P578Use of a smartphone application to increase adherence to medical treatment in patients with acute coronary syndrome: a randomized clinical trial
Bibliographic record
Abstract
Abstract Background Adherence to cardiovascular medications following acute coronary syndrome (ACS) hospitalization is generally poor and is associated with increased risk of rehospitalization and mortality. There are still significant opportunities to identify simple and low-cost interventions that improve medication adherence and clinical outcomes. Purpose To evaluate the use of a digital platform for smartphones to improve adherence to medical treatment and outcomes for 90-days post discharge in patients hospitalized for ACS with or without ST-elevation. Methods This was a unicentric, single-blinded, randomized controlled trial enrolling 90 patients with an ACS event requiring hospitalization. The intervention consisted of a smartphone application which allowed for the loading of medication prescription together with reminder of the daily compliance. Patients in the intervention group (n=46) were equipped with the smartphone application. Patients in the control group (n=44) received written and oral instructions as per standard of care. The primary outcome was adherence to medical treatment measured at 90-days post discharge using the 8-item Morisky Medication Adherence Scale (MMAS-8). The secondary outcome was a composite of re-hospitalizations for ACS, consultations to the emergency department (ED), or unplanned visits to the clinic. Results The mean age of the population was 63.2±9.9 and 75.6% were male. At 90 days, 64.7% of patients using the smartphone application were adherent compared with 20.5% of patients in the control group (p<0.001). Patients in the intervention group had higher adherence (mean MMAS-8 score 7.52±1.25) compared with the control group (mean MMAS-8 score 6.47±1.23; p<0.001). The secondary outcome measures showed that there were no significant differences in patients using the smartphone application versus the standard of care (4.3% vs 15.9%, p=0.07, respectively). Table 1 Variables Global (n=90) Control (n=44) Intervention (n=46) p MMAS-8 score 7±1.34 6.47±1.23 7.52±1.25 <0.001 Adherents 40 (44.4%) 9 (20.5%) 31 (67.4%) <0.001 Events 9 (10.1%) 7 (15.9%) 2 (4.3%) 0.071 ED consultations 9 7 2 Score assessment 8.85±1.4 Conclusions In patients with ACS, the use of a smartphone application increased the medication adherence compared with the standard of care. These data suggest that there is potential for a simple, low-cost intervention to help patients adhere to medications. ClinicalTrials.gov unique identifier: NCT03766789.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".