Echocardiographic Parameters and Outcomes in Methamphetamine-Associated Heart Failure: A Propensity Score-Weighted Analysis
Bibliographic record
Abstract
Background: Methamphetamines are a common cause of systolic heart failure (HF). There are limited data on the prognosis associated with hospitalizations for decompensated HF in the setting of methamphetamine use. We aimed to evaluate patient characteristics and outcomes among patients admitted with decompensated HF who had positive drug screens for amphetamines as well as to determine whether any parameters from transthoracic echocardiogram (TTE) can predict outcomes in this population. Methods: This was a retrospective cohort study of consecutive adult patients admitted to the Loma Linda Medical Center who had an active hospital problem of acute on chronic systolic (or systolic and diastolic) HF from 2013 to 2018. Electronic medical records were mined for relevant patient data. Methamphetamine-associated heart failure (MethHF) group was defined as those with an admission urine drug screen (UDS) that was positive for methamphetamines, whereas non-MethHF was defined by patients with negative methamphetamine on UDS or UDS was not done on physician's discretion. The primary outcomes of the study were 30-day composite outcome (defined as combined all-cause readmission and all-cause mortality), 365-day all-cause mortality, and length of stay (LOS). Propensity score weighting for these outcomes was performed using demographics, laboratory and clinical variables, and left ventricular ejection fraction (LVEF) as covariates. TTE parameters from presentation were also evaluated to determine if any had prognostic implications. Results: A total of 1,655 patients were included (101 patients with positive urine methamphetamine and 1,554 patients without). Patients with MethHF were younger, more likely to be male, had fewer comorbidities, had lower LVEF, and were more likely to have right ventricular systolic dysfunction. In propensity-weighted analyses, there were no significant differences in LOS, 30-day composite outcome, or 365-day mortality between the MethHF and non-MethHF group in (P > 0.05 for all). Presence of at least moderate tricuspid valve regurgitation (TR) was the only TTE predictor of 30-day composite outcome (odds ratio (OR) = 4.67, 95% confidence interval (CI): 1.5 - 14.50, P < 0.01) and 365-day mortality (OR = 4.67, 95% CI: 1.5 - 14.50, P < 0.01) in the MethHF group. Conclusion: Patients with MethHF admitted for decompensated HF had similar outcomes compared to non-MethHF after adjusting for baseline characteristics. TR is the only TTE value to predict outcomes in this population.
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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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| 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".