Comparative effectiveness of the different components of care provided in heart failure clinics—protocol for a systematic review and network meta-analysis
Bibliographic record
Abstract
BACKGROUND: Heart failure (HF) is a complex chronic condition, leading to frequent hospitalization, decreased quality of life, and increased mortality. Current guidelines recommend that multidisciplinary care be provided in specialized HF clinics. A number of studies have demonstrated the effectiveness of these clinics; however, there is a wide range in the services provided across different clinics. This network meta-analysis will aim to identify the aspects of HF clinic care that are associated with the best outcomes: a reduction in mortality, hospitalization, and visits to emergency department (ED) and improvements to quality of life. METHODS: Relevant electronic databases will be systematically searched to identify eligible studies. Controlled trials and observational cohort studies of adult (≥ 18 years of age) patients will be eligible for inclusion if they evaluate at least one component of guideline-based HF clinic care and report all-cause or HF-related mortality, hospitalizations, or ED visits or health-related quality of life assessed after a minimum follow-up of 30 days. Both controlled trials and observational studies will be included to allow us to compare the efficacy of the interventions in an ideal context versus their effectiveness in the real world. Two reviewers will independently perform both title and abstract full-text screenings and data abstraction. Study quality will be assessed through a modified Cochrane risk of bias tool for randomized controlled trials (RCTs) or the ROBINS-I tool for observational studies. The strength of evidence will be assessed using a modified Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) system. Network meta-analysis methods will be applied to synthesize the evidence across included studies. To contrast findings between study designs, data from RCTs will be analyzed separately from non-randomized controlled trials and cohort studies. We will estimate both the probability that a particular component of care is the most effective and treatment effects for specified combinations of care. DISCUSSION: To our knowledge, this will be the first study to evaluate the comparative effectiveness of the different components of care offered in HF clinics. The findings from this systematic review will provide valuable insight about which components of HF clinic care are associated with improved outcomes, potentially informing clinical guidelines as well as the design of future care interventions in dedicated HF clinics. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017058003.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.057 | 0.009 |
| Bibliometrics | 0.000 | 0.001 |
| 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".