Efficacy and safety of blood purification in the treatment of autoimmune encephalitis: a meta-analysis
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Bibliographic record
Abstract
Objective: To systematically evaluate the efficacy and safety of blood purification in the treatment of autoimmune encephalitis (AE).Methods: Databases including PubMed, Embase, and Cochrane Library were systematically searched.Prospective and retrospective cohort studies were included.Data on patients' baseline characteristics, interventions, and outcomes were extracted.The Newcastle-Ottawa Scale (NOS) was used to assess the quality of included studies.Meta-analysis was performed using RevMan 5.4 software.Results: Fifteen studies (531 patients) were included; NOS scores of 7-9 indicated high quality.Efficacy analysis showed that in studies with control groups, blood purification significantly increased the likelihood of clinical improvement (Odds Ratio (OR)=5.61,95% Confidence Interval (CI) [2.72, 11.56], P<0.00001).In studies without control groups, most efficacy indicators (e.g., clinical improvement, modified Rankin Scale (mRS) score improvement) showed statistical significance.Safety analysis revealed that the risk of therapeutic plasma exchange (TPE)-related adverse events was significantly increased (Risk Difference (RD)=0.46,95% CI [0.40, 0.52], P<0.00001).The risks of complications and seizures were also elevated (RD=0.57and 0.74, respectively, both P<0.05).The risk of total adverse reactions per cycle was increased (RD=0.09,95% CI [0.04, 0.14], P=0.0004).The 1-year relapse risk was significantly increased (RD=0.07,95% CI [0.02, 0.11], P=0.004), while there was no significant difference in mortality (P>0.05).Publication bias was assessed via funnel plots and Egger's test, with no evidence of bias, and sensitivity analysis results were stable.Conclusion: Blood purification can significantly improve clinical outcomes in AE patients, but it is associated with higher risks of adverse events and relapse.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it