Evidence map›Paper›PMID 40205949›Full record

ArticleClinical chemistry and laboratory medicine2025

Cell population data for early detection of sepsis in patients with suspected infection in the emergency department.

Marta Cancella De Abreu, Caren Brumpt, Timothé Sala, Nathalie Oueidat, Martin Larsen, Pierre Hausfater

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Article in Clinical chemistry and laboratory medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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.

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

Who cites it

4 citing papers in PubMed.

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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

6 authors.

Marta Cancella De AbreuEmergency Department, APHP-Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France.ORCID 0000-0001-7218-8485
Caren BrumptHematology Department, APHP-Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France.
Timothé SalaEmergency Department, APHP-Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France.
Nathalie OueidatMetabolic and Biochemical Department, APHP-Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France.
Martin LarsenSorbonne University, Centre D'Immunologie et des Maladies Infectieuses (CIMI Paris), Paris, France.
Pierre HausfaterEmergency Department, APHP-Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTraditional biomarkers used for sepsis diagnosis have limited sensitivity and specificity and, so far, are not recommended for sepsis diagnosis. We aimed to evaluate diagnostic accuracy of XN-9000

methodsWe conducted a cross-sectional cohort study on patients admitted to an emergency department (ED) with a suspicion of infection, having a complete blood count with differential (CBC-Diff). CBC-Diff were performed on XN-9000

resultsA total of 1,155 patients with a suspicion of infection were included and 230 had sepsis. Median age was 64 years and 49 % were female. Except for lymphocyte count with an area under the receiver operating characteristic (AUROC) of 0.67 (95 % confidential interval 0.63-0.70), the other CPD exhibited modest performances with AUROC under 0.65. The ICIS and NEMO scores had a modest performance with AUROC of 0.56 (0.52-0.61) and 0.55 (0.51-0.59) respectively.

conclusionsNone of the biomarkers and scores tested demonstrated sufficient diagnostic accuracy to be recommended for routine sepsis screening in the ED.

Indexed as

Emergency Service, HospitalSepsisAdultAgedBiomarkersBlood Cell CountCohort StudiesCross-Sectional StudiesEarly DiagnosisFemaleHumansMaleMiddle AgedROC CurveBiomarkersbiomarkerscell population datacomplete blood count with differentialdiagnosisemergency departmentsepsis

Identifiers

PMID40205949

What OpenQuestion holds

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Registered trials

None linked

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.