<scp>SGLT</scp>‐2 inhibitors and the risk of hospitalization for <scp>community‐acquired</scp> pneumonia: A population‐based cohort study
Bibliographic record
Abstract
PURPOSE: Sodium-glucose co-transporter 2 inhibitors (SGLT-2i) have been associated with an increased risk of genitourinary tract infections. Through similar biological mechanisms, they may also increase the risk of community-acquired pneumonia. Our objective was to compare the rate of hospitalization for community-acquired pneumonia (HCAP) with SGLT-2i compared to dipeptidyl peptidase-4 inhibitors (DPP-4i) among patients with type 2 diabetes. METHODS: We used the United Kingdom's Clinical Practice Research Datalink Gold, linked to hospitalization data, to construct a cohort of patients with type 2 diabetes. Using a time-dependent Cox proportional hazards model, we estimated the adjusted hazard ratio (HR) for HCAP with current use of SGLT-2i versus DPP-4i. RESULTS: Among 29 896 patients, 705 HCAPs occurred over a mean follow-up of 1.7 years (SD: 1.2). Incidence rates for SGLT-2i and DPP-4i users were 6.2 (95% confidence interval [CI]: 3.7, 10.2) and 17.8 (95% CI: 15.3, 20.7) per 1000 person-years, respectively. Current use of SGLT-2i was associated with a decreased risk of HCAP compared to current use of DPP-4i (adjusted HR: 0.48, 95% CI: 0.28, 0.82). However, a comparison of SGLT-2i versus glucagon-like peptide-1 receptor agonists (GLP-1 RA) found no difference in risk of HCAP (adjusted HR: 0.94, 95% CI: 0.44, 1.89). CONCLUSIONS: SGLT-2i are associated with a decreased rate of HCAP compared to DPP-4i, but not when compared to GLP-1 RA, among patients with type 2 diabetes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".