Is there a role for modified probiotics as beneficial microbes: a systematic review of the literature
Bibliographic record
Abstract
Our objective was to conduct a systematic review and meta-analysis for the use of modified (heat-killed or sonicated) probiotics for the efficacy and safety to prevent and treat various diseases. Recent clinical research has focused on living strains of probiotics, but use in high-risk patients and potential adverse reactions including bacteremia has focused interest on alternatives to the use of live probiotics. We searched MEDLINE/PubMed, Embase, Cochrane Central Register of Controlled Trials, CINAHL, Alt Health Watch, Web of Science, Scopus, PubMed, from inception to February 14, 2017 for randomised controlled trials involving modified probiotic strains. The primary outcome was efficacy to prevent or treat disease and the secondary outcome was incidence of adverse events. A total of 40 trials were included (n=3,913): 14 trials (15 arms with modified probiotics and 20 control arms) for the prevention of diseases and 26 trials (29 arms with modified probiotics and 32 control arms) for treatment of various diseases. Modified microbes were compared to either placebo (44%), or the same living probiotic strain (39%) or to only standard therapies (17%). Modified microbes were not significantly more or less effective than the living probiotic in 86% of the preventive trials and 69% of the treatment trials. Modified probiotic strains were significantly more effective in 15% of the treatment trials. Incidence rates of adverse events were similar for modified and living probiotics and other control groups, but many trials did not collect adequate safety data. Although several types of modified probiotics showed significant efficacy over living strains of probiotics, firm conclusions could not be reached due to the limited number of trials using the same type of modified microbe (strain, daily dose and duration) for a specific disease indication. Further research may illuminate other strains of modified probiotics that may have potential as clinical biotherapeutics.
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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 | 0.034 | 0.091 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.020 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".