Abstract
Background
An increasing number of older adults have been hospitalized in cardiac intensive care units. Their more complex medical profiles and frailty dictate treatment decisions and affect outcomes. There is no universally agreed‐upon age definition for an older adult, with common thresholds being 65 or 75 years. Our objective was to evaluate the predictive value of various age groups while accounting for frailty.
Methods
In this observational cohort study, we analyzed data from a prospective registry of consecutive patients admitted to the cardiac intensive care unit at a tertiary hospital between January 2014 and March 2022 with a diagnosis of acute coronary syndrome. The primary outcome was the composite of 90‐day all‐cause death, shock, acute heart failure, acute kidney injury, stroke, mechanical ventilation, and ventricular arrhythmias. Frailty was dichotomized using the routinely measured Norton score for all inpatients; a ≤17 score was defined as frail.
Results
The study included 4790 patients with acute coronary syndrome, divided into age groups: 2249 aged <65 years, 1294 aged 65 to 74 years, and 1247 aged ≥75 years, with a higher proportion of women in the older age groups. Due to the interaction between age and frailty, the cohort was divided and analyzed separately on the basis of frailty status. Among the nonfrail group (3915 [81.7%]), 16% reached the outcome. Adjusted odds ratios for the primary outcome in patients aged ≥75 years were 2.18 (95% CI, 1.69–2.81) and 1.46 (95% CI, 1.15–1.85) compared with those aged <65 years and 65 to 74 years, respectively. For patients aged 65 to 74 years compared with those <65 years, the odds ratio was 1.49 (95% CI, 1.16–1.91). In the frail group, where 60% reached the outcome, no significant association was found between age groups and outcomes.
Conclusions
Our results suggest that frailty may be a surrogate for aging and is a stronger predictor than chronological age for adverse outcomes among patients with acute coronary syndrome in the cardiac intensive care unit.
Keywords: acute coronary syndrome, aging, intensive care unit, frailty, older adults
Subject Categories: Myocardial Infarction
Clinical Perspective.
What Is New?
In this study, frailty modifies the association between age group and adverse cardiovascular outcomes among patients with acute coronary syndrome hospitalized in the cardiac intensive care unit.
What Are the Clinical Implications?
Frailty should be routinely measured for patients of all age groups who are admitted with acute coronary syndrome in the cardiac intensive care units for prognostication and decision‐making purposes.
Chronological age is not a good surrogate of biological age in patients with frailty.
Age is considered the single most important risk factor for acute coronary syndrome (ACS), 1 and an important prognostic factor among patients hospitalized due to ACS. 2 Older patients tend to have more frequently nontypical clinical presentations and more complex clinical courses during hospitalization and after discharge. 3 However, there is a paucity of data on the clinical course of older adults of different age groups hospitalized with ACS 4 and specifically the association between age groups and adverse outcomes among these patients. This gap of evidence resulted in different age cutoffs used for defining older adults in research, with the most commonly used in cardiovascular studies being ages 65 and 75 years. 5
Frailty is a common geriatric syndrome among inpatients with ACS in the cardiac intensive care unit (CICU). 6 , 7 While there are many challenges in frailty assessment in patients hospitalized in the intensive care unit, it was recognized as a valuable tool for evaluating aging beyond chronological age, 8 promoting its implementation as part of the baseline evaluation of patients. 9
In this study, we aim to evaluate the prognostic value of different age groups for adverse outcomes among patients hospitalized in the CICU while also considering frailty status.
Methods
Study Population and Variables
In this prospective cohort study, the database was based on the Sheba Medical Center CICU registry. The registry was prospectively created and included all consecutive adult (aged ≥18 years) patients admitted to the CICU between January 2014 and March 2022. Patients’ charts were filled in for each patient by the attending physician in the CICU service and were updated daily throughout the CICU stay. The registry includes demographic data, medical history, medical procedures that the patient had undergone during the index hospitalization, and adverse outcomes. For data set creation, the CICU registry was linked with the computerized records of each patient using the national identification number. This study included patients whose primary diagnosis was any of the ACS‐related diagnoses (based on the International Classification of Diseases, Ninth Revision [ICD‐9]). Individuals were included more than once if they had multiple hospitalizations with ACS as their primary diagnosis during the study period.
The data set used for the statistical analysis was encrypted and was anonymous to the authors who analyzed it. The Institutional Review Board of the Sheba Medical Center approved this study on the basis of strict maintenance of participants’ anonymity during database analyses. The Institutional Review Board prohibited any data sharing concerning this study. No individual consent was obtained.
The age variable was divided into 3 groups: <65, 65 to 74, and ≥75 years old. Frailty status was based on the Norton score, which is a mandatory field for all admissions to the CICU at Sheba Medical Center. It is manually filled by the treating nurse upon admission to the CICU and is available for 99% of our study population (61 patients had missing frailty data and were excluded from analysis). It was originally developed to evaluate the risk for pressure ulcers during hospitalization and includes 5 components with a score of 1 (lowest function) to 4 (highest function) for each of the following components: physical condition, mental condition, mobility (the patient’s ability to change position independently), activity (the patient’s ability to move and be active), and bladder and bowel incontinence. Since it evaluates physical function and additional functional domains, it was shown to serve as a frailty index in the older adult population, particularly in those with cardiovascular conditions, 10 , 11 where a score of ≤17 was considered as frail (this is also the cutoff to define a patient as vulnerable for pressure ulcers).
Study Outcome
The primary outcome of this study was a composite outcome of 90 days’ all‐cause death and hospitalization complications. Mortality data were retrieved from the Israeli Ministry of Interior and were available for all patients in this study. Complications during hospitalization that comprised the primary outcome were those that were documented by the treating physician in the CICU as part of the prospective registry during hospitalization and included ventricular arrhythmia, defined as any of the following: sustained ventricular tachycardia or ventricular fibrillation on the 3‐lead monitor or 12‐lead ECG; acute heart failure, as designated by the treating physician on the basis of the physical examination findings and imaging as needed; acute kidney injury, defined by an increase in creatine on >50% or >0.5 mg/dL from baseline; stroke, as diagnosed by a neurologist on the basis of clinical findings and imaging; invasive mechanical ventilation with intubation; and shock of any cause that necessitated vasopressors (norepinephrine or vasopressin) or inotropes (such as dobutamine or milrinone). The secondary outcome included 90‐day all‐cause death.
Statistical Analysis
Categorical variables were compared with χ2 or Fisher’s exact test. T test and 1‐way ANOVA were used to compare continuous normally distributed variables, while Mann–Whitney was used as a nonparametric test. The tests were 2‐tailed, with P<0.05 as the significance cutoff. Odds ratio (OR) and 95% CI for the outcome were calculated using logistic regression models. Multicollinearity between variables in the multivariable models was excluded after calculating the variance inflation factor, which was <2 for all. Prespecified interaction analysis was conducted between age groups, frailty, and the outcome. Multivariable models were adjusted for sex, admission year, baseline comorbidities (ischemic heart disease, heart failure, hypertension, chronic kidney disease, atrial fibrillation or flutter, stroke, diabetes, chronic obstructive pulmonary disease, dyslipidemia, and cancer), ACS categorization (ST‐segment–elevation ACS versus non–ST‐segment–elevation ACS), and maximal troponin level during hospitalization. The E value was calculated to address potential residual confounding. 12
Statistical analysis was performed using R software version 4.0.4 (R Core Team, Vienna, Austria) and SPSS software version 23 (IBM, Armonk, NY).
Results
The final cohort included 4790 patient hospitalizations, with a median age of 65 (interquartile range, 56–75) years, of whom 2249, 1294 and 1247 were in the age groups of <65, 65 to 74, and ≥75 years, respectively; 251 (5.2%) of the hospitalizations were readmissions during the study period. A higher proportion of women was evident in the increasing age groups, with only 329 (14.6%) in the age group of <65 years, 301 (23.3%) in the age group of 65 to 74 years, and 455 (36.5%) in the age group of ≥75 years. As expected, the older age group had a higher proportion of baseline comorbidities (Table). However, individuals in the older age group were less likely to undergo percutaneous coronary intervention during their hospitalization (P<0.01).
Table.
Baseline Cohort Characteristics by Age Group
| <65 y (N=2249) | 65–74 y (N=1294) | ≥75 y (N=1247) | Overall (N=4790) | |
|---|---|---|---|---|
| Female sex, n (%) | 329 (14.6) | 301 (23.3) | 455 (36.5) | 1085 (22.7) |
| Ischemic heart disease, n (%) | 621 (27.6) | 565 (43.7) | 653 (52.4) | 1839 (38.4) |
| Hypertension, n (%) | 1013 (45.1) | 879 (67.9) | 979 (78.5) | 2871 (60.0) |
| Heart failure, n (%) | 148 (6.6) | 212 (16.4) | 350 (28.1) | 710 (14.8) |
| Diabetes, n (%) | 686 (30.5) | 638 (49.3) | 591 (47.4) | 1915 (40.0) |
| Dyslipidemia, n (%) | 1060 (47.2) | 846 (65.4) | 883 (70.8) | 2789 (58.2) |
| Chronic kidney disease, n (%) | 123 (5.5) | 189 (14.6) | 347 (27.8) | 659 (13.8) |
| Prior stroke, n (%) | 159 (7.1) | 196 (15.1) | 258 (20.7) | 613 (12.8) |
| Atrial fibrillation/flutter, n (%) | 41 (1.8) | 104 (8.0) | 185 (14.8) | 330 (6.9) |
| Chronic obstructive pulmonary disease, n (%) | 141 (6.3) | 160 (12.4) | 173 (13.9) | 474 (9.9) |
| Prior cancer diagnosis, n (%) | 135 (6.0) | 185 (14.3) | 272 (21.8) | 592 (12.4) |
| Anemia, n (%) | 112 (5.0) | 166 (12.8) | 275 (22.1) | 553 (11.5) |
| STEMI as ACS, n (%) | 1194 (53.1) | 614 (47.4) | 503 (40.3) | 2311 (48.3) |
| Maximal troponin, mean±SD | 15.5±33.4 | 14.1±36.2 | 16.0±38.9 | 15.3±35.6 |
| Maximal high‐sensitivity troponin, mean±SD | 4020±7890 | 4900±8670 | 4360±8430 | 4360±8270 |
| Treated with PCI during the hospitalization, n (%) | 1721 (76.6) | 933 (72.1) | 787 (63.1) | 3441 (71.9) |
| Frailty, n (%) | 183 (8.1) | 191 (14.7) | 501 (40.1) | 875 (18.2) |
Until January 2020, troponin I was used in clinical practice, and starting from February 2020, all patients were tested only with high‐sensitivity troponin I. ACS indicates acute coronary syndrome; PCI, percutaneous coronary intervention; and STEMI, ST‐segment–elevation myocardial infarction.
Frailty
The frail group comprised 875 (18.3%) patients; 183 patients (8.1% of age group) of age <65 years had frailty, 191 (14.8%) in the age group of 65 to 74 years, and 501 (40.1%) patients were aged ≥75 years (Figure 1). Overall, patients with frailty were older compared with the rest of the cohort, with a median age of 77 (interquartile range, 66–84) versus 63 (interquartile range, 55–71) years and had a higher proportion of women, 39% versus 19%, respectively (P<0.01 for both). The frail group had a higher rate of comorbidities compared with those without frailty in total and in every age group separately, and they were less likely to be treated with percutaneous coronary intervention (P=0.017; Table S1). In the multivariable logistic regression model, frailty was associated with the composite outcome with an adjusted OR of 5.16 (95% CI, 4.28–6.24).
Figure 1. Cohort buildup.
ACS indicates acute coronary syndrome; and CICU; cardiac intensive care unit.
Outcomes
Overall, there were 1137 (24%) primary outcome events, with 414 (14.9%) events among patients in the younger group, 309 (24.1%) among the age group 65 to 74 years, and 505 (41.0%) among age group ≥75 years. The probability of the event was much higher for any age group among the frail (with an overall 60%) compared with the respective age group among the nonfrail, whose overall incidence rate of the outcome was 16% (Figure 2). Due to an interaction (P<0.001) between age groups and frailty status with outcomes, all analyses were conducted separately for those with and without frailty. The results of the unadjusted models in the frail and the nonfrail group stratum are presented in Table S2. Figure 3 presents the event risk by age group in the frail and nonfrail groups separately, as well as the results of the multivariable models. In the nonfrail group, the crude ORs for the primary outcome among those aged ≥75 years were 3.73 (95% CI, 3.01–4.63) and 2.0 (95% CI, 1.62–2.48) compared with the age groups of <65 and 65 to 74 years, respectively, and 1.86 (95% CI, 1.49–2.32) for the age group of 65 to 74 years compared with <65 years. The adjusted ORs for the primary outcome among those aged ≥75 years were 2.18 (95% CI, 1.69–2.81) and 1.46 (95% CI, 1.15–1.85) compared with the age groups of <65 and 65 to 74 years, respectively. In a comparison of individuals aged 65 to 74 years with those of <65 years, the adjusted OR was 1.49 (95% CI, 1.16–1.91). In the frail group, crude ORs for the comparisons between the age groups are presented in Table S2. In the adjusted models, there was no association between the age group and the outcome in any of the comparisons (Figure 3), with an adjusted OR of 0.76 (95% CI, 0.48–1.19) for the comparison between the age group of 65 to 74 years and the age group of ≥75 years.
Figure 2. Proportion of primary outcome events by frailty status and age group.
Among the nonfrail patients, P<0.01 for all age comparisons (3 comparisons between the following age groups: <65 vs 65 to 74 years, <65 vs ≥75 years, 65 to 74 vs ≥75 years. Among the frail patients, statistically not significant for all 3 comparisons. The primary outcome was the composite of 90‐day all‐cause death, shock, acute heart failure, acute kidney injury, stroke, mechanical ventilation, and ventricular arrhythmias.
Figure 3. Rates of the primary outcome by frailty status and age groups and the results of the logistic regression multivariable‐adjusted models.
Group 1 and group 2 correspond to the first and second age groups, respectively, presented in each age comparison for every line in the forest plot. Primary outcome was the composite of 90‐day all‐cause death, shock, acute heart failure, acute kidney injury, stroke, mechanical ventilation, and ventricular arrhythmias. Multivariable models were adjusted to sex, year of admission, acute coronary syndrome categorization (ST‐segment–elevation vs non–ST‐segment–elevation(, maximal troponin level during hospitalization and the following comorbidities: ischemic heart disease, heart failure, hypertension, chronic kidney disease, atrial fibrillation or flutter, stroke, diabetes, chronic obstructive pulmonary disease, dyslipidemia, and cancer.
E values for the comparison in the nonfrail group were between 2.17 and 3.38 (see Table S3 for each comparison).
For the secondary outcome of 90 days of all‐cause death, there were overall 40 cases in the age group of <65 years, 73 cases in the age group of 65 to 74 years, and 182 cases in the age group of ≥75 years. Figure 4 presents the event risk by age group in the nonfrail and frail groups separately and the results of the multivariable models. In the nonfrail group, the adjusted ORs for the primary outcome among patients in the age group of ≥75 years were 5.23 (95% CI, 2.91–9.79) and 2.51 (95% CI, 1.36–4.77) compared with the age groups of <65 and 65 to 74 years, respectively. In a comparison of individuals aged 65to 74 years with those aged <65 years, the OR was 2.08 (95% CI, 1.31–3.35). In the frail group, there was an association between the age group and the outcome, only with a comparison of those aged ≥75 years with patients aged <65 years, with an OR of 2.18 (95% CI, 1.29–3.82); the comparisons of other age groups were nonsignificant (Figure 4).
Figure 4. Rates of 90‐day all‐cause death by frailty status and age groups and the results of the logistic regression multivariable‐adjusted models.
Group 1 and group 2 correspond to the first and second age groups, respectively, presented in each age comparison for every line in the forest plot. Multivariable models were adjusted to sex, year of admission, acute coronary syndrome categorization (ST‐segment–elevation vs non–ST‐segment elevation(, maximal troponin level during hospitalization and the following comorbidities: ischemic heart disease, heart failure, hypertension, chronic kidney disease, atrial fibrillation or flutter, stroke, diabetes, chronic obstructive pulmonary disease, dyslipidemia, and cancer.
Discussion
In this prospective cohort of patients admitted with a primary diagnosis of ACS to the CICU, we found that frailty was a crucial determinant in patients’ prognosis, even more than age. Patients with frailty had a high risk of adverse outcomes irrespective of their age group. On the contrary, among patients without frailty, there was an increasing risk for adverse outcomes as patients age, and yet, younger patients with frailty had significantly worse prognoses than older patients without frailty.
Age is a strong predictor and is universally considered a risk factor in all studies of populations with cardiovascular morbidities. 13 , 14 However, age is not synonymous with aging, and there is high interindividual variability in the functional deterioration of people of the same chronological age. 15 This has motivated the conceptualization of frailty, which may serve as a better surrogate for the impact of aging on health in terms of functional deterioration. 16 The lack of agreement on the optimal tool for frailty measurement reflects, in part, the different phenotypes of frailty. 7
Frailty was reported to involve up to 60% of older patients who were hospitalized with ACS, and it was established as one of the most important prognostic factors in these patients. 17 , 18 It was also the strongest predictive factor in our cohort. Frailty was shown to drive treatment decision making in the CICU setting. Being frail often precludes older patients with ACS from some of the recommended treatments, such as revascularization, as also suggested in our study, and potent antiplatelet agents. 19 , 20 , 21 This, in turn, has an additional adverse impact on the prognosis of these patients’ outcomes, especially in light of evidence supporting an invasive approach regardless of frailty status. 21 , 22 In our study, frailty was evaluated using the Norton score, which was shown to be strongly correlated with adverse outcomes among inpatients with non–ST‐segment–elevation myocardial infarction 23 and among elective patients admitted for transcatheter aortic valve replacement. 11 The Norton score is commonly used as part of the routine nursing assessment for newly admitted patients, making it an available measure of frailty without the need for additional time and resources by the care team. Notably, this score is subject to between‐person variation among different nursing staff members who evaluate patients as part of their daily work. In contrast with many commonly used frailty scores, which were developed on the basis of the Rockwood deficit accumulation theory, the Norton score is a real‐time prospective evaluation of the patient by medical staff rather than relying on medical records. Furthermore, this minimizes the possibility of overadjustment for baseline comorbidities that may occur when frailty is incorporated into statistical multivariable models, which include the same specific comorbidities used for frailty scoring. 24
A recent article by Gordon et al demonstrated that frailty is also common (27%) in hospitalized young adult patients (aged ≤49 years) and up to 40% of hospitalized middle‐aged (aged 50–69 years) patients. 25 This is in concordance with our results, which demonstrate that frailty was evident in up to 8% of middle‐aged patients. These results support the paradigm 26 that frailty is not only a geriatric syndrome but rather an essential parameter in younger patients’ evaluation as well, including in those hospitalized with ACS. 27
No previous studies have addressed the interplay between the different age groups and frailty among patients with ACS. Our results demonstrate that chronological age is not a significant prognostic factor among frail adults with ACS, suggesting that age poorly correlates with biological aging in these patients. On the contrary, in patients without frailty, there is an association between age and adverse prognosis. The analysis of 90‐day death, which is a common hard clinical end point in studies of patients hospitalized in the intensive care unit, shows an overall similar trend to the primary outcome analysis, with higher point estimates in the nonfrail group, highlighting the role of frailty. Therefore, frailty should be measured routinely among inpatients as well as among outpatients to mitigate and control potentially reversible factors causing frailty, such as ischemic heart disease, atrial fibrillation, and heart failure. 28 Chronological age in patients without frailty is indeed a very strong predictor for adverse outcomes; however, in patients with frailty, it played a lesser prognostic role. In the latter group, frailty rather than chronological age can serve as a valuable tool for reflecting a patient’s biological age, aiding in prognosis assessment and guiding future treatment decisions. Additionally, it may help the medical team reflect the patient’s overall health status to the patients and their families, facilitating informed discussions on treatment options and code status. One of the caveats of frailty evaluation in most studies, including the Norton score in this study, is that it is evaluated during acute illness rather than in a chronic state. It is important to consider that there is a bidirectional association between frailty and acute illness, 29 particularly concerning ACS. 28 , 30 In some cases, measured frailty may be, in fact, a consequence of the acute illness itself and may be expressing the acute rather than patients’ chronic state. 31 This potential reversibility of frailty due to acute illness, may explain evidence from real‐life data demonstrating the benefit of coronary angiography and other advanced therapies among highly frail patients with ACS. 22 , 23 Due to the lower rate of comorbidities and precipitating factors for ACS, 32 frailty is expected to be reversible to a greater extent among younger patients. However, the frailty of these younger patients probably does represent their increased vulnerability to stressors compared with their age‐matched counterparts.
Another limitation of our study is potential unmeasured confounding such as socioeconomic factors, baseline cognitive and functional status and medical compliance. Other potential unmeasured factors include undocumented comorbidities and the level of their control. Using the E‐value calculation, we showed that the observed adjusted hazard ratio in every age subgroup among the nonfrail groups would have to be confounded by an unmeasured factor that was associated with death by a hazard ratio of at least 2.17 controlled for other measured cofactors to change the main analysis’s results, but weaker confounding could not do so. An additional limitation is that this was a single‐center study. Therefore, our study might poorly represent some ethnicities, such as East Asians. However, the population in this study is considered to have a heterogeneous genetic ancestry. 33 , 34
In conclusion, we demonstrated that among patients with ACS, the association between different age groups and adverse outcome is modified by frailty. Frailty might serve as a better surrogate for aging among patients at the CICU and needs to be addressed for therapeutic and prognostic implications.
Sources of Funding
None.
Disclosures
None.
Supporting information
Table S1
Table S2
Table S3
This manuscript was sent to Manju Jayanna, MD, MS, Assistant Editor, for review by expert referees, editorial decision, and final disposition.
Supplemental Material is available at https://www.ahajournals.org/doi/suppl/10.1161/JAHA.124.040688
For Sources of Funding and Disclosures, see page 7.
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Supplementary Materials
Table S1
Table S2
Table S3