Table 1_The correlation between the systemic inflammation response index and 6-month readm

A retrospective cohort of 158 patients with hypertensive heart disease-related heart failure (HHD-HF) from June 2022 to December 2024. The dataset was used to investigate the association between the Systemic Inflammation Response Index (SIRI) and 6-month readmission risk, and to develop a nomogram prediction model. The model, which also incorporates left ventricular mass index and diabetes history, was developed by Suqin Wang.

Use Cases

• Predicting 6-month readmission risk in heart failure patients based on inflammation markers and clinical history.
• Benchmarking the predictive performance of the Systemic Inflammation Response Index (SIRI) against other biomarkers like CRP, NLR, and BNP.
• Interpreting feature contributions in a clinical prediction model using SHAP analysis on variables like SIRI, LVMI, and diabetes history.

Strengths

• Dataset includes 158 patient records with a defined time range from June 2022 to December 2024.
• The derived prediction model demonstrated high discriminative ability, with AUCs of 0.950 and 0.948 in training and validation cohorts.
• Analysis includes SHAP interpretation and subgroup analysis by heart failure phenotype (HFrEF and HFpEF).

Limitations

• Row count for the underlying clinical data is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 15.4 KB, indicating limited scope.

Provenance

Source

figshare, author Suqin Wang.

Collection Method

Retrospective cohort study; data likely collected from clinical records, laboratory indicators, and cardiac parameters.

Time Range

June 2022 to December 2024

Freshness

Last updated 2026-05-28 05:58:09; freshness should be verified.