Evidence map›Paper›PMID 37608883›Full record

ArticleJournal of inflammation research2023

Lymphocyte to C-Reactive Protein Ratio as an Early Biomarker to Distinguish Sepsis from Pneumonia in Neonates.

Xinrui Liu, Yuan Mu

Open access · goldAbstract read
In one paragraph

Article in Journal of inflammation research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
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

7 citing papers in PubMed, 11 citations in OpenAlex.

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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

2 authors at 2 institutions in 1 country.

Xinrui LiuZhengzhou Key Laboratory of Children's Infection and Immunity, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou, People's Republic of China.
Yuan MuInstitute of Thermology, Henan Institute of Metrology and Testing Sciences, Zhengzhou, People's Republic of China.
Shandong Institute of Metrology · CNZhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Neonatal sepsis is an acute and severe disease that seriously threatens the life and health of newborns. Neonates with pneumonia may also have unrecognized neonatal sepsis. Early diagnosis of neonatal sepsis is beneficial for early treatment. This study aimed to evaluate the clinical significance of the lymphocyte-to-C-reactive protein ratio (LCR) as an early biomarker to distinguish sepsis from pneumonia. Methods: This retrospective study enrolled 1635 neonates with pneumonia from February 2016 to March 2022. Among them, 182 cases were diagnosed with sepsis based on the positive blood culture results. Clinical and laboratory data were extracted from the electronic medical records. LCR was calculated as the ratio of the total lymphocyte count (×10 Results: The neonates with pneumonia combined with sepsis had a lower LCR than that of the neonates with pneumonia. Further analysis showed that the prevalence of neonatal pneumonia combined with sepsis was significantly higher in the low-LCR group than in the high-LCR group (20.7% vs 5.5%, P < 001). Binary logistic regression revealed that LCR was an independent risk factor for identifying pneumonia combined with sepsis. The ROC curve analysis revealed that LCR had better power than the lymphocyte count and CRP level individually in diagnosing neonatal pneumonia combined with sepsis (0.72 vs 0.65 vs 0.66, P < 0.001), with 62% sensitivity and 72% specificity. Conclusion: LCR can be a potential early biomarker in distinguishing neonates with sepsis from those with pneumonia.

Indexed as

lymphocyte to C-reactive protein rationeonatespneumoniasepsis

Identifiers

PMID37608883
PMCPMC10441656
OpenAlexW4385852210

What Socratic holds

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LicenceCC BY-NC
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Registered trials

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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.