Novel Graphical Comparative Analyses of 7 Prehospital Stroke Scales (S5.007)
Bibliographic record
Abstract
Objective: To illustrate novel graphical methods of comparing the operating characteristics of different prehospital stroke scales. Background: Stroke patients unrecognized in the field experience delayed hospital care. Numerous stroke scales have been created to aid in prehospital identification of stroke but these scales have never been compared graphically. Methods: Separate two by two tables of performance measures for each stroke scale were entered in the Meta-DiSc software. Sensitivities and false positive rates were compared on a receiver operating curve (ROC) plane. For stroke scales reviewed in more than two studies, we graphed the symmetric summary ROC (SSROC) and area under the curve (AUC) was calculated. The methodology for generating SSROC was chosen based on the measured between-study heterogeneity, as calculated by the inconsistency index (I2) and tau squared (τ2), with I2 > 50% or τ2 > 1 pointing towards substantial statistical heterogeneity. Results: We reviewed studies validating Cincinnati Prehospital Stroke Scale (CPSS), Los Angeles Prehospital Stroke Screen (LAPSS), Melbourne Ambulance Stroke Screen (MASS), Face Arm Speech Test (FAST), Ontario Prehospital Stroke Screening (OPSS), Medic Prehospital Assessment for Code Stroke (Med PACS) and Recognition Of Stroke in the Emergency Room (ROSIER). On the ROC plane, Med PACS, ROSIER and FAST were closest to the line of an uninformative test (sensitivity + specificity = 1). In contrast, point estimates of LAPSS, OPSS and MASS were concentrated in the upper left corner of the graph, suggesting better performance. We could plot SSROC only for CPSS and LAPSS and, because they reported considerable heterogeneity (CPSS: I2 =97.8%, τ2 = 4.33, LAPSS: I2 =96.8%, τ2 = 4.16), we used the DerSimonian and Laird methodology to generate SSROC. AUC for CPSS was 0.813±SE 0.129 and for LAPSS 0.964±SE 0.028. Conclusion: Robust graphical and statistical comparison of the performance of different prehospital stroke scales would help emergency medical services directors, vascular neurologists, and state health departments involved in prehospital stroke care choose the best screening method.
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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 | 0.062 | 0.208 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.019 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.043 | 0.002 |
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".