Background <p>Urine color (Uc) assessment is impacted by container, volume, and light conditions, potentially influencing Uc scoring. This study aimed to evaluate a 3D Uc model vs. Printed Uc chart’s accuracy for identifying a low vs. high urine concentration in the morning and afternoon.</p> Results <p>Participants (<i>n</i> = 73, 12% female, age: ~ 27&#xa0;years) collected all urine voids for two consecutive days (32&#xa0;h total), resulting in two partially concurrent 24-h urine collections that were compared with a morning and afternoon assessment. Median and [interquartile range] Uc differed between the Printed chart and 3D Uc model in the morning (2.0 [1.5–3.0] vs. 2.0 [2.0–4.0], <i>p</i> &lt; 0.001), but not in the afternoon (2.0 [1.0 – 3.0] vs. 2.0 [1.0 – 3.0], <i>p</i> = 0.07). The models had a moderate correlation in the morning (<i>r</i> = 0.66, <i>p</i> &lt; 0.001) and a strong correlation in the afternoon (<i>r</i> = 0.83, <i>p</i> &lt; 0.001). Bland–Altman plots revealed a slight bias (-0.60 and -0.27 for morning and afternoon, respectively), with significant reporting bias only for the morning, <i>p</i> = 0.04. The Area Under the Curve (AUC), to correctly classify urine concentration, was poor for morning Printed (0.62) and 3D (0.59) vs. fair for afternoon Printed (0.78) and 3D (0.74) for USG 24&#xa0;h. Interestingly, the AUC for spot urine sample color was high (i.e., morning: 0.84 and 0.79), and afternoon: 0.91 and 0.92) for the Printed chart and 3D Uc model, respectively.</p> Conclusions <p>The printed chart and 3D Uc model presented similar scores but with slightly higher accuracy in the afternoon.</p>

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A 3D color model reports urine color similarly to a printed color chart with similar accuracy to determine a low vs. high urine concentration

  • Raul Freire,
  • Kinta D. Schott,
  • Brooke Butterick,
  • Zack Stow,
  • Parker Kooima,
  • Sai Tejaswari Gopalakrishnan,
  • Emily Dow,
  • Jason C. Siegler,
  • Jefferey L. Burgess,
  • Floris C. Wardenaar

摘要

Background

Urine color (Uc) assessment is impacted by container, volume, and light conditions, potentially influencing Uc scoring. This study aimed to evaluate a 3D Uc model vs. Printed Uc chart’s accuracy for identifying a low vs. high urine concentration in the morning and afternoon.

Results

Participants (n = 73, 12% female, age: ~ 27 years) collected all urine voids for two consecutive days (32 h total), resulting in two partially concurrent 24-h urine collections that were compared with a morning and afternoon assessment. Median and [interquartile range] Uc differed between the Printed chart and 3D Uc model in the morning (2.0 [1.5–3.0] vs. 2.0 [2.0–4.0], p < 0.001), but not in the afternoon (2.0 [1.0 – 3.0] vs. 2.0 [1.0 – 3.0], p = 0.07). The models had a moderate correlation in the morning (r = 0.66, p < 0.001) and a strong correlation in the afternoon (r = 0.83, p < 0.001). Bland–Altman plots revealed a slight bias (-0.60 and -0.27 for morning and afternoon, respectively), with significant reporting bias only for the morning, p = 0.04. The Area Under the Curve (AUC), to correctly classify urine concentration, was poor for morning Printed (0.62) and 3D (0.59) vs. fair for afternoon Printed (0.78) and 3D (0.74) for USG 24 h. Interestingly, the AUC for spot urine sample color was high (i.e., morning: 0.84 and 0.79), and afternoon: 0.91 and 0.92) for the Printed chart and 3D Uc model, respectively.

Conclusions

The printed chart and 3D Uc model presented similar scores but with slightly higher accuracy in the afternoon.