Blood pressure and adverse cardiovascular outcomes in older people with type 2 diabetes and chronic kidney disease: Findings based on the Clinical Practice Research Datalink databases in England
Bibliographic record
Abstract
AIMS: Managing blood pressure (BP) in older adults with type 2 diabetes (T2D) and chronic kidney disease (CKD) remains controversial, particularly regarding optimal targets and the impact of inadequate monitoring. Using Clinical Practice Research Datalink (CPRD) data, this study assessed associations between baseline systolic and diastolic BP (SBP and DBP) and the risk of major adverse cardiovascular events (MACE) and mortality in adults aged ≥65 with both T2D and CKD, the impact of missing BP records (proxy for inadequate monitoring), and sex-based differences in these relationships. MATERIALS AND METHODS: A retrospective cohort study was conducted using CPRD data. The primary outcome was MACE (nonfatal stroke, myocardial infarction, and cardiovascular death); the secondary outcome was all-cause mortality. Baseline BP was modelled continuously and categorised as high (≥140/90 mmHg), normal (<140/90 mmHg), or missing (no BP record within 2 years prior to diagnosis). Flexible parametric competing risks models estimated adjusted 5-year outcome risks. RESULTS: MACE analysis included 160 764 individuals; mortality analysis included 181 307. The 5-year MACE risk was 14.1% for normal, 13.8% for high, and 19.6% for missing SBP. For all-cause mortality, risks were 20.6% (normal), 19.4% (high), and 34.0% (missing). SBP was a stronger risk indicator than DBP for both outcomes. Lower SBP (120 mmHg) was moderately associated with increased MACE and mortality; higher DBP (90 mmHg) was linked to increased mortality. Men had higher MACE and mortality risks than women. CONCLUSIONS: In older adults with T2D and CKD, lower SBP and DBP were moderately associated with a higher risk of MACE and mortality, but the strongest indicator of adverse outcomes was the absence of regular blood pressure monitoring.
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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 | 0.008 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".