Real-world evidence on the safety and effectiveness of integrative Korean medicine for older patients post-traffic accident: A retrospective observational study
Bibliographic record
Abstract
With the rapid aging of its population, Korea is becoming a super-aged society, and the proportion of older individuals among traffic accident patients continues to rise. Older adults often exhibit delayed recovery after trauma, multimorbidity, and polypharmacy, necessitating a tailored treatment approach. Integrative Korean medicine (IKM) treatment may serve as a suitable alternative, and its effectiveness and safety in older adults involved in traffic accidents warrant further evaluation. This retrospective chart review assessed the therapeutic efficacy and safety of IKM in hospitalized traffic accident patients aged 65 years or older, using electronic medical records from 4 branches of Korean medicine hospitals between 2021 and 2023. A total of 1788 patients were included in the analysis. Descriptive analyses were performed to summarize demographic and clinical characteristics, and within-group comparisons between admission and discharge were conducted for primary outcomes, including pain, quality of life, functional disability, and range of motion. Safety was assessed based on adverse events (AEs). A total of 1788 older inpatients with traffic-related injuries showed significant improvements (P < .001) in pain numeric rating scale (NRS), quality of life (European quality of life - 5 dimensions), functional disability indicators (neck disability index, Oswestry disability index, shoulder pain and disability index, Western Ontario and McMaster Universities osteoarthritis index), and range of motion after receiving IKM treatment. Specifically, the mean neck NRS score showed a reduction from 5.17 ± 0.93 at admission to 3.49 ± 1.24 at discharge, and the mean lower back NRS score improved from 5.19 ± 0.91 to 3.55 ± 1.21. Most AEs were mild, and there were no reports of serious AEs. IKM may be a viable and safe therapeutic approach to improving pain, function, and quality of life in older patients hospitalized after traffic accidents.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| 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) | 0.002 | 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".