Association between tumor necrosis factor-α promoter −308 A/G polymorphism and susceptibility to sepsis and sepsis mortality: A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: The tumor necrosis factor (TNF)-alpha promoter -308 A/G polymorphism has been reported to be associated with sepsis with inconsistent results. We conducted a systematic review and meta-analysis to determine whether the TNF-alpha -308 A/G polymorphism TNF2 (G/A or A/A) confers susceptibility to sepsis or is associated with increased risk of death from sepsis. DATA SOURCES: We performed an electronic search of OVID MEDLINE from 1950 to June 2008 and EMBASE from 1980 to June 2008. STUDY SELECTION: From 1935 reviewed study articles, 25 were included based on predefined inclusion criteria. DATA EXTRACTION: Two reviewers independently extracted data onto standardized forms. DATA SYNTHESIS: An association between development of sepsis and the TNF2 genotype was found in the overall population (odds ratio, 2.15; 95% confidence interval, 1.45-3.19; p < .01). Stratification by ethnicity indicated that the contribution to this observation may be stronger among the Asian population (odds ratio, 3.16; 95% confidence interval, 1.92 to 5.20; p < .01) compared with other ethnicities. There was no association between the TNF2 genotype and mortality from sepsis (odds ratio, 1.48; 95% confidence interval, 0.81 to 2.70; p = .20). However, when stratified for ethnicity, there may be an increased risk for fatal outcomes among Asians (odds ratio, 10.75; 95% confidence interval, 2.98 to 38.78; p < .01). CONCLUSIONS: Our systematic review and meta-analysis demonstrates that the TNF2 polymorphism is associated with sepsis. However, TNF2 is not associated with sepsis mortality.
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 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 | 0.011 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.023 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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 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".