Influence of prestroke glycemic status on outcomes by age in patients with acute ischemic stroke and diabetes mellitus
Bibliographic record
Abstract
BACKGROUND: This study aimed to explore the association between admission HbA1c and the risk of 1-year vascular outcomes stratified by age group in patients with acute ischemic stroke (AIS) and diabetes mellitus (DM). METHODS: This study analyzed prospective multicenter data from patients with AIS and DM. Admission HbA1C were categorized as:≤6.0%, 6.1%-7.0%, 7.1%-8.0%, and >8.0%. Age was analyzed in categories:≤55 years, 56-65 years, 66-75 years, 76-85 years, and >85 years. The primary outcome was 1-year composite of stroke, MI, and all-cause mortality. The modifying effect of age on the relationships between HbA1c and 1-year primary outcome was explored by Cox proportional hazards model. RESULTS: A total of 16,077 patients (age 69.0 ± 12.4 years; 59.4% males) were analyzed in this study. Among patients ≤55 years, the hazard ratio (HR) of the 1-year primary outcomes increased with an HbA1C > 8.0% (adjusted HR 1.39[1.13-1.70]). For patients aged 56-65 and 66-75, the highest HRs were observed for an HbA1c of 7.1-8.0% (aHRs; 1.21 [1.01-1.46] and 1.22 [1.05-1.41], respectively). In the 85+ age group, the highest HR occurred for HbA1c ≤ 6.0% (aHR 1.47 [0.98-2.19]). The HbA1c 8.0% showed evident age-dependent heterogeneity in the post hoc HR plots. CONCLUSION: Our study revealed that in patients with AIS and diabetes under 55, higher admission hbA1c was associated with an increased risk of the 1-year primary outcome, while in patients aged over 85, lower HbA1c value (≤6.0%) may be associated with an increased risk of vascular events. The results of our study suggest the age-stratified, heterogeneous associations between admission HbA1c and 1-year vascular outcomes in patients with AIS and diabetes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".