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Record W2598003106 · doi:10.1159/000460265

Hemorrhagic Transformations after Thrombectomy: Risk Factors and Clinical Relevance

2017· article· en· W2598003106 on OpenAlexaboutno aff
Johannes Kaesmacher, Mirjam Kaesmacher, Christian Maegerlein, Claus Zimmer, Alexandra S. Gersing, Silke Wunderlich, Benjamin Friedrich, Tobias Boeckh‐Behrens, Justus F. Kleine

Bibliographic record

VenueCerebrovascular Diseases · 2017
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineClinical significanceStroke (engine)Internal medicineOdds ratioLogistic regressionRetrospective cohort studyHematomaModified Rankin ScaleSurgeryIschemic strokeIschemia

Abstract

fetched live from OpenAlex

BACKGROUND: Hemorrhagic transformation (HT) is a major complication of acute ischemic stroke, potentially associated with clinical deterioration. We attempted to identify risk factors and evaluated clinical relevance of minor and major HTs following endovascular thrombectomy (ET) in isolated middle cerebral artery (MCA) occlusions. METHODS: This is a retrospective single-center analysis of 409 patients with isolated MCA occlusion treated with ET. Patients' and procedural characteristics, severity of HT according to the European Cooperative Acute Stroke Study criteria, and clinical outcomes were analyzed. Multivariate logistic regression models with standard retention criteria (p < 0.1) were used to determine risk factors and clinical relevance of HT. Results are shown as adjusted OR (aOR) and respective 95% CIs. Good neurologic short-term outcome was defined as National Institutes of Health Stroke Scale (NIHSS) score <5 at the day of discharge. RESULTS: Of 299 patients included, hemorrhagic infarction (HI) was detected in 87 patients, while 13 patients developed parenchymal hematoma (PH). Higher age (aOR 0.970, 95% CI 0.947-0.993, p = 0.012), eligibility for intravenous recombinant tissue plasminogen activator (IV rtPA; aOR 0.512, 95% CI 0.267-0.982, p = 0.044), and complete recanalization (TICI 3, aOR 0.408, 95% CI 0.210-0.789, p = 0.008) were associated with a lower risk of HI. Risk factors for HI included higher admission NIHSS score (aOR 1.080, 95% CI 1.010-1.153, p = 0.024) and higher admission glucose levels (aOR 1.493, 95% CI 1.170-1.904, p = 0.001). Further, female sex tended to be associated with a lower risk of HI (aOR 0.601, 95% CI 0.316-1.143, p = 0.121), while a statistical trend was observable for proximal MCA occlusion (aOR 1.856, 95% CI 0.945-3.646, p = 0.073) and a history of hypertension (aOR 2.176, 95% CI 0.932-5.080, p = 0.072) to increase risk of HI. Longer intervals from symptom onset to first digital subtraction angiography runs (aOR 1.013, 95% CI 1.003-1.022, p = 0.009), lower preinterventional Alberta Stroke Program Early CT score (aOR 0.536, 95% CI 0.307-0.936, p = 0.028) and wake-up stroke (aOR 18.540, 95% CI 1.352-254.276, p = 0.029) were associated with PH. Both, PH and HI were independently associated with lower rates of good neurologic outcome (aOR 0.086, 95% CI 0.008-0.902, p = 0.041 and aOR 0.282, 95% CI 0.131-0.606, p = 0.001). CONCLUSION: Risk of HI following MCA occlusion and subsequent ET is mainly determined by factors influencing infarct severity. Good recanalization results seem to be protective against subsequent HI. Our results support the notion that occurrence of PH after ET is time dependent and risk increases with more extensive early ischemic damage. Both, HI and PH do not seem to be facilitated by bridging therapy with IV rtPA or the use of oral anticoagulants, but were independently associated with more severe neurologic disability. These results support the notion that HI is not a "benign" imaging sign.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.015
GPT teacher head0.292
Teacher spread0.277 · 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 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

Citations164
Published2017
Admission routes1
Has abstractyes

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