Is DPP-4 Use Associated With a Decreased Mortality for COVID-19 Diabetic Patients? A Meta-Analysis
Bibliographic record
Abstract
Abstract Introduction: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Dipeptidyl peptidase-4 (DPP-4) is a multi-expressed glycoprotein that is speculated to be a functional SARS-CoV-2 receptor. Previous studies remain controversial regarding whether DPP-4 use is associated with reduced risk for COVID-19 diabetic patients. Thus, this meta-analysis is performed. Method: A comprehensive literature search on PubMed was conducted to identify all relevant studies published prior to October 2020. This meta-analysis was reported in conformity to the Preferred Reporting Project declared by the Systematic Review and Meta-Analysis (PRISMA). The quality assessment was performed by the Newcastle-Ottawa Scale (NOS). The pooled odds ratio (OR) and 95% confidence intervals (CI) were calculated. Random-effect model or fixed-effect model was used based on heterogeneity. Subgroup analyses were performed based on types of diabetes, geographic locations, study designs, and different sample sizes. Sensitivity analysis and publication bias detection were also performed. All statistical analyses were performed using RevMan and STATA 12.0 statistical software, and all P values were two-tailed, the test level was 0.05. Result: 69 articles were obtained. 5 articles involving 49,989 participants were included. All included studies were considered moderate to high quality. No decreased mortality of COVID-19 diabetic patients was found among DPP-4 users (OR 0.86, 95%CI: 0.22,3.41, P=0.083, I2=81%). In the subgroup analysis, studies in Asia (OR 3.11, 95%CI: 0.78, 12.34, P=0.001, I2=70%) did not found reduced mortality, whereas studies in Europe (OR 0.36, 95%CI: 0.23, 0.56, P<0.00001, I2=0%) were associated with reduced mortality. Based on study designs, the four case-control studies (OR 1.27, 95%CI: 0.27, 5.93, P=0.76, I2=89%) did not find reduced mortality, but one cohort study (OR 0.13, 95%CI: 0.02, 0.84, P=0.03) showed a reduced mortality. The four studies investigating Type 2 Diabetes Mellitus (T2DM) did found reduced mortality (OR 0.74, 95%CI: 0.13, 4.24, P=0.73, I2=90%). For sample size >200, reduced risk of mortality (OR 0.28, 95%CI: 0.07, 1.15, P=0.08, I2=32%) was found, however, for sample ≤200, no statistically significant association (OR 1.44, 95%CI: 0.23, 8.89, P=0.70, I2=93%) was found. Sensitivity analysis by changing models and omitting each study at a time confirm the stability of the result. Begg’s test (z=-0.24, P=1.000) and Egger’s test (t=0.56, P=0.618) did not detect a significant risk of publication bias. Conclusion: The current meta-analysis did not find reduced mortality for COVID-19 diabetic patients who take DPP-4. However, subgroup-analyses found reduced mortality in Europe. More high-quality original studies are needed to further explore the association between DPP-4 use and the mortality risk of COVID-19.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.053 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".