Influence of neighborhood household income on early death or urgent hospital readmission
Bibliographic record
Abstract
BACKGROUND: The relationship of socioeconomic status (SES) with hospital readmissions is unclear. METHODS: We used population-based administrative datasets to randomly select 40,827 adult Ontarians discharged from hospital to the community. Patient postal codes were linked to average neighborhood household-income quintiles. The association of this SES measure with 30-day death or urgent readmission was measured after controlling for outcome risk using a validated index, LACE+: length of stay (L), acuity of the admission (A), comorbidity of the patient (measured with the Charlson Comorbidity Index score (C), and emergency-department use (E). RESULTS: Within 1 month of discharge, 2638 (6.5%) people died or were urgently readmitted. Lower neighborhood income was significantly associated with both an increased outcome risk (P < 0.0001) and LACE+ score. After adjusting for LACE+ score, neighborhood income was no longer associated with 30-day death or urgent readmission (P = 0.21). CONCLUSIONS: After accounting for known risk factors, early death or readmission is not more common in people from lower-income neighborhoods. Further study is required to determine if SES is associated with adverse postdischarge outcomes in settings without publicly funded healthcare.
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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 | 0.005 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".