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Record W2915821179 · doi:10.2147/cia.s195451

<p>The mean platelet volume on admission predicts unfavorable stroke outcomes in patients treated with IV thrombolysis</p>

2019· article· en· W2915821179 on OpenAlexaboutno aff
Jacek Staszewski, Aleksandra Pogoda-Wesołowska, Kamila Data, Klaudia Walczak, Maciej Nowocień, Emilia Frankowska, Adam Stępień

Bibliographic record

VenueClinical Interventions in Aging · 2019
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineModified Rankin ScaleThrombolysisInternal medicineStroke (engine)ConfoundingMean platelet volumeRetrospective cohort studyTissue plasminogen activatorFibrinolytic agentEtiologyCohortSurgeryCardiologyIschemic strokePlateletMyocardial infarctionIschemia

Abstract

fetched live from OpenAlex

Purpose: The role of biomarkers in the prediction of acute ischemic stroke (AIS) outcome or response to thrombolytic therapy (with recombinant tissue plasminogen activator [rt-PA]) remains limited. The aim of this study was to evaluate whether mean platelet volume (MPV) could predict short-term functional outcome in patients with AIS following rt-PA treatment. Patients and methods: This was a retrospective analysis of 237 AIS patients (mean age 71.04±0.8 years, 50.6% women) consecutively admitted to a tertiary care center between 2011 and 2015. Results: The mean MPV in the cohort was 9.8±0.35 fL (lowest tertile 8.8 fL). Patients in the lowest tertile compared to median and highest tertiles were less often dependent (modified Rankin scale [mRS] ≥3) at admission (87.2% vs 96.1% and 96.1%, respectively, P =0.04) and less often had a poor stroke outcome (mRS 4–6) at discharge (28.2% vs 55.3% and 44.7%, P <0.01). However, there was no significant difference between tertiles with regard to AIS etiology, CT (Alberta Stroke Program Early CT) score, frequency of stroke due to large artery occlusion, risk of secondary hemorrhage, and early neurologic deterioration. Multivariable analysis after adjustment for confounders showed that patients in the second and third tertiles had a significantly higher risk of poor stroke outcome (OR =1.9, 95% CI =1.01–4), lack of early improvement (OR =1.91, 95% CI =1.05–3.47), lower chance of good outcome (mRS 0–2; OR =0.38, 95% CI =0.18–0.78), or minor stroke at discharge (OR =0.47, 95% CI =0.26–0.84). Receiver operating characteristic analysis for prediction of poor stroke outcome showed that the optimal cut-off point of MPV was 8.8 fL (area under the curve 0.586 [0.512–0.659], P =0.03) with a sensitivity of 82.7% and a specificity of 43.9%. Conclusion: Disabling or fatal ischemic stroke in thrombolyzed patients was observed more often in patients with high admission MPV. The prognostic value of MPV was independent of other well-defined individual risk factors. Keywords: acute ischemic stroke, rt-PA, prognosis, MPV, biomarker, platelet activity, reperfusion

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.344
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2019
Admission routes1
Has abstractyes

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