Sex, Race, and Age Differences in Cardiovascular Outcomes in Implantable Cardioverter–Defibrillator Randomized Controlled Trials: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background Data are limited regarding the use of implantable cardioverter–defibrillators (ICDs) in diverse populations. This study explores cardiovascular (CV) outcomes and mortality from ICD randomized controlled trials (RCTs), by sex, race, and age. Methods Five electronic databases (PubMed, Emcare, Embase, MEDLINE, and Cumulative Index to Nursing & Allied Health Literature CINAHL) were searched for dates from their inception to July 12, 2021, for RCTs of ICD therapy in adult patients. Data were analyzed for clinical outcomes, including all-cause or CV death, and heart failure hospitalization (HFH). Results Among 5 RCTs (mean age: 63 years; 78% male; 76% White) with moderate overall risk of bias, clinical outcomes in patients with an ICD (n = 3260) vs a control group (n = 3685) were compared. No between-group sex differences were observed for all-cause death (odds ratio [OR] 0.86, P = 0.51), CV death (OR 0.98, P = 0.96), HFH (OR 0.95, P = 0.87), or HFH and all-cause death (OR 0.83, P = 0.51) in the ICD group, in a comparison of male vs female sex. All-cause death (OR 1.20, P = 0.67) did not differ for White vs Black patients receiving ICD therapy. Outcomes data for other non-White, non-Black race groups were often unreported. Most RCTs originated in North America, had male leadership, and were evenly sponsored by industry vs peer-reviewed funding. Conclusions Outcomes data are sparse, by sex, race, and age, in current RCTs evaluating ICD therapy. Although ICD patient outcomes did not significantly differ by sex or race, improved data analyses and reporting are needed to determine the relationship between these sociocultural factors and clinical outcomes among distinct ICD patient cohorts.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
| gpt | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
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 | 0.021 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.025 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".