In-Hospital and Long-Term Outcomes of Beta-Blocker Treatment in Cocaine Users: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Although β-blocker treatment is generally contraindicated in patients presenting with acute cocaine intoxication due to concern for unopposed α-receptor stimulation, some studies have reported that β-blocker treatment did not increase adverse events in these patients. As this treatment is still controversial, we performed a meta-analysis of observational studies on this topic. METHODS: By searching three electronic databases (MEDLINE, EMBASE, and the Cochrane Library) from their inception to June 11, 2018, we identified eight observational studies with 2,048 patients who presented to hospital with cocaine-associated chest pain or after recent cocaine use. Outcomes of interest were myocardial necrosis or infarction (MI) and death during hospital stay or follow-up. Pooled relative risks (RRs) with 95% confidence intervals (CIs) were calculated by using a random-effects meta-analysis based on the DerSimonian-Laird method. RESULTS: Among patients presenting with cocaine-associated chest pain or recent cocaine use, there was no significant difference in in-hospital all-cause mortality (RR, 0.59; 95% CI, 0.24 - 1.47) and MI (RR, 1.24; 95% CI, 0.74 - 2.06) between patients who did and did not receive β-blocker treatment during their hospital stay. During long-term follow-up (mean 2.6 years), there was no significant difference in all-cause mortality (RR, 0.79; 95% CI, 0.44 - 1.41) and MI (RR, 0.96; 95% CI, 0.40 - 2.33) between the two groups. CONCLUSIONS: These results suggest that β-blocker treatment in patients presenting with cocaine intoxication may not be as harmful as originally believed. Further clinical studies are needed to investigate this topic.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.040 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".