Abstract 16282: Telemedicine Application in the Care of Acute Myocardial Infarction Patients: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: Telemedicine strategies have the potential to increase healthcare professionals’ adherence to the therapeutic measures established for acute myocardial infarction (MI), to improve MI care. However, the real impact of this intervention in clinical outcomes is still unknown or poorly documented. Our aim is to conduct a systematic review and meta-analysis of studies assessing the impact of telemedicine interventions combined with usual care compared to usual care alone on AMI mortality. Methods: Electronic databases MEDLINE, Cochrane Central Register of Controlled Trials, LILACS, BDENF, IBECs, Web of Science, Scopus and Google Scholar were searched to identify relevant studies published from Jan/2004 to May/2015. The search was supplemented by references from the selected articles. Study search and selection were performed by independent reviewers. Random effects model was applied to estimate the pooled results. Methodological quality of non-randomized studies was assessed by Newcastle Ottawa scale (NOS). Results: Of the 5.407 articles retrieved, 16 studies (8,945 patients) were included: 8 in Europe, 5 in North America, 2 in South America and 1 in Asia. No randomized controlled trial was identified; 13 studies were nonrandomized controlled, 3 historically controlled, and 1 quasi-experimental. Fourteen studies were in ST elevation MI patients, and in 14 studies the intervention involved prehospital ECG and transmission to the emergency physician or cardiologist of a percutaneous coronary intervention center. The studies were classified as moderate quality by NOS. Telemedicine was associated with a statistically significant reduction in in-hospital mortality (12 studies [n=6033], risk ratio [RR] 0.54 [CI 95% 0.46-0.64], I 2 2 23%, no evidence of publication bias) and one-year mortality (3 studies[n=1549], RR 0.47 [IC 95% 0.33-0.68], I 2 Conclusions: Telemedicine strategies combined with the usual care for MI patients are associated with improved in-hospital, 30-day and one-year mortality.
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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 | 0.000 |
| 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".