HIV Hyperuricemia Risk Model Data from Hangzhou, China (2016-2024)

631 participants from a retrospective longitudinal cohort study at Hangzhou Xixi Hospital were used to develop a risk prediction model for hyperuricemia in people living with HIV. The model, created by Wenhui Zhang and validated internally, incorporates baseline serum uric acid levels and CD4+ T-cell count. Data covers patients treated between July 2016 and December 2024.

Use Cases

• Validate hyperuricemia risk prediction models based on baseline serum uric acid and CD4+ T-cell count.
• Analyze the longitudinal effects of different antiretroviral therapy regimens on serum uric acid levels over time.
• Compare clinical characteristics like hypercholesterolemia and eGFR between defined high- and low-risk patient groups.

Strengths

• Model performance was validated internally with a 7:3 training/validation split on 631 participants.
• Model evaluation includes multiple metrics: AUC for 1-, 3-, and 5-year risks, calibration curves, C-index, and decision curve analysis.
• Data includes longitudinal follow-up, allowing for time-to-event analysis for hyperuricemia.

Limitations

• Row count and column-level documentation are unknown, which may limit suitability assessment.
• Data is specific to a single hospital in Hangzhou, China, which may limit generalizability.
• The dataset is very small at 24.1 KB, indicating limited scope.

Provenance

Source

figshare, authored by Wenhui Zhang.

Collection Method

Retrospective longitudinal cohort study of patients treated at Hangzhou Xixi Hospital.

Time Range

July 2016 to December 2024.

Freshness

Last updated 2026-04-16 05:25:11; freshness should be verified.

Geography

Hangzhou, China.