Multi-detector computed tomography evaluation ofsuspected acute blunt cervical spine traumain adult patients at King ChulalongkornMemorial Hospital
Bibliographic record
Abstract
Background : According to the American College of Radiology (ACR) appropriateness criteria for imaging of suspected spine trauma, multi-detector computed tomography (MDCT) is the recommended screening imaging procedure in adult patients with high-risk criteria by national emergency x-radiography utilization study (NEXUS) criteria and the Canadian cervical spines rule (CCR). Objectives : To evaluate imaging features of cervical spine fracture and to assess the anappropriateness of performing cervical spine CT according to NEXUS criteria and CCR at the emergency room of King Chulalongkorn Memorial Hospital (KCMH). Design : Retrospective study. Setting : King Chulalongkorn Memorial Hospital. Material and Methods : Our study recruited cervical spine CT images performed at the ER from November 2012 to October 2013 in adult patients suspected of acute cervical spine injury. Patients aged <18 >years, non-acute trauma settings (≥ 72 hours), non-traumatic conditions, penetrating cervical injuries and refer red cases from other hospitals were excluded from this study. Results : Of the 150 cervical spine CT studies analyzed, 15 (10%) were positive for cervical fracture as followings; Clay shoveler fracture, burst fracture, transverse process fracture, Hangman's fracture, dens/odontoid process fracture, hyperextension fracture dislocation and inferior endplate fracture. 137 (91.3%) patients with documented clinical indication for ordering cervical spine CT underwent cervical spine CT properly based on NEXUS criteria or CCR. The remaining 13 (8.7%) patients had no documentation about clinical indication but subsequent imaging showed no cervical spine fracture. Additionally, 51% (76/150) of the patients performed both cervical spine CT and cervical spine radiographs, in which being considered as "inappropriate". Conclusions : Strict application of the ACR appropriateness criteria into practical use could reduce some CT over utilization and dramatically decrease the rate of unnecessary radiographs to clear the cervical spine.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".