Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Country Description Black-Box

Which country-linked CT.gov portfolios carry the most older studies that are overdue, unlinked, and missing both detailed description and primary outcome description? We analysed 249,507 eligible older closed interventional studies from the March 29, 2026 full-registry snapshot and exploded country links. We defined a description black-box study as one with a two-year results gap, no linked publication, no detailed description, and no primary outcome description, then ranked country-linked portfolios with at least 500 linked studies. The United States led the country-linked stock table at 5,833 studies, followed by France at 1,353, Germany at 1,262, and Canada at 1,036. Japan had the highest large-country description-black-box rate at 10.7 percent, while South Korea reached 9.1 percent and Germany 8.4 percent. Country-linked black-box tables show where the strictest narrative opacity remains concentrated after studies failed results and linkage tests. Country-linked rows are non-exclusive because multinational studies can contribute to more than one national portfolio in the registry for readers.

Outside Notes

Type: methods
Primary estimand: Description black-box stock among older studies with no results, no linked publication, no detailed description, and no primary outcome description
App: CT.gov Country Description Black-Box dashboard
Data: 249,507 eligible older closed interventional studies with description-black-box stock and rate summaries
Code: https://github.com/mahmood726-cyber/ctgov-country-description-black-box
Version: 1.0.0
Validation: FULL REGISTRY RUN

References

1. ClinicalTrials.gov API v2. National Library of Medicine. Accessed March 29, 2026.
2. DeVito NJ, Bacon S, Goldacre B. Compliance with legal requirement to report clinical trial results on ClinicalTrials.gov: a cohort study. Lancet. 2020;395(10221):361-369.
3. Zarin DA, Tse T, Williams RJ, Carr S. Trial reporting in ClinicalTrials.gov. N Engl J Med. 2016;375(20):1998-2004.

AI Disclosure

This work represents a compiler-generated evidence micro-publication built from structured registry data and deterministic summary code. AI was used as a constrained coding and drafting assistant for interface generation, packaging, and prose refinement, not as an autonomous author. The analytical choices, interpretation, and final outputs were reviewed by the author, who takes responsibility for the content.