Relationship Between Enrolling Country Income Level and Patient Profile, Protocol Completion, and Trial End Points
Bibliographic record
Abstract
BACKGROUND: Globalization of clinical trials fosters inclusion of higher and lower income countries, but the influence of enrolling country income level on heart failure trial performance is unclear. This study sought to evaluate associations between enrolling country income level, acute heart failure patient profile, protocol completion, and trial end points. METHODS AND RESULTS: The ASCEND-HF (Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure) trial included 7141 patients with acute heart failure from 30 countries. Country income data in gross national income per capita in current US dollars from the year 2007 (ie, the year trial enrollment began) were abstracted from the World Bank. Patients were grouped by enrolling country income level (ie, high [>$11 455], upper middle [$3706-$11 455], lower middle [$936-$3705], and low [<$936]). Income data were available for 29 (97%) countries (N=7064). There were 3996 (57%), 1518 (21%), and 1550 (22%) patients from high-income, upper-middle-income, and lower-middle-income countries, respectively. There were no patients from low-income countries. Patients from lower-middle-income countries tended to be younger with fewer comorbidities and lower utilization of guideline-directed therapies. Rates of adverse events (13.8%) and protocol noncompletion (4.9%) during 180-day follow-up were highest among high-income countries (all P <0.01). After adjustment for race, geographic region, and clinical characteristics, compared with lower-middle-income countries, enrollment from higher income countries was associated with increased 30-day mortality or rehospitalization (high income: odds ratio, 1.70; 95% CI, 1.02-2.85; upper-middle-income: odds ratio, 2.16; 95% CI, 1.23-3.81), driven by higher rates of rehospitalization. Mortality was similar at 30 and 180 days. The association between higher country income and the 30-day composite end point was similar across geographic regions, with exception of Latin America ( P for interaction, 0.03). CONCLUSIONS: In this global acute heart failure trial, patients from higher income countries had lower rates of protocol completion, higher rates of adverse events, and similar mortality rates. After adjustment for race, geographic region, and clinical factors, enrollment from a higher income country was associated with worse clinical outcomes, driven by higher rates of rehospitalization. Variation in enrolling country income level may influence study end points and trial performance independent of geographic region. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT00475852.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".