Article

A Machine Learning-Derived “Cryptic Shock” Phenotype Provides Incremental Prognostic Value and Supports Bedside Risk Stratification in Elderly Mechanically Ventilated Patients: A Multicenter Study with External Validation

2026-06-05

Abstract excerpt

<title>Abstract</title> <p> <bold>Background</bold> Traditional severity scoring systems heavily weight overt macro-hemodynamic instability, potentially overlooking "cryptic shock" in elderly critically ill patients with blunted physiological responses. We aimed to identify machine learning-derived clinical phenotypes in elderly mechanically ventilated patients and evaluate their incremental prognostic value be...

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Literature Corpus work: 86a2082e-31f2-5316-a36c-e8c9aa2ec0f6
DOI: 10.21203/rs.3.rs-9450676/v1

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A Machine Learning-Derived “Cryptic Shock” Phenotype Provides Incremental Prognostic Value and Supports Bedside Risk Stratification in Elderly Mechanically Ventilated Patients: A Multicenter Study with External ValidationDOI 10.21203/rs.3.rs-9450676/v1Read

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