| Literature DB >> 22533539 |
Petr Kala1, Jan Kanovsky, Richard Rokyta, Michal Smid, Jan Pospisil, Jiri Knot, Filip Rohac, Martin Poloczek, Tomas Ondrus, Maria Holicka, Jindrich Spinar, Jiri Jarkovsky, Ladislav Dusek.
Abstract
BACKGROUND: Older age, as a factor we cannot affect, is consistently one of the main negative prognostic values in patients with acute myocardial infarction. One of the most powerful factors that improves outcomes in patients with acute coronary syndromes is the revascularization preferably performed by percutaneous coronary intervention. No data is currently available for the role of age in large groups of consecutive patients with PCI as the nearly sole method of revascularization in AMI patients. The aim of this study was to analyze age-related differences in treatment strategies, results of PCI procedures and both in-hospital and long-term outcomes of consecutive patients with acute myocardial infarction.Entities:
Mesh:
Year: 2012 PMID: 22533539 PMCID: PMC3407529 DOI: 10.1186/1471-2261-12-31
Source DB: PubMed Journal: BMC Cardiovasc Disord ISSN: 1471-2261 Impact factor: 2.298
Age-related baseline differences
| Number of patients | 1800 | 2014 | NA |
|---|---|---|---|
| | | | |
| Males | 1454 (80.8%) | 1132 (56.2%) | <0.001 |
| History of DM | 389 (21.6%) | 763 (37.9%) | <0.001 |
| History of previous MI | 268 (14.9%) | 505 (25.1%) | <0.001 |
| | | | |
| I | 1501 (83.4%) | 1361 (67.6%) | <0.001 |
| II | 179 (9.9%) | 410 (20.4%) | <0.001 |
| III | 54 (3.0%) | 131 (6.5%) | <0.001 |
| IV | 66 (3.7%) | 112 (5.6%) | 0.006 |
| | | | |
| STEMI + new LBBB | 1060 (58.9%) | 956 (47.5%) | <0.001 |
| NonSTEMI | 740 (41.1%) | 1058 (52.5%) | <0.001 |
| | | | |
| CAG | 1726 (95.9%) | 1860 (92.4%) | <0.001 |
| No indication for CAG | 74 (4.1%) | 154 (7.6%) | <0.001 |
| | | | |
| Single vessel disease | 717 (39.8%) | 463 (23.0%) | <0.001 |
| Two vessel disease | 506 (28.1%) | 546 (27.1%) | 0.491 |
| Three vessel disease | 478 (26.6%) | 807 (40.1%) | <0.001 |
| Left main artery disease | 25 (1.4%) | 44 (2.2%) | 0.069 |
| | | | |
| Left main | 26 (1.4%) | 42 (2.1%) | 0.143 |
| LAD | 660 (36.7%) | 763 (37.9%) | 0.441 |
| LCX | 360 (20.0%) | 293 (14.5%) | <0.001 |
| RCA | 585 (32.5%) | 562 (27.9%) | 0.002 |
| ACB | 14 (0.8%) | 25 (1.2%) | 0.197 |
| Not known | 155 (8.6%) | 329 (16.3%) | <0.001 |
| | | | |
| TIMI 0-1 | 877 (48.7%) | 781 (38.8%) | <0.001 |
| TIMI 2 | 288 (16.0%) | 315 (15.6%) | 0.790 |
| TIMI 3 | 480 (26.7%) | 589 (29.2%) | 0.077 |
| | | | |
| PCI total number | 1541 (85.6%) | 1505 (74.7%) | <0.001 |
| No PCI | 259 (14.4%) | 509 (25.3%) | <0.001 |
| 1541/1726 (89.3%) | 1505/1860 (80.9%) | <0.001 |
Numbers in the second and third column represent absolute numbers of patients and percentage of the related group. Statistically significant difference is p < 0.05.
DM diabetes mellitus, MI myocardial infarction, ECG electrocardiogram, STEMI ST segment elevation myocardial infarction, LBBB left bundle branch block, NonSTEMI non-ST elevation myocardial infarction.
Age-related endpoints of the project
| Number of patients | 1800 | 2014 | NA |
|---|---|---|---|
| | | | |
| TIMI 0-1 | 46 (2.6%) | 78 (3.9%) | 0.022 |
| TIMI 2 | 64 (3.6%) | 102 (5.1%) | 0.026 |
| TIMI 3 | 1434 (79.7%) | 1343 (66.7%) | <0.001 |
| 1..3 | 118 (6.6%) | 105 (5.2%) | 0.084 |
| 0..3 | 655 (36.4%) | 514 (25.5%) | <0.001 |
Numbers in the second and third column represent absolute numbers of patients and percentage of the related group, unless specified differently. Statistically significant difference is p < 0.05.
CAG Coronary Angiography, PCI Percutaneous Coronary Intervention, TIMI Thrombolysis In Myocardial Infarction.
Figure 1Long-term survival of patients in two selected centers.
Risk factors influencing long term survival of patients in two selected centers
| | |||||||
|---|---|---|---|---|---|---|---|
| Age (10 years) | - | 1.76 (1.35; 2.28) | <0.001 | - | 2.03 (1.75; 2.35) | <0.001 | 0.458 |
| Men | 1116 | 1.18 (0.78; 1.79) | 0.441 | 856 | 0.90 (0.76; 1.08) | 0.262 | 0.227 |
| DM | 303 | 1.91 (1.38; 2.65) | <0.001 | 574 | 1.41 (1.18; 1.68) | <0.001 | 0.085 |
| Previous MI | 219 | 2.02 (1.42; 2.87) | <0.001 | 385 | 1.46 (1.20; 1.76) | <0.001 | 0.189 |
| Killip I | 1114 | | 958 | | | ||
| Killip II | 155 | 2.52 (1.67; 3.81) | <0.001 | 334 | 1.80 (1.47; 2.22) | <0.001 | 0.298 |
| Killip III | 39 | 6.04 (3.48; 10.48) | <0.001 | 104 | 3.14 (2.36; 4.18) | <0.001 | 0.051 |
| Killip IV | 53 | 12.24 (7.94; 18.89) | <0.001 | 75 | 5.65 (4.14; 7.70) | <0.001 | 0.030 |
| PCI | 1169 | 0.60 (0.42; 0.88) | 0.008 | 1109 | 0.46 (0.38; 0.55) | <0.001 | 0.202 |
| No PCI | 199 | 1.66 (1.14; 2.41) | 370 | 2.19 (1.83; 2.63) | |||
| STEMI + new onset of LBBB | 948 | 1.02 (0.72; 1.43) | 0.924 | 990 | 1.21 (1.00; 1.47) | 0.056 | 0.312 |
| NonSTEMI | 420 | 0.98 (0.70; 1.38) | 489 | 0.83 (0.68; 1.01) | |||
| Final TIMI flow 2-3 | 1162 | 0.20 (0.10; 0.41) | <0.001 | 1096 | 0.32 (0.22; 0.47) | <0.001 | 0.151 |
| Final TIMI flow 0-1 | 19 | 5.00 (2.43; 10.18) | 46 | 3.13 (2.11; 4.65) | |||
| Single vessel disease | 532 | | 339 | | | ||
| Two vessel disease | 402 | 1.30 (0.86; 1.96) | 0.223 | 431 | 1.53 (1.13; 2.06) | 0.006 | 0.371 |
| Three vessel disease | 359 | 2.10 (1.43; 3.09) | <0.001 | 594 | 2.24 (1.70; 2.95) | <0.001 | 0.508 |
| Left main artery disease | 11 | 4.12 (1.28; 13.28) | 0.018 | 8 | 5.85 (2.50; 13.67) | <0.001 | 0.564 |
| | | | | | | | |
| Left main | 18 | 4.52 (1.77; 11.57) | 0.002 | 28 | 5.26 (3.26; 8.48) | <0.001 | 0.995 |
| LAD incl. its branches | 490 | 1.77 (1.17; 2.66) | 0.006 | 556 | 1.10 (0.86; 1.41) | 0.431 | 0.093 |
| LCX incl. its branches | 269 | 1.36 (0.83; 2.24) | 0.222 | 221 | 1.09 (0.80; 1.48) | 0.608 | 0.546 |
| RCA incl. its branches | 444 | | 401 | | | ||
| Bypass graft | 12 | 0.05 (0.00; 545.31) | 0.524 | 20 | 0.80 (0.30; 2.17) | 0.662 | - |
| IRA not known | 135 | 2.69 (1.63; 4.43) | <0.001 | 253 | 2.37 (1.83; 3.05) | <0.001 | 0.815 |
N number of patients in given category.
HR hazard ratio based on Cox proportional hazards model supplemented by its statistical significance.
Influence of age category of patients on HR value within these age categories is analyzed using interaction term in Cox proportional hazards model.