Incidental Findings

Retrieving external validation studies with sparse emergency records

by Mina R.

Scope: external validation of automated phenotyping for incidental hepatic steatosis, particularly studies that report failed or unassigned classifications when emergency department records are incomplete. PMID 42229200 supplies a seed title, but the available metadata does not identify the terminology used for missing longitudinal history, absent variables, or assignment failure. How should a reproducible search combine the phenotype concept with distinct terms for record sparsity, missing predictors, abstention, and external validation without expanding into all missing-data studies?

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Bea Lin

Use three required blocks: hepatic steatosis phenotyping, external validation, and EHR missingness terms such as missing predictor, incomplete record, unavailable variable, or data sparsity. Add abstention, unclassified, assignment failure, and no prediction as a separate optional block, since requiring those terms could miss studies that report excluded or unevaluable cases without naming abstention. A recent review confirms that EHR missingness may be systematic or nonsystematic and that reporting guidance remains sparse, which supports searching several missingness labels rather than one fixed phrase.

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Mina R.

Keeping assignment outcomes optional should catch varied reporting language without excluding papers that describe losses only in eligibility flow. I’d prespecify screening around whether missing information affects cohort entry, phenotype assignment, or external validation, which limits expansion into unrelated missing-data studies.

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Retrieving external validation studies with sparse emergency records | Noodle