conflicts of interest to disclose.
References
- 1.Abellan van Kan G, Rolland Y, Houles M, Gillette-Guyonnet S, Soto M, Vellas B. The Assessment of Frailty in Older Adults. Clin Geriatr Med 2010. May 1;26(2):275–86. [DOI] [PubMed] [Google Scholar]
- 2.Esses G, Andreopoulos E, Lin H-M, Arya S, Deiner S. A Comparison of Three Frailty Indices in Predicting Morbidity and Mortality After On-Pump Aortic Valve Replacement: Anesth Analg 2018. January;126(1):39–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Farhat JS, Velanovich V, Falvo AJ, Horst HM, Swartz A, Patton JHJ, et al. Are the frail destined to fail? Frailty index as predictor of surgical morbidity and mortality in the elderly. J Trauma Acute Care Surg 2012. June;72(6):1526. [DOI] [PubMed] [Google Scholar]
- 4.Joseph B, Pandit V, Zangbar B, Kulvatunyou N, Hashmi A, Green DJ, et al. Superiority of Frailty Over Age in Predicting Outcomes Among Geriatric Trauma Patients: A Prospective Analysis. JAMA Surg 2014. August 1;149(8):766–72. [DOI] [PubMed] [Google Scholar]
- 5.Keller DS, Bankwitz B, Nobel T, Delaney CP. Using Frailty to Predict Who Will Fail Early Discharge After Laparoscopic Colorectal Surgery With an Established Recovery Pathway. Dis Colon Rectum 2014. March;57(3):337. [DOI] [PubMed] [Google Scholar]
- 6.Makary MA, Segev DL, Pronovost PJ, Syin D, Bandeen-Roche K, Patel P, et al. Frailty as a predictor of surgical outcomes in older patients. J Am Coll Surg 2010. June 1;210(6):901–8. [DOI] [PubMed] [Google Scholar]
- 7.Pearl JA, Dattatraya P, Arya S, Alemozaffar M, Master VA, Ogan K. Patient Frailty and Discharge Disposition Following Radical Cystectomy. Clin Genitourin Cancer 2017. August 1;15(4):e615–21. [DOI] [PubMed] [Google Scholar]
- 8.Tsiouris A, Hammoud ZT, Velanovich V, Hodari A, Borgi J, Rubinfeld I. A modified frailty index to assess morbidity and mortality after lobectomy. J Surg Res 2013. July 1;183(1):40–6. [DOI] [PubMed] [Google Scholar]
- 9.DeMartino RR, Brooke BS, Neal D, Beck AW, Conrad MF, Arya S, et al. Development of a validated model to predict 30-day stroke and 1-year survival after carotid endarterectomy for asymptomatic stenosis using the Vascular Quality Initiative. J Vasc Surg [Internet] 2017. August [cited 2018 Oct 5];66(2):433–444.e2. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0741521417310704 [DOI] [PubMed] [Google Scholar]
- 10.Kraiss LW, Al-Dulaimi R, Presson AP, Arya S, Lee GK, Goodney PP, et al. A Vascular Quality Initiative-Based Frailty Instrument Predicts 9-Month Postoperative Mortality. J Vasc Surg 2016. August;64(2):551–2. [Google Scholar]
- 11.Morisaki K, Yamaoka T, Iwasa K, Ohmine T. Influence of frailty on treatment outcomes after revascularization in patients with critical limb ischemia. J Vasc Surg [Internet] 2017. December [cited 2018 Oct 5];66(6):1758–64. Available from: https://linkinghub.elsevier.com/retrieve/pii/S074152141731251X [DOI] [PubMed] [Google Scholar]
- 12.Fang ZB, Hu FY, Arya S, Gillespie TW, Rajani RR. Preoperative frailty is predictive of complications after major lower extremity amputation. J Vasc Surg [Internet] 2017. March [cited 2018 Oct 5];65(3):804–11. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0741521416316640 [DOI] [PubMed] [Google Scholar]
- 13.Shah R, Attwood K, Arya S, et al. Association of frailty with failure to rescue after low-risk and high-risk inpatient surgery. JAMA Surg [Internet] 2018. May 16;153(5):e180214 Available from: 10.1001/jamasurg.2018.0214 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Tracci MC, Roy RA, Upchurch GR. Aortoiliac Aneurysms: Evaluation, Decision Making, and Medical Management. In: Rutherford’s Vascular Surgery and Endovascular Therapy [Internet] 9th ed. Philadelphia, PA: Elsevier; 2019. [cited 2018 Jul 30]. p. 884–893.e3. Available from: https://www.clinicalkey.com/#!/content/book/3-s2.0-B9780323427913000700?scrollTo=%23hl0000556 [Google Scholar]
- 15.Arya S, Kim SI, Duwayri Y, Brewster LP, Veeraswamy R, Salam A, et al. Frailty increases the risk of 30-day mortality, morbidity, and failure to rescue after elective abdominal aortic aneurysm repair independent of age and comorbidities. J Vasc Surg 2015. February 1;61(2):324–31. [DOI] [PubMed] [Google Scholar]
- 16.Hall DE, Arya S, Schmid KK, et al. Development and initial validation of the risk analysis index for measuring frailty in surgical populations. JAMA Surg 2017. February 1;152(2):175–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Kraiss LW, Al-Dulaimi R, Thelen J, Brooke BS. Postoperative Outcomes Correlate With Frailty Defined Using Vascular Quality Initiative Data. J Vasc Surg 2015. August 1;62(2):532. [Google Scholar]
- 18.Rockwood K Conceptual Models of Frailty: Accumulation of Deficits. Can J Cardiol 2016. September 1;32(9):1046–50. [DOI] [PubMed] [Google Scholar]
- 19.Velanovich V, Antoine H, Swartz A, Peters D, Rubinfeld I. Accumulating deficits model of frailty and postoperative mortality and morbidity: its application to a national database. J Surg Res 2013. July 1;183(1):104–10. [DOI] [PubMed] [Google Scholar]
- 20.Porock D, Parker-Oliver D, Petroski GF, Rantz M. The MDS Mortality Risk Index: The evolution of a method for predicting 6-month mortality in nursing home residents. BMC Res Notes [Internet] 2010. July 16 [cited 2018 Oct 5];3:200 Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2913927/ [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Hall DE, Arya S, Schmid KK, et al. Association of a frailty screening initiative with postoperative survival at 30, 180, and 365 days. JAMA Surg 2017. March 1;152(3):233–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Chaikof EL, Dalman RL, Eskandari MK, Jackson BM, Lee WA, Mansour MA, et al. The Society for Vascular Surgery practice guidelines on the care of patients with an abdominal aortic aneurysm. J Vasc Surg 2018. January;67(1):2–77.e2. [DOI] [PubMed] [Google Scholar]
- 23.Hubbard RE, Lang IA, Llewellyn DJ, Rockwood K. Frailty, Body Mass Index, and Abdominal Obesity in Older People. J Gerontol Ser A 2010. April 1;65A(4):377–81. [DOI] [PubMed] [Google Scholar]
- 24.Bruin JLD, Prinssen M. Long-Term Outcome of Open or Endovascular Repair of Abdominal Aortic Aneurysm. N Engl J Med 2010;9. [DOI] [PubMed] [Google Scholar]
- 25.Lederle FA, Freischlag JA, Kyriakides TC, et al. Outcomes following endovascular vs open repair of abdominal aortic aneurysm: A randomized trial. JAMA 2009. October 14;302(14):1535–42. [DOI] [PubMed] [Google Scholar]
- 26.Endovascular versus Open Repair of Abdominal Aortic Aneurysm. N Engl J Med 2010. May 20;362(20):1863–71. [DOI] [PubMed] [Google Scholar]
- 27.Powell JT, Sweeting MJ, Ulug P, Blankensteijn JD, Lederle FA, Becquemin J-P, et al. Meta-analysis of individual-patient data from EVAR-1, DREAM, OVER and ACE trials comparing outcomes of endovascular or open repair for abdominal aortic aneurysm over 5 years. Br J Surg [Internet] 2017. February [cited 2018 Nov 1];104(3):166–78. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5299468/ [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Brahmbhatt R, Gander J, Duwayri Y, Rajani RR, Veeraswamy R, Salam A, et al. Improved trends in patient survival and decreased major complications after emergency ruptured abdominal aortic aneurysm repair. J Vasc Surg 2016. January;63(1):39–48. [DOI] [PubMed] [Google Scholar]
- 29.Endovascular Repair of Aortic Aneurysm in Patients Physically Ineligible for Open Repair. N Engl J Med [Internet] 2010. May 20 [cited 2018 Dec 22];362(20):1872–80. Available from: http://www.nejm.org/doi/abs/10.1056/NEJMoa0911056 [DOI] [PubMed] [Google Scholar]
- 30.Lederle FA, Johnson GR, Wilson SE, et al. Rupture rate of large abdominal aortic aneurysms in patients refusing or unfit for elective repair. JAMA [Internet] 2002. June 12;287(22):2968–72. Available from: 10.1001/jama.287.22.2968 [DOI] [PubMed] [Google Scholar]
- 31.Kent KC. Abdominal Aortic Aneurysms. Solomon CG, editor. N Engl J Med [Internet] 2014. November 27 [cited 2018 Dec 20];371(22):2101–8. Available from: http://www.nejm.org/doi/10.1056/NEJMcp1401430 [DOI] [PubMed] [Google Scholar]
- 32.Parkinson F, Ferguson S, Lewis P, Williams IM, Twine CP. Rupture rates of untreated large abdominal aortic aneurysms in patients unfit for elective repair. J Vasc Surg [Internet] 2015. June [cited 2018 Oct 30];61(6):1606–12. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0741521414019053 [DOI] [PubMed] [Google Scholar]
- 33.Kwok AC, Semel ME, Lipsitz SR, Bader AM, Barnato AE, Gawande AA, et al. The intensity and variation of surgical care at the end of life: a retrospective cohort study. The Lancet 2011. October;378(9800):1408–13. [DOI] [PubMed] [Google Scholar]
- 34.Itoga NK, Rothenberg KA, Suarez P, Ho T-V, Mell MW, Xu B, et al. Metformin prescription status and abdominal aortic aneurysm disease progression in the U.S. veteran population. J Vasc Surg [Internet] 2018. September 6 [cited 2018 Dec 21]; Available from: http://www.sciencedirect.com/science/article/pii/S0741521418316835 [DOI] [PMC free article] [PubMed]
- 35.Baxter BT, Matsumura J, Curci J, McBride R, Blackwelder WC, Liu X, et al. Non-Invasive Treatment of Abdominal Aortic Aneurysm Clinical Trial (N-TA3CT): Design of a Phase IIb, Placebo-Controlled, Double-Blind, Randomized Clinical Trial of Doxycycline for the Reduction of Growth of Small Abdominal Aortic Aneurysm. Contemp Clin Trials [Internet] 2016. May [cited 2018 Dec 21];48:91–8. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4964873/ [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Hicks CW, Obeid T, Arhuidese I, Qazi U, Malas MB. Abdominal aortic aneurysm repair in octogenarians is associated with higher mortality compared with nonoctogenarians. J Vasc Surg [Internet] 2016. October [cited 2018 Oct 5];64(4):956–965.e1. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0741521416300246 [DOI] [PubMed] [Google Scholar]
- 37.Patel VI, Lancaster RT, Mukhopadhyay S, Aranson NJ, Conrad MF, LaMuraglia GM, et al. Impact of chronic kidney disease on outcomes after abdominal aortic aneurysm repair. J Vasc Surg [Internet] 2012. November [cited 2018 Oct 5];56(5):1206–13. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0741521412010208 [DOI] [PubMed] [Google Scholar]
- 38.Tucker P, Flink B, Varley P, Hall D, Johanning J, Clevenger C, et al. Implementation of a RAI-frailty screening across surgical clinics: a quality improvement initiative. BMJ Qual Saf [Internet] 2016. December [cited 2018 Oct 5];25(12):1012.1–1012. Available from: http://qualitysafety.bmj.com/lookup/doi/10.1136/bmjqs-2016-IHIabstracts.26 [Google Scholar]
- 39.Arya S, Long CA, Brahmbhatt R, Shafil S, Brewster LB, Veeraswamy R, et al. Preoperative Frailty Increases Risk of Nonhome Discharge after Elective Vascular Surgery in Home-Dwelling Patients. Ann Vasc Surg 2016. August 1;35:19–29. [DOI] [PubMed] [Google Scholar]
- 40.Edgerton JR, Herbert MA, Mahoney C, Armstrong D, Dewey TM, Holper E, et al. Long-Term Fate of Patients Discharged to Extended Care Facilities After Cardiovascular Surgery. Ann Thorac Surg [Internet] 2013. September [cited 2018 Nov 1];96(3):871–7. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0003497513008540 [DOI] [PubMed] [Google Scholar]
- 41.Puts MTE, Toubasi S, Andrew MK, Ashe MC, Ploeg J, Atkinson E, et al. Interventions to prevent or reduce the level of frailty in community-dwelling older adults: a scoping review of the literature and international policies. Age Ageing 2017. May;46(3):383–92. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Racine AM, Fong TG, Gou Y, Travison TG, Tommet D, Erickson K, et al. Clinical outcomes in older surgical patients with mild cognitive impairment. Alzheimers Dement 2018. May;14(5):590–600. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Partridge JSL, Dhesi JK, Cross JD, Lo JW, Taylor PR, Bell R, et al. The prevalence and impact of undiagnosed cognitive impairment in older vascular surgical patients. J Vasc Surg [Internet] 2014. October [cited 2018 Dec 21];60(4):1002–1011.e3. Available from: https://linkinghub.elsevier.com/retrieve/pii/S074152141400843X [DOI] [PubMed] [Google Scholar]
- 44.Sepehri A, Beggs T, Hassan A, Rigatto C, Shaw-Daigle C, Tangri N, et al. The impact of frailty on outcomes after cardiac surgery: A systematic review. J Thorac Cardiovasc Surg [Internet] 2014. December [cited 2018 Dec 21];148(6):3110–7. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0022522314010678 [DOI] [PubMed] [Google Scholar]
- 45.Brown CH, Max L, Laflam A, Kirk L, Gross A, Arora R, et al. The Association Between Preoperative Frailty and Postoperative Delirium After Cardiac Surgery. Anesth Analg [Internet] 2016. August [cited 2018 Dec 21];123(2):430–5. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406128/ [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Kassahun WT. The effects of pre-existing dementia on surgical outcomes in emergent and nonemergent general surgical procedures: assessing differences in surgical risk with dementia. BMC Geriatr [Internet] 2018. July 3 [cited 2018 Aug 6];18. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029045/ [DOI] [PMC free article] [PubMed]
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