Evidence map›Paper›PMID 31511662›Full record

ReviewNature reviews. Nephrology2020

Prognostic and predictive enrichment in sepsis.

Natalja L Stanski, Hector R Wong

Registry-linked trialAbstract readReview
In one paragraph

Review in Nature reviews. Nephrology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04904289 (Early Recognition and Dynamic Risk Warning System of Multiple Organ Dysfunction Syndrome Caused by Sepsis), which is not on this map. Cited by 230 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
230citing papers in PubMed, 7 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04904289 unknown statusnot on this mapstarted 2022, after this paper: background citation

Early Recognition and Dynamic Risk Warning System of Multiple Organ Dysfunction Syndrome Caused by Sepsis

TypeobservationalSponsorSun Yat-sen UniversityRan2022 to 2023Enrolled60,000ConditionsSepsis, MODSArmsAll intervention of real world
3 · Its place in the literature

Who cites it

230 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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170 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Natalja L StanskiDivision of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Hector R WongDivision of Critical Care Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. Hector.Wong@cchmc.org.ORCID http://orcid.org/0000-0001-7989-1173

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis is a heterogeneous disease state that is both common and consequential in critically ill patients. Unfortunately, the heterogeneity of sepsis at the individual patient level has hindered advances in the field beyond the current therapeutic standards, which consist of supportive care and antibiotics. This complexity has prompted attempts to develop a precision medicine approach, with research aimed towards stratifying patients into more homogeneous cohorts with shared biological features, potentially facilitating the identification of new therapies. Several investigators have successfully utilized leukocyte-derived mRNA and discovery-based approaches to subgroup patients on the basis of biological similarities defined by transcriptomic signatures. A critical next step is to develop a consensus sepsis subclassification system, which includes transcriptomic signatures as well as other biological and clinical data. This goal will require collaboration among various investigative groups, and validation in both existing data sets and prospective studies. Such studies are required to bring precision medicine to the bedside of critically ill patients with sepsis.

Indexed as

Precision MedicineAcute Kidney InjuryHumansPrognosisRespiratory Distress SyndromeRisk AssessmentSepsisTranscriptomeTreatment Outcome

Identifiers

PMID31511662
PMCPMC7097452

What OpenQuestion holds

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Read underepoch 390

Registered trials

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.