Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 324

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Developing a Clinically Feasible Personalized Medicine Approach to Pediatric Septic Shock

Open access
Wong, Hector R., Cvijanovich, Natalie Z., Anas, Nick, Allen, Geoffrey L., Thomas, Neal J., Bigham, Michael T., Weiss, Scott L., Fitzgerald, Julie, Checchia, Paul A., Meyer, Keith, Shanley, Thomas P., Quasney, Michael, Hall, Mark, Gedeit, Rainer, Freishtat, Robert J., Nowak, Jeffrey, Shekhar, Raj S., Gertz, Shira, Dawson, Emily, Howard, Kelli, Harmon, Kelli, Beckman, Eileen, Frank, Erin, Lindsell, Christopher J.·2015·American Journal of Respiratory and Critical Care Medicine

Abstract

RATIONALE: Using microarray data, we previously identified gene expression-based subclasses of septic shock with important phenotypic differences. The subclass-defining genes correspond to adaptive immunity and glucocorticoid receptor signaling. Identifying the subclasses in real time has theranostic implications, given the potential for immune-enhancing therapies and controversies surrounding adjunctive corticosteroids for septic shock. OBJECTIVES: To develop and validate a real-time subclassification method for septic shock. METHODS: Gene expression data for the 100 subclass-defining genes were generated using a multiplex messenger RNA quantification platform (NanoString nCounter) and visualized using gene expression mosaics. Study subjects (n = 168) were allocated to the subclasses using computer-assisted image analysis and microarray-based reference mosaics. A gene expression score was calculated to reduce the gene expression patterns to a single metric. The method was tested prospectively in a separate cohort (n = 132). MEASUREMENTS AND MAIN RESULTS: The NanoString-based data reproduced two septic shock subclasses. As previously, one subclass had decreased expression of the subclass-defining genes. The gene expression score identified this subclass with an area under the curve of 0.98 (95% confidence interval [CI95] = 0.96-0.99). Prospective testing of the subclassification method corroborated these findings. Allocation to this subclass was independently associated with mortality (odds ratio = 2.7; CI95 = 1.2-6.0; P = 0.016), and adjunctive corticosteroids prescribed at physician discretion were independently associated with mortality in this subclass (odds ratio = 4.1; CI95 = 1.4-12.0; P = 0.011). CONCLUSIONS: We developed and tested a gene expression-based classification method for pediatric septic shock that meets the time constraints of the critical care environment, and can potentially inform therapeutic decisions.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1164/rccm.201410-1864oc

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

See all 324

Metadata

Authors
Wong, H. R., Cvijanovich, N. Z., Anas, N., Allen, G. L., Thomas, N. J., Bigham, M. T., Weiss, S. L., Fitzgerald, J., Checchia, P. A., Meyer, K., Shanley, T. P., Quasney, M., Hall, M., Gedeit, R., Freishtat, R. J., Nowak, J., Shekhar, R. S., Gertz, S., Dawson, E., Howard, K., Harmon, K., Beckman, E., Frank, E., & Lindsell, C. J.
Venue
American Journal of Respiratory and Critical Care Medicine
Published
2015-02-01
Volume
191
Issue
3
Pages
309-315
ISSN
  • 1073-449X (ISSN-L)
  • 1535-4970
OpenAlex
W2135993691
Cited by
324
References
2
FWCI
17.98
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Developing a Clinically Feasible Personalized Medicine Approach to Pediatric Septic Shock. https://app.cochat.ai/papers/10.1164/rccm.201410-1864oc
The paper
Wong, H. R., Cvijanovich, N. Z., Anas, N., Allen, G. L., Thomas, N. J., Bigham, M. T., Weiss, S. L., Fitzgerald, J., Checchia, P. A., Meyer, K., Shanley, T. P., Quasney, M., Hall, M., Gedeit, R., Freishtat, R. J., Nowak, J., Shekhar, R. S., Gertz, S., Dawson, E., . . . Lindsell, C. J. (2015). Developing a Clinically Feasible Personalized Medicine Approach to Pediatric Septic Shock. American Journal of Respiratory and Critical Care Medicine. https://doi.org/10.1164/rccm.201410-1864oc

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.