An inquiry into the treatment of sepsis using plasma exchange therapy: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Sepsis is a potentially lethal condition that occurs when the body's response to infection damages tissue and organs. The production of inflammatory mediators typically assists in defending the body against infection; however, an overreaction to inflammation can cause coagulation problems, vascular endothelial damage, and organ hypoperfusion. Blood purification methods, such as plasmapheresis, can effectively remove inflammatory mediators from plasma. The purpose of this meta‐analysis was to explore the efficacy of plasma exchange for sepsis treatment as noted in recent studies. The authors searched the Pubmed (Medline), Cochrane Central Register of Controlled Trials (The Cochrane Library), Embase (Ovid), and Scopus databases and included controlled clinical studies that compared plasmapheresis or plasma filtration with conventional treatment in patients with severe sepsis. The Newcastle–Ottawa Scale literature quality assessment tool was used to assess the risk of bias. The primary study outcome was all‐cause mortality. The random effects model was adopted for conducting the meta‐analysis. Among the 1013 records found, the study included 5 trials, all of which carried a low risk of bias. The use of plasmapheresis was associated with a longer stay in the intensive care unit (odds ratio [OR], 0.85, 95% confidence interval [CI], 0.39–1.32, heterogeneity [I2] = 0%), a significant reduction in all‐cause mortality (OR, 0.54, 95% CI, 0.33–0.89, I2 = 70%), and reduced mortality (OR, 0.29, 95% CI, 0.13–0.67, I2 = 0%) in adults; the results for children differed from this (OR, 0.79, 95% CI, 0.36–1.72, I2 = 89%). Four trials reported no adverse events; one trial reported an adverse event related to plasma exchange, including an instance of hypotension in one patient. Plasmapheresis appeared to be an effective treatment for patients suffering from sepsis. A large number of additional randomised controlled trials are needed to confirm this finding.
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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 | 0.022 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.042 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".