Mahmood Ahmad
Tahir Heart Institute
author@example.com

CT.gov Cardiovascular Hiddenness

How quiet is the older cardiovascular trial record in ClinicalTrials.gov once heart and vascular studies are grouped into one registry-first family? We analysed 26,062 eligible older cardiovascular studies from the March 29, 2026 full-registry snapshot, spanning coronary, stroke, heart-failure, rhythm, and vascular records. Primary comparisons tracked two-year no-results rates, ghost protocols, sponsor-class mix, phase patterns, and the sponsors holding the biggest unresolved stock. Across older cardiovascular studies, 75.0 percent lacked posted results and 39.3 percent showed neither results nor a linked publication trail. PHASE1 remained the largest phase bucket, while Assistance Publique - Hôpitaux de Paris carried the biggest named sponsor stock at 144 older missing-results studies in the cardiovascular family. The cardiovascular record is therefore not just incomplete. It remains structurally quiet across common phases despite its central place in evidence-based medicine. This matters for guideline-facing cardiovascular medicine. These family-level estimates measure registry-visible absence rather than legal culpability or publication quality within this cardiovascular frame.

Outside Notes

Type: methods
Primary estimand: 2-year no-results rate within the cardiovascular family among eligible older CT.gov studies
App: CT.gov Cardiovascular Hiddenness dashboard
Data: 26,062 eligible older cardiovascular studies in the March 29, 2026 full-registry snapshot
Code: https://github.com/mahmood726-cyber/ctgov-cardiovascular-hiddenness
Version: 1.0.0
Validation: FULL REGISTRY RUN

References

1. ClinicalTrials.gov API v2. National Library of Medicine. Accessed March 29, 2026.
2. PubMed E-utilities. National Center for Biotechnology Information. Accessed March 29, 2026.
3. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement. BMJ. 2021;372:n71.

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.