| Title |
Admission hyperglycemia and outcome after intravenous thrombolysis: is there a difference among the stroke-subtypes?
|
|---|---|
| Published in |
BMC Neurology, July 2016
|
| DOI | 10.1186/s12883-016-0617-0 |
| Pubmed ID | |
| Authors |
Irene Miedema, Gert-Jan Luijckx, Raf Brouns, Jacques De Keyser, Maarten Uyttenboogaart |
| Abstract |
The prognostic influence of hyperglycemia in acute stroke has been well established. While in cortical stroke there is a strong association between hyperglycemia and poor outcome, this relation is less clear in lacunar stroke. It has been suggested that this discrepancy is present among patients treated with intravenous tissue plasminogen activator (tPA), but confirmation is needed. In two prospectively collected cohorts of patient treated with intravenous tPA for acute ischemic stroke, we investigated the effect of hyperglycemia (serum glucose level >8 mmol/L) on functional outcome in lacunar and non-lacunar stroke. Poor functional outcome was defined as modified Rankin Scale score ≥ 3 at 3 months. A total of 1012 patients was included of which 162 patients (16 %) had lacunar stroke. The prevalence of hyperglycemia did not differ between stroke subtypes (22 % vs 21 %, p = 0.85). In multivariate analysis hyperglycemia was associated with poor functional outcome in non-lacunar stroke (OR 2.1, 95 % CI 1.39-3.28, p = 0.001). In patients with lacunar stroke, we did not find an association (OR 1.8, 95 % CI 0.62-4.08, p = 0.43). This study confirms a difference in prognostic influence of hyperglycemia between non-lacunar and lacunar ischemic stroke. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 67% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 44 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 7 | 16% |
| Student > Ph. D. Student | 6 | 14% |
| Researcher | 6 | 14% |
| Student > Postgraduate | 3 | 7% |
| Student > Doctoral Student | 2 | 5% |
| Other | 7 | 16% |
| Unknown | 13 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 19 | 43% |
| Neuroscience | 5 | 11% |
| Physics and Astronomy | 1 | 2% |
| Computer Science | 1 | 2% |
| Social Sciences | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 16 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 July 2016.
All research outputs
#16,099,609
of 23,881,329 outputs
Outputs from BMC Neurology
#1,539
of 2,532 outputs
Outputs of similar age
#233,198
of 360,155 outputs
Outputs of similar age from BMC Neurology
#44
of 58 outputs
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