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Record W1956771503 · doi:10.1161/strokeaha.114.007343

Accuracy of the ABC/2 Score for Intracerebral Hemorrhage

2015· review· en· W1956771503 on OpenAlexaff
Alastair J.S. Webb, Natalie Ullman, Tim C. Morgan, John Muschelli, Joshua Kornbluth, Issam A. Awad, Stephen L. Mayo, Michael Rosenblum, Wendy Ziai, Mario Zuccarrello, François Aldrich, Sayona John, Sagi Harnof, George Α. Lopez, William C. Broaddus, Christine A.C. Wijman, Paul Vespa, Ross Bullock, Stephen J. Haines, Salvador Cruz‐Flores, Stan Tuhrim, Michael D. Hill, Raj K. Narayan, Daniel F. Hanley, Ashis Tayal, Alberto Torres Díaz, Alan Hoffer, Asma Moheet, Sachin Agarwal, Mason Markowski, Guy Rosenthal, Inam Kureshi, Panayiotis N. Varelas, Pedro Telles Cougo Pinto, Joan Martí‐Fábregas, Paul J. Camarata, David B. Seder, William D. Freeman, Ann Helms, Christos Lazaridis, Kavian Shahi, David Sinclair, Martin Gizzi, Michel Torbey, Kevin M. Cockroft, David Antezana, Julius Gene Latorre, Nevo Margalit, H. Mark Crabtree, Darren Lovick, Chitra Venkatasubramanian, Michael Weaver, Jack Jallo, Michael Reinert, Kenneth Butcher, Jody Leonardo, Agnieszka Ardelt, Opeolu Adeoye, László Csiba, Katja E. Wartenberg, Julian Bösel, Fernando D. Testai, Harold P. Adams, Carsten Hobohm, Thomas Kerz, Lawrence R. Wechsler, Paul A. Gardner, David A. Decker, Diederik Bulters, Nicole R. Gonzales, Jean-Louis Caron, Christiana E. Hall, Safdar Ansari, Andreas R. Luft, Fuat Arikán, R. Scott Graham, Kristi Tucker

Bibliographic record

VenueStroke · 2015
Typereview
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsUniversity of AlbertaMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institute of Neurological Disorders and Stroke
KeywordsIntracerebral hemorrhageMedicineIntraventricular hemorrhageNuclear medicineSurgerySubarachnoid hemorrhage

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The ABC/2 score estimates intracerebral hemorrhage (ICH) volume, yet validations have been limited by small samples and inappropriate outcome measures. We determined accuracy of the ABC/2 score calculated at a specialized reading center (RC-ABC) or local site (site-ABC) versus the reference-standard computed tomography-based planimetry (CTP). METHODS: In Minimally Invasive Surgery Plus Recombinant Tissue-Type Plasminogen Activator for Intracerebral Hemorrhage Evacuation-II (MISTIE-II), Clot Lysis Evaluation of Accelerated Resolution of Intraventricular Hemorrhage (CLEAR-IVH) and CLEAR-III trials. ICH volume was prospectively calculated by CTP, RC-ABC, and site-ABC. Agreement between CTP and ABC/2 was defined as an absolute difference up to 5 mL and relative difference within 20%. Determinants of ABC/2 accuracy were assessed by logistic regression. RESULTS: In 4369 scans from 507 patients, CTP was more strongly correlated with RC-ABC (r(2)=0.93) than with site-ABC (r(2)=0.87). Although RC-ABC overestimated CTP-based volume on average (RC-ABC, 15.2 cm(3); CTP, 12.7 cm3), agreement was reasonable when categorized into mild, moderate, and severe ICH (κ=0.75; P<0.001). This was consistent with overestimation of ICH volume in 6 of 8 previous studies. Agreement with CTP was greater for RC-ABC (84% within 5 mL; 48% of scans within 20%) than for site-ABC (81% within 5 mL; 41% within 20%). RC-ABC had moderate accuracy for detecting ≥5 mL change in CTP volume between consecutive scans (sensitivity, 0.76; specificity, 0.86) and was more accurate with smaller ICH, thalamic hemorrhage, and homogeneous clots. CONCLUSIONS: ABC/2 scores at local or central sites are sufficiently accurate to categorize ICH volume and assess eligibility for the CLEAR-III and MISTIE III studies and moderately accurate for change in ICH volume. However, accuracy decreases with large, irregular, or lobar clots. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: MISTIE-II NCT00224770; CLEAR-III NCT00784134.

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)0.005
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.094
GPT teacher head0.384
Teacher spread0.291 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations173
Published2015
Admission routes1
Has abstractyes

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