Time Trends, Predictors, and Outcome of Emergency Department Use for Gout: A Nationwide US Study
Bibliographic record
Abstract
OBJECTIVE: To assess gout-related emergency department (ED) use/charges and discharge disposition. METHODS: We used the US National ED Sample (NEDS) data to examine the time trends in total ED visits and charges and ED-related hospitalizations with gout as the primary diagnosis. We assessed multivariable-adjusted predictors of ED charges and hospitalization for gout-related visits using the 2012 NEDS data. RESULTS: There were 180,789, 201,044, and 205,152 ED visits in 2009, 2010, and 2012 with gout as the primary diagnosis, with total ED charges of $195 million, $239 million, and $287 million, respectively; these accounted for 0.14%-0.16% of all ED visits. Mean/median 2012 ED charges/visit were $1398/$956. Of all gout-related ED visits, 7.7% were admitted to the hospital in 2012. Mean/median length of hospital stay was 3.9/2.6 days and mean/median inpatient charge/admission with gout as the primary diagnosis was $22,066/$15,912 in 2012. In multivariable-adjusted analyses, these factors were associated with higher ED charges: older age, female sex, highest income quartile, being uninsured, metropolitan residence, Western United States hospital location, heart disease, renal failure, heart failure, hypertension (HTN), diabetes, osteoarthritis (OA), and chronic obstructive pulmonary disease (COPD). These factors were associated with higher odds of hospitalization: older age, Northeast location, metropolitan teaching hospital, higher income quartile, heart disease, renal failure, heart failure, hyperlipidemia, HTN, diabetes, COPD, and OA, whereas self-pay insurance status was associated with lower odds of hospitalization, following an ED visit for gout. CONCLUSION: Absolute ED use and charges for gout increased over time, but relative use remained stable. Modifiable comorbidity factors associated with higher gout-related use should be targeted to reduce morbidity and healthcare use.
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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 | 0.001 | 0.001 |
| 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".