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ArticleObesity surgery2026

Metabolic and Bariatric Surgery and Change in the AI-ECG-Derived Biological-Age Gap: A Longitudinal Cohort Study.

Reza Shahriarirad, Parvin Kalhor, Masoomeh Aslahishahri, Wissam Ghusn, Zachi Itzhak Attia, Nour El Ghazal, Omar Ghanem, Simon Laplante

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Article in Obesity surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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8 authors.

Reza ShahriariradDepartment of Surgery, Mayo Clinic, Rochester, Minnesota, USA. shahriarirad.reza@mayo.edu.
Parvin KalhorDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Masoomeh AslahishahriDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Wissam GhusnDivision of Metabolic and Abdominal Wall Reconstructive Surgery, Mayo Clinic, Rochester, Minnesota, USA.
Zachi Itzhak AttiaDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Nour El GhazalDivision of Metabolic and Abdominal Wall Reconstructive Surgery, Mayo Clinic, Rochester, Minnesota, USA.ORCID http://orcid.org/0000-0001-9179-6021
Omar GhanemDivision of Metabolic and Abdominal Wall Reconstructive Surgery, Mayo Clinic, Rochester, Minnesota, USA.
Simon LaplanteDivision of Metabolic and Abdominal Wall Reconstructive Surgery, Mayo Clinic, Rochester, Minnesota, USA. laplante.simon@mayo.edu.ORCID http://orcid.org/0000-0001-6174-3287

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObesity is associated with accelerated aging, yet whether metabolic and bariatric surgery (MBS) can reverse or attenuate this process, as measured by the artificial intelligence-electrocardiogram (AI-ECG)-derived age gap, remains uncertain.

methodsWe retrospectively studied 2,380 adults who underwent primary MBS from 2008 to 2023 and contributed 6,149 ECG observations. The outcome, δage, was AI-ECG-predicted age minus chronological age. Linear mixed-effects models used continuous time with a clinically prespecified 1-year knot and decomposed weight into between-person and within-person components. Secondary analyses evaluated alternative adiposity measures, observed ECG-age normalization, exploratory mediation, and mortality.

resultsMedian preoperative δage was 3.86 years (IQR, - 1.30 to 9.03), and 69.6% had δage > 0. δage changed by + 0.275 years/year during the first postoperative year (95% CI, - 0.187 to 0.738; P=.244) and by - 0.192 years/year thereafter (95% CI, - 0.303 to - 0.081; P=.001). The piecewise model was not superior to a linear model (P=.093). Higher between-person mean weight was associated with higher δage (+ 0.548 years per 10 kg; P<.001), whereas within-person weight change was not (+ 0.117 years per 10 kg; P=.084). Baseline, observed postoperative nadir, and maximum BMI were positively associated with δage; %EWL and observed weight regain were not. The exploratory indirect effect through weight change was near zero (ACME, + 0.0008 years; P=.814). Among 1,657 patients with baseline δage > 0, 335 (20.2%) had an observed δage ≤ 0 during follow-up.

conclusionsMBS was associated with a modest late decline in AI-ECG-derived δage. Chronic adiposity, but not within-person weight change, was associated with δage.

Indexed as

AgingArtificial IntelligenceBariatric SurgeryElectrocardiographyObesityAdultFemaleHumansLongitudinal StudiesMaleMiddle AgedRetrospective StudiesAgingArtificial intelligenceElectrocardiographyMediation analysisWeight loss

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.