- Email: [email protected]
Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate
HLC3025_proof ■ 25 November 2019 ■ 1/8
ORIGINAL ARTICLE
Heart, Lung and Circulation (2019) -, -–1443-9506/19/$36.00 https://doi.org/10.1016/j.hlc.2019.10.007
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59
Q1
Q7
Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate Sudish Lal, MBChB a,*, Andrew Gray, BCom b, Eric Kim, MBChB a, Richard W. Bunton, MBChB c, Philip Davis, MBChB c, Ivor F. Galvin, MBChB c, Michael J.A. Williams, MD a,d a
Department of Cardiology, Dunedin Hospital, Dunedin, New Zealand Biostatistics Unit, Office of the Dean, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand c Department of Cardiothoracic Surgery, Dunedin Hospital, Dunedin, New Zealand d Department of Medicine, University of Otago, Dunedin School of Medicine, Dunedin, New Zealand b
Q2
Received 6 March 2019; received in revised form 16 July 2019; accepted 13 October 2019; online published-ahead-of-print xxx
Background
Cardiac surgery risk scoring systems predict operative mortality but not outcomes related to preoperative frailty. The aim of this study was to assess frailty in a cohort of older cardiac surgery patients as a predictor of postoperative outcomes.
Methods
Prospective data was collected on patients 65 years of age and older undergoing cardiac surgery between September 2015 and October 2016 at Dunedin Hospital. Frailty was assessed with the Edmonton frail scale and five-metre gait speed. The primary endpoint was length of hospital stay. Secondary outcomes included postoperative complications, major adverse events, death and 12-month readmission rate.
Results
Among the 96 patients, median age was 74 (interquartile range 10.5) and 65 (68%) were males. Of the sample 64 (67%) were scored as not frail, 22 (23%) as vulnerable, and 10 (10%) as frail. The median (interquartile range) postoperative days’ stay were: not frail 6 (2), vulnerable 9.5 (8), and frail 15 (13). Survival analysis adjusting for EuroSCORE II, age, sex and surgery type showed that greater Edmonton frail scale scores were independently predictive of longer post-surgery hospital stay with a hazard ratio for discharge of 0.83 (95% confidence interval 0.76–0.91, p,0.001) per point. The Edmonton frail scale score was associated with the 12-month post discharge number of readmissions (adjusted incidence rate ratio 1.24 (95% confidence interval 1.13–1.37, p,0.001) per point.
Conclusions
The Edmonton frail scale score predicts length of hospital stay post cardiac surgery and 12-month readmission rate in patients older than 65 years of age.
Keywords
Frailty Elderly Cardiac surgery Edmonton frail scale
Introduction Frailty is considered a multi-dimensional syndrome resulting from a reduction in physiological reserves and an increase in physical and functional decline when exposed to external stressors [1]. The concept of frailty is generally associated with the physiological process of ageing (‘biological age’)
rather than chronological age alone, with, for example, some fit and well patients in their eighties being more robust than others with multiple co-morbidities in their sixties. Among those greater than 75 years of age, cardiovascular disease is the leading cause of major morbidity and mortality and the proportion of patients who undergo cardiac surgery in this age range is rapidly increasing [2]. It is recognised that
*Corresponding author at: Department of Medicine, Dunedin Hospital, 201 Great King Street, Dunedin, 9054, New Zealand., Email: [email protected] Ó 2019 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118
HLC3025_proof ■ 25 November 2019 ■ 2/8
2
119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183
development of models which include frailty assessment will be extremely beneficial in estimating not only mortality but also morbidity in elderly patients undergoing cardiac surgery [3,4]. Rolfson et al. found that the Edmonton frail scale (EFS) and the geriatrician’s impression of frailty were highly similar, with the advantage of the EFS being able to be carried out by a non-geriatrician in a relatively short time [5]. The five-metre gait speed is a very simple test to screen for frailty in elderly patients and, in a large population-based cohort study, was shown to be independently predictive, after adjusting for the Society of Thoracic Surgeons (STS) risk score, of mortality (odds ratio [OR] 1.11 per 0.1 metre/second decrease in gait speed; 95% confidence interval [CI] 1.07–1.16) in elderly patients undergoing cardiac surgery [6]. The aim of the present study was to determine if there were significant associations between frailty, as measured objectively with the EFS and the five-metre gait speed test, and the length of hospital stay and adverse events for elderly patients undergoing cardiac surgery. Such associations would, if independent of age and current surgical risk scoring tools, be indications for the use of frailty measures during routine preoperative assessment to better risk stratify the elderly and potentially focus specific interventions in those with higher frailty.
Materials and Methods Study Population Consent for this prospective observational study was obtained from the University of Otago Human Ethics Committee (Health). A consecutive cohort of elective or inhospital patients aged 65 years undergoing coronary artery bypass grafting (CABG), valve surgery, or a combination at our institution were recruited between 1 September 2015 and 30 October 2016. The only exclusion criteria were if a patient: could not consent, refused consent, underwent emergency surgery (defined as unscheduled surgery required within 24 hours of unplanned admission), or was bedbound.
Sample Size Calculation A sample size of n=100 patients was determined based on pragmatic grounds given the time and resources available but also as sufficient to allow up to 10 statistical predictors for continuous outcomes based on the heuristic of 10 observations per predictor from linear regression models. Assuming approximately 10% of patients would be frail, this would provide around n=10 such patients [7,8].
Risk Assessment Frailty was assessed using the EFS, which looks at multidimensional aspects of patient well-being, including cognition, assistance with activities of daily living, and medication use (Supplementary Table 1) [5]. The five-metre gait speed test was recorded as the mean time from three attempts by a patient to walk at a comfortable pace from a line marked
S. Lal et al.
zero to a distance marked five metres away with rest in between attempts as needed [9]. Patients were allowed to use walking aids if they generally did so when mobilising. These assessments were performed at least 24 hours prior to the day of surgery. In addition to this, baseline variables were documented along with calculation of the logistic European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) [10].
Outcomes The primary outcome was length of hospital stay postsurgery. Secondary study endpoints included time in intensive care unit, postoperative complications, major adverse cardiac or cerebrovascular event, and death. These outcomes were assessed from the date of surgery. One-year follow-up was carried out via the hospital database to assess the number of readmissions and mortality during the 12 months post discharge.
Statistical Methods Appropriate descriptive statistics were calculated for all variables of interest (counts and percentages for categorical variables, means and standard deviations for approximately normally distributed continuous variables, and medians and inter-quartile ranges [IQR] for skewed continuous variables). Categorical variables were compared between levels of frailty using Chi-squared tests, except where fewer than 80% of cells had expected cell counts of five or greater, in which case Fisher’s exact test was used instead. Continuous variables were compared in a similar way using Kruskal-Wallis tests. For continuous outcomes, linear regression was used but where model assumptions around residuals (normally distributed and homoscedastic) were not satisfied, quantile regression was used to model medians instead. For binary outcomes, logistic regression was used to model associations with EFS scores; with exact logistic regression used where the number of events was small (,10). The association between EFS score and time to discharge was modelled using Cox’s proportional hazards regression. Counts of events post-discharge were modelled using Poisson or, where there was evidence of overdispersion from a likelihood ratio test, negative binomial regression. Non-linearities were investigated through the addition of a quadratic term and use of a likelihood ratio test. Where the number of events (10 observations per predictor for linear and quantile regression, 10 cases with events and ten without the event per predictor for logistic regression, 10 events per predictor for Cox’s proportional hazard models, and 10 counts per predictor for Poisson or negative binomial regression) permitted, models were adjusted for all or of EuroSCORE II, age, sex, and type of surgery (CABG/valve/both) [11,12]. The effects of adding variables to predictive models (for example, adding the EFS score to a model already containing the walking score, and vice versa) were evaluated using likelihood ratio tests. Statistical analyses were performed using Stata 15.1 with twosided p,0.05 considered statistically significant.
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248
HLC3025_proof ■ 25 November 2019 ■ 3/8
3
Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate
249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313
Results A total of 96 patients were recruited into the study with a median (IQR) age of 74 (10.5) and comprising n=65 (68%) males (Table 1). All patients recruited met the inclusion criteria for the study. Overall, 46 (48%) patients underwent CABG, 25 (26%) valve surgery, and 25 (26%) both. Prior to
surgery, 64 (67%) were scored as not frail (EFS scores 0–5), 22 (23%) as vulnerable (EFS scores 6–7), and 10 (10%) as frail (EFS scores 8–17). The median (IQR) EFS score was 4 (4) overall, with a minimum of 0 and a maximum of 11 recorded, and medians (IQRs) of 3 (2), 6 (1), 8 (2) for the not frail, vulnerable, and frail groups respectively. The median (IQR) EuroSCORE II was 1.6 (1.3), 3.4 (4.0), and 2.7 (1.0) for the not
Q3
Table 1 Baseline characteristics. Edmonton Frail Scale category Not frail n=64
Vulnerable n=22
Frail n=10
Total n=96
P-value
65 (68)
0.226 0.123
Sex Male (%) Patient type
47 (73)
12 (55)
6 (60)
Elective (%)
36 (56)
8 (36)
3 (30)
47 (49)
Inpatient (%)
28 (44)
14 (64)
7 (70)
49 (51)
65-74 (%)
40 (63)
9 (41)
1 (10)
50 (52)
751 (%)
24 (38)
13 (59)
9 (90)
46 (48)
,25 (%) 25-29.9 (%)
12 (19) 32 (50)
2 (10) 10 (48)
2 (20) 4 (40)
16 (17) 46 (48)
30.01 (%)
20 (31)
9 (43)
4 (40)
33 (35)
Diabetes (%)
8 (13)
6 (27)
4 (40)
18 (19)
0.052*
Hypertension (%)
42 (66)
14 (64)
7 (70)
63 (66)
0.940
Any MI (%)
25 (39)
9 (41)
2 (20)
36 (38)
0.477
Endocarditis (%)
0 (0)
2 (9)
1 (10)
3 (3)
0.035*
Previous CVA/TIA/SEE (%)
5 (8)
5 (23)
2 (20)
12 (13)
0.109*
Heart Failure on admission (%) Atrial fibrillation (%)
5 (8) 6 (9)
4 (18) 4 (18)
2 (20) 4 (40)
11 (11) 14 (15)
0.224* 0.033*
Mild (%)
6 (9)
4 (18)
2 (20)
12 (13)
Moderate (%)
5 (8)
1 (5)
1 (10)
7 (7)
Severe (%)
2 (3)
0 (0.0)
0 (0.0)
2 (2)
CABG (%)
35 (55)
8 (36)
3 (30)
46 (48)
Valve surgery (%) CABG and Valve surgery (%)
16 (25) 13 (20)
5 (23) 9 (41)
4 (40) 3 (30)
25 (26) 25 (26)
,5s (%)
6 (9)
1 (5)
0 (0)
7 (7)
5s-6s (%)
41 (64)
7 (32)
0 (0)
48 (50)
.6s (%)
17 (27)
14 (64)
10 (100)
41 (43)
0.004
Age group
0.787*
BMI category
0.747*
Pulmonary hypertension
0.236*
Surgery type
,0.001*
5-metre gait speed test
median (IQR)
,0.001**
5.6 (1.0)
6.4 (1.3)
7.2 (1.1)
5.9 (1.5)
Ejection fraction median (IQR)
60.0 (12.5)
55.0 (10.0)
59.0 (14.0)
60.0 (11.5)
0.560**
CrCl (ml/min) median (IQR) Pre-op Hb (g/L) median (IQR)
69.0 (20.0) 137.0 (17.5)
55.0 (22.0) 129.0 (24.0)
59.5 (12.0) 113.5 (24.0)
66.0 (22.0) 133.0 (20.5)
,0.001** ,0.001** ,0.001**
EuroSCORE II median (IQR)
1.6 (1.3)
3.4 (4.0)
2.7 (1.0)
2.0 (2.0)
Pre-op length of stay median (IQR)
2.5 (9.0)
7.5 (14.0)
12.0 (17.0)
6.0 (12.0)
Edmonton Frail Scale score median
3 (2)
6 (1)
8 (2)
4 (4)
0.099** —
(IQR) P-values from Chi-squared tests aside from *Fisher’s exact test and **Kruskal2Wallis test. Abbreviations: BMI, body mass index; CABG, coronary artery bypass surgery; CrCl, creatinine clearance; CVA, cerbrovascular accident; Hb, haemoglobin; IQR, Q4
314 315 316 317 318 319 320 321 322
interquartile range; MI, myocardial infarction; Pre-op, preoperative; SE, systemic embolism; TIA, transient ischaemic attack.
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375
HLC3025_proof ■ 25 November 2019 ■ 4/8
4
376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440
S. Lal et al.
unadjusted and adjusted (for EuroSCORE II and surgery type) models (Table 4). In both the unadjusted and adjusted models, each one-unit increase in the EFS score was associated with a 17% reduction in the chance of discharge at a given point in time (unadjusted HR 0.83, 95% CI 0.77–0.91, p,0.001; adjusted for EuroSCORE II and procedure type HR 0.83, 95% CI 0.76–0.90, p,0.001). In other words, a patient moving from the median score for the not frail group (score of 3) to the median score for the vulnerable group (score of 6) would decrease the chance of discharge at any point in time by 42% in the unadjusted model and 43% in the adjusted model, and moving from the median score for the not frail group to the median score for the frail group (score of 8) would decrease this chance by 60% in both the unadjusted and adjusted models. The median lengths of stay reported above were 37% lower in the not frail group compared to the vulnerable group and 60% lower in the not frail group compared to the frail group. In the adjusted model, there was no evidence that EuroSCORE II was associated with discharge (p=0.376) and only a non-statistically significant tendency that surgery type was associated with discharge (Wald p=0.079). Adding age (likelihood ratio p=0.287) or sex (p=0.581) did not improve this adjusted model or meaningfully change the estimates (HR 0.83, 95% CI 0.76 to 0.91). As can be seen in the KaplanMeier plot in Figure 1, the unadjusted difference between categories of EFS scores is primarily between those not frail and those with any frailty, with little difference between those with scores in the vulnerable (range 6–7) and frail range (range 8–11). There was no evidence of associations in unadjusted models for EFS scores and each of: blood transfusion, new
frail, vulnerable, and frail groups respectively. Increasing proportions of patients with diabetes (13%, 27%, 40%), atrial fibrillation (9%, 18%, 40%), .6 seconds to complete fivemetre gait speed test (27%, 64%, 100%) were seen in the not frail, vulnerable and frail group respectively. Higher proportions of patients requiring inpatient surgery were also seen in the frail (70%) and vulnerable (64%) group when compared to the not frail (44%). The median (IQR) length of stay prior to surgical intervention was: not frail 2.5 (9) days, vulnerable 7.5 (14) days and frail 12 (17) days. The overall median length of hospital stay post cardiac surgery was 7 days (Table 2). Inpatient and elective surgeries were not statistically significantly different in terms of length of stay post cardiac surgery (results not shown, unadjusted p=0.546, adjusted for age, sex, EuroSCORE II, and procedure p=0.485). As shown in Table 2, there was no evidence of differences in terms of sex, inpatient versus elective, or age group for the procedures types. There was no evidence that length of stay varied between the three procedures (unadjusted Wald p=0.174, adjusted for age, sex, and EuroSCORE II Wald p=0.463). EuroSCORE II, however, differed between procedures (unadjusted Wald p,0.001), being greater in the combined procedure group compared to each of valve (p=0.004) or CABG (p,0.001) only. Results were similar after adjusting for age and sex (Wald p,0.001, both versus valve only p,0.001, and both versus CABG only p,0.001). Among patients grouped into not frail, vulnerable, and frail categories based on the EFS risk score, post-surgery outcomes are summarised in Table 3. The median lengths of hospital stay were 6 days, 9.5 days, and 15 days respectively. Survival analyses for post-surgery length of stay found statistically significant associations with EFS scores in
Table 2 Procedure type, patient demographic and length of hospital stay post cardiac surgery. Procedure Valve only n (%)
CABG only n (%)
Both n (%)
Total (n=96) n (%)
Sex Female
12 (48)
12 (26)
7 (28)
31 (32)
Male
13 (52)
34 (74)
18 (72)
65 (68)
Elective
15 (60)
17 (37)
15 (60)
47 (49)
Inpatient
10 (40)
29 (63)
10 (40)
49 (51)
Unadjusted p-value
Adjusted p-value
0.146
Patient type 0.078
Age group 65-74
10 (40)
29 (63)
11 (44)
50 (52)
751
15 (60)
17 (37)
14 (56)
46 (48)
Median (IQR)
Median (IQR)
Length of hospital stay (days) EuroSCORE II
Median (IQR)
0.115
Median (IQR)
6 (5)
6 (3)
8 (8)
7 (4)
1.9 (2.1)
1.6 (1.2)
3.4 (4.4)
2.0 (2.0)
0.174
0.463*
,0.001
,0.001†
P-values for sex, patient type, and age group are from Chi-squared tests. Results for length of stay from Cox’s proportional hazards regression and for EuroSCORE II from quantile regression modelling medians * Adjusted for age, sex, and EuroSCORE II
†
Adjusted for age and sex.
Abbreviations: CABG, coronary artery bypass surgery; IQR, interquartile range.
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505
HLC3025_proof ■ 25 November 2019 ■ 5/8
5
Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate
506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570
Table 3 Outcomes following cardiac surgery in patients categorised using Edmonton Frail Scale. Not frail (n=64) n (%)
Vulnerable (n=22) n (%)
Frail (n=10) n (%)
Total (n=96) n (%)
30-day mortality
0 (0)
0 (0)
1 (10)
1 (1)
Blood transfusion
9 (14)
6 (27)
2 (20)
17 (18)
New AF
23 (36)
8 (36)
4 (40)
35 (36)
Pneumonia
3 (5)
3 (14)
1 (10)
7 (7)
Delirium
3 (5)
3 (14)
1 (10)
7 (7)
AKI Resternotomy
4 (6) 3 (5)
5 (23) 1 (5)
4 (40) 2 (20)
13 (14) 6 (6)
Wound infection
1 (2)
1 (5)
4 (40)
6 (6)
CVA
5 (8)
5 (23)
1 (10)
11 (11)
Median (IQR)
Median (IQR)
Median (IQR)
Median (IQR)
6.0 (2)
9.5 (8)
15.0 (13)
7.0 (4)
Length of hospital stay (days)
Abbreviations: CVA, cerebrovascular accident; IQR, interquartile range; AKI, acute kidney injury; AF, atrial fibrillation.
atrial fibrillation, delirium, and cerebrovascular accident. Adjusting the new atrial fibrillation model for EuroSCORE II only did not change this result. Unadjusted models found evidence of increasing risks for each of pneumonia, acute kidney injury, resternotomy, and wound infection, with higher EFS scores (all p#0.046). Adding EFS scores to models already containing walk test scores was associated with improved prediction of length of stay (likelihood ratio p,0.001 for continuous and categorical walk scores in models also adjusting for age, sex, procedure
Table 4 Edmonton frailty score and association with outcomes Odds ratio (95% CI)
P-value
0.96 (0.78 – 1.19)
0.709
1.01 (0.85 – 1.19)
0.934
Adjusted
1.06 (0.89 – 1.27)
0.489
Pneumonia
1.37 (1.01 – 1.90)
0.046
Delirium
1.25 (0.92 – 1.71)
0.161
AKI Resternotomy
1.36 (1.11 – 1.66) 1.45 (1.04 – 2.09)
0.003 0.029
Wound infection
1.82 (1.25 – 2.91)
0.001
CVA
1.23 (0.96 – 1.58)
0.095
Blood transfusion New AF Unadjusted a
Hazard ratio (95% CI) Total length of hospital stay Unadjusted
0.83 (0.77 – 0.91)
,0.001
Adjusteda
0.83 (0.76 – 0.91)
,0.001
Abbreviations: AF, atrial fibrillation, AKI, acute kidney injury; CVA, cerebrovascular accident. a
Adjusted for EuroSCORE II, age, sex, type of surgery.
and EuroSCORE II). However, going in the opposite direction, adding walk test scores to models already containing EFS scores was not associated with improved prediction (likelihood ratio p0.493 for continuous and categorical walk scores in models also adjusting for age, sex, procedure and EuroSCORE II). In the 12-month post discharge, there were 19 patients with 33 hospital admissions related to major adverse cardiovascular or cerebrovascular events (MACCE), and 47 patients with 85 non-MACCE related admissions including 26 patients with 31 admissions for elective non-cardiac surgery/procedure. Post discharge follow-up analysis (Table 5) showed the EFS score was associated with the number of readmissions. With each point increase on the scale the adjusted incidence rate ratio was 1.24 (p,0.001) for readmissions.
Discussion Our study shows that frailty is an independent risk factor for length of hospital stay post cardiac surgery. The median (IQR) length of postoperative hospital stay in days was 6 (2), 9.5 (8), and 15 (13) in the not frail, vulnerable, and frail group respectively. For each point increase on EFS, there was a 17% lower chance of discharge on any particular day. Frailty was also positively associated with some adverse outcomes postsurgery: pneumonia, acute kidney injury, resternotomy, and wound infection. At 1-year follow-up, frailty was associated with a higher rate of readmission with an adjusted incidence rate ratio of 1.26 for each point increase in the EFS. The syndrome of frailty is often associated with ageing. In our cohort, whilst 75-year olds made up 38% of the not frail group, they made up 90% of the frail category. There exists a large knowledge gap in cardiovascular care of the elderly population, especially for those who have multiple
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635
HLC3025_proof ■ 25 November 2019 ■ 6/8
6
print & web 4C=FPO
636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700
S. Lal et al.
Figure 1 Time to discharge grouped by not frail (blue), vulnerable (red), and frail (green) patients.
comorbidities or those with complexity of care [13]. Two scoring systems in routine clinical practise used for assessing perioperative mortality in patients undergoing cardiac surgery are the EuroSCORE II and the STS score. Both these risk assessment models have been shown to have limitations [14,15]. An important limitation of both scoring systems is their inability to predict outcomes such as length of hospital stay, readmissions, or quality of life post procedure. There is significant variability in the prevalence of frailty depending on the criteria used for assessment (phenotype vs cumulative deficit indices). The median age in our cohort was 74 years with a 10% prevalence of frailty while 23% of the patients were in the vulnerable category. In a study of community-dwelling 75 year olds, the prevalence of frailty was 9.6% (95% CI 7.6–11.5) and pre-frailty 47% (95% CI 42.7–51.2) [16]. In a systematic review of adults 65 years of age, the overall weighted prevalence of frailty was 10.7% (95% CI 9.6–10.2) and 44% (44.2–44.7) for pre-frailty [8]. Investigators in this review, however, identified substantial variation in the reported frailty rates among various studies ranging from 4% to 59% based on the model used for
measuring it. Frailty appeared to be more prevalent in women than men (9.6% vs 5.2%). There was a trend of increasing frailty with age with a 4% prevalence in the 65–69year age group rising to 26% in the older than 85-year age group. Similarly, among elderly patients that proceed to cardiac surgery, the prevalence of frailty reported has been between 20% to 60% [17]. Frailty has been shown to be associated with quality of life, hospital admissions, institutionalisation, and mortality in the community dwelling elderly [18,19]. In the Canadian Study of Health and Aging (CSHA), 2,305 elderly patients 65 years were assessed with a seven-point CSHA Clinical Frailty Scale and followed for 5 years [20]. The investigators found that, with each incremental rise in category (very fit, well without active disease, well with treated comorbidity, vulnerable, mildly frail, moderately frail, severely frail), there was a 21% (95% CI 12.5–30.6) higher risk of death in the medium-term of about 70 months. Independent of age, increasing degree of frailty in geriatric medical and surgical patients has also been shown to be associated with protracted length of hospital stay, discharge to institutional care, major morbidity and mortality [21,22]. A systematic review encompassing 54,000 elderly people from various studies demonstrated the association between cardiovascular disease and frailty with an odds ratio between 2.7 and 4.1 [23]. Greater disease burden, comorbidities, and surgical urgency with higher morbidity and mortality have been documented in the elderly undergoing CABG or valve surgery [24,25]. Paradoxically the studies also reveal it is the elderly that stand to gain more with mortality and morbidity in the subset of elderly with fewer comorbidities approaching that of the younger population [24–26]. Therefore, selecting the elderly not based merely on their age or traditional “end-ofthe-bed” assessment to determine who will benefit the most with the least chance of a major adverse outcome is paramount. Once those at risk are identified, specific interventions can be tested to determine if post-surgical hospital stay can be modified in the vulnerable and frail groups. Frailty is increasingly recognised as an independent risk factor associated with poor outcomes in an elderly individual having cardiac surgery [27,28]. Various validated methods
Table 5 Associations between Edmonton frailty score and 12-month outcomes.
Q5
Unadjusted Incidence rate ratio (95% CI)
P-value
Adjusted Incidence rate ratio (95% CI)
P-value
Admissions due to MACCE
1.54 (1.29–1.84)
,0.001
—
—
Non-MACCE admissions Total admissions
1.16 (1.03–1.31) 1.26 (1.14–1.39)
0.012 ,0.001
1.16 (1.03–1.31)b 1.24 (1.13–1.37)b
0.016 ,0.001
Number of other elective surgery
1.04 (0.90–1.21)
0.561
1.04 (0.90–1.21)a
0.585
IRRs, 95% CIs, and p-values are from Poisson or (where there was evidence of overdispersion) negative binomial regression models. — Number of events too small for adjusted modelling (,20 non-zero counts). Abbreviations: MACCE, major adverse cardiovascular or cerebrovascular events; IRR, a
Adjusted for EuroSCORE II (at least 20 non-zero counts).
b
Adjusted for EuroSCORE II and surgery type (CABG/valve/both) (at least 40 non-zero counts).
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765
HLC3025_proof ■ 25 November 2019 ■ 7/8
Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate
766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830
for identifying frailty exist [29]. Models used in assessing frailty in older patients with cardiovascular disease undergoing surgical or transcatheter interventions have consistently shown frailty to be independently associated with predicting mortality and major morbidity [17,30,31]. The Frailty in Older Adults Undergoing Aortic Valve Replacement study looked at seven different frailty scales in predicting outcomes post aortic valve replacement (transcatheter aortic valve replacement [TAVR] or surgical aortic valve replacement) and found poor outcome at 1-year increased from 35% for the entire cohort to .50% in those who were frail [32]. The Comprehensive Assessment of Frailty (CAF) score was developed and applied preoperatively to 400 patients 74 years undergoing CABG, valve surgery or TAVR [33]. The investigators showed an association between high CAF score and 30-day mortality. However specific equipment was required and took time to conduct, leading to their acknowledgement that it may not be suitable for daily clinical practice. They developed a new easily applicable score which could be performed in a few minutes, and found an association between this and 1-year mortality [34]. Afilalo et al., in a large study of 15,171 patients undergoing CABG, valve surgery, or a combination, evaluated the prognostic value of gait speed by performing a five-metre gait speed test as a simple surrogate of frailty [6]. The impact of slow gait speed was independently associated with operative mortality (11% relative increase with each 0.1m/s decrease, p,0.01) with a weaker association between the composite of mortality or major morbidity. It was concluded that gait speed should be used in conjunction with other established frailty tests to discriminate frailty in the older population undergoing cardiac surgery better. From a practical point of view the criterion that is employed in daily practise should be easy to understand, not necessarily require a geriatrician to perform and not be time consuming. Preoperative frailty assessment in elderly patients undergoing cardiac surgery is an emerging paradigm. There is presently no general agreement as to which single frailty assessment tool to use in this group though the expert consensus in geriatric medicine is that elderly people should be screened for frailty especially if undergoing invasive procedures [1,35]. Our study demonstrates identifying frailty as a continuum with EFS in elderly patients undergoing cardiac surgery adding incremental information in addition to the EuroSCORE II. The EFS is simple to understand, practical to perform in patients awaiting cardiac surgery, time-efficient, and easy to administer at bedside. Cardiac surgery is associated with substantial stressors with potential of adverse outcomes particularly in vulnerable frail elderly individuals. Frailty assessment using EFS to screen and identify such individuals preoperatively and quantify frailty on the continuous gradation scale is likely to further enhance the decisionmaking process between clinicians and older adults considered for cardiac surgery. Employing EFS as a frailty assessment tool has the potential to impact on planning, implementation, delivery and measurement of outcomes of
7
health care in the cardio-surgical elderly population. A comprehensive systematic literature review of 24 populationbased studies estimated that 3–5% of deaths among older adults could be delayed if frailty was prevented [7]. This is an initial observational study which was not designed to detect a mortality difference by frailty (due to the low expected number of events within a limited follow-up period). We have focussed on surrogate endpoints such as length of stay, adverse events post-surgery, and readmissions within 12 months. As an observational study, it is possible that our findings of frailty being associated with poorer outcomes were confounded by unknown variables despite adjusting for known influences when possible. Larger studies would be needed to consider potential confounding more carefully. All invited subjects consented to the study so results may be generalised to the wider population of patients undertaking this procedure without concerns about participation biases. We had complete 12-month follow-up data so missing data mechanisms did not affect our results.
Conclusions These results support incorporating routine preoperative frailty assessment alongside current risk scores in elderly patients considered for cardiac surgery to improve decisionmaking. Such assessments could be useful in characterising those who will benefit, those who will have minimal gain, and those who may actually be harmed in this growing group of patients. The EFS score predicts length of hospital stay post cardiac surgery in patients older than 65 years of age. It also assists in predicting those at higher risk of complications post-surgery and readmissions post discharge. The EFS is a quantifiable frailty assessment tool and when used in screening of elderly cardiac surgical adults it provides gradation of frailty potentially facilitating better identification of those who may benefit most. Larger studies are needed to further explore an indication for integration of this simple to perform scale as a risk stratification measure to complement the pre-existing surgical scoring tools.
Conflict of Interest There is no conflict of interest for all authors
IRB Approval University of Otago Human Ethics Committee (Health), 12 February 2014, H14/013
Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j. hlc.2019.10.007.
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 Q6881 882 883 884 885 886 887 888 889 890 891 892 893 894 895
HLC3025_proof ■ 25 November 2019 ■ 8/8
8
896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952
References [1] Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet 2013;381:752–62. [2] Alexander KP, Newby LK, Cannon CP, Armstrong PW, Gibler WB, Rich MW, et al. Acute coronary care in the elderly, part I: Non–STsegment–elevation acute coronary syndromes: a scientific statement for healthcare professionals from the American Heart Association Council on Clinical Cardiology: in collaboration with the Society of Geriatric Cardiology. Circulation 2007;115:2549–69. [3] Alexander KP, Newby LK, Armstrong PW, Cannon CP, Gibler WB, Rich MW, et al. Acute coronary care in the elderly, part II: ST-segment– elevation myocardial infarction: a scientific statement for healthcare professionals from the American Heart Association Council on Clinical Cardiology: in collaboration with the Society of Geriatric Cardiology. Circulation 2007;115:2570–89. [4] Neupane I, Arora RC, Rudolph JL. Cardiac surgery as a stressor and the response of the vulnerable older adult. Exp Gerontol 2017;87:168–74. [5] Rolfson DB, Majumdar SR, Tsuyuki RT, Tahir A, Rockwood K. Validity and reliability of the Edmonton Frail Scale. Age Ageing 2006;35:526–9. [6] Afilalo J, Kim S, O’Brien S, Brennan JM, Edwards FH, Mack MJ, et al. Gait speed and operative mortality in older adults following cardiac surgery. JAMA Cardiol 2016;1:314–21. [7] Shamliyan T, Talley KM, Ramakrishnan R, Kane RL. Association of frailty with survival: a systematic literature review. Ageing Res Rev 2013;12:719–36. [8] Collard RM, Boter H, Schoevers RA, Oude Voshaar RC. Prevalence of frailty in community-dwelling older persons: a systematic review. J Am Geriatr Soc 2012;60:1487–92. [9] Afilalo J, Eisenberg MJ, Morin J-F, Bergman H, Monette J, Noiseux N, et al. Gait speed as an incremental predictor of mortality and major morbidity in elderly patients undergoing cardiac surgery. J Am Coll Cardiol 2010;56:1668–76. [10] Nashef SA, Roques F, Sharples LD, Nilsson J, Smith C, Goldstone AR, et al. EuroSCORE II. Eur J Cardiothorac Surg 2012;41:734–45. [11] Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol 1996;49:1373–9. [12] Peduzzi P, Concato J, Feinstein AR, Holford TR. Importance of events per independent variable in proportional hazards regression analysis II. Accuracy and precision of regression estimates. J Clin Epidemiol 1995;48:1503–10. [13] Rich MW, Chyun DA, Skolnick AH, Alexander KP, Forman DE, Kitzman DW, et al. Knowledge gaps in cardiovascular care of the older adult population: a scientific statement from the American Heart Association, American College of Cardiology, and American Geriatrics Society. J Am Coll Cardiol 2016;67:2419–40. [14] Barili F, Pacini D, Capo A, Rasovic O, Grossi C, Alamanni F, et al. Does EuroSCORE II perform better than its original versions? A multicentre validation study. Eur Heart J 2013;34:22–9. [15] Wendt D, Osswald BR, Kayser K, Thielmann M, Tossios P, Massoudy P, et al. Society of Thoracic Surgeons score is superior to the EuroSCORE determining mortality in high risk patients undergoing isolated aortic valve replacement. Ann Thorac Surg 2009;88:468–75. [16] Jürschik P, Nunin C, Botigué T, Escobar MA, Lavedán A, Viladrosa M. Prevalence of frailty and factors associated with frailty in the elderly population of Lleida, Spain: the FRALLE survey. Arch Gerontol Geriatr 2012;55:625–31.
S. Lal et al.
[17] Afilalo J, Alexander KP, Mack MJ, Maurer MS, Green P, Allen LA, et al. Frailty assessment in the cardiovascular care of older adults. J Am Coll Cardiol 2014;63:747–62. [18] Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146–57. [19] Song X, Mitnitski A, Rockwood K. Prevalence and 10-year outcomes of frailty in older adults in relation to deficit accumulation. J Am Geriatr Soc 2010;58:681–7. [20] Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ 2005;173:489–95. [21] Partridge JS, Harari D, Dhesi JK. Frailty in the older surgical patient: a review. Age Ageing 2012;41:142–7. [22] Robinson TN, Wallace JI, Wu DS, Wiktor A, Pointer LF, Pfister SM, et al. Accumulated frailty characteristics predict postoperative discharge institutionalization in the geriatric patient. J Am Coll Surg 2011;213:37–42. [23] Afilalo J, Karunananthan S, Eisenberg MJ, Alexander KP, Bergman H. Role of frailty in patients with cardiovascular disease. Am J Cardiol 2009;103:1616–21. [24] Filsoufi F, Rahmanian PB, Castillo JG, Chikwe J, Silvay G, Adams DH. Results and predictors of early and late outcomes of coronary artery bypass graft surgery in octogenarians. J Cardiothorac Vasc Anesth 2007;21:784–92. [25] Graham MM, Ghali WA, Faris PD, Galbraith PD, Norris CM, Knudtson ML. Survival after coronary revascularization in the elderly. Circulation 2002;105:2378–84. [26] Alexander KP, Anstrom KJ, Muhlbaier LH, Grosswald RD, Smith PK, Jones RH, et al. Outcomes of cardiac surgery in patients age 80 years: results from the National Cardiovascular Network. J Am Coll Cardiol 2000;35:731–8. [27] Graham A, Brown CH. Frailty, aging, and cardiovascular surgery. Anesth Analg 2017;124:1053–60. [28] 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 2014;148:3110–7. [29] de Vries NM, Staal JB, van Ravensberg CD, Hobbelen JS, Olde Rikkert MG, Nijhuis-van der Sanden MW. Outcome instruments to measure frailty: a systematic review. Ageing Res Rev 2011;10:104–14. [30] Afilalo J, Mottillo S, Eisenberg MJ, Alexander KP, Noiseux N, Perrault LP, et al. Addition of frailty and disability to cardiac surgery risk scores identifies elderly patients at high risk of mortality or major morbidity. Circ Cardiovasc Qual Outcomes 2012;5:222–8. [31] Esses G, Andreopoulos E, Lin HM, Arya S, Deiner S. A Comparison of three frailty indices in predicting morbidity and mortality after on-pump aortic valve replacement. Anesth Analg 2018;126:39–45. [32] Afilalo J, Lauck S, Kim DH, Lefevre T, Piazza N, Lachapelle K, et al. Frailty in older adults undergoing aortic valve replacement: the FRAILTY-AVR study. J Am Coll Cardiol 2017;70:689–700. [33] Sundermann S, Dademasch A, Praetorius J, Kempfert J, Dewey T, Falk V, et al. Comprehensive assessment of frailty for elderly high-risk patients undergoing cardiac surgery. Eur J Cardiothorac Surg 2011;39:33–7. [34] Sundermann S, Dademasch A, Rastan A, Praetorius J, Rodriguez H, Walther T, et al. One-year follow-up of patients undergoing elective cardiac surgery assessed with the Comprehensive Assessment of Frailty test and its simplified form. Interact Cardiovasc Thorac Surg 2011;13:119–23. [35] Morley JE, Vellas B, Abellan van Kan G, Anker SD, Bauer JM, Bernabei R, et al. Frailty consensus: a call to action. J Am Med Dir Assoc 2013;14:392–7.
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009
ORIGINAL ARTICLE
Heart, Lung and Circulation (2019) -, -–1443-9506/19/$36.00 https://doi.org/10.1016/j.hlc.2019.10.007
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59
Q1
Q7
Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate Sudish Lal, MBChB a,*, Andrew Gray, BCom b, Eric Kim, MBChB a, Richard W. Bunton, MBChB c, Philip Davis, MBChB c, Ivor F. Galvin, MBChB c, Michael J.A. Williams, MD a,d a
Department of Cardiology, Dunedin Hospital, Dunedin, New Zealand Biostatistics Unit, Office of the Dean, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand c Department of Cardiothoracic Surgery, Dunedin Hospital, Dunedin, New Zealand d Department of Medicine, University of Otago, Dunedin School of Medicine, Dunedin, New Zealand b
Q2
Received 6 March 2019; received in revised form 16 July 2019; accepted 13 October 2019; online published-ahead-of-print xxx
Background
Cardiac surgery risk scoring systems predict operative mortality but not outcomes related to preoperative frailty. The aim of this study was to assess frailty in a cohort of older cardiac surgery patients as a predictor of postoperative outcomes.
Methods
Prospective data was collected on patients 65 years of age and older undergoing cardiac surgery between September 2015 and October 2016 at Dunedin Hospital. Frailty was assessed with the Edmonton frail scale and five-metre gait speed. The primary endpoint was length of hospital stay. Secondary outcomes included postoperative complications, major adverse events, death and 12-month readmission rate.
Results
Among the 96 patients, median age was 74 (interquartile range 10.5) and 65 (68%) were males. Of the sample 64 (67%) were scored as not frail, 22 (23%) as vulnerable, and 10 (10%) as frail. The median (interquartile range) postoperative days’ stay were: not frail 6 (2), vulnerable 9.5 (8), and frail 15 (13). Survival analysis adjusting for EuroSCORE II, age, sex and surgery type showed that greater Edmonton frail scale scores were independently predictive of longer post-surgery hospital stay with a hazard ratio for discharge of 0.83 (95% confidence interval 0.76–0.91, p,0.001) per point. The Edmonton frail scale score was associated with the 12-month post discharge number of readmissions (adjusted incidence rate ratio 1.24 (95% confidence interval 1.13–1.37, p,0.001) per point.
Conclusions
The Edmonton frail scale score predicts length of hospital stay post cardiac surgery and 12-month readmission rate in patients older than 65 years of age.
Keywords
Frailty Elderly Cardiac surgery Edmonton frail scale
Introduction Frailty is considered a multi-dimensional syndrome resulting from a reduction in physiological reserves and an increase in physical and functional decline when exposed to external stressors [1]. The concept of frailty is generally associated with the physiological process of ageing (‘biological age’)
rather than chronological age alone, with, for example, some fit and well patients in their eighties being more robust than others with multiple co-morbidities in their sixties. Among those greater than 75 years of age, cardiovascular disease is the leading cause of major morbidity and mortality and the proportion of patients who undergo cardiac surgery in this age range is rapidly increasing [2]. It is recognised that
*Corresponding author at: Department of Medicine, Dunedin Hospital, 201 Great King Street, Dunedin, 9054, New Zealand., Email: [email protected] Ó 2019 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118
HLC3025_proof ■ 25 November 2019 ■ 2/8
2
119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183
development of models which include frailty assessment will be extremely beneficial in estimating not only mortality but also morbidity in elderly patients undergoing cardiac surgery [3,4]. Rolfson et al. found that the Edmonton frail scale (EFS) and the geriatrician’s impression of frailty were highly similar, with the advantage of the EFS being able to be carried out by a non-geriatrician in a relatively short time [5]. The five-metre gait speed is a very simple test to screen for frailty in elderly patients and, in a large population-based cohort study, was shown to be independently predictive, after adjusting for the Society of Thoracic Surgeons (STS) risk score, of mortality (odds ratio [OR] 1.11 per 0.1 metre/second decrease in gait speed; 95% confidence interval [CI] 1.07–1.16) in elderly patients undergoing cardiac surgery [6]. The aim of the present study was to determine if there were significant associations between frailty, as measured objectively with the EFS and the five-metre gait speed test, and the length of hospital stay and adverse events for elderly patients undergoing cardiac surgery. Such associations would, if independent of age and current surgical risk scoring tools, be indications for the use of frailty measures during routine preoperative assessment to better risk stratify the elderly and potentially focus specific interventions in those with higher frailty.
Materials and Methods Study Population Consent for this prospective observational study was obtained from the University of Otago Human Ethics Committee (Health). A consecutive cohort of elective or inhospital patients aged 65 years undergoing coronary artery bypass grafting (CABG), valve surgery, or a combination at our institution were recruited between 1 September 2015 and 30 October 2016. The only exclusion criteria were if a patient: could not consent, refused consent, underwent emergency surgery (defined as unscheduled surgery required within 24 hours of unplanned admission), or was bedbound.
Sample Size Calculation A sample size of n=100 patients was determined based on pragmatic grounds given the time and resources available but also as sufficient to allow up to 10 statistical predictors for continuous outcomes based on the heuristic of 10 observations per predictor from linear regression models. Assuming approximately 10% of patients would be frail, this would provide around n=10 such patients [7,8].
Risk Assessment Frailty was assessed using the EFS, which looks at multidimensional aspects of patient well-being, including cognition, assistance with activities of daily living, and medication use (Supplementary Table 1) [5]. The five-metre gait speed test was recorded as the mean time from three attempts by a patient to walk at a comfortable pace from a line marked
S. Lal et al.
zero to a distance marked five metres away with rest in between attempts as needed [9]. Patients were allowed to use walking aids if they generally did so when mobilising. These assessments were performed at least 24 hours prior to the day of surgery. In addition to this, baseline variables were documented along with calculation of the logistic European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) [10].
Outcomes The primary outcome was length of hospital stay postsurgery. Secondary study endpoints included time in intensive care unit, postoperative complications, major adverse cardiac or cerebrovascular event, and death. These outcomes were assessed from the date of surgery. One-year follow-up was carried out via the hospital database to assess the number of readmissions and mortality during the 12 months post discharge.
Statistical Methods Appropriate descriptive statistics were calculated for all variables of interest (counts and percentages for categorical variables, means and standard deviations for approximately normally distributed continuous variables, and medians and inter-quartile ranges [IQR] for skewed continuous variables). Categorical variables were compared between levels of frailty using Chi-squared tests, except where fewer than 80% of cells had expected cell counts of five or greater, in which case Fisher’s exact test was used instead. Continuous variables were compared in a similar way using Kruskal-Wallis tests. For continuous outcomes, linear regression was used but where model assumptions around residuals (normally distributed and homoscedastic) were not satisfied, quantile regression was used to model medians instead. For binary outcomes, logistic regression was used to model associations with EFS scores; with exact logistic regression used where the number of events was small (,10). The association between EFS score and time to discharge was modelled using Cox’s proportional hazards regression. Counts of events post-discharge were modelled using Poisson or, where there was evidence of overdispersion from a likelihood ratio test, negative binomial regression. Non-linearities were investigated through the addition of a quadratic term and use of a likelihood ratio test. Where the number of events (10 observations per predictor for linear and quantile regression, 10 cases with events and ten without the event per predictor for logistic regression, 10 events per predictor for Cox’s proportional hazard models, and 10 counts per predictor for Poisson or negative binomial regression) permitted, models were adjusted for all or of EuroSCORE II, age, sex, and type of surgery (CABG/valve/both) [11,12]. The effects of adding variables to predictive models (for example, adding the EFS score to a model already containing the walking score, and vice versa) were evaluated using likelihood ratio tests. Statistical analyses were performed using Stata 15.1 with twosided p,0.05 considered statistically significant.
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248
HLC3025_proof ■ 25 November 2019 ■ 3/8
3
Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate
249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313
Results A total of 96 patients were recruited into the study with a median (IQR) age of 74 (10.5) and comprising n=65 (68%) males (Table 1). All patients recruited met the inclusion criteria for the study. Overall, 46 (48%) patients underwent CABG, 25 (26%) valve surgery, and 25 (26%) both. Prior to
surgery, 64 (67%) were scored as not frail (EFS scores 0–5), 22 (23%) as vulnerable (EFS scores 6–7), and 10 (10%) as frail (EFS scores 8–17). The median (IQR) EFS score was 4 (4) overall, with a minimum of 0 and a maximum of 11 recorded, and medians (IQRs) of 3 (2), 6 (1), 8 (2) for the not frail, vulnerable, and frail groups respectively. The median (IQR) EuroSCORE II was 1.6 (1.3), 3.4 (4.0), and 2.7 (1.0) for the not
Q3
Table 1 Baseline characteristics. Edmonton Frail Scale category Not frail n=64
Vulnerable n=22
Frail n=10
Total n=96
P-value
65 (68)
0.226 0.123
Sex Male (%) Patient type
47 (73)
12 (55)
6 (60)
Elective (%)
36 (56)
8 (36)
3 (30)
47 (49)
Inpatient (%)
28 (44)
14 (64)
7 (70)
49 (51)
65-74 (%)
40 (63)
9 (41)
1 (10)
50 (52)
751 (%)
24 (38)
13 (59)
9 (90)
46 (48)
,25 (%) 25-29.9 (%)
12 (19) 32 (50)
2 (10) 10 (48)
2 (20) 4 (40)
16 (17) 46 (48)
30.01 (%)
20 (31)
9 (43)
4 (40)
33 (35)
Diabetes (%)
8 (13)
6 (27)
4 (40)
18 (19)
0.052*
Hypertension (%)
42 (66)
14 (64)
7 (70)
63 (66)
0.940
Any MI (%)
25 (39)
9 (41)
2 (20)
36 (38)
0.477
Endocarditis (%)
0 (0)
2 (9)
1 (10)
3 (3)
0.035*
Previous CVA/TIA/SEE (%)
5 (8)
5 (23)
2 (20)
12 (13)
0.109*
Heart Failure on admission (%) Atrial fibrillation (%)
5 (8) 6 (9)
4 (18) 4 (18)
2 (20) 4 (40)
11 (11) 14 (15)
0.224* 0.033*
Mild (%)
6 (9)
4 (18)
2 (20)
12 (13)
Moderate (%)
5 (8)
1 (5)
1 (10)
7 (7)
Severe (%)
2 (3)
0 (0.0)
0 (0.0)
2 (2)
CABG (%)
35 (55)
8 (36)
3 (30)
46 (48)
Valve surgery (%) CABG and Valve surgery (%)
16 (25) 13 (20)
5 (23) 9 (41)
4 (40) 3 (30)
25 (26) 25 (26)
,5s (%)
6 (9)
1 (5)
0 (0)
7 (7)
5s-6s (%)
41 (64)
7 (32)
0 (0)
48 (50)
.6s (%)
17 (27)
14 (64)
10 (100)
41 (43)
0.004
Age group
0.787*
BMI category
0.747*
Pulmonary hypertension
0.236*
Surgery type
,0.001*
5-metre gait speed test
median (IQR)
,0.001**
5.6 (1.0)
6.4 (1.3)
7.2 (1.1)
5.9 (1.5)
Ejection fraction median (IQR)
60.0 (12.5)
55.0 (10.0)
59.0 (14.0)
60.0 (11.5)
0.560**
CrCl (ml/min) median (IQR) Pre-op Hb (g/L) median (IQR)
69.0 (20.0) 137.0 (17.5)
55.0 (22.0) 129.0 (24.0)
59.5 (12.0) 113.5 (24.0)
66.0 (22.0) 133.0 (20.5)
,0.001** ,0.001** ,0.001**
EuroSCORE II median (IQR)
1.6 (1.3)
3.4 (4.0)
2.7 (1.0)
2.0 (2.0)
Pre-op length of stay median (IQR)
2.5 (9.0)
7.5 (14.0)
12.0 (17.0)
6.0 (12.0)
Edmonton Frail Scale score median
3 (2)
6 (1)
8 (2)
4 (4)
0.099** —
(IQR) P-values from Chi-squared tests aside from *Fisher’s exact test and **Kruskal2Wallis test. Abbreviations: BMI, body mass index; CABG, coronary artery bypass surgery; CrCl, creatinine clearance; CVA, cerbrovascular accident; Hb, haemoglobin; IQR, Q4
314 315 316 317 318 319 320 321 322
interquartile range; MI, myocardial infarction; Pre-op, preoperative; SE, systemic embolism; TIA, transient ischaemic attack.
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375
HLC3025_proof ■ 25 November 2019 ■ 4/8
4
376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440
S. Lal et al.
unadjusted and adjusted (for EuroSCORE II and surgery type) models (Table 4). In both the unadjusted and adjusted models, each one-unit increase in the EFS score was associated with a 17% reduction in the chance of discharge at a given point in time (unadjusted HR 0.83, 95% CI 0.77–0.91, p,0.001; adjusted for EuroSCORE II and procedure type HR 0.83, 95% CI 0.76–0.90, p,0.001). In other words, a patient moving from the median score for the not frail group (score of 3) to the median score for the vulnerable group (score of 6) would decrease the chance of discharge at any point in time by 42% in the unadjusted model and 43% in the adjusted model, and moving from the median score for the not frail group to the median score for the frail group (score of 8) would decrease this chance by 60% in both the unadjusted and adjusted models. The median lengths of stay reported above were 37% lower in the not frail group compared to the vulnerable group and 60% lower in the not frail group compared to the frail group. In the adjusted model, there was no evidence that EuroSCORE II was associated with discharge (p=0.376) and only a non-statistically significant tendency that surgery type was associated with discharge (Wald p=0.079). Adding age (likelihood ratio p=0.287) or sex (p=0.581) did not improve this adjusted model or meaningfully change the estimates (HR 0.83, 95% CI 0.76 to 0.91). As can be seen in the KaplanMeier plot in Figure 1, the unadjusted difference between categories of EFS scores is primarily between those not frail and those with any frailty, with little difference between those with scores in the vulnerable (range 6–7) and frail range (range 8–11). There was no evidence of associations in unadjusted models for EFS scores and each of: blood transfusion, new
frail, vulnerable, and frail groups respectively. Increasing proportions of patients with diabetes (13%, 27%, 40%), atrial fibrillation (9%, 18%, 40%), .6 seconds to complete fivemetre gait speed test (27%, 64%, 100%) were seen in the not frail, vulnerable and frail group respectively. Higher proportions of patients requiring inpatient surgery were also seen in the frail (70%) and vulnerable (64%) group when compared to the not frail (44%). The median (IQR) length of stay prior to surgical intervention was: not frail 2.5 (9) days, vulnerable 7.5 (14) days and frail 12 (17) days. The overall median length of hospital stay post cardiac surgery was 7 days (Table 2). Inpatient and elective surgeries were not statistically significantly different in terms of length of stay post cardiac surgery (results not shown, unadjusted p=0.546, adjusted for age, sex, EuroSCORE II, and procedure p=0.485). As shown in Table 2, there was no evidence of differences in terms of sex, inpatient versus elective, or age group for the procedures types. There was no evidence that length of stay varied between the three procedures (unadjusted Wald p=0.174, adjusted for age, sex, and EuroSCORE II Wald p=0.463). EuroSCORE II, however, differed between procedures (unadjusted Wald p,0.001), being greater in the combined procedure group compared to each of valve (p=0.004) or CABG (p,0.001) only. Results were similar after adjusting for age and sex (Wald p,0.001, both versus valve only p,0.001, and both versus CABG only p,0.001). Among patients grouped into not frail, vulnerable, and frail categories based on the EFS risk score, post-surgery outcomes are summarised in Table 3. The median lengths of hospital stay were 6 days, 9.5 days, and 15 days respectively. Survival analyses for post-surgery length of stay found statistically significant associations with EFS scores in
Table 2 Procedure type, patient demographic and length of hospital stay post cardiac surgery. Procedure Valve only n (%)
CABG only n (%)
Both n (%)
Total (n=96) n (%)
Sex Female
12 (48)
12 (26)
7 (28)
31 (32)
Male
13 (52)
34 (74)
18 (72)
65 (68)
Elective
15 (60)
17 (37)
15 (60)
47 (49)
Inpatient
10 (40)
29 (63)
10 (40)
49 (51)
Unadjusted p-value
Adjusted p-value
0.146
Patient type 0.078
Age group 65-74
10 (40)
29 (63)
11 (44)
50 (52)
751
15 (60)
17 (37)
14 (56)
46 (48)
Median (IQR)
Median (IQR)
Length of hospital stay (days) EuroSCORE II
Median (IQR)
0.115
Median (IQR)
6 (5)
6 (3)
8 (8)
7 (4)
1.9 (2.1)
1.6 (1.2)
3.4 (4.4)
2.0 (2.0)
0.174
0.463*
,0.001
,0.001†
P-values for sex, patient type, and age group are from Chi-squared tests. Results for length of stay from Cox’s proportional hazards regression and for EuroSCORE II from quantile regression modelling medians * Adjusted for age, sex, and EuroSCORE II
†
Adjusted for age and sex.
Abbreviations: CABG, coronary artery bypass surgery; IQR, interquartile range.
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505
HLC3025_proof ■ 25 November 2019 ■ 5/8
5
Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate
506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570
Table 3 Outcomes following cardiac surgery in patients categorised using Edmonton Frail Scale. Not frail (n=64) n (%)
Vulnerable (n=22) n (%)
Frail (n=10) n (%)
Total (n=96) n (%)
30-day mortality
0 (0)
0 (0)
1 (10)
1 (1)
Blood transfusion
9 (14)
6 (27)
2 (20)
17 (18)
New AF
23 (36)
8 (36)
4 (40)
35 (36)
Pneumonia
3 (5)
3 (14)
1 (10)
7 (7)
Delirium
3 (5)
3 (14)
1 (10)
7 (7)
AKI Resternotomy
4 (6) 3 (5)
5 (23) 1 (5)
4 (40) 2 (20)
13 (14) 6 (6)
Wound infection
1 (2)
1 (5)
4 (40)
6 (6)
CVA
5 (8)
5 (23)
1 (10)
11 (11)
Median (IQR)
Median (IQR)
Median (IQR)
Median (IQR)
6.0 (2)
9.5 (8)
15.0 (13)
7.0 (4)
Length of hospital stay (days)
Abbreviations: CVA, cerebrovascular accident; IQR, interquartile range; AKI, acute kidney injury; AF, atrial fibrillation.
atrial fibrillation, delirium, and cerebrovascular accident. Adjusting the new atrial fibrillation model for EuroSCORE II only did not change this result. Unadjusted models found evidence of increasing risks for each of pneumonia, acute kidney injury, resternotomy, and wound infection, with higher EFS scores (all p#0.046). Adding EFS scores to models already containing walk test scores was associated with improved prediction of length of stay (likelihood ratio p,0.001 for continuous and categorical walk scores in models also adjusting for age, sex, procedure
Table 4 Edmonton frailty score and association with outcomes Odds ratio (95% CI)
P-value
0.96 (0.78 – 1.19)
0.709
1.01 (0.85 – 1.19)
0.934
Adjusted
1.06 (0.89 – 1.27)
0.489
Pneumonia
1.37 (1.01 – 1.90)
0.046
Delirium
1.25 (0.92 – 1.71)
0.161
AKI Resternotomy
1.36 (1.11 – 1.66) 1.45 (1.04 – 2.09)
0.003 0.029
Wound infection
1.82 (1.25 – 2.91)
0.001
CVA
1.23 (0.96 – 1.58)
0.095
Blood transfusion New AF Unadjusted a
Hazard ratio (95% CI) Total length of hospital stay Unadjusted
0.83 (0.77 – 0.91)
,0.001
Adjusteda
0.83 (0.76 – 0.91)
,0.001
Abbreviations: AF, atrial fibrillation, AKI, acute kidney injury; CVA, cerebrovascular accident. a
Adjusted for EuroSCORE II, age, sex, type of surgery.
and EuroSCORE II). However, going in the opposite direction, adding walk test scores to models already containing EFS scores was not associated with improved prediction (likelihood ratio p0.493 for continuous and categorical walk scores in models also adjusting for age, sex, procedure and EuroSCORE II). In the 12-month post discharge, there were 19 patients with 33 hospital admissions related to major adverse cardiovascular or cerebrovascular events (MACCE), and 47 patients with 85 non-MACCE related admissions including 26 patients with 31 admissions for elective non-cardiac surgery/procedure. Post discharge follow-up analysis (Table 5) showed the EFS score was associated with the number of readmissions. With each point increase on the scale the adjusted incidence rate ratio was 1.24 (p,0.001) for readmissions.
Discussion Our study shows that frailty is an independent risk factor for length of hospital stay post cardiac surgery. The median (IQR) length of postoperative hospital stay in days was 6 (2), 9.5 (8), and 15 (13) in the not frail, vulnerable, and frail group respectively. For each point increase on EFS, there was a 17% lower chance of discharge on any particular day. Frailty was also positively associated with some adverse outcomes postsurgery: pneumonia, acute kidney injury, resternotomy, and wound infection. At 1-year follow-up, frailty was associated with a higher rate of readmission with an adjusted incidence rate ratio of 1.26 for each point increase in the EFS. The syndrome of frailty is often associated with ageing. In our cohort, whilst 75-year olds made up 38% of the not frail group, they made up 90% of the frail category. There exists a large knowledge gap in cardiovascular care of the elderly population, especially for those who have multiple
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635
HLC3025_proof ■ 25 November 2019 ■ 6/8
6
print & web 4C=FPO
636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700
S. Lal et al.
Figure 1 Time to discharge grouped by not frail (blue), vulnerable (red), and frail (green) patients.
comorbidities or those with complexity of care [13]. Two scoring systems in routine clinical practise used for assessing perioperative mortality in patients undergoing cardiac surgery are the EuroSCORE II and the STS score. Both these risk assessment models have been shown to have limitations [14,15]. An important limitation of both scoring systems is their inability to predict outcomes such as length of hospital stay, readmissions, or quality of life post procedure. There is significant variability in the prevalence of frailty depending on the criteria used for assessment (phenotype vs cumulative deficit indices). The median age in our cohort was 74 years with a 10% prevalence of frailty while 23% of the patients were in the vulnerable category. In a study of community-dwelling 75 year olds, the prevalence of frailty was 9.6% (95% CI 7.6–11.5) and pre-frailty 47% (95% CI 42.7–51.2) [16]. In a systematic review of adults 65 years of age, the overall weighted prevalence of frailty was 10.7% (95% CI 9.6–10.2) and 44% (44.2–44.7) for pre-frailty [8]. Investigators in this review, however, identified substantial variation in the reported frailty rates among various studies ranging from 4% to 59% based on the model used for
measuring it. Frailty appeared to be more prevalent in women than men (9.6% vs 5.2%). There was a trend of increasing frailty with age with a 4% prevalence in the 65–69year age group rising to 26% in the older than 85-year age group. Similarly, among elderly patients that proceed to cardiac surgery, the prevalence of frailty reported has been between 20% to 60% [17]. Frailty has been shown to be associated with quality of life, hospital admissions, institutionalisation, and mortality in the community dwelling elderly [18,19]. In the Canadian Study of Health and Aging (CSHA), 2,305 elderly patients 65 years were assessed with a seven-point CSHA Clinical Frailty Scale and followed for 5 years [20]. The investigators found that, with each incremental rise in category (very fit, well without active disease, well with treated comorbidity, vulnerable, mildly frail, moderately frail, severely frail), there was a 21% (95% CI 12.5–30.6) higher risk of death in the medium-term of about 70 months. Independent of age, increasing degree of frailty in geriatric medical and surgical patients has also been shown to be associated with protracted length of hospital stay, discharge to institutional care, major morbidity and mortality [21,22]. A systematic review encompassing 54,000 elderly people from various studies demonstrated the association between cardiovascular disease and frailty with an odds ratio between 2.7 and 4.1 [23]. Greater disease burden, comorbidities, and surgical urgency with higher morbidity and mortality have been documented in the elderly undergoing CABG or valve surgery [24,25]. Paradoxically the studies also reveal it is the elderly that stand to gain more with mortality and morbidity in the subset of elderly with fewer comorbidities approaching that of the younger population [24–26]. Therefore, selecting the elderly not based merely on their age or traditional “end-ofthe-bed” assessment to determine who will benefit the most with the least chance of a major adverse outcome is paramount. Once those at risk are identified, specific interventions can be tested to determine if post-surgical hospital stay can be modified in the vulnerable and frail groups. Frailty is increasingly recognised as an independent risk factor associated with poor outcomes in an elderly individual having cardiac surgery [27,28]. Various validated methods
Table 5 Associations between Edmonton frailty score and 12-month outcomes.
Q5
Unadjusted Incidence rate ratio (95% CI)
P-value
Adjusted Incidence rate ratio (95% CI)
P-value
Admissions due to MACCE
1.54 (1.29–1.84)
,0.001
—
—
Non-MACCE admissions Total admissions
1.16 (1.03–1.31) 1.26 (1.14–1.39)
0.012 ,0.001
1.16 (1.03–1.31)b 1.24 (1.13–1.37)b
0.016 ,0.001
Number of other elective surgery
1.04 (0.90–1.21)
0.561
1.04 (0.90–1.21)a
0.585
IRRs, 95% CIs, and p-values are from Poisson or (where there was evidence of overdispersion) negative binomial regression models. — Number of events too small for adjusted modelling (,20 non-zero counts). Abbreviations: MACCE, major adverse cardiovascular or cerebrovascular events; IRR, a
Adjusted for EuroSCORE II (at least 20 non-zero counts).
b
Adjusted for EuroSCORE II and surgery type (CABG/valve/both) (at least 40 non-zero counts).
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765
HLC3025_proof ■ 25 November 2019 ■ 7/8
Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate
766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830
for identifying frailty exist [29]. Models used in assessing frailty in older patients with cardiovascular disease undergoing surgical or transcatheter interventions have consistently shown frailty to be independently associated with predicting mortality and major morbidity [17,30,31]. The Frailty in Older Adults Undergoing Aortic Valve Replacement study looked at seven different frailty scales in predicting outcomes post aortic valve replacement (transcatheter aortic valve replacement [TAVR] or surgical aortic valve replacement) and found poor outcome at 1-year increased from 35% for the entire cohort to .50% in those who were frail [32]. The Comprehensive Assessment of Frailty (CAF) score was developed and applied preoperatively to 400 patients 74 years undergoing CABG, valve surgery or TAVR [33]. The investigators showed an association between high CAF score and 30-day mortality. However specific equipment was required and took time to conduct, leading to their acknowledgement that it may not be suitable for daily clinical practice. They developed a new easily applicable score which could be performed in a few minutes, and found an association between this and 1-year mortality [34]. Afilalo et al., in a large study of 15,171 patients undergoing CABG, valve surgery, or a combination, evaluated the prognostic value of gait speed by performing a five-metre gait speed test as a simple surrogate of frailty [6]. The impact of slow gait speed was independently associated with operative mortality (11% relative increase with each 0.1m/s decrease, p,0.01) with a weaker association between the composite of mortality or major morbidity. It was concluded that gait speed should be used in conjunction with other established frailty tests to discriminate frailty in the older population undergoing cardiac surgery better. From a practical point of view the criterion that is employed in daily practise should be easy to understand, not necessarily require a geriatrician to perform and not be time consuming. Preoperative frailty assessment in elderly patients undergoing cardiac surgery is an emerging paradigm. There is presently no general agreement as to which single frailty assessment tool to use in this group though the expert consensus in geriatric medicine is that elderly people should be screened for frailty especially if undergoing invasive procedures [1,35]. Our study demonstrates identifying frailty as a continuum with EFS in elderly patients undergoing cardiac surgery adding incremental information in addition to the EuroSCORE II. The EFS is simple to understand, practical to perform in patients awaiting cardiac surgery, time-efficient, and easy to administer at bedside. Cardiac surgery is associated with substantial stressors with potential of adverse outcomes particularly in vulnerable frail elderly individuals. Frailty assessment using EFS to screen and identify such individuals preoperatively and quantify frailty on the continuous gradation scale is likely to further enhance the decisionmaking process between clinicians and older adults considered for cardiac surgery. Employing EFS as a frailty assessment tool has the potential to impact on planning, implementation, delivery and measurement of outcomes of
7
health care in the cardio-surgical elderly population. A comprehensive systematic literature review of 24 populationbased studies estimated that 3–5% of deaths among older adults could be delayed if frailty was prevented [7]. This is an initial observational study which was not designed to detect a mortality difference by frailty (due to the low expected number of events within a limited follow-up period). We have focussed on surrogate endpoints such as length of stay, adverse events post-surgery, and readmissions within 12 months. As an observational study, it is possible that our findings of frailty being associated with poorer outcomes were confounded by unknown variables despite adjusting for known influences when possible. Larger studies would be needed to consider potential confounding more carefully. All invited subjects consented to the study so results may be generalised to the wider population of patients undertaking this procedure without concerns about participation biases. We had complete 12-month follow-up data so missing data mechanisms did not affect our results.
Conclusions These results support incorporating routine preoperative frailty assessment alongside current risk scores in elderly patients considered for cardiac surgery to improve decisionmaking. Such assessments could be useful in characterising those who will benefit, those who will have minimal gain, and those who may actually be harmed in this growing group of patients. The EFS score predicts length of hospital stay post cardiac surgery in patients older than 65 years of age. It also assists in predicting those at higher risk of complications post-surgery and readmissions post discharge. The EFS is a quantifiable frailty assessment tool and when used in screening of elderly cardiac surgical adults it provides gradation of frailty potentially facilitating better identification of those who may benefit most. Larger studies are needed to further explore an indication for integration of this simple to perform scale as a risk stratification measure to complement the pre-existing surgical scoring tools.
Conflict of Interest There is no conflict of interest for all authors
IRB Approval University of Otago Human Ethics Committee (Health), 12 February 2014, H14/013
Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j. hlc.2019.10.007.
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 Q6881 882 883 884 885 886 887 888 889 890 891 892 893 894 895
HLC3025_proof ■ 25 November 2019 ■ 8/8
8
896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952
References [1] Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet 2013;381:752–62. [2] Alexander KP, Newby LK, Cannon CP, Armstrong PW, Gibler WB, Rich MW, et al. Acute coronary care in the elderly, part I: Non–STsegment–elevation acute coronary syndromes: a scientific statement for healthcare professionals from the American Heart Association Council on Clinical Cardiology: in collaboration with the Society of Geriatric Cardiology. Circulation 2007;115:2549–69. [3] Alexander KP, Newby LK, Armstrong PW, Cannon CP, Gibler WB, Rich MW, et al. Acute coronary care in the elderly, part II: ST-segment– elevation myocardial infarction: a scientific statement for healthcare professionals from the American Heart Association Council on Clinical Cardiology: in collaboration with the Society of Geriatric Cardiology. Circulation 2007;115:2570–89. [4] Neupane I, Arora RC, Rudolph JL. Cardiac surgery as a stressor and the response of the vulnerable older adult. Exp Gerontol 2017;87:168–74. [5] Rolfson DB, Majumdar SR, Tsuyuki RT, Tahir A, Rockwood K. Validity and reliability of the Edmonton Frail Scale. Age Ageing 2006;35:526–9. [6] Afilalo J, Kim S, O’Brien S, Brennan JM, Edwards FH, Mack MJ, et al. Gait speed and operative mortality in older adults following cardiac surgery. JAMA Cardiol 2016;1:314–21. [7] Shamliyan T, Talley KM, Ramakrishnan R, Kane RL. Association of frailty with survival: a systematic literature review. Ageing Res Rev 2013;12:719–36. [8] Collard RM, Boter H, Schoevers RA, Oude Voshaar RC. Prevalence of frailty in community-dwelling older persons: a systematic review. J Am Geriatr Soc 2012;60:1487–92. [9] Afilalo J, Eisenberg MJ, Morin J-F, Bergman H, Monette J, Noiseux N, et al. Gait speed as an incremental predictor of mortality and major morbidity in elderly patients undergoing cardiac surgery. J Am Coll Cardiol 2010;56:1668–76. [10] Nashef SA, Roques F, Sharples LD, Nilsson J, Smith C, Goldstone AR, et al. EuroSCORE II. Eur J Cardiothorac Surg 2012;41:734–45. [11] Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol 1996;49:1373–9. [12] Peduzzi P, Concato J, Feinstein AR, Holford TR. Importance of events per independent variable in proportional hazards regression analysis II. Accuracy and precision of regression estimates. J Clin Epidemiol 1995;48:1503–10. [13] Rich MW, Chyun DA, Skolnick AH, Alexander KP, Forman DE, Kitzman DW, et al. Knowledge gaps in cardiovascular care of the older adult population: a scientific statement from the American Heart Association, American College of Cardiology, and American Geriatrics Society. J Am Coll Cardiol 2016;67:2419–40. [14] Barili F, Pacini D, Capo A, Rasovic O, Grossi C, Alamanni F, et al. Does EuroSCORE II perform better than its original versions? A multicentre validation study. Eur Heart J 2013;34:22–9. [15] Wendt D, Osswald BR, Kayser K, Thielmann M, Tossios P, Massoudy P, et al. Society of Thoracic Surgeons score is superior to the EuroSCORE determining mortality in high risk patients undergoing isolated aortic valve replacement. Ann Thorac Surg 2009;88:468–75. [16] Jürschik P, Nunin C, Botigué T, Escobar MA, Lavedán A, Viladrosa M. Prevalence of frailty and factors associated with frailty in the elderly population of Lleida, Spain: the FRALLE survey. Arch Gerontol Geriatr 2012;55:625–31.
S. Lal et al.
[17] Afilalo J, Alexander KP, Mack MJ, Maurer MS, Green P, Allen LA, et al. Frailty assessment in the cardiovascular care of older adults. J Am Coll Cardiol 2014;63:747–62. [18] Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146–57. [19] Song X, Mitnitski A, Rockwood K. Prevalence and 10-year outcomes of frailty in older adults in relation to deficit accumulation. J Am Geriatr Soc 2010;58:681–7. [20] Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ 2005;173:489–95. [21] Partridge JS, Harari D, Dhesi JK. Frailty in the older surgical patient: a review. Age Ageing 2012;41:142–7. [22] Robinson TN, Wallace JI, Wu DS, Wiktor A, Pointer LF, Pfister SM, et al. Accumulated frailty characteristics predict postoperative discharge institutionalization in the geriatric patient. J Am Coll Surg 2011;213:37–42. [23] Afilalo J, Karunananthan S, Eisenberg MJ, Alexander KP, Bergman H. Role of frailty in patients with cardiovascular disease. Am J Cardiol 2009;103:1616–21. [24] Filsoufi F, Rahmanian PB, Castillo JG, Chikwe J, Silvay G, Adams DH. Results and predictors of early and late outcomes of coronary artery bypass graft surgery in octogenarians. J Cardiothorac Vasc Anesth 2007;21:784–92. [25] Graham MM, Ghali WA, Faris PD, Galbraith PD, Norris CM, Knudtson ML. Survival after coronary revascularization in the elderly. Circulation 2002;105:2378–84. [26] Alexander KP, Anstrom KJ, Muhlbaier LH, Grosswald RD, Smith PK, Jones RH, et al. Outcomes of cardiac surgery in patients age 80 years: results from the National Cardiovascular Network. J Am Coll Cardiol 2000;35:731–8. [27] Graham A, Brown CH. Frailty, aging, and cardiovascular surgery. Anesth Analg 2017;124:1053–60. [28] 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 2014;148:3110–7. [29] de Vries NM, Staal JB, van Ravensberg CD, Hobbelen JS, Olde Rikkert MG, Nijhuis-van der Sanden MW. Outcome instruments to measure frailty: a systematic review. Ageing Res Rev 2011;10:104–14. [30] Afilalo J, Mottillo S, Eisenberg MJ, Alexander KP, Noiseux N, Perrault LP, et al. Addition of frailty and disability to cardiac surgery risk scores identifies elderly patients at high risk of mortality or major morbidity. Circ Cardiovasc Qual Outcomes 2012;5:222–8. [31] Esses G, Andreopoulos E, Lin HM, Arya S, Deiner S. A Comparison of three frailty indices in predicting morbidity and mortality after on-pump aortic valve replacement. Anesth Analg 2018;126:39–45. [32] Afilalo J, Lauck S, Kim DH, Lefevre T, Piazza N, Lachapelle K, et al. Frailty in older adults undergoing aortic valve replacement: the FRAILTY-AVR study. J Am Coll Cardiol 2017;70:689–700. [33] Sundermann S, Dademasch A, Praetorius J, Kempfert J, Dewey T, Falk V, et al. Comprehensive assessment of frailty for elderly high-risk patients undergoing cardiac surgery. Eur J Cardiothorac Surg 2011;39:33–7. [34] Sundermann S, Dademasch A, Rastan A, Praetorius J, Rodriguez H, Walther T, et al. One-year follow-up of patients undergoing elective cardiac surgery assessed with the Comprehensive Assessment of Frailty test and its simplified form. Interact Cardiovasc Thorac Surg 2011;13:119–23. [35] Morley JE, Vellas B, Abellan van Kan G, Anker SD, Bauer JM, Bernabei R, et al. Frailty consensus: a call to action. J Am Med Dir Assoc 2013;14:392–7.
Please cite this article in press as: Lal S, et al. Frailty in Elderly Patients Undergoing Cardiac Surgery Increases Hospital Stay and 12-Month Readmission Rate. Heart, Lung and Circulation (2019), https://doi.org/10.1016/j.hlc.2019.10.007
953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009