Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Country Narrative Gap

Which country-linked CT.gov portfolios most often leave older closed study pages without both detailed descriptions and primary outcome descriptions? We analysed 249,507 eligible older closed interventional studies from the March 29, 2026 full-registry snapshot and exploded country links. We defined a narrative-gap study as one missing both detailed description and primary outcome description, then ranked country-linked portfolios with at least 500 linked studies by stock and rate. The United States led the narrative-gap stock table at 9,049 studies, followed by Germany at 2,438, France at 2,420, and Canada at 1,853. Japan had the sharpest large-country narrative-gap rate at 17.9 percent, ahead of Finland at 16.6 percent and Germany at 16.3 percent. Country-linked narrative gaps show where registry pages remain text-thin even when they retain dates, status fields, and other basic metadata on the public page for readers. Country-linked rows are non-exclusive because multinational studies can contribute to more than one national portfolio in the registry tables.

Outside Notes

Type: methods
Primary estimand: Narrative-gap stock among older studies missing both detailed descriptions and primary outcome descriptions
App: CT.gov Country Narrative Gap dashboard
Data: 249,507 eligible older closed interventional studies with country-linked narrative-gap stock and rate summaries
Code: https://github.com/mahmood726-cyber/ctgov-country-narrative-gap
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.