Development and External Validation of Models to Predict Persistent Hypoxemic Respiratory Failure for Clinical Trial Enrichment

Copyright © 2024 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved..

OBJECTIVES: Improving the efficiency of clinical trials in acute hypoxemic respiratory failure (HRF) depends on enrichment strategies that minimize enrollment of patients who quickly resolve with existing care and focus on patients at high risk for persistent HRF. We aimed to develop parsimonious models predicting risk of persistent HRF using routine data from ICU admission and select research immune biomarkers.

DESIGN: Prospective cohorts for derivation ( n = 630) and external validation ( n = 511).

SETTING: Medical and surgical ICUs at two U.S. medical centers.

PATIENTS: Adults with acute HRF defined as new invasive mechanical ventilation (IMV) and hypoxemia on the first calendar day after ICU admission.

INTERVENTIONS: None.

MEASUREMENTS AND MAIN RESULTS: We evaluated discrimination, calibration, and practical utility of models predicting persistent HRF risk (defined as ongoing IMV and hypoxemia on the third calendar day after admission): 1) a clinical model with least absolute shrinkage and selection operator (LASSO) selecting Pa o2 /F io2 , vasopressors, mean arterial pressure, bicarbonate, and acute respiratory distress syndrome as predictors; 2) a model adding interleukin-6 (IL-6) to clinical predictors; and 3) a comparator model with Pa o2 /F io2 alone, representing an existing strategy for enrichment. Forty-nine percent and 69% of patients had persistent HRF in derivation and validation sets, respectively. In validation, both LASSO (area under the receiver operating characteristic curve, 0.68; 95% CI, 0.64-0.73) and LASSO + IL-6 (0.71; 95% CI, 0.66-0.76) models had better discrimination than Pa o2 /F io2 (0.64; 95% CI, 0.59-0.69). Both models underestimated risk in lower risk deciles, but exhibited better calibration at relevant risk thresholds. Evaluating practical utility, both LASSO and LASSO + IL-6 models exhibited greater net benefit in decision curve analysis, and greater sample size savings in enrichment analysis, compared with Pa o2 /F io2 . The added utility of LASSO + IL-6 model over LASSO was modest.

CONCLUSIONS: Parsimonious, interpretable models that predict persistent HRF may improve enrichment of trials testing HRF-targeted therapies and warrant future validation.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:52

Enthalten in:

Critical care medicine - 52(2024), 5 vom: 01. Apr., Seite 764-774

Sprache:

Englisch

Beteiligte Personen:

Sathe, Neha A [VerfasserIn]
Zelnick, Leila R [VerfasserIn]
Morrell, Eric D [VerfasserIn]
Bhatraju, Pavan K [VerfasserIn]
Kerchberger, V Eric [VerfasserIn]
Hough, Catherine L [VerfasserIn]
Ware, Lorraine B [VerfasserIn]
Fohner, Alison E [VerfasserIn]
Wurfel, Mark M [VerfasserIn]

Links:

Volltext

Themen:

Interleukin-6
Journal Article

Anmerkungen:

Date Completed 16.04.2024

Date Revised 25.04.2024

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1097/CCM.0000000000006181

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM366883291