Validity of HAT Score for Predicting Symptomatic Intracranial Hemorrhage in Acute Stroke Patients with Proximal Occlusions: Data from Randomized Trials of Sonothrombolysis
Bibliographic record
Abstract
BACKGROUND: The Hemorrhage after Thrombolysis (HAT) score has recently been introduced as a practical scale for risk stratification of intracranial hemorrhage (ICH) in patients receiving intravenous tissue plasminogen activator (tPA). We aimed to externally validate and evaluate the predictive ability of the HAT score in patients with proximal arterial occlusions (PAO) enrolled into randomized clinical trials of sonothrombolysis. METHODS: The HAT score (range 0, minimum risk, to 5, maximum risk) was retrospectively calculated for each patient using clinical trial data (baseline NIHSS, extent of hypodensity on CT, history of diabetes mellitus and serum glucose). Symptomatic ICH (sICH) was defined as imaging evidence of ICH with clinical worsening (NIHSS ≥ 4) within 72 h from stroke onset. The predictive ability of the HAT score for sICH and any ICH (both asymptomatic and symptomatic) was calculated using c statistics. RESULTS: A total of 161 tPA-treated patients (mean age 68 ± 13 years, 58% men, median NIHSS 16, interquartile range 9) with PAO were randomized in TUCSON (n = 35) and CLOTBUST (n = 126). sICH occurred in 9 (5.6%) cases, and 6 had asymptomatic ICH. The rates of sICH for the corresponding HAT scores were: HAT 0-1: 3%; 2: 9%; 3: 14%; 4-5: 14%. The risk of sICH (c statistic 0.72, 95% CI: 0.58-0.86; p = 0.027) and any ICH (c statistic 0.70, 95% CI: 0.58-0.82; p = 0.011) increased with higher HAT scores. Higher HAT scores were also associated with higher likelihood of persisting occlusion (c statistic 0.63, 95% CI: 0.54-0.72; p = 0.004). CONCLUSIONS: The HAT score has reasonable external validity for predicting the risk of sICH following intravenous thrombolysis in patients with PAO. Moreover, higher HAT scores appear to be associated with higher likelihood of persisting occlusion in tPA-treated patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".