IgA Antibody Levels and Risk Factors for Severe COVID-19 Pneumonia

An investigation explores relationships between humoral antibodies, including IgA, and established risk factors for severe COVID-19 pneumonia, characterized by the NIH Ordinal Score. The dataset and associated machine learning code were contributed by author David Brett-Major via Harvard Dataverse. It was last updated in April 2026.

Use Cases

• Modeling the NIH Ordinal Score for disease severity using IgA antibody levels as a predictor.
• Investigating the interaction between humoral antibody relationships and other acknowledged clinical risk factors.
• Developing machine learning models to identify patients at high risk for severe pneumonia based on immunological and clinical data.

Strengths

• Dataset is associated with machine learning code for analysis.
• Focuses on a specific clinical outcome (severe pneumonia) using the standardized NIH Ordinal Score.

Limitations

• The number of rows, columns, and sample size are unknown.
• Specific data collection methodology and geographic scope are not detailed.

Provenance

Source

Harvard Dataverse, contributed by David Brett-Major.

Collection Method

Investigation of clinical and immunological factors; specific collection method unknown.

Freshness

Last updated in April 2026.