Pharmacogenetics of Type 2 diabetes mellitus: A Systematic Review Protocol (Preprint)
Bibliographic record
Abstract
UNSTRUCTURED The objective of this systematic review is to determine the effect of genetic variants that associate with antidiabetic medications and their efficacy and toxicity in T2DM patients. The understanding may allow interventions for improving management of T2DM and later systematically evaluated in more in-depth studies. We will have performed a comprehensive search using PubMed, Scopus, EMBASE, Web of Sciences and Cochrane database from 1990 to 2018. Relevant journals and references of all included studies will be hand searched to find the additional studied. Eligible studies such as pharmacogenetics studies in terms of drug response and toxicity in the type 2 diabetes patients and performed just on human will be included. Data extraction and quality assessment will be carried out by two independent reviewers and disagreements will be resolved through third expert reviewer. Risk of bias will be assessed with the Cochrane Risk of Bias tool for randomized studies and Newcastle-Ottawa Scale (NOS) for observational Studies. Narrative synthesis will be conducted by the combination of key findings. The results of this study will be submitted to a peer-reviewed journal for publication and also presented at PROSPERO. We expect this review will provide highly relevant information for clinicians, pharmaceutical industry that will benefit from the summary of the best available data regarding the efficacy of antidiabetic medication in the aspect of pharmacogenetics. PROSPERO Registration number (CRD42018104843)
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 | 0.037 | 0.051 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.103 | 0.012 |
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".