Association between selective serotonin reuptake inhibitor and risk of peripheral artery disease in diabetes mellitus
Bibliographic record
Abstract
ABSTRACT: An increasing number of studies have demonstrated the bidirectional hemostatic effect of selective serotonin reuptake inhibitors (SSRIs) on the risk of cerebrovascular and cardiovascular diseases. However, no previous study has focused on the relationship between SSRI and the risk of peripheral artery disease (PAD) in diabetes mellitus (DM). We sought to evaluate the association between SSRIs and the PAD risk in individuals with DM.We conducted a retrospective, population-based cohort study using data from the Longitudinal Health Insurance Database from 1999 to 2010 in Taiwan. A total of 5049 DM patients were included and divided into 2 groups: DM with SSRI users and DM with SSRI non-users. Propensity score matching and 1-year landmark analysis were used for our study design. Stratified Cox proportional hazard regressions were used to analyze the hazard ratio of the PAD risk in certain subgroups.DM with SSRI users did not affect the PAD risk compared to DM with SSRI non-users. These findings were consistent with all sensitivity analyses (i.e., age, sex, SSRI doses, antithrombotic medication use, and medical and psychiatric comorbidities).In this study, we found that there was no significant difference of PAD risk between DM with SSRI users and DM with SSRI non-users. DM with SSRI user did not affect PAD risk across any SSRI dose, age, sex, antithrombotic medications, and multiple comorbidities in the subgroup analysis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".