Evidence map›Paper›PMID 42704284›Full record

ArticleCritical care medicine2026

Evaluation of a Rapid Immunoassay for Molecular Subphenotype Classification in Pediatric Acute Cardiorespiratory Failure.

Colin J Sallee, Clove S Taylor, Matt S Zinter, Daniela Markovic, Michelle J Lim, Ana Costa Monteiro, Ruth Cortado, Andreas Schwingshackl, Michael Agus, Michael Matthay and 1 more

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Article in Critical care medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Colin J SalleeDivision of Pediatric Critical Care Medicine, Department of Pediatrics, University of California Los Angeles, Los Angeles, CA.ORCID 0000-0002-2834-2657
Clove S TaylorDivision of Pediatric Critical Care Medicine, Department of Pediatrics, University of California Los Angeles, Los Angeles, CA.
Matt S ZinterDepartment of Pediatrics, University of California San Francisco, San Francisco, CA.
Daniela MarkovicDivision of General Internal Medicine and Health Sciences Research, Department of Medicine, University of California Los Angeles, Los Angeles, CA.
Michelle J LimDepartment of Pediatrics, University of California Davis, Sacramento, CA.
Ana Costa MonteiroDivision of General Internal Medicine and Health Sciences Research, Department of Medicine, University of California Los Angeles, Los Angeles, CA.
Ruth CortadoDivision of Pediatric Critical Care Medicine, Department of Pediatrics, University of California Los Angeles, Los Angeles, CA.
Andreas SchwingshacklDivision of Pediatric Critical Care Medicine, Department of Pediatrics, University of California Los Angeles, Los Angeles, CA.
Michael AgusDepartment of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, MA.
Michael MatthayCardiovascular Research Institute (CVRI), Departments of Medicine and Anesthesia, University of California San Francisco, San Francisco, CA.
Anil SapruDivision of Pediatric Critical Care Medicine, Department of Pediatrics, University of California Los Angeles, Los Angeles, CA.ORCID 0000-0003-1528-8249

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesMolecular subphenotypes, identified through latent class analysis (LCA) of biomarker profiles, have the potential to guide targeted therapeutics in critical care. We have previously published that intensive insulin management has subphenotype-specific beneficial effects among children with hyperglycemia accompanying cardiorespiratory failure. However, the real-time application of subphenotype-based strategies in clinical settings remains challenging due to the operational aspects of biomarker assays. Our study had three objectives: 1) to compare biomarker measurements from rapid immunoassay and conventional multiplex platforms; 2) to evaluate the cross-platform transportability of a conventional assay-based parsimonious classifier for LCA-derived subphenotypes and compare it with a classifier trained directly on rapid immunoassay data; and 3) to assess the prognostic and predictive significance of rapid immunoassay-based subphenotypes.

designRetrospective cohort study.

settingMulticenter PICUs. PATIENTS: Two hundred sixty-nine critically ill children with acute cardiorespiratory failure and hyperglycemia (2012-2016).

interventionsNone. MEASUREMENTS AND MAIN

resultsLCA was previously used to derive hyperinflammatory and hypoinflammatory classes using a conventional multiplex assay of 13 plasma biomarkers. After feature selection, a parsimonious classifier using interleukin (IL)-6, IL-8, and soluble tumor necrosis factor receptor 1 (sTNFR-1) was developed to predict LCA-derived subphenotypes. We applied this classifier to rapid immunoassay biomarker measurements, yielding an area under the receiver operating characteristic curve (AUROC) of 0.90 (95% CI, 0.85-0.95). However, calibration was poor due to systematic underestimation of sTNFR-1 concentrations by the rapid platform. We then derived and internally validated via bootstrapping a de novo classifier using rapid immunoassay data, achieving an AUROC of 0.90 (95% CI, 0.86-0.95) and excellent calibration. Using a probability threshold of ≥ 0.5, the de novo classifier matched LCA-derived classifications in 241 of 269 cases (accuracy 89.6%). Rapid immunoassay-based subphenotypes demonstrated differences in mortality (33.3% in hyperinflammatory vs. 11.8% in hypoinflammatory; p = 0.009) and differential response to intensive insulin management (interaction p = 0.024).

conclusionsA parsimonious, rapid immunoassay-based classifier can approximate LCA-derived molecular subphenotypes while preserving their prognostic and predictive significance, with the potential to inform future subphenotype-based precision trials.

Indexed as

biological heterogeneityclinical trialsmolecular subphenotypingprecision medicinerapid immunoassay

Identifiers

PMID42704284

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.