A Machine Learning-Derived Risk Scorecard for Pneumonia Hospitalization in Japanese Old-Old Adults

Aim To develop and internally validate a machine learning-based risk scorecard for 1-year pneumonia hospitalization among community-dwelling Japanese adults aged ≥ 75 years using routinely collected frailty screening and claims data. Methods We conducted a retrospective cohort study of 1 098 404 community-dwelling adults aged ≥ 75 years who completed the Questionnaire for Medical Checkup of Old-Old (QMCOO) between April 2020 and March 2024, using the Late-Stage Medical Care System claims database. Data were spli…

A Machine Learning-Derived Risk Scorecard for Pneumonia Hospitalization in Japanese Old-Old Adults
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In brief

Researchers developed and internally validated a machine learning-based risk scorecard for 1-year pneumonia hospitalization among 1,098,404 community-dwelling Japanese adults aged 75 years or older who completed the QMCOO frailty screening between April 2020 and March 2024. Using Late-Stage Medical Care System claims, a 20-learner Super Learner ensemble and a 17-feature 0-21 point scorecard were trained and tested, with the scorecard achieving AUC 0.786 and good calibration.

The tool stratified the population into low, moderate, and high risk groups with a 15.9-fold gradient in observed hospitalization rates, suggesting potential utility for identifying high-risk individuals during routine checkups. As of the October 2026 publication date, the findings reflect internal validation only, and the authors note that external validation would be needed before supporting targeted preventive assessment in primary care.

Main points

  1. Retrospective cohort of 1,098,404 community-dwelling adults aged ≥ 75 years who completed the Questionnaire for Medical Checkup of Old-Old between April 2020 and March 2024
  2. Data source was the Late-Stage Medical Care System claims database with 70% training and 30% test split
  3. Outcome was 1-year pneumonia hospitalization defined by ICD-10 J12-J18, J69, occurring in 4525 participants (0.41%)
  4. 17-feature point-based scorecard (0-21 points) derived from training set with Platt calibration

The gain

A Super Learner ensemble and derived 17-feature point-based scorecard predicted 1-year pneumonia hospitalization among community-dwelling Japanese adults aged 75+ with good discrimination and calibration on internal test data.

The rundown

The study used routinely collected frailty screening via the Questionnaire for Medical Checkup of Old-Old and claims from the Late-Stage Medical Care System. Participants had mean age 80.6 years and 40.3% were male. The prediction target was hospitalization with ICD-10 codes J12-J18 and J69 within one year.

Performance was reported on a held-out 30% test set. The full ensemble reached AUC 0.823 and the simplified scorecard reached AUC 0.786 with calibration slope 1.017 and calibration-in-the-large -0.001. Risk stratification showed event rates of 0.12% in low, 0.49% in moderate, and 1.91% in high groups.

Sources

  1. Peer-reviewedGeriatrics & Gerontology International2026-10-01

The debate