원저 : 성별의 차이가 중증도 및 중증 외상성 뇌손상의 예후에 미치는 영향 -메타분석을 이용한 체계적 문헌고찰-
Bibliographic record
Abstract
Purpose: Case-control and cohort studies have reported inconsistent findings for the association between gender and mortality from a traumatic brain injury. We investigated the effect and association of gender on moderate to severe traumatic brain injury using meta-analysis. Methods: We searched electronic health care databases including MEDLINE (Pubmed), the Cochrane Library, CINAHL, and Koreamed (January 2001 to December 2009) in August 2010. The keywords searched included traumatic brain injury or traumatic head injury, gender, and mortality. Two independent investigators selected and reviewed articles according to predefined inclusion and exclusion criteria. The quality of selected articles was evaluated by applying the Newcastle Ottawa scale. Data were abstracted by predetermined criteria. Odds ratios were calculated and combined using fixed and random effect models. Results: Of 130 articles, four case-control studies and three cohort studies were included in the final analysis. In total, 89,335 patients were included(26,287 females and 63,048 males). Compared with the mortality of male patients, the combined odds ratio for the mortality of female patients was 1.074(95% confidence interval [CI], 1.027~1.124) in a fixed effect model, and 1.319(95% CI, 1.104~1.576) in a random effects model, respectively. The heterogeneity of all participants was severe, so the results were discarded and a subgroup analysis was conducted. The total number of participants was divided into premenopausal and postmenopausal groups by the menopausal age defined in each article. The pooled odds ratio of the premenopausal group was 1.014(95% CI, 0.949~1.083) in the fixed effect model and that of the postmenopausal group was 1.237(95% CI, 0.895~1.712) in the random effects model. The pooled estimate of the random effect model was adopted because of the severe heterogeneity of the postmenopausal group. Conclusion: We found no distinct effect of gender on moderate to severe traumatic brain injury. Large-scaled prospective studies based on female hormone levels are needed.
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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 | 0.019 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".