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Record W4367152119 · doi:10.1161/svin.03.suppl_1.162

Abstract Number ‐ 162: Hydration Status and Functional Outcomes in Patients with Large Vessel Occlusion Stroke Undergoing Endovascular Therapy

2023· article· en· W4367152119 on OpenAlexaboutno aff
Abigail Baldwin‐LeClair, Avish Patel, Karan N Patel, James E. Siegler, Scott Kamen, Lauren Thau, Jared Wolfe, Linda Zhang, Kavya Thomas, Nicholas Vigilante, Jesse Thon

Bibliographic record

VenueStroke Vascular and Interventional Neurology · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInterquartile rangeModified Rankin ScaleOdds ratioThrombolysisStroke (engine)Internal medicineConfidence intervalCreatinineBlood urea nitrogenCardiologySurgeryMyocardial infarctionIschemic strokeIschemia

Abstract

fetched live from OpenAlex

Introduction Large vessel occlusion (LVO) and dehydration are both independently associated with poor functional outcomes and increased odds of mortality in acute ischemic stroke. Dehydration has previously been shown to affect collateral blood flow in LVO stroke, but it is unclear if this leads to worsened clinical outcomes. Methods A stroke center registry (10/2019‐12/2021) of consecutive adults who had undergone successful endovascular therapy (EVT, with thrombolysis in cerebral infarction score 2b/3) for anterior circulation LVO (ICA, M1, or M2) was queried. Dehydration on presentation was defined using laboratory surrogates: blood urea nitrogen/creatinine ratio >15 or serum osmolality >296 mOsm/kg. The primary outcome was a favorable shift in 90‐day modified Rankin Scale (mRS) using a proportional odds model, adjusting for age, pre‐stroke mRS, National Institutes of Health Stroke Scale (NIHSS), and Alberta Stroke Program Early Computed Tomography Scale (ASPECTS). Secondary outcomes included early improvement in 24h NIHSS. Results Of the 318 patients with anterior LVO who underwent EVT, 206 (65%) met criteria for dehydration, and 181 (87.9%) had both mRS and ASPECTS data available. Younger age, lower NIHSS, lower mRS, and higher ASPECTS were all strongly and independently associated with a favorable shift in 90d mRS. Dehydrated patients had similar changes in 24‐hr NIHSS scores (‐5 [interquartile range, IQR ‐10 to 0] vs. ‐5 [IQR ‐8 to 0], p = 0.37). Dehydration was not associated with a less favorable shift in 90‐day mRS (odds ratio [OR] 0.74, 95% confidence interval [CI] 0.41‐1.33), which remained non‐significant after multivariable adjustment (OR 1.46, 95%CI 0.74‐2.86). With serum osmolality assessed continuously, higher serum osm was associated with a less favorable shift in mRS at 90d (OR 0.95, 95%CI 0.92‐0.99, p = 0.009), but this did not persist after multivariable adjustment (p = 0.92) and was driven by the association between higher osmolality and age (r = 0.24, p(bonferroni)< 0.01) and pre‐stroke mRS (r = 0.20, p(bonferroni) = 0.04). Conclusions There was no association between dehydration and lower odds of early clinical improvement or long‐term functional recovery following successful endovascular thrombectomy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.247
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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