Evidence mapPaperPMID 42043553Full record

ArticleIntensive care medicine2026

Risk heterogeneity within hypoinflammatory acute respiratory failure: continuous probabilities identify high-risk patients masked by binary classification.

Nanditha Venkatesan, Faraaz Ali Shah, William Bain, Zhiyi Yang, Charles S Dela Cruz, Rebecca M Baron, Benjamin Zuchelkowski, Alicia N Rizzo, Sonia Joshi, Antonio Arciniegas and 8 more

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Article in Intensive 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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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

18 authors.

Nanditha VenkatesanInternal Medicine Residency Program, UPMC Presbyterian/Shadyside, Pittsburgh, USA.
Faraaz Ali ShahDivision of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, UPMC Montefiore Hospital, Pittsburgh, USA.
William BainDivision of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, UPMC Montefiore Hospital, Pittsburgh, USA.
Zhiyi YangDepartment of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, USA.
Charles S Dela CruzDivision of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, UPMC Montefiore Hospital, Pittsburgh, USA.
Rebecca M BaronDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
Benjamin ZuchelkowskiInternal Medicine Residency Program, UPMC Presbyterian/Shadyside, Pittsburgh, USA.
Alicia N RizzoDivision of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, UPMC Montefiore Hospital, Pittsburgh, USA.
Sonia JoshiDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
Antonio ArciniegasDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
Katherin ZambranoDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
Hamam AneisInternal Medicine Residency Program, UPMC McKeesport, McKeesport, USA.
Florian B MayrThe Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) Center, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, USA.
Alison MorrisDivision of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, UPMC Montefiore Hospital, Pittsburgh, USA.
Victor B TalisaDepartment of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, USA.
Bryan J McVerryAcute Lung Injury and Infection Center, University of Pittsburgh, Pittsburgh, USA.
Seyed Mehdi NouraieDivision of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, UPMC Montefiore Hospital, Pittsburgh, USA.
Georgios D KitsiosDivision of Pulmonary, Allergy, Critical Care and Sleep Medicine, University of Pittsburgh, UPMC Montefiore Hospital, Pittsburgh, USA. kitsiosg@upmc.edu.ORCID http://orcid.org/0000-0002-1018-948X

Funding

NHLBI NIH HHS R21 HL168070NIGMS NIH HHS R01 GM141081NIH HHS 1R21 HL168070NIH HHS 5R01 GM141081NIH HHS P01 HL114453NIH HHS R01 176668
6 · The paper itself

Abstract

purposeBinary inflammatory subphenotype classification (hyperinflammatory vs. hypoinflammatory) may guide trial enrollment in acute hypoxemic respiratory failure (AHRF), but assumes within-category homogeneity. We determined whether continuous probabilities reveal clinically meaningful heterogeneity.

methodsWe analyzed 575 critically ill adults with AHRF (Pittsburgh Acute Lung Injury Registry) and validated findings in 1134 patients from the EDEN trial, the COVID-19 cohorts, and the RoCI registry. Continuous subphenotype probabilities were calculated using a parsimonious biomarker model (IL-6, sTNFR-1, bicarbonate; probability threshold 0.5). The primary outcome was 90-day mortality.

resultsAmong 575 patients, 77 patients (13%) were hyperinflammatory and 498 (87%) hypoinflammatory. Hyperinflammatory patients demonstrated prognostic homogeneity (mortality overall 55%, p = 0.72, across tertiles). Hypoinflammatory patients exhibited marked heterogeneity: 90-day mortality increased from 19 to 31% to 40% across probability tertiles (P < 0.001). Restricted cubic spline modeling demonstrated a strong non-linear relationship between continuous probabilities and mortality, with the steepest risk increases occurring below the 0.5 threshold. Clinical severity scores and biomarkers of immune activation increased progressively across hypoinflammatory tertiles (all P < 0.001). Among 330 patients with longitudinal sampling, rising probability trajectories within hypoinflammatory groups predicted 50-100% mortality vs. 16-40% for stable or declining trajectories (all P < 0.001); hyperinflammatory patients had poor outcomes regardless of trajectory. External validation confirmed heterogeneity and preserved non-linear probability-mortality patterns across cohorts. Similar patterns were observed with the procalcitonin-based model.

conclusionsBinary classification obscures substantial prognostic heterogeneity within hypoinflammatory AHRF patients. Continuous probability-based stratification may identify additional trial-eligible high-risk patients and improve enrollment strategies for subphenotype-guided trials.

Indexed as

COVID-19InflammationRespiratory InsufficiencyAgedBiomarkersCritical IllnessFemaleHumansInterleukin-6MaleMiddle AgedProbabilityPrognosisRegistriesRisk AssessmentBiomarkersInterleukin-6Acute lung injuryBiomarkersInflammationPrognosisSubphenotype

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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 Socratic graph.