Risk of Hospitalization for Community Acquired Pneumonia with Renin-Angiotensin Blockade in Elderly Patients: A Population-Based Study
Bibliographic record
Abstract
OBJECTIVE: To characterize the 90-day risk of hospitalization with pneumonia among patients treated with different anti-hypertensive drug classes. DESIGN: Population based cohort study using five linked databases. PARTICIPANTS: Individuals over the age of 65 who filled a new outpatient prescription for one of four anti-hypertensive medications: ACE inhibitors (n = 86 775), ARBs (n = 33,953), calcium channel blockers (CCB, n = 34,240), beta blockers (BB, n = 35,331) and thiazide diuretics (n = 64 186). PRIMARY OUTCOME: Hospitalization with pneumonia within 90 days of a qualifying prescription. We adjusted for ten a priori selected covariates, including age, sex, diabetes and number of visits to a family doctor. RESULTS: Baseline characteristics of the groups were relatively well matched, except for age, sex, diabetes and frequency of family doctor visits. 128 of the 86 775 patients (0.15%) initiated on an ACE inhibitor and 43 of the 33953 patients (0.13%) of patients initiated on an ARB were hospitalized with pneumonia in the subsequent 90 days. 135 of 64 186 patients (0.21%) initiated on a thiazide, 112 of 35 331 patients (.32%) initiated on a BB, and 89 of 34 240 (0.26%) patients initiated on a CCB achieved the primary outcome. Compared to calcium channel blockers, ACE inhibitors (adjusted OR 0.61, 95% CI 0.46 to 0.81) and ARBs (adjusted OR 0.52, 95% CI 0.36 to 0.76) were associated with a lower risk of pneumonia. No benefit was seen with thiazides (adjusted OR 0.87, 95% CI 0.66 to 1.14) or beta blockers (adjusted OR 1.21, 95% CI 0.91 to 1.60). CONCLUSION: Initiating medications that block the renin angiotensin system, compared to other anti-hypertensive medications, is associated with a small absolute reduction in the 90 day risk of hospitalization with pneumonia.
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".