FEASIBILITY OF AN INTERVENTION FOR DEFIBRILLATOR CANDIDATES
Bibliographic record
Abstract
Background: Implantable cardioverter defibrillators (ICDs) deliver therapy in the form of an internal shock should a life-threatening arrhythmia occur. Literature suggests that patients have misconceptions regarding ICD therapy and unmet information needs. Purpose: This study assessed the feasibility of delivering a pre-implantation nurse-led educational intervention to ICD candidates. Methods: ICD candidates attending an outpatient preoperative clinic were invited to participate. Consented participants were randomized to standard care or standard care plus an educational intervention. The educational intervention addressing information gaps identified in the ICD literature was delivered during the preoperative visit. The primary outcome was feasibility with the following targeted rates, (1) 80% recruitment; (2) ≥ 95% consent; (3) 90% randomization; (4) ≥ 90% completion of questionnaires; (5) 80% of intervention sessions delivered less than 45 minutes; and (6) 90% of intervention content delivered. At baseline, demographic data and Patient-Reported Outcomes Measurement Information System (PROMIS) anxiety scores were collected. Four weeks post-ICD implantation, participants completed the PROMIS anxiety measure, Florida Patient Acceptance Survey (FPAS), and Florida Shock Anxiety Scale (FSAS). Results: Twenty patients consented to the study (10 standard care/10 standard care plus the educational intervention). Feasibility outcomes achieved were, (1) recruitment rate of 80%; (2) consent rate of 87%; (3) 100% randomization; (4) 80% completion of questionnaires; (5) 100% of intervention sessions completed in less than 45 minutes; and (6) intervention checklist completion rate of 100%. The four-week mean (SD) FPAS scores were 80.0 (13.4) in the intervention group compared to 77.0 (16.5) in standard care. Mean (SE) four-week PROMIS scores were 45.4 (6.4) in the intervention group and 43.7 (8.6) in standard care. Mean FSAS (SD) scores were 14.7 (4.6) in the intervention group and 13.3 (3.9) in standard care. Conclusion: The results demonstrated feasibility of delivering a pre-implantation nurse-led educational intervention in an outpatient clinic setting to ICD candidates. Further studies to evaluate the effectiveness of the intervention on patient-reported outcomes are warranted.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".