Proteflazid®: outcome analysis of clinical trials studying the impact of human herpesvirus infection on some cellular immunity indicators and gestation course in women.
Bibliographic record
Abstract
An outcome analysis of the clinical trials evaluating the clinical and immunological efficacy of the drug Proteflazid® in the treatment of diseases associated with herpesvirus infection in pregnant women is presented. AIM: Objective of the study was to evaluate the effects of Proteflazid® on the cellular component of the immune system and gestation course in women with HHV infection by using meta-analysis and statistical analysis (based on Student's t-test) of the clinical findings. MATERIALS AND METHODS: The analysis comprises 5 scientific sources with the results of controlled clinical trials involving 234 pregnant women during the period from 2003 to 2012. RESULTS: The obtained data prove the efficacy of the preparation Proteflazid ® in treating pregnant women with HHV infection. Administration of the drug Proteflazid® in the treatment of herpesvirus infection in pregnant women contributes to the cellular immunity normalization, which in turn has a positive effect on the course and outcome of pregnancy. CONCLUSIONS: Therapy with the drug Proteflazid® is etiologically and pathogenetically substantiated, contributes to the normalization of cellular immunity parameters, which, in turn, has a positive effect on the course and outcome of pregnancy.
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.012 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".