Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Country Excess Watchlist

Which country-linked CT.gov portfolios remain most opaque after visible study mix is held more constant? We analysed 249,507 eligible older closed interventional studies from the March 29, 2026 full-registry snapshot and exploded named-country links. We summed adjusted no-results excess, adjusted ghost excess, black-box stock, and strict-core spillover across country-linked study portfolios with at least 500 linked studies. France carried the largest country-linked adjusted excess no-results stock at 2,187 studies, followed by China at 1,299 and Egypt at 824. China and Egypt also showed large ghost excess, while South Korea reached a 21.2 percent black-box rate and France still carried 3,093 black-box studies. The geography story therefore mixes large Western institutional stock with sharper hiddenness tails in several Asian and Middle Eastern portfolios once adjusted stock, ghost excess, and black-box depth are read together. Country watchlists count country-linked studies rather than assigning each study to only one nation, so multinational records can contribute to multiple national portfolios.

Outside Notes

Type: methods
Primary estimand: Adjusted excess no-results and ghost stock across country-linked study portfolios with at least 500 linked studies
App: CT.gov Country Excess Watchlist dashboard
Data: 249,507 eligible older closed interventional studies exploded into named-country links for country-linked watchlists
Code: https://github.com/mahmood726-cyber/ctgov-country-excess-watchlist
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.