Uploaded August 2026 | Updated September 2026, 2 weeks ago
Inside Dave Feldman’s KetoCa study and the questions surrounding its data, analysis, and quality control
At the 2026 Unbreakable Health Retreat in Miami, Dave Feldman explained the controversy surrounding the KetoCa study, which tracked changes in coronary plaque in 100 participants using high-resolution CT angiography. Feldman describes how unexpected patterns in the initial analysis—including the near-universal classification of participants as plaque progressors—led him to question the reliability of the measurements and push for independent verification.
Feldman walks through what happened when the same scans were analyzed using different methods, revealing substantial discrepancies that raised questions about measurement error, blinding, statistical noise, and quality control. He also describes anomalies he discovered after gaining access to the anonymized data and the surprising results when some participants later had their scans independently reanalyzed through their own cardiologists.
Beyond the KetoCa controversy itself, Feldman uses the experience to illustrate a fundamental principle of good science: unexpected results should invite greater scrutiny, not greater certainty. His account makes the case for operational blinding, transparent quality control, independent analysis, and a willingness to question conclusions when the underlying measurements don’t add up.
Inside Dave Feldman’s KetoCa study and the questions surrounding its data, analysis, and quality control
At the 2026 Unbreakable Health Retreat in Miami, Dave Feldman explained the controversy surrounding the KetoCa study, which tracked changes in coronary plaque in 100 participants using high-resolution CT angiography. Feldman describes how unexpected patterns in the initial analysis—including the near-universal classification of participants as plaque progressors—led him to question the reliability of the measurements and push for independent verification.
Feldman walks through what happened when the same scans were analyzed using different methods, revealing substantial discrepancies that raised questions about measurement error, blinding, statistical noise, and quality control. He also describes anomalies he discovered after gaining access to the anonymized data and the surprising results when some participants later had their scans independently reanalyzed through their own cardiologists.
Beyond the KetoCa controversy itself, Feldman uses the experience to illustrate a fundamental principle of good science: unexpected results should invite greater scrutiny, not greater certainty. His account makes the case for operational blinding, transparent quality control, independent analysis, and a willingness to question conclusions when the underlying measurements don’t add up.
