Identifying Hemophagocytic Lymphohistiocytosis and Describing Outcomes Using Computable Phenotypes: Retrospective Cohort Study

Constructing HLH cohorts from EHR data is challenging, with diagnosis codes, treatment plans, and clinical criteria each capturing distinct but overlapping populations.

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Publication Details

Journal
JMIR Cancer
Published
2026-03-03
DOI
https://doi.org/10.2196/87347
Primary Topic
Autoimmune and Inflammatory Disorders Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Identifying Hemophagocytic Lymphohistiocytosis and Describing Outcomes Using Computable Phenotypes: Retrospective Cohort Study

Lillian C. Sung, Adam P. Yan, Yi Man, Ahmed Naqvi et al.
JMIR Cancer
Autoimmune and Inflammatory Disorders Research
article

Identifying Hemophagocytic Lymphohistiocytosis and Describing Outcomes Using Computable Phenotypes: Retrospective Cohort Study

Lillian C. Sung, Adam P. Yan, Yi Man, Ahmed Naqvi, Ida Mehrdadi, Sumit Gupta, Agata Wolochacz, Suheyla Ocak
article en

Abstract

Constructing HLH cohorts from EHR data is challenging, with diagnosis codes, treatment plans, and clinical criteria each capturing distinct but overlapping populations.

JMIR CancerVol. 12
Hospital for Sick Children (CA), Istanbul University-Cerrahpaşa (TR), SickKids Foundation (CA), Institute for Clinical Evaluative Sciences (CA)
Zero hunger
Openalex Percentile: Top 36%
Autoimmune and Inflammatory Disorders Research
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