Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Publication Index Gap

How much of CT.gov publication-link missingness survives when no-link studies are re-audited with broader exact-ID search beyond the earlier PubMed-only pass? We re-audited the existing 1,050-study sponsor-class-stratified sample of older no-link studies drawn from 140,363 eligible no-link records in the March 29, 2026 registry snapshot. We compared PubMed exact-ID matches with Europe PMC exact-ID matches, separating total rescue, non-MED rescue, and weighted publication-only visibility. Weighted PubMed exact-ID matching captured only 1.2 percent of no-link records, but Europe PMC exact-ID rescue added 39.6 points, lifting weighted any-match visibility to 40.8 percent. Non-MED rescue was much smaller at 2.8 points, while weighted external-publication-only visibility still reached 29.1 percent. Publication-link missingness therefore combines real silence with a much larger indexing and linkage gap than the PubMed-only audit suggested, especially in NIH-linked and network-linked no-link portfolios. The audit is sample-based, exact-ID only, and cannot adjudicate whether every retrieved paper fully reports the registered study or whether links were added later.

Outside Notes

Type: methods
Primary estimand: Weighted exact-ID external publication rescue among older CT.gov no-link studies
App: CT.gov Publication Index Gap dashboard
Data: 1,050-study sponsor-class-stratified exact-ID audit representing 140,363 eligible older no-link studies
Code: https://github.com/mahmood726-cyber/ctgov-publication-index-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.