Comparision of NexusII,New Orleans and Canada cranial CT rules in Head Trauma Patients: A retrospective study.
Bibliographic record
Abstract
The imaging method of choice to precisely diagnose intracranial injuries is a head CT scan.During recent years the usage of CT in EDs has increased greater than before.Although there is a consensus to scan patients with moderate or severe head trauma urgently, an ongoing debate continues as to which patients with mild head injury should be scanned.In our study we aimed to compare the clinical effects of CCHR, NOC, and NEXUS-II rules to identify the clinically significant brain injuries.Our research was performed at a single Training and Research hospital with 200.000 annual ED visits.Acute mild head injury was defined as a closed head injury by blunt force within 24 hours, with a Glasgow Coma Scale (GCS) score of 13 to 15.All patients who visited our ER with minor head trauma were enrolled in study prospectively, and all CCHR, NOC, and NEXUS rules were evaluated separately for each patient.The determined outcome lesions were subarachnoid haemorrhage, subdural hematoma, contusion, epidural hematoma, skull fracture, intraparenchymal haemorrhage, and cerebral oedema.The sensitivity, specificity, and predictive values with 95% confidence intervals (CIs) for the performance of each rule for CT scan and each criterion of rules and all symptoms predicted to be caused by head trauma were calculated.P < 0.05 was considered statistically significant.A total of 140 patients were included in the study.The mean age of the patients included in the study was 55.59 ± 23.258 (median 57.00)years .Of all patients, 62.1% (n: 87) were male and 37.9% (n: 53) were female.In terms of gender, it was found that men had more minor head trauma.The mean age of male patients was 49.90 and 64.94 for female patients.Among whole study population, 43.57% (n = 61) of the patients were 65 years and older.Sensitivity, specificity, and positive predictive value negative predictive value of NOC were 87.5%, 6.57%, 44.09% and 38.46%, respectively.The sensitivity of CCHR rule was 82.81%, its specificity was 32.8%, its positive predictive value was 50.96%, and its negative predictive value was 69.4%.The sensitivity of NEXUS II rule was 93.75%, specificity was 3.94%, positive predictive value was 45.11%, and the negative predictive value was 42.85%.There are different interpretations in the literature about which rule should be used to decide performing a CT scan in patients with minor head trauma.Additional studies may be demonstrated by focusing specifically on the sensitivity and specificity of each criterion separately.Additionally, more studies should be performed especially in geriatric population to specify a criterion for each rule separately.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| 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".