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Record W2090587263 · doi:10.1159/000355500

Stroke Prenotification Is Associated with Shorter Treatment Times for Warfarin-Associated Intracerebral Hemorrhage

2013· article· en· W2090587263 on OpenAlexaffabout
Dar Dowlatshahi, Jason K. Wasserman, Kenneth Butcher, Manya L. Bernbaum, A. Adam Cwinn, Antonio Giulivi, Eddy Lang, Man‐Chiu Poon, Jessica Tomchishen-Pope, Mukul Sharma, Shelagh B. Coutts

Bibliographic record

VenueCerebrovascular Diseases · 2013
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsMcMaster UniversityUniversity of AlbertaPopulation Health Research InstituteUniversity of CalgaryOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineIntracerebral hemorrhageStroke (engine)WarfarinAnesthesiaCardiologyInternal medicineSubarachnoid hemorrhageAtrial fibrillation

Abstract

fetched live from OpenAlex

BACKGROUND: Warfarin-associated intracerebral hemorrhage (WAICH) is a devastating disease with increasing incidence. In this setting, treatment with prothrombin complex concentrates (PCC) is essential to correct coagulopathy. Yet despite the availability of coagulopathy correction strategies, significant treatment delays can occur in emergency departments (EDs), which may be overcome using stroke prenotification strategies. To explore this, we compared arrival-to-treatment times with PCC for WAICH between two different stroke response systems that used the same international normalized ratio (INR) correction protocol. METHODS: We established a registry of consecutive patients presenting with WAICH and treated with PCC presenting to two Canadian tertiary-care academic stroke centers: one with a stroke prenotification system, and one with a traditional ED assessment, treatment and referral system. In this comparative cohort design, we defined the WAICH diagnosis time as the earliest time point where both INR and CT were available. We compared median times from arrival to treatment, as well as arrival to diagnosis, and diagnosis to treatment. RESULTS: Between 2008 and 2010, we collected data from 123 consecutive patients with intracranial hemorrhage who received PCC for INR correction (79 from ED referral, and 44 prenotification). Onset-to-arrival times, demographics, Glasgow Coma Scale scores, and baseline INR were similar between the two systems. Arrival-to-treatment times were significantly shorter in the prenotification system as compared to the traditional ED referral system (135 vs. 267 min; p = 0.001), which was driven by both decreased arrival-to-diagnosis time (49 vs. 117 min; p = 0.006), as well as decreased diagnosis-to-treatment time (56 vs. 112 min; p < 0.001). Arrival-to-scan times and arrival-to-INR times were similarly shorter in the prenotification system (68 vs. 118 min and 20.5 vs. 47 min, respectively). CONCLUSION: Stroke prenotification was associated with shorter arrival-to-treatment times for emergent INR correction in patients with WAICH, which was driven by both faster diagnosis and treatment. Our results are consistent with those seen in ischemic stroke, suggesting that prenotification systems present an opportunity to optimize acute intracerebral hemorrhage therapy.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0030.000

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 head0.015
GPT teacher head0.250
Teacher spread0.235 · 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.

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

Citations5
Published2013
Admission routes2
Has abstractyes

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