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Record W2935912623 · doi:10.3174/ajnr.a6038

Predicting Motor Outcome in Acute Intracerebral Hemorrhage

2019· article· en· W2935912623 on OpenAlexafffund
Josep Puig, Gerard Blasco, Mikel Terceño, Pepus Daunis‐i‐Estadella, Gottfried Schlaug, María Hernández‐Pérez, Víctor Cuba, Gerard Carbó, Joaquı́n Serena, Marco Essig, Chase R. Figley, Kambiz Nael, Carlos Leiva‐Salinas, Salvador Pedraza, Yolanda Silva

Bibliographic record

VenueAmerican Journal of Neuroradiology · 2019
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaMultiple Sclerosis Society of CanadaFondation Brain CanadaNational Institute of Neurological Disorders and StrokeHealth Sciences Centre Foundation
KeywordsMedicineIntracerebral hemorrhageOutcome (game theory)AnesthesiaSubarachnoid hemorrhage

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Predicting motor outcome following intracerebral hemorrhage is challenging. We tested whether the combination of clinical scores and DTI-based assessment of corticospinal tract damage within the first 12 hours of symptom onset after intracerebral hemorrhage predicts motor outcome at 3 months. MATERIALS AND METHODS: We prospectively studied patients with motor deficits secondary to primary intracerebral hemorrhage within the first 12 hours of symptom onset. Patients underwent multimodal MR imaging including DTI. We assessed intracerebral hemorrhage and perihematomal edema location and volume, and corticospinal tract involvement. The corticospinal tract was considered affected when the tractogram passed through the intracerebral hemorrhage or/and the perihematomal edema. We also calculated affected corticospinal tract-to-unaffected corticospinal tract ratios for fractional anisotropy, mean diffusivity, and axial and radial diffusivities. Motor impairment was graded by the motor subindex scores of the modified NIHSS. Motor outcome at 3 months was classified as good (modified NIHSS 0-3) or poor (modified NIHSS 4-8). RESULTS: Of 62 patients, 43 were included. At admission, the median NIHSS score was 13 (interquartile range = 8-17), and the median modified NIHSS score was 5 (interquartile range = 2-8). At 3 months, 13 (30.23%) had poor motor outcome. Significant independent predictors of motor outcome were NIHSS and modified NIHSS at admission, posterior limb of the internal capsule involvement by intracerebral hemorrhage at admission, intracerebral hemorrhage volume at admission, 72-hour NIHSS, and 72-hour modified NIHSS. The sensitivity, specificity, and positive and negative predictive values for poor motor outcome at 3 months by a combined modified NIHSS of >6 and posterior limb of the internal capsule involvement in the first 12 hours from symptom onset were 84%, 79%, 65%, and 92%, respectively (area under the curve = 0.89; 95% CI, 0.78-1). CONCLUSIONS: Combined assessment of motor function and posterior limb of the internal capsule damage during acute intracerebral hemorrhage accurately predicts motor outcome.

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)0.003
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.013
GPT teacher head0.297
Teacher spread0.284 · 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

Citations24
Published2019
Admission routes2
Has abstractyes

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