Validation of a clinical prediction model for falls in community-dwelling older adults with COPD: A preliminary analysis

Abstract

Background: People with chronic obstructive pulmonary disease (COPD) are at a higher risk of falls. This preliminary study aims to externally validate a previously developed clinical prediction model for falls in community-dwelling older adults with COPD.

Methods: This was a secondary analysis of a 12-month prospective cohort study. Older adults (≥60 years) with COPD, who reported a fall in the past year and/or had balance concerns, were tracked for 12-month future falls. Baseline predictors included 12-month history of ≥2 falls, total chronic conditions, and Timed Up and Go Dual-Task (TUG-DT) test scores. Model performance was assessed for discrimination (c-statistic), calibration (E:O, CITL, and calibration slope), and clinical value (decision curve analysis).

Results: The study included 89 participants (average age 73 ± 9 years; 83 females; FEV₁%predicted = 47%). Of these, 35 (39%) reported ≥1 future fall, totaling 89 falls. The model demonstrated acceptable discrimination (c-statistic = 0.62, CI [0.51,0.72]), and calibration (E:O = 1, CITL = 0, and a calibration slope = 1). Decision curve analysis showed greater clinical value when using the prediction model compared to screening for fall history alone.

Conclusions: A 12-month history of ≥2 falls, higher total chronic conditions, and worse TUG-DT test scores, predicts falls in community-dwelling older adults with COPD. Larger studies are needed before clinical application.

Trial registration: ClinicalTrials.gov NCT03229473.

Keywords: COPD; external validation; falls; older adults; prediction model.

Figure 1.

Calibration plot for the fall prediction model in community-dwelling older adults with COPD (N = 89) with the smoothed prediction model overlayed onto an ideal reference line (indicates perfect calibration). Calibration plots display the observed values on the y-axis over the expected (predicted) values on the x-axis. The spike plot at the bottom of the calibration plot shows the distribution of the observed and expected probabilities, with the observed data dichotomised into <50% below the midline and ≥50% above the midline.

Figure 2.

Calibration plot for the recalibrated fall prediction model in community-dwelling older adults with COPD (N = 89) with the smoothed prediction model overlayed onto an ideal reference line (indicates perfect calibration). Calibration plots display the observed values on the y-axis over the expected (predicted) values on the x-axis. The spike plot at the bottom of the calibration plot shows the distribution of the observed and expected probabilities, with the observed data dichotomised into <50% below the midline and ≥50% above the midline.

Figure 3.

Decision curves for treating all, treating none, treating based on 12-month history of ≥1 fall, and treating based on predicted likelihood of ≥1 fall using the prediction model derived from a sample of community-dwelling older adults with COPD (N = 89). Decision curves are plotted with net benefit on the y-axis, indicating the net true positives, over the x-axis, representing the threshold probability or the minimum likelihood of a fall that is deemed actionable by a clinical decision maker.