Combined Immunoglobulin Free Light Chains Are Novel Predictors of Cardiovascular Events in Patients With Abdominal Aortic Aneurysm

Coronary health index based on immunoglobulin light chains to assess coronary heart disease risk with machine learning: a diagnostic trial

BACKGROUND

Recent studies suggest a connection between immunoglobulin light chains (IgLCs) and coronary heart disease (CHD). However, current diagnostic methods using peripheral blood IgLCs levels or subtype ratios show limited accuracy for CHD, lacking comprehensive assessment and posing challenges in early detection and precise disease severity evaluation. We aim to develop and validate a Coronary Health Index (CHI) incorporating total IgLCs levels and their distribution. Additionally, we aim to evaluate its effectiveness by integrating patient data and using machine learning models through diagnostic trial.

METHODS

The CHI was developed and combined with other clinical data. Nine machine learning models were screened to identify optimal diagnostic performance, with the XGBoost model emerging as the top performer. Performance was assessed based on accuracy, sensitivity, and its ability to identify severe CHD cases characterized by complex lesions (SYNTAX score > 33).

RESULTS

The XGBoost model demonstrated high accuracy and sensitivity in diagnosing CHD, with an area under the curve (AUC) of 0.927. It also accurately identified patients with severe CHD, achieving an AUC of 0.991. An online web tool was introduced for broader external validation, confirming the model's effectiveness.

CONCLUSIONS

Combining the CHI with the XGBoost model offers significant advantages in diagnosing CHD and assessing disease severity. This approach can guide clinical interventions and improve large-scale CHD screening.

Blood immunological profile of abdominal aortic aneurysm based on autoimmune injury

Abdominal aortic aneurysm (AAA) occupies a large part of aorta aneurysm, and if there's no timely intervention or treatment, the risks of rupture and death would rise sharply. With the depth of research in AAA, more and more evidence showed correlations between AAA and autoimmune injury. Currently, a variety of bioactive peptides and cells have been confirmed to be related with AAA progression. Despite the tremendous progress, more than half researches were sampling from lesion tissues, which would be difficult to obtain. Given that the intrusiveness and convenience, serological test take advantages in initial diagnosis. Here we review blood biomarkers associated with autoimmune injury work in AAA evolution, aiming to make a profile on blood immune substances of AAA and provide a thought for potential clinical practice.