The aim of this study was to evaluate the predictive ability of frailty for bleeding after percutaneous coronary intervention (PCI). In 2439 patients who underwent their PCI, frailty was prospectively assessed according to the Canadian Study of Health and Aging clinical frailty scale (CFS). Patients were divided into three groups according to the CFS: low (CFS levels 1 to 3; 1748 patients, 71.7%), intermediate (CFS levels 4 to 6; 519 patients, 21.3%), and high CFS groups (CFS levels 7 to 9; 172 patients, 7.1%). Academic Research Consortium High Bleeding Risk (ARC-HBR) was present in 47.3% in the low CFS group, in 83.2% in the intermediate CFS group and in 89.0% in the high CFS group (p <0.001). Patients in the intermediate and high CFS groups were associated with higher 1-year major bleeding risk after PCI in the overall cohort (HR 3.82, 95% CI 2.65 to 5.51, p <0.001, and HR 7.81, 95% CI 5.07 to 12.0, p <0.001, respectively). Patients in the high CFS group were also associated with higher 1-year major bleeding risk regardless of having the high bleeding risk (HBR) according to ARC-HBR. In conclusion, the association of frailty with 1-year major bleeding was consistently observed in patients with and without HBR, indicating that frailty per se might be a predictor for major bleeding after PCI on top of HBR criteria.
Frailty is a geriatric syndrome that is defined as a state of reduced physiological reserve against pathological or iatrogenic stressors due to age-related impairments. Since frail patients are likely to be excluded from clinical studies due to those factors including an unwillingness of the patients to participate, the physician’s decisions, and/or perceptions for poor prognosis, the causative role of frailty for the long-term bleeding risk after percutaneous coronary intervention (PCI) remains unclear. – Moreover, none of the currently available bleeding risk scores included frailty as a potential predictor for bleeding events; in the consensus from the Academic Research Consortium for HBR (ARC-HBR) criteria, frailty per se was not included as a criterion, although advanced age and coexisting ARC-HBR criteria may account for frailty at least to some degree. To address these issues, we sought to evaluate the impact of frailty on 1-year bleeding events in patients who underwent PCI in an all-comer registry from a single-center.
Methods
From February 24, 2016, to December 4, 2017, a total of consecutive 2439 patients underwent their PCI in Kokura Memorial Hospital, Kitakyushu, Japan. Written informed consents from the patients were waived, because we retrospectively enrolled the patients. No patients refused to participate in the study when contacted for follow-up. This opt-out consent strategy is concordant with the guidelines of the Japanese Ministry of Health, Labor and Welfare. The institutional review board of Kokura Memorial Hospital approved the protocol of this observational study. Moreover, the study was conducted following the Declaration of Helsinki. The objectives and detailed design are provided on the University Hospital Medical Information Network (UMIN000042266).
Frailty was routinely assessed for all patients by healthcare professionals in the cardiovascular center, according to the clinical frailty scale (CFS) derived from Canadian Study of Health and Aging ( Supplemental Table 1 ). , Frailty was defined as a score ≥4 on the Clinical Frailty Scale. Patients were divided into three groups according to the CFS: low (CFS levels 1 to 3), intermediate (CFS levels 4 to 6), and high CFS groups (CFS levels 7 to 9) to assess the impact of frailty on clinical outcomes. We further subclassified clinical frailty according to the original CFS in patients within the intermediate and high CFS group (CFS levels 4 to 9), while clinical frailty was not subclassified in patients within the low CFS group (i.e., CFS levels 1 to 3).
Bleeding risk was assessed using the ARC-HBR criteria, the JCS-HBR (Japanese Circulation Society High Bleeding Risk) criteria, the PRECISE-DAPT (Predicting Bleeding Complications in Patients Undergoing Stent Implantation and Subsequent Dual Antiplatelet Therapy) score, the PARIS (Patterns of Non-Adherence to Antiplatelet Regimens In Stented Patients) bleeding score, and the CREDO-Kyoto (Coronary Revascularization Demonstrating Outcome Study in Kyoto) bleeding score. HBR was regarded as present in patients with at least one major or two minor ARC-HBR criteria, at least one major or two minor JCS-HBR criteria, a PRECISE-DAPT score of 25 or higher, a PARIS bleeding score of 8 or higher, or a CREDO-Kyoto bleeding score of 3 or higher. The variables for each bleeding risk score/criteria were shown in the Supplemental Table 2 .
We obtained clinical follow-up information from the medical records, patients’ referral documents, and telephone interviews with the patients, their families, or their family doctors. As the main outcome measures, we assessed all-cause death and major bleeding at 1-year (Bleeding Academic Research Consortium [BARC] type 3 or 5 bleeding). We also assessed cardiovascular death, non-cardiovascular death, myocardial infarction, stroke, ischemic stroke, hemorrhagic stroke, target vessel revascularization, target lesion revascularization, and definite stent thrombosis according to the Academic Research Consortium (ARC) criteria.
Continuous variables were expressed as mean ± standard deviations or as medians (interquartile ranges) and were compared using Kruskal-Wallis test. Categorical variables were presented as values and percentages and were compared using the χ 2 test. Kaplan-Meier curves were used to estimate the cumulative incidence of clinical events. Gray method was used to account for the competing risk for all-cause death. Hazard ratios and their 95% confidence intervals were calculated using Cox proportional hazards model. Because we consider frailty as stand-alone predictor summarizing many risk factors of patients, we did not construct multivariable models to adjust such risk factors. Instead, patients were stratified into those with or without HBR according to each bleeding risk score/criteria to explore the discriminative ability of frailty on bleeding risk in patients with and without HBR, separately. We assessed the interaction between the presence or absence of HBR and the effect of frailty on the risk of 1-year major bleeding, as well as the interaction between the presence or absence of each HBR criterion and the effect of frailty on the risk of 1-year major bleeding. Moreover, since data on the impact of frailty on clinical outcomes in non-ACS patients and in cardiogenic shock patients are scarce, we stratified patients according to the ACS presentation and according to cardiogenic shock as exploratory analyses. A two-sided P-value of less than 0.05 was considered statistically significant for all tests. All analyses were performed using R software, version 3.6.3 (R Foundation for Statistical Computing, Vienna, Austria) and JMP version 14.3.0 (SAS Institute Incorporated, Cary, NC, USA).
Results
The CFS level was low (1 to 3) in 1748 (71.7%) patients, intermediate (4 to 6) in 519 (21.3%) patients, and high (7 to 9) in 172 (7.1%) patients ( Figure 1 ). The baseline clinical characteristics, according to the CFS groups, are summarized in Table 1 . Frailer patients were older and had more comorbidities, such as renal failure and anemia. All risk scores successfully stratified the risk for 1-year major bleeding, while the prevalence of high bleeding risk was different largely according to each risk score ( Supplemental Figure 1 ).
| Overall (N = 2439) | Clinical frailty scale groups | p values | |||
|---|---|---|---|---|---|
| Low (1-3) | Intermediate (4-6) | High (7-9) | |||
| N = 1748 | N = 519 | N = 172 | |||
| Variable | |||||
| Age (years) | 71.9±10.1 | 69.3±10.2 | 77.9±9.9 | 80.5±9.9 | <0.001 |
| Age ≥75 | 1072 (44.0%) | 583 (33.4%) | 359 (69.2%) | 130 (75.6%) | <0.001 |
| Men | 1772 (72.7%) | 1399 (80.0%) | 297 (57.2%) | 76 (44.2%) | <0.001 |
| Body mass index (kg/m 2 ) | 23.8±3.5 | 24.3±3.4 | 23.1±3.7 | 21.3±3.9 | <0.001 |
| Low body weight <55 kg (men)/ <50 kg (women) | 569 (23.4%) | 262 (15.0%) | 203 (39.1%) | 104 (60.5%) | <0.001 |
| Acute coronary syndrome at presentation | 698 (28.6%) | 473 (27.1%) | 143 (27.6%) | 82 (47.7%) | <0.001 |
| Cardiogenic shock | 53 (2.2%) | 20 (1.1%) | 16 (3.1%) | 17 (9.9%) | <0.001 |
| Prior myocardial infarction | 462 (18.9%) | 349 (20.0%) | 87 (16.8%) | 26 (15.1%) | 0.10 |
| Hypertension | 1968 (80.7%) | 1399 (80.0%) | 425 (81.9%) | 144 (83.7%) | 0.36 |
| Diabetes mellitus | 1057 (43.3%) | 727 (41.6%) | 260 (50.1%) | 70 (40.7%) | 0.002 |
| Dyslipidemia | 1251 (71.6%) | 295 (56.8%) | 295 (56.8%) | 73 (42.2%) | <0.001 |
| Current smoker | 359 (14.7%) | 286 (16.4%) | 55 (10.6%) | 18 (10.5%) | 0.07 |
| Renal failure | |||||
| eGFR <30 mL/min per 1.73m or dialysis | 343 (14.1%) | 146 (8.4%) | 138 (26.6%) | 59 (34.3%) | <0.001 |
| eGFR 30-59 mL/min per 1.73m | 859 (35.2%) | 583 (33.4%) | 213 (41.0%) | 63 (36.6%) | 0.006 |
| Chronic obstructive pulmonary disease | 52 (2.1%) | 31 (1.7%) | 19 (3.7%) | 2 (1.2%) | 0.03 |
| Peripheral artery disease | 282 (11.6%) | 149 (8.5%) | 102 (19.7%) | 31 (18.0%) | <0.001 |
| Atrial fibrillation | 301 (12.3%) | 177 (10.1%) | 79 (15.2%) | 45 (26.2%) | <0.001 |
| Prior heart failure | 236 (9.7%) | 103 (5.9%) | 85 (16.4%) | 48 (27.9%) | <0.001 |
| Liver cirrhosis with portal hypertension | 11 (0.5%) | 5 (0.3%) | 6 (1.2%) | 0 (0%) | 0.03 |
| Prior spontaneous major bleeding * | |||||
| in the past 6 months or at any time if recurrent | 20 (0.8%) | 12 (0.7%) | 4 (0.8%) | 4 (2.3%) | 0.16 |
| in the past 6-12 months and not recurrent | 3 (0.1%) | 1 (0.1%) | 2 (0.4%) | 0 (0%) | 0.22 |
| Prior spontaneous intracranial hemorrhage | 49 (2.0%) | 22 (1.3%) | 20 (3.9%) | 7 (4.1%) | <0.001 |
| Prior ischemic stroke | |||||
| moderate or severe stroke within 6 months † | 14 (0.6%) | 4 (0.2%) | 8 (1.5%) | 2 (1.2%) | 0.003 |
| mild stroke within 6 months or any stroke > 6 months | 237 (9.7%) | 130 (7.4%) | 72 (13.9%) | 35 (20.4%) | <0.001 |
| Recent major surgery or major trauma within 30 days | 7 (0.3%) | 4 (0.2%) | 2 (0.4%) | 1 (0.6%) | 0.68 |
| Non-deferrable major surgery on dual antiplatelet therapy | 3 (0.1%) | 0 (0%) | 1 (0.2%) | 2 (1.2%) | 0.007 |
| Active malignancy | 107 (4.4%) | 71 (4.1%) | 25 (4.8%) | 11 (6.4%) | 0.34 |
| White blood cell count, × 10 6 /L | 68.2±26.5 | 67.6±24.3 | 66.4±25.1 | 79.9±45.1 | 0.003 |
| Anemia | |||||
| Hemoglobin <11g/dl | 429 (17.6%) | 169 (9.7%) | 177 (34.1%) | 83 (48.3%) | <0.001 |
| Hemoglobin 11-12.9g/dl (men) / 11-11.9g/dl (women) | 573 (23.5%) | 388 (22.2%) | 141 (27.2%) | 44 (25.6%) | 0.054 |
| Thrombocytopenia (Platelet<100 × 10 9 /L) | 73 (3.0%) | 32 (1.8%) | 27 (5.2%) | 14 (8.1%) | <0.001 |
| ARC-HBR | 1411 (57.9%) | 826 (47.3%) | 432 (83.2%) | 153 (89.0%) | <0.001 |
| JCS-HBR | 1586 (65.0%) | 964 (55.2%) | 462 (89.0%) | 160 (93.0%) | <0.001 |
| PRECISE DAPT score | 24 (15-34) | 21 (13-28) | 35 (26-44) | 43 (33-51) | <0.001 |
| PRECISE DAPT score ≥25 | 1210 (49.6%) | 647 (37.0%) | 416 (80.2%) | 147 (85.5%) | <0.001 |
| PARIS bleeding score | 7 (4-10) | 6 (4-8) | 9 (7-11) | 10.5 (8-11) | <0.001 |
| PARIS bleeding score ≥8 | 1034 (42.4%) | 543 (31.1%) | 351 (67.6%) | 140 (81.4%) | <0.001 |
| CREDO-Kyoto bleeding score | 1 (0-2) | 0 (0-1) | 2 (0-3) | 2 (1-4) | <0.001 |
| CREDO-Kyoto bleeding score ≥3 | 431 (17.7%) | 205 (11.7%) | 161 (31.1%) | 65 (37.8%) | <0.001 |
| Medication at discharge | |||||
| P2Y 12 inhibitors | 2348 (96.3%) | 1690(96.7%) | 496 (95.6%) | 162 (94.2%) | 0.19 |
| Clopidogrel | 2224 (91.2%) | 1589 (90.9%) | 480 (92.5%) | 155 (90.1%) | 0.46 |
| Prasugrel | 114 (4.7%) | 88 (5.0%) | 18 (3.5%) | 8 (4.7%) | 0.31 |
| Aspirin | 2266 (98.5%) | 899 (98.9%) | 267 (97.8%) | 118 (98.5%) | 0.28 |
| Oral anticoagulant | 313 (12.8%) | 171 (9.8%) | 97 (18.7%) | 45 (26.2%) | <0.001 |
| Nonsteroidal anti-inflammatory drugs or steroids | 143 (5.8%) | 87 (5.0%) | 46 (8.9%) | 10 (5.8%) | 0.007 |
| Proton pump inhibitor | 1756 (72.0%) | 1222 (69.9%) | 399 (76.9%) | 135 (78.5%) | 0.001 |
Stay updated, free articles. Join our Telegram channel
Full access? Get Clinical Tree
