PhenoAge and KDM biological age from EHR data linked to mortality and readmission
In 2,434 patients aged 30–75, biological age estimated from routine EHR biomarkers with PhenoAge and KDM was associated with mortality and 30-day readmission beyond chronological age; this is an observational association, not proof of cause. [1]
Automatic summary · not editorially reviewed
The key findings
The retrospective study covered 93,200 encounters from 2,434 unique patients aged 30–75 at a western Pennsylvania health system, with median follow-up of 10.2 years. [1]
Chronological age alone was not significantly associated with 30-day readmission (p = 0.78), while PhenoAge and KDM acceleration were associated with higher readmission rates. [1]
PhenoAge and KDM acceleration were each independently associated with mortality beyond chronological age (hazard ratios 1.17 and 1.08 per 5-year increase). [1]
The source at a glance
- Study type / format
- Retrospective observational cohort study using electronic health record data (abstract).
- Population / context
- 2,434 unique patients aged 30–75 with 93,200 encounters at a large health system in western Pennsylvania.
- Summary based on
- Study abstract
- Publication status
- Preprint · peer-review status not confirmed
- Original publication
- September 21, 2026
EHR cohort of 2,434 patients compared on two age measures
The authors describe a retrospective study of 93,200 encounters from 2,434 unique patients aged 30–75 at a large health system in western Pennsylvania, with a median follow-up of 10.2 years. They applied Levine PhenoAge and the Klemera-Doubal Method (KDM), two ways of estimating biological age from clinical biomarkers, using a nine-biomarker panel. Age acceleration was defined as the residual of biological age regressed on chronological age. The stated aim was to test feasibility and clinical relevance in a real-world, multi-disease population and to compare the two measures head-to-head, which the authors say has rarely been done with identical biomarkers in the same population.
Supporting source [1]
Accelerated biological age and readmission, not chronological age
The cohort had a mean age of 50.6 years and was 59.6% female. Mean PhenoAge was 54.3 years and mean KDM age 50.8 years; both correlated strongly with chronological age (r = 0.75 and 0.638) and with each other (r = 0.78). Chronological age alone was not significantly associated with 30-day readmission rate (p = 0.78). In contrast, PhenoAge and KDM acceleration were associated with increased readmission rate, by 17.6% and 5.8% per 5-year increase respectively. The authors interpret this as biological age acceleration capturing readmission risk that chronological age misses. These are associations from regression models, not evidence that biological age causes readmission.
Supporting source [1]
Mortality link beyond age in a retrospective EHR study
PhenoAge and KDM acceleration were each independently associated with mortality beyond chronological age, with hazard ratios of 1.17 and 1.08 per 5-year increase. Both significantly improved model fit over age and sex alone (likelihood ratio test χ² = 62.99 and 30.90). Associations with comorbidities, frailty and readmission were evaluated with Cox proportional hazards, logistic and negative binomial regression models. Because this is a retrospective observational study in one health system, the results show associations rather than causes and may not generalize to other populations or care settings.
Supporting source [1]
How to interpret this
Abstract only; the full text was not reviewed. This is a retrospective observational study in a single western Pennsylvania health system, so findings are associations, not causes, and generalizability is uncertain. The abstract text is truncated, so some results may be incomplete.
Based on the study abstract; the full paper, tables and supplementary data were not reviewed.
Source & supporting passages
Edakalavan S, Morris A, Methe B, Radder J, Konigshoff M, Nouraie SM. · europepmc.org · September 21, 2026