MR Steiger: Maternal Sepsis Burden and Causal Factors, 1990-2021

13.5 KB of data from a study integrating global disease burden trends with causal inference for maternal sepsis and infections (MSMI). The dataset likely contains results from Global Burden of Disease 2021 analyses and two-sample multivariable Mendelian randomization, identifying causal inflammatory biomarkers. It was authored by Anqi Jiang and last updated on 2026-05-27.

Use Cases

• Analyze temporal trends in maternal sepsis burden based on Global Burden of Disease data from 1990 to 2021
• Evaluate causal effects of inflammatory biomarkers on MSMI risk based on multivariable Mendelian randomization results
• Compare forecasting model outputs for MSMI based on ARIMA and Bayesian age–period–cohort methods mentioned in the description

Strengths

• Data integrates population-level trend analysis with causal inference via Mendelian randomization
• Analysis spans a 31-year time range from 1990 to 2021
• Dataset is openly licensed under CC-BY-4.0

Limitations

• Dataset is very small at 13.5 KB, indicating limited scope
• Row count and column-level documentation are unknown
• Description metadata is limited; actual data quality requires manual inspection after download

Provenance

Source

Global Burden of Disease (GBD) 2021 study

Collection Method

Analysis of temporal trends using ARIMA and BAPC models, and two-sample multivariable Mendelian randomization

Time Range

1990 to 2021

Freshness

Last updated 2026-05-27 17:51:39; freshness should be verified

Geography

Global, with focus on low-SDI regions