Metabolomic machine learning predictor for the diagnosis of aspiration pneumonia
Abstract
Aspiration pneumonia (AP) is a common disease, particularly among the elderly, and is diagnostically challenging due to its non-specific presentation and lack of a diagnostic gold standard or reliable biomarkers. Metabolomics may enable accurate non-invasive diagnosis. To address this gap, this study aims to develop and validate metabolomic machine learning models for AP diagnosis within a multicenter prospective observational cohort.
We enrolled 121 patients (Cohort 1) with AP or non-aspiration pneumonia (NonAP), nearly all of whom were from the intensive care unit. Non-targeted metabolomic profiling of serum, bronchoalveolar lavage fluid, and sputum was performed using liquid chromatography–mass spectrometry. Machine learning models were constructed for each biofluid. We also measured peripheral blood cytokines and built corresponding diagnostic models, against which the performance of the metabolomic models was compared. The optimal serum model was subsequently validated using targeted metabolomics in 175 patients.
In Cohort 1, distinct metabolic profiles distinguished AP from NonAP patients across all sample types. The serum-based model demonstrated superior diagnostic performance (area under the receiver operating characteristic curve (AUROC) 0.973) compared to bronchoalveolar lavage fluid and sputum models. A cytokine-only model performed poorly (AUROC 0.700), and integrating cytokines with metabolomics did not improve accuracy. Consequently, the serum biomarker panel…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 175 participants or records.
Read the paper
Related studies
- Diagnosis and management of glutaric aciduria type I – revised recommendations
- EZH2 Codon 641 Mutations are Common in BCL2-Rearranged Germinal Center B Cell Lymphomas
- Consensus guidelines for the diagnosis and management of pyridoxine‐dependent epilepsy due to α‐aminoadipic semialdehyde dehydrogenase deficiency
- Systemic Metabolomic Changes in Blood Samples of Lung Cancer Patients Identified by Gas Chromatography Time-of-Flight Mass Spectrometry
- Human OTULIN haploinsufficiency impairs cell-intrinsic immunity to staphylococcal α-toxin
- Discovery of Novel Recurrent Mutations in Childhood Early T-Cell Precursor Acute Lymphoblastic Leukemia by Whole Genome Sequencing - a Report From the St Jude Children's Research Hospital - Washington University Pediatric Cancer Genome Project
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.