BRAIN. Broad Research in Artificial Intelligence and Neuroscience

Kidney Stone AI Evidence Explorer

Insights into anthropometric predictors and the exploratory role of AI in kidney stone recurrence and stone type.

Academic digest from the article

Abstract

Evidence dashboard

Dietary, anthropometric and stone-type signals

The visualizations reconstruct the numerical findings reported in the article tables and results section.

Relapse status: ideal weight, measured weight and water intake

Mann-Whitney U: ideal weight p = 0.006; measured weight p = 0.053.

Evidence chart Interactive chart showing article values for relapse status, stone type and dietary factors.
Strongest statistical signal Ideal weight

Associated with relapse status and stone type; p = 0.006 for relapse status, p = 0.025 across stone types.

Protective trend Water intake

Non-relapsers reported 2.1 L/day compared with 1.7 L/day in relapsers; p approximately 0.09.

Null dietary signals Fast food, carbonated drinks, meat, coffee, tea

No statistically significant associations were detected for isolated dietary components.

Computational framework

From clinical nutrition data to exploratory AI modelling

The article uses standard statistical testing and machine-learning models to rank variable importance, not to deliver a clinically validated prediction tool.

Dataset

Clinical cohort and variables

    Reconstructed tables

    Core numerical evidence from the article

    Values are transcribed from Table 1 and Table 2, then reorganized for reading on screen.

    Table 1. Dietary factors and patient characteristics

    ParameterGroupValueObservation
    Fast-foodConsumers60.0%Relapse percentages and mean values were rounded; no differences reached statistical significance.
    Fast-foodNon-consumers58.9%
    Carbonated drinksConsumers59.6%
    Carbonated drinksNon-consumers58.9%
    Meat intakeRelapse group210.8 g/day
    Meat intakeNon-relapsed192.3 g/day
    Water intakeRelapse group1.7 L/day
    Water intakeNon-relapsed2.1 L/day
    Stone typeOxalateWeight: 92.6 kg
    Ideal Weight: 64.8 kg
    Water Intake: 2.0 L/day
    Uric acid stone patients had higher weight and ideal weight, with lower water intake.
    Stone typeUric acidWeight: 103.3 kg
    Ideal Weight: 73.3 kg
    Water Intake: 1.6 L/day
    Stone typeOtherWeight: 83.9 kg
    Ideal Weight: 64.5 kg
    Water Intake: 1.9 L/day

    Table 2. Weight and ideal weight

    Parameter / GroupNIdeal weightWeightObservation
    Relapse8562.4 / 66.6 ± 8.9 kg92.1 / 92.4 ± 13.7 kgMann-Whitney U: ideal weight p = 0.006; weight p = 0.053.
    Non-relapse5872.3 / 70.7 ± 9.1 kg96.5 / 98.8 ± 17.5 kg
    Oxalate11464.8 / 67.7 ± 9.2 kg92.6 kgKruskal-Wallis: ideal weight p = 0.025; weight p = 0.011.
    Uric acid2273.8 / 72.2 ± 8.1 kg103.3 kg
    Other660.5 / 64.8 ± 11.3 kg81.8 kg