Overuse of computed tomography for mild head injury: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Computed tomography (CT) scan is a common imaging technique used to evaluate the severity of a head injury. The overuse of diagnostic interventions in the health system is a growing concern worldwide. Objectives: The aim of this systematic review is to investigate the rate of CT scan overuse in cases of mild head injury. METHODS: Eligibility criteria: We encompassed observational studies-either designed as cohort, case-control, or cross-sectional investigations-that reported on CT scan overuse rates for mild head injuries. Studies had to be published in peer-reviewed, English-language sources and provide full content access Information sources: Web of Sciences, Scopus, Medline via PubMed, the Cochrane Library and Embase were searched from inception until April 1, 2023. Studies were included if reporting the overuse of CT scans for mild head injuries using validated criteria. Risk of bias: We used the Risk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) tool to evaluate the risk bias assessment of included studies. Two independent reviewers evaluated the eligibility of studies, extracted data, and assessed study quality by using the Newcastle-Ottawa Scale. Synthesis of results: Overuse estimates were calculated using a random-effects model. Subgroup analyses were performed to investigate any sources of heterogeneity. Point rate of overuse of CT scans for mild head injuries was the main outcome measured as percentage point estimates with corresponding 95% CIs. RESULTS: Included studies: Of the 913 potentially relevant studies identified, eight studies were selected for the final analysis. Synthesis of results: The pooled rate of CT scan overuse in patients with mild head injury was found to be 27% [95% CI: 16-43; I2 = 99%]. The rate of CT scan overuse in mild head injury cases varied depending on the criteria used. The rate of CT scan overuse was 37% [95% CI: 32-42; I2 = 0%] with the Glasgow Coma Scale (GCS), 30% [95% CI: 16-49; I2 = 99%] with the Canadian computed tomography head rule, and 10% [95% CI: 8-14; I2 = 0%] with the Pediatric Emergency Care Applied Research Network criterion (PERCAN). Based on subgroup analyses, the rate of CT scan overuse in mild head injury cases was observed to be 30% with the Canadian computed tomography head rule criterion, 43% with the National Institute for Health and Clinical Excellence criterion, and 18% with the New Orleans criterion. CONCLUSION: Limitations of evidence: The restricted number of included studies may impact generalizability. High heterogeneity was observed, leading to subgroup analyses based on age, assessment criteria, and study region. Absent data on overuse causes hinders drawing conclusions on contributing factors. Furthermore, this study solely addressed overuse rates, not associated harm or benefits. Interpretation: The overuse of CT scans in mild head injury patients is concerning, as it can result in unnecessary radiation exposure and higher healthcare costs. Clinicians and policymakers should prioritize the implementation of guidelines to reduce unnecessary radiation exposure, healthcare costs, and potential harm to patients. TRIAL REGISTRATION: The study protocol of this review was registered in PROSPERO under the identification code CRD42023416080. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023416080.
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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 | 0.018 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.029 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".