A comparison of Canadian Head CT rule and New Orleans criteria in mild TBI (Traumatic Brain Injury) patients in a Tertiary Hospital in Karachi, Pakistan.
Bibliographic record
Abstract
Objectives: The aim of our study is to compare the Canadian Head CT rule to New Orleans Criteria, to find a more efficient guideline in predicting the important CT findings in mild Traumatic Brain Injury (TBI) cases. Study Design: Observational study. Setting: Tertiary Health Care Facility in Karachi, Pakistan. Period: 6 months from June 2017 to December 2017. Material & Methods: We divided a sample of 150 mild TBI patients into two groups of Glasgow coma scale (GCS) scores of 13-14 and GCS score of 15. Then using a separate scoring system for both the CCHR and NOC, we evaluated their accuracy and efficiency in predicting mild TBI through a total of 7 major clinical items. Specificity and sensitivity were calculated to compare both the scoring systems and results were compared through univariate and multivariate analysis. A p value of less than 0.05 was considered to be statistically significant. Results: We analyzed the relation between clinical items and important CT findings and found that the CCHR, through multivariate analysis, was more closely associated with important CT findings. We also found that the factors of age, and the Glasgow comma scale score were also strong indicators of important CT findings regardless of which guideline was used. Conclusion: In our study, we found CCHR to be a stronger predictor of important CT findings than the NOC. We found that CCHR performed significantly higher than the NOC.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".