Hospitalization and Adverse Events in Older People Population-based cohort study
Bibliographic record
Abstract
OBJECTIVEdLittle is known about the prognostic impact of hypoglycemia associated with hospitalization. We hypothesized that hospitalized hypoglycemia would be associated with in-creased long-term morbidity and mortality, irrespective of diabetes status. RESEARCH DESIGN AND METHODSdWe undertook a cohort study using linked administrative health care and laboratory databases in Alberta, Canada. From 1 January 2004 to 31March 2009, we included all outpatients 66 years of age and older who had at least one serum creatinine and one A1Cmeasured. To examine the independent association between hospitalized hypoglycemia and all-cause mortality, we used time-varying Cox proportional hazards (adjusted hazard ratio [aHR]), and for all-cause hospitalizations, we used Poisson regression (adjusted incidence rate ratio [aIRR]). RESULTSdThe cohort included 85,810 patients: mean age 75 years, 51 % female, and 50% had diabetes defined by administrative data. Overall, 440 patients (0.5%) had severe hypogly-cemia associated with hospitalization and most (93%) had diabetes. During 4 years of follow-up, 16,320 (19%) patients died. Hospitalized hypoglycemia was independently associated with in-creased mortality (60 vs. 19 % mortality for no hypoglycemia; aHR 2.55 [95 % CI 2.25–2.88]),
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".