Virtual follow-up and care for patients with cardiac electronic implantable devices: protocol for a systematic review
Bibliographic record
Abstract
BACKGROUND: Capacity to deliver outpatient care for patients with cardiac implantable electronic devices (CIEDs) may soon be outweighed by need. This systematic review aims to investigate the comparative effectiveness, safety, and cost for virtual or remote clinic interventions for patients with CIEDs and explores how outcomes may be influenced by patient or system factors in-depth. METHODS: We will perform a systematic literature search in MEDLINE, Embase, PsycINFO, CINAHL, Proquest Dissertations & Theses, other EBM Reviews, and trial registry databases. Two authors will independently screen titles and abstracts for eligibility. We will include randomized and non-randomized controlled trials, quasi-randomized and experimental studies, cohort, and case-control studies. Study populations of interest are individuals with a CIED (pacemaker, ICD, CRT). Eligibility will be restricted to virtual or remote follow-up or care interventions compared to any other approach. The co-primary outcomes of interest are mortality and patient satisfaction. Secondary outcomes include clinical effectiveness (e.g., ICD shock, time-to-detection of medical event, hospitalizations), safety (e.g., serious or device-related adverse events), device efficacy (e.g., transmissions, malfunctions), costs, workflow (e.g., resources, process outcomes, time-saved), and patient reported (e.g., burden, quality of life). Data will be extracted by one author and checked by a second using a standardized template. We will use published frameworks to capture data relevant to intervention effects that may be influenced by intervention definition or complexity, context and setting, or in socially disadvantaged populations. Detailed descriptive results will be presented for all included studies and outcomes, and where feasible, synthesized using meta-analysis. Risk of bias will be assessed by two review authors independently using Cochrane Risk of Bias tools. Certainty of evidence will be assessed using the GRADE approach. DISCUSSION: Increases in number of CIEDs implanted, combined with an aging population and finite health resource allocations at the system-level may lead to increased reliance on virtual follow-up or care models in the future. These models must prioritize consistent, equitable, and timely care as a priority. Results from this systematic review will provide important insight into the potential contextual factors which moderate or mediate the effectiveness, safety, and cost of virtual follow-up or care models for patients. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration number CRD42020145210.
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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 | 0.065 | 0.081 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.017 | 0.016 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.074 | 0.009 |
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".