Low serum albumin (SA) on admission in patients with acute myocardial infarction (AMI) has been reported to be associated with adverse cardiovascular events. The relation between low SA and post-AMI bleeding events is presently unknown. We analyzed 1,724 patients with AMI enrolled in the HAGAKURE-ACS registry who underwent primary percutaneous coronary intervention from January 2014 to December 2018. To assess the influence of low SA at admission, patients were divided into 3 groups according to the albumin tertiles: the low SA group (<3.8 g/100 ml), the middle SA (MSA) group (3.8 to 4.1 g/100 ml), and the normal SA (NSA) group (≥4.2 g/100 ml). The primary end point was the incidence of Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries moderate/severe bleeding. The cumulative 3-year incidence of the primary end point was significantly higher in the low SA group than in the MSA and NSA groups (30.8% and 11.9% vs 7.7%; p < 0.001). In the landmark analysis at 30 days, the cumulative incidences of the primary end point were also significantly higher in the low SA group than in the MSA and NSA groups, both within and beyond 30 days (20.1% and 6.1% vs 3.5%; p < 0.001, and 12.4% and 6.2% vs 4.5%; p < 0.001, respectively). After adjusting for confounders, the low SA group showed excess risk of bleeding events relative to NSA (hazard ratio 1.56; 95% confidence interval 1.06 to 2.30; p = 0.026), whereas risk of bleeding was neutral in MSA relative to NSA (hazard ratio 0.94; 95% confidence interval 0.63 to 1.34; p = 0.752). In conclusion, low SA at admission was independently associated with higher risk for bleeding events in patients with AMI undergoing percutaneous coronary intervention.
Short- and long-term prognoses in patients with acute myocardial infarction (AMI) have improved in the primary reperfusion therapy era. , The development of coronary stents, optimal medical therapy, and cardiac rehabilitation have all contributed to the reduction of cardiovascular events after AMI. , Risk reduction for bleeding events is also important to achieve further improvement of prognoses of patients with AMI because bleeding events have been reported to be associated with higher mortality after percutaneous coronary intervention (PCI). Although several risk models were established to stratify the patients with high bleeding risk after PCI, there is a need for further risk stratification in patients with AMI as those risk scores were not dedicated to the AMI population. Because serum albumin (SA) is a well-known biomarker of nutrition, frailty, and inflammation, low SA could be a predictor for bleeding events in patients with AMI undergoing PCI. However, there are limited data evaluating the association between low SA and bleeding events after PCI in patients with AMI.
Methods
The HAGAKURE (Heart And vascular disease outcome study in saGA and KyUshu Region) – acute coronary syndrome (ACS) registry is a multicenter, nonrandomized, retrospective study performed in 3 cardiovascular centers in Japan. Among the total of 2,156 consecutive patients with ACS enrolled from January 2014 to December 2018, 1,787 patients with AMI had primary PCI after excluding 369 patients with recurrent ACS, unstable angina pectoris, and those without primary PCI. After excluding 63 patients who were lacking data on albumin, the present study population consisted of 1,724 patients with AMI who had either ST-segment elevation myocardial infarction (STEMI) or non–ST-segment elevation myocardial infarction (NSTEMI) ( Figure 1 ). The patients were stratified into 3 groups according to the tertiles of SA levels at admission: low SA group (<3.8 g/100 ml), middle SA (MSA) group (3.8 to 4.1 g/100 ml), and normal SA (NSA) group (≥4.2 g/100 ml) ( Figure 1 ). All procedures were followed in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Declaration of Helsinki 1964 and later revisions. Written informed consents were waived because of the retrospective nature of the study. Ethics approval was obtained from the Institutional Review Board of Saga University, Miyazaki Medical Association Hospital, and Ureshino Medical Center.
Diagnoses of STEMI and NSTEMI, based on the 2007 universal definitions, were made by each cardiologist. Details of STEMI and NSTEMI definitions are shown in Supplementary Methods. The therapeutic strategies for AMI treatment depended on the practice of each cardiologist, but all patients’ treatments followed the guidelines set forth by the Japanese Circulation Society and the American College of Cardiology/American Heart Association for the diagnosis and treatment of AMI.
The following data were collected: baseline demographics and clinical characteristics of the study patients, including medical history, presenting signs and symptoms, results of blood tests, transthoracic echocardiography, electrocardiography, cardiac procedures, and clinical end points. In addition, blood biomarkers were measured within 24 hours after admission as acute phase data. Clinical follow-up data were obtained from clinic visits, telephone calls, and records from hospital admissions. According to clinical data including follow-up, over 90% of these data were obtained by a single physician in each facility.
The primary end point was major bleeding, defined as Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries moderate/severe bleeding events. Traumatic brain bleeding was included in intracranial bleeding. Secondary end points were all-cause death, cardiovascular death, and hospitalization for heart failure.
In order to evaluate the clinical impact of low SA on bleeding events, we carried out subgroup analysis of patients with or without Academic Research Consortium for High Bleeding Risk (ARC-HBR) criteria. Details of the classification of ARC-HBR in the present analysis are shown in Supplementary Methods.
For continuous variables, normally distributed data are reported as mean ± SD; nonparametric data are reported as median and interquartile range. For categoric variables, data are presented as count and percentage. Comparisons of continuous variables between groups were performed with the analysis of variance or Kruskal-Wallis tests, as appropriate. Comparisons of categoric variables were assessed with the chi-square test. The cumulative incidence of an end point was calculated according to the Kaplan–Meier method. The effect of SA level on the primary end point was determined with a multivariate Cox proportional hazards regression model adjusting for confounding baseline factors selected by stepwise model. As a sensitivity analysis, we also used Cox proportional hazards model to estimate the risk of low SA group relative to other groups adjusting for all variables (Model 1) and variables related to bleeding events as well as those chosen by stepwise model (Model 2). A 2-sided p value <0.05 was considered statistically significant. All statistical analyses were performed with JMP 14 (SAS Institute Inc., Cary, North Carolina).
Results
Patient clinical characteristics and treatments during the acute phase are summarized in Table 1 . The low SA group more often had diabetes mellitus, smoking habits, atrial fibrillation, malignancy, anemia, chronic kidney disease, and histories of myocardial infarction than the other 2 groups.
| Serum albumin (g/dL) | ||||
|---|---|---|---|---|
| Variables | Total | <3.8 | 3.8-4.1 | ≥4.2 |
| (n = 1724) | (n = 539) | (n = 515) | (n = 670) | |
| Man | 1252 (72.6%) | 328 (60.9%) | 389 (75.5%) | 535 (79.9%) |
| Age (years) | 69.9 ± 12.5 | 76.1 ± 10.8 | 70.7 ± 11.6 | 64.2 ± 12.0 |
| Body mass index (kg/m 2 ) | 23.8 ± 4.0 | 22.6 ± 3.7 | 24.0 ± 4.2 | 24.8 ± 3.7 |
| Heart rate (/min) | 77.0 ± 20.4 | 76.9 ± 24.1 | 76.5 ± 20.4 | 77.8 ± 16.8 |
| Systolic blood pressure (mm Hg) | 139 ± 31 | 129 ± 33 | 137 ± 30 | 149 ± 27 |
| Medical history | ||||
| Hypertension | 1216 (70.5%) | 381 (70.7%) | 364 (70.7%) | 471 (70.3%) |
| Dyslipidemia | 919 (53.3%) | 231 (42.9%) | 278 (54.0%) | 410 (61.2%) |
| Diabetes mellitus | 500 (29.0%) | 193 (35.8%) | 140 (27.2%) | 167 (24.9%) |
| Smoker | 807 (46.8%) | 212 (39.3%) | 256 (49.7%) | 339 (50.6%) |
| Family history of cardiovascular disease | 195 (11.3%) | 47 (8.7%) | 70 (13.6%) | 78 (11.6%) |
| Healed myocardial infarction | 89 (5.2%) | 38 (7.1%) | 31 (6.0%) | 20 (3.0%) |
| Atrial fibrillation | 83 (4.8%) | 43 (8.0%) | 22 (4.3%) | 18 (2.7%) |
| Warfarin use at admission | 20 (1.2%) | 6 (1.1%) | 9 (1.8%) | 5 (0.8%) |
| Direct oral anticoagulant at admission | 52 (3.0%) | 28 (5.2%) | 11 (2.1%) | 13 (1.9%) |
| Malignancy | 94 (5.5%) | 44 (8.2%) | 24 (4.7%) | 26 (3.9%) |
| ARC-HBR | 698 (40.5%) | 373 (69.2%) | 192 (37.3%) | 133 (19.9%) |
| Serum albumin at admission (g/dL) | 4.0 ± 0.5 | 3.3 ± 0.4 | 4.0 ± 0.1 | 4.5 ± 0.2 |
| WBC (× 10 3 /mL) | 90 (71-116) | 91 (69-117) | 89 (71-113) | 91 (71-118) |
| Hemoglobin (g/dL) | 13.7 ± 2.1 | 12.2 ± 2.1 | 13.8 ± 1.8 | 14.9 ± 1.6 |
| Platelet (× 10 4 /μL) | 22.1 ± 9.9 | 21.0 ± 7.8 | 22.2 ± 12.7 | 23.1 ± 8.9 |
| eGFR (mL/min/1.73m 2 ) | 64.7 ± 24.0 | 53.9 ± 24.4 | 64.6 ± 23.3 | 73.4 ± 20.6 |
| Triglyceride, mg/dL | 107 (74-160) | 86 (62-117) | 107 (76-154) | 132 (85-200) |
| Total-cholesterol (mg/dL) | 193.1 ± 44.6 | 171.8 ± 38.6 | 190.1 ± 37.8 | 211.7 ± 45.9 |
| LDL-cholesterol (mg/dL) | 120.2 ± 36.1 | 104.6 ± 32.2 | 118.9 ± 34.6 | 133.4 ± 35.2 |
| HDL-cholesterol (mg/dL) | 48.2 ± 13.1 | 46.3 ± 14.3 | 48.6 ± 12.7 | 49.5 ± 12.3 |
| High-sensitivity troponin T (ng/mL) (Upper limit of normal: 0.032) | 0.27 (0.05-2.61) | 0.71 (0.09-5.87) | 0.23 (0.05-1.97) | 0.19 (0.04-1.12) |
| Brain natriuretic peptide (pg/mL) (Upper limit of normal: 18.4) | 67.8 (24.1-211.6) | 226.8 (73.3-674.8) | 69.7 (28.2-191.1) | 34.3 (15.4-87.0) |
| NT-pro brain natriuretic peptide (pg/mL) (Upper limit of normal: 125) | 319.9 (106.2-1792.5) | 1193.0 (287.1-3760.0) | 235.5 (96.0-785.8) | 153.0 (45.1-383.4) |
| STEMI | 1173 (68.0%) | 366 (67.9%) | 347 (67.4%) | 460 (68.7%) |
| NSTEMI | 551 (32.0%) | 173 (32.1%) | 168 (32.6%) | 210 (31.3%) |
| Killip class ≥3 | 172 (10.0%) | 119 (22.1%) | 40 (7.8%) | 13 (1.9%) |
| LVEF (%) | 54.0 ± 13.5 | 51.4 ± 15.4 | 54.3 ± 13.8 | 55.9 ± 11.2 |
| Peak creatine kinase (IU/L) | 1380 (396-3051) | 1044 (316-2615) | 1378 (402-3051) | 1607 (458-3365) |
| Culprit coronary artery | ||||
| Right | 545 (31.9%) | 202 (37.8%) | 158 (31.0%) | 185 (27.7%) |
| Left main | 45 (2.6%) | 26 (4.9%) | 12 (2.4%) | 7 (1.1%) |
| Left anterior descending | 783 (45.7%) | 213 (39.8%) | 248 (48.6%) | 322 (48.2%) |
| Left circumflex | 267(15.6%) | 78 (14.6%) | 74 (14.5%) | 115 (17.2%) |
| Other and MVD | 84 (4.9%) | 20 (3.7%) | 23 (4.5%) | 41 (6.1%) |
| Femoral approach | 310 (30.4%) | 164 (30.4%) | 86 (16.7%) | 60 (9.0%) |
| IABP | 233 (13.5%) | 116 (21.5%) | 66 (12.8%) | 51 (7.6%) |
| ECMO | 48 (2.8%) | 29 (5.4%) | 12 (2.3%) | 7 (1.0%) |
| In-hospital mortality | 80 (4.6%) | 57 (10.6%) | 16 (3.1%) | 7 (1.0%) |
| Medication at discharge | n = 1644 | n = 482 | n = 499 | n = 663 |
| Aspirin | 1582 (96.2%) | 455 (94.4%) | 481 (96.4%) | 646 (97.4%) |
| P2Y12 inhibitor | 1538 (93.6%) | 438 (90.9%) | 465 (93.2%) | 635 (95.8%) |
| Prasugrel | 584 (35.5%) | 145 (30.1%) | 186 (37.3%) | 253 (38.2%) |
| Clopidogrel | 967 (58.8%) | 301 (62.5%) | 281 (56.3%) | 385 (58.1%) |
| Warfarin | 40 (2.4%) | 22 (4.6%) | 9 (1.8%) | 9 (1.4%) |
| Direct oral anticoagulant | 153 (9.3%) | 64 (13.3%) | 49 (9.8%) | 40 (6.0%) |
| Statin | 1529 (93.0%) | 421 (87.3%) | 470 (94.2%) | 638 (96.2%) |
| β-blocker | 870 (52.9%) | 248 (51.5%) | 263 (52.7%) | 359 (54.2%) |
| ACE-I | 736 (44.8%) | 173 (35.9%) | 247 (49.5%) | 316 (47.7%) |
| ARB | 455 (28.0%) | 135 (28.0%) | 143 (28.7%) | 177 (26.7%) |
| Proton pump inhibitor | 1173 (71.4%) | 330 (68.5%) | 359 (71.9%) | 484 (73.0%) |
| Histamine Ⅱ blocker | 166 (10.1%) | 61 (12.7%) | 56 (11.2%) | 49 (7.4%) |
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