Quantifying the Risk of Infectious Diseases for People With Diabetes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: In vitro evidence shows that immune function is compromised in people with diabetes. Although certain rare infections are more common and infection-related mortality is higher, the risk of acquiring an infectious disease for diabetic patients has never been quantified. RESEARCH DESIGN AND METHODS: A retrospective cohort study using administrative data compared all people with diabetes in Ontario, Canada, on 1 April 1999 to matched nondiabetic people (n = 513,749 in each group). The risk ratios of having an infectious disease and of death attributable to infectious disease between those with and without diabetes were calculated. Secondary analysis individually examined common infectious diseases. The study was repeated using a second pair of cohorts defined in 1996 to confirm stability of the estimates. RESULTS: Nearly half of all people with diabetes had at least one hospitalization or physician claim for an infectious disease in each cohort year. The risk ratio for diabetic versus nondiabetic people was 1.21 (99% CI 1.20-1.22) in both cohort years. The risk ratio for infectious disease-related hospitalization was up to 2.17 (99% CI 2.10-2.23). The risk ratio for death attributable to infection was up to 1.92 (1.79-2.05). Many individual infections were more common in people with diabetes, especially serious bacterial infections. CONCLUSIONS: Diabetes confers an increased risk of developing and dying from an infectious disease, corroborating both in vitro evidence and commonly held clinical belief. In addition to microvascular and macrovascular sequelae, clinicians should consider infection a complication of diabetes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it