Incidencia, pronóstico y predicción de la transformación hemorrágica tras el tratamiento revascularizador del ictus
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Haemorrhagic transformation is a major complication of acute ischaemic stroke (AIS). We sought to determine the predictors and clinical impact of intracranial haemorrhage (ICH) after revascularisation therapy. METHODS: We conducted a retrospective, single-centre study including 235 patients with AIS who underwent intravenous recombinant tissue plasminogen activator (IV-rtPA) therapy and/or endovascular treatment. A binary logistic regression model was used to determine the variables associated with ICH, parenchymal haematomas (PH), modified Rankin Scale (mRS) scores, and mortality. RESULTS: ICH was detected in 57 (30 with PH) of 183 patients included. Mechanical thrombectomy, either alone (OR 3.3 [1.42-7.63], P=.005) or in combination with IV-rtPA (OR 3.39 [1,52-7.56], P=.003), was associated with higher risk of ICH, while higher Alberta Stroke Program Early CT scores (OR 0.71 [0.55-0.91], P=.007) were associated with lower risk. Patients with older age (OR 1.07 [1.02-1.13], P=.006) and occlusion of the terminal branch of the internal carotid artery (OR 4.03 [1.35-11.99], P = .012) had a higher risk of PH, while the use of IV-rtPA alone (OR 0.24 [0.08-0.68], P=.008) was associated with lower risk of PH. Only PH was associated with disability as measured by the mRS (OR 3.2 [1.17-8.76], P=.02) and higher mortality (OR 5.06 [1.65-15.5], P=.005). CONCLUSIONS: Greater understanding about the predictors of ICH, mRS scores, and mortality could enable better selection of patients and treatments.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it