Medical Calculator#igan#iga

International IgAN Prediction Tool post-biopsy - Adults

Determine prognosis in adults with IgA nephropathy

1
ml/min/1.73m²

<b>Please note:</b><br /> Pick a fixed landmark time for risk stratification as either 1 or 2 years post-biopsy and use the same landmark time for all variables entered in this model.

2
mmHg

<b>Please note:</b><br /> Pick a fixed landmark time for risk stratification as either 1 or 2 years post-biopsy and use the same landmark time for all variables entered in this model.

3
mmHg

<b>Please note:</b><br /> Pick a fixed landmark time for risk stratification as either 1 or 2 years post-biopsy and use the same landmark time for all variables entered in this model.

4
g/day

<b>Please note:</b><br /> Pick a fixed landmark time for risk stratification as either 1 or 2 years post-biopsy and use the same landmark time for all variables entered in this model.

5
Years

<b>Please note:</b><br /> Pick a fixed landmark time for risk stratification as either 1 or 2 years post-biopsy and use the same landmark time for all variables entered in this model.

6
7
8
9
10
11
12
13
Months

Most users will use a 60-month (5-year) risk horizon.

Results

Real-time automated computation

0/1 calculated
Risk of Progression
Awaiting input values...
Clinical Parameters (0/13)
0%
Medical calculation formulas standardized according to evidence-based clinical protocols.
About

The risk equations were generated by updating the original International IgA Nephropathy Prediction Tool at biopsy so that it could be used instead at a landmark time of 1 or 2 years after biopsy. The models were derived in a multi-ethnic international cohort of 2,507 patients with biopsy proven idiopathic IgA nephropathy, and are designed to predict the risk of a 50% decline in eGFR or ESRD after the landmark time.

Two risk equations were developed, one that included race and one that did not. The risk equations were externally validated in a multi-ethnic international cohort of 722 patients. If the patient's race is not adequately represented by Chinese patients from China, Japanese patients from Japan, or Caucasian patients from Europe or North America, then we suggest using the model without race to predict the outcome. As such, this app uses the model with race if Chinese, Japanese or Caucasian race is selected, and uses the model without race if Other race is selected.

The C-statistic for both models were 0.85-0.87 in both the derivation and validation cohorts, and both models were well calibrated in the external validation cohort. These equations require further validation in other ethnic groups and in pediatric patients less than 18 years old.

Published Literature & References: