Development and Validation of a Nomogram Predictive of Kidney Function After CPR

A clinical dataset from Tianjin Medical University General Hospital and First Affiliated Hospital of Hebei North University, spanning January 2017 to June 2024. It contains retrospective data on 439 patients who underwent cardiopulmonary resuscitation, used to develop and validate a nomogram for predicting estimated glomerular filtration rate. The dataset was published on figshare by figshare admin karger in April 2026.

Use Cases

• Predicting kidney function (eGFR) after CPR based on patient age, hypertension, and diabetes status.
• Assessing the risk of Acute Kidney Injury (AKI) progression using factors like no-flow time and lactic acid levels.
• Validating a clinical nomogram model with internal and external cohorts to quantify predictive accuracy.
• Identifying independent risk factors for Chronic Kidney Disease (CKD) progression post-CPR using baseline eGFR and ACR.

Strengths

• Dataset includes 439 patient records across training, internal validation, and external validation cohorts.
• Model validation shows high accuracy: 97.07% in training, 95.45% in internal validation, and 91.08% in external validation cohorts.
• The nomogram demonstrates strong predictive ability for AKI and CKD, with AUC scores up to 0.933 and 0.882 respectively.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect geographic bias inherent to the hospitals in Tianjin and Hebei, China.

Provenance

Source

Tianjin Medical University General Hospital and First Affiliated Hospital of Hebei North University

Collection Method

Retrospective analysis of clinical data from patients after cardiopulmonary resuscitation.

Time Range

January 2017 to June 2024

Freshness

Last updated 2026-04-22 05:55:19; freshness should be verified.

Geography

Hospitals in Tianjin and Hebei, China