| Literature DB >> 25106063 |
Jonathan Emberson1, Kennedy R Lees2, Patrick Lyden3, Lisa Blackwell1, Gregory Albers4, Erich Bluhmki5, Thomas Brott6, Geoff Cohen7, Stephen Davis8, Geoffrey Donnan9, James Grotta10, George Howard11, Markku Kaste12, Masatoshi Koga13, Ruediger von Kummer14, Maarten Lansberg4, Richard I Lindley15, Gordon Murray7, Jean Marc Olivot4, Mark Parsons16, Barbara Tilley10, Danilo Toni17, Kazunori Toyoda13, Nils Wahlgren18, Joanna Wardlaw7, William Whiteley7, Gregory J del Zoppo19, Colin Baigent20, Peter Sandercock7, Werner Hacke21.
Abstract
BACKGROUND: Alteplase is effective for treatment of acute ischaemic stroke but debate continues about its use after longer times since stroke onset, in older patients, and among patients who have had the least or most severe strokes. We assessed the role of these factors in affecting good stroke outcome in patients given alteplase.Entities:
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Year: 2014 PMID: 25106063 PMCID: PMC4441266 DOI: 10.1016/S0140-6736(14)60584-5
Source DB: PubMed Journal: Lancet ISSN: 0140-6736 Impact factor: 79.321
Baseline characteristics of patients in participating trials
| Number randomised | 291 | 333 | 620 | 800 | 142 | 613 | 821 | 101 | 3035 | 6756 | |
| Treatment delay (hours) | 2·0 (0·6) | 2·0 (0·6) | 4·4 (1·1) | 4·3 (1·1) | 4·3 (1·1) | 4·4 (0·8) | 4·0 (0·4) | 4·9 (0·8) | 4·2 (1·2) | 4·0 (1·2) | |
| ≤3·0 | 290 (>99%) | 333 (100%) | 87 (14%) | 158 (20%) | 22 (15%) | 39 (6%) | .. | .. | 620 (20%) | 1549 (23%) | |
| >3·0≤4·5 | 1 (<1%) | .. | 233 (38%) | 265 (33%) | 53 (37%) | 249 (41%) | 788 (96%) | 31 (31%) | 1148 (38%) | 2768 (41%) | |
| >4·5 | .. | .. | 295 (48%) | 370 (46%) | 67 (47%) | 321 (52%) | 6 (1%) | 69 (68%) | 1266 (42%) | 2394 (35%) | |
| Missing | .. | .. | 5 (1%) | 7 (1%) | .. | 4 (1%) | 27 (3%) | 1 (1%) | 1 (<1%) | 45 (1%) | |
| Age (years) | 66 (11) | 68 (12) | 65 (12) | 66 (11) | 66 (13) | 66 (11) | 65 (12) | 72 (13) | 77 (12) | 71 (13) | |
| ≤80 | 279 (96%) | 289 (87%) | 615 (>99%) | 792 (99%) | 142 (100%) | 608 (>99%) | 805 (98%) | 76 (75%) | 1418 (47%) | 5024 (74%) | |
| >80 | 12 (4%) | 44 (13%) | 5 (1%) | 8 (1%) | .. | 3 (<1%) | 15 (2%) | 25 (25%) | 1617 (53%) | 1729 (26%) | |
| Missing | .. | .. | .. | .. | .. | 2 (<1%) | 1 (<1%) | .. | .. | 3 (<1%) | |
| Stroke severity (NIHSS) | 14 (7) | 15 (7) | 12 (6) | 12 (6) | 13 (7) | 11 (6) | 10 (5) | 13 (6) | 12 (7) | 12 (7) | |
| 0–4 | 16 (5%) | 13 (4%) | 34 (5%) | 47 (6%) | 10 (7%) | 47 (8%) | 98 (12%) | 1 (1%) | 400 (13%) | 666 (10%) | |
| 5–10 | 78 (27%) | 98 (29%) | 189 (30%) | 339 (42%) | 57 (40%) | 279 (46%) | 389 (47%) | 40 (40%) | 1064 (35%) | 2533 (37%) | |
| 11–15 | 68 (23%) | 63 (19%) | 183 (30%) | 232 (29%) | 28 (20%) | 128 (21%) | 163 (20%) | 22 (22%) | 601 (20%) | 1488 (22%) | |
| 16–21 | 76 (26%) | 78 (23%) | 146 (24%) | 113 (14%) | 25 (18%) | 106 (17%) | 142 (17%) | 29 (29%) | 618 (20%) | 1333 (20%) | |
| ≥22 | 45 (15%) | 74 (22%) | 28 (5%) | 43 (5%) | 20 (14%) | 33 (5%) | 18 (2%) | 9 (9%) | 352 (12%) | 622 (9%) | |
| Missing | 8 (3%) | 7 (2%) | 40 (6%) | 26 (3%) | 2 (1%) | 20 (3%) | 11 (1%) | .. | 114 (2%) | ||
| Female | 120 (41%) | 142 (43%) | 231 (37%) | 331 (41%) | 45 (32%) | 250 (41%) | 325 (40%) | 43 (43%) | 1570 (52%) | 3057 (45%) | |
| History of hypertension | 188 (65%) | 220 (66%) | 258 (42%) | 412 (52%) | 87 (61%) | 364 (59%) | 514 (63%) | 71 (70%) | 1954 (64%) | 4068 (60%) | |
| History of stroke | 49 (17%) | 34 (10%) | 83 (13%) | 158 (20%) | 31 (22%) | 89 (15%) | 89 (11%) | 11 (11%) | 699 (23%) | 1243 (18%) | |
| History of diabetes mellitus | 64 (22%) | 67 (20%) | 81 (13%) | 169 (21%) | 27 (19%) | 130 (21%) | 129 (16%) | 23 (23%) | 388 (13%) | 1078 (16%) | |
| History of atrial fibrillation | 55 (19%) | 60 (18%) | 113 (18%) | 188 (24%) | 37 (26%) | 97 (16%) | 108 (13%) | 42 (42%) | 914 (30%) | 1614 (24%) | |
| Aspirin use | 78 (27%) | 93 (28%) | 87 (14%) | 196 (25%) | 59 (42%) | 211 (34%) | 201 (24%) | 30 (30%) | 1306 (43%) | 2261 (33%) | |
| Weight (kg) | 78 (17) | 78 (19) | 74 (12) | 75 (14) | 80 (20) | 79 (18) | 78 (15) | 75 (19) | 72 (15) | 75 (16) | |
| Systolic blood pressure (mmHg) | 154 (21) | 152 (21) | 154 (23) | 152 (21) | 152 (24) | 152 (21) | 153 (21) | 148 (19) | 155 (24) | 154 (22) | |
| Diastolic blood pressure (mmHg) | 85 (13) | 85 (14) | 87 (13) | 84 (13) | 81 (14) | 82 (14) | 84 (14) | 78 (13) | 82 (15) | 83 (14) | |
Categorical data presented as n (%), continuous data presented as mean (SD). NINDS=National Institute of Neurological Disorders and Stroke; ECASS=European Cooperative Acute Stroke Study; ATLANTIS=Alteplase Thrombolysis for Acute Noninterventional Therapy in Ischemic Stroke; EPITHET=Echoplanar Imaging Thrombolytic Evaluation Trial; IST=International Stroke Trial.
In IST-3, 244 patients had their baseline NIHSS score predicted from other measurements recorded at their baseline assessment. Ignoring these patients, the numbers of IST-3 patients in each category of baseline NIHSS score above would be 385, 972, 531, 559 and 344 respectively.
Figure 1Effect of timing of alteplase treatment on good stroke outcome (mRS 0–1)
The solid line is the best linear fit between the log odds ratio for a good stroke outcome for patients given alteplase compared with those given control (vertical axis) and treatment delay (horizontal axis; pinteraction=0·016). Estimates are derived from a regression model in which alteplase, time to treatment, age, and stroke severity (handled in a quadratic manner) are included as main effects but the only treatment interaction included is with time to treatment. Only 198 patients (159 from IST–3) had a time from stroke onset to treatment of more than 6 h. The white box shows the point at which the estimated treatment effect crosses 1. The black box shows the point at which the lower 95% CI for the estimated treatment effect first crosses 1·0. mRS=modified Rankin Scale.
Figure 2Effect of alteplase on good stroke outcome (mRS 0–1), by treatment delay, age, and stroke severity
*For each of the three baseline characteristics, estimates were derived from a single logistic regression model stratified by trial, which enables separate estimation of the OR for each subgroup after adjustment for the other two baseline characteristics (but not for possible interactions with those characteristics). mRS=modified Rankin Scale.
Figure 3Effect of alteplase on a good stroke outcome (mRS 0–1) by age, with different treatment delays
Effect of age on the interaction between treatment delay and treatment effect p=0·08 (ie, not significant but, if anything, in the direction of it lengthening, not shortening, the period during which alteplase is effective in older people). *All six estimates derived from a single stratified logistic regression model that enables the odds ratio to be estimated separately for each group (also adjusted for baseline National Institutes of Health Stroke Scale score). mRS=modified Rankin Scale.
Figure 4Effect of alteplase on fatal intracranial haemorrhage within 7 days by treatment delay, age, and stroke severity
*For each of the three baseline characteristics, estimates were derived from a single logistic regression model stratified by trial, which enables separate estimation of the OR for each subgroup after adjustment for the other two baseline characteristics (but not possible interactions with those characteristics). The overall effect in all patients is the trial-stratified logistic regression estimate adjusted only for treatment allocation. NE=not estimable.
Figure 5Effect of alteplase on 90-day mortality by follow-up period
Patients can only contribute to a particular risk period if they have already survived any preceding periods. *Estimated by Cox proportional hazards regression stratified by trial (and adjusted only for treatment allocation). †Includes 91 versus 13 deaths caused by intracranial haemorrhage (with evidence of parenchymal haemorrhage type 2; figure 4) and 191 versus 191 deaths from other causes.
Figure 6Effect of alteplase on 90-day mortality by treatment delay
*Estimated by Cox proportional hazards regression stratified by trial (and adjusted only for treatment allocation). HR=hazard ratio.