Abstract 13529: Outcomes After Emergency Department Visits for Dyspnea: Population-Based Interrupted Time-Series Analysis of Implementation of B-Type Natriuretic Peptide Assays
Bibliographic record
Abstract
Introduction: The population-level impact of hospital-based natriuretic peptide (NP) implementation in a universal health care system is unclear. We examined temporal associations between introduction of NP testing in-hospital with outcomes after emergency department (ED) visits for dyspnea. Hypothesis: Implementation of NP testing is associated with improved outcomes for ED patients seeking care for dyspnea. Methods: Administrative databases were linked to identify adults ≥40 years of age with a first ED visit for dyspnea between 2014 and 2019 at hospitals introducing onsite NP testing between 2016 and 2018 in Ontario, Canada. We calculated quarterly rates of 1-year age- and sex-standardized mortality and readmission (all-cause, cardiovascular, heart failure [HF]), restricted to 2 years before and after NP introduction to minimize temporal advances in treatment. We conducted an interrupted time series analysis using linear regression and Newey-West autocorrelation adjusted standard errors to quantify rate of change in outcomes before and after NP introduction. Time zero at each hospital was set at 2 years prior to the introduction of NP tests for each hospital (point of interruption). Results: We studied 20,294 patients (median age 69 years, 52% female) before and 21,857 patients (median age 68 years, 53% female) after NP introduction across 16 hospitals. The cohort before NP introduction had a higher prevalence of prior HF and chronic obstructive pulmonary disease (P<0.01). Rates of all outcomes were stable prior to NP introduction. Following NP introduction, there were significant declines in rates of all-cause mortality (-1.5/100 persons per year), all-cause readmission (-3.6/100 persons per year), cardiovascular readmission (-1.4/100 persons per year) and HF readmission (-0.8/100 persons per year; Figure). Conclusions: Introduction of hospital-based NP tests was associated with decreasing rates of adverse outcomes after ED visits for dyspnea.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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".