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  3. Discriminative performance of pancreatic stone protein in predicting ICU mortality and infection severity in adult patients with infection: a systematic review and individual patient level meta-analysis.
 

Discriminative performance of pancreatic stone protein in predicting ICU mortality and infection severity in adult patients with infection: a systematic review and individual patient level meta-analysis.

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BORIS DOI
10.48350/186330
Date of Publication
December 2023
Publication Type
Article
Division/Institute

Universitätsklinik fü...

Department of Clinica...

Contributor
Zürcher, Patrick
Universitätsklinik für Intensivmedizin
Moser, Andréorcid-logo
Department of Clinical Research (DCR) - Statistics & Methodology
Clinical Trials Unit Bern (CTU) - Statistics & Methodology
Department of Clinical Research (DCR)
Garcia de Guadiana-Romualdo, Luis
Llewelyn, Martin J
Graf, Rolf
Reding, Theresia
Eggimann, Philippe
Que, Yok-Aiorcid-logo
Universitätsklinik für Intensivmedizin
Prazak, Josef
Universitätsklinik für Intensivmedizin
Subject(s)

600 - Technology::610...

Series
Infection
ISSN or ISBN (if monograph)
0300-8126
Publisher
Springer
Language
English
Publisher DOI
10.1007/s15010-023-02093-w
PubMed ID
37707744
Uncontrolled Keywords

Biomarker Infection M...

Description
BACKGROUND

Several studies suggested pancreatic stone protein (PSP) as a promising biomarker to predict mortality among patients with severe infection. The objective of the study was to evaluate the performance of PSP in predicting intensive care unit (ICU) mortality and infection severity among critically ill adults admitted to the hospital for infection.

METHODS

A systematic search across Cochrane Central Register of Controlled Trials and MEDLINE databases (1966 to February 2022) for studies on PSP published in English using 'pancreatic stone protein', 'PSP', 'regenerative protein', 'lithostatin' combined with 'infection' and 'sepsis' found 46 records. The search was restricted to the five trials that measured PSP using the enzyme-linked immunosorbent assay technique (ELISA). We used Bayesian hierarchical regression models for pooled estimates and to predict mortality or disease severity using PSP, C-Reactive Protein (CRP) and procalcitonin (PCT) as main predictor. We used statistical discriminative measures, such as the area under the receiver operating characteristic curve (AUC) and classification plots.

RESULTS

Among the 678 patients included, the pooled ICU mortality was 17.8% (95% prediction interval 4.1% to 54.6%) with a between-study heterogeneity (I-squared 87%). PSP was strongly associated with ICU mortality (OR = 2.7, 95% credible interval (CrI) [1.3-6.0] per one standard deviation increase; age, gender and sepsis severity adjusted OR = 1.5, 95% CrI [0.98-2.8]). The AUC was 0.69 for PSP 95% confidence interval (CI) [0.64-0.74], 0.61 [0.56-0.66] for PCT and 0.52 [0.47-0.57] for CRP. The sensitivity was 0.96, 0.52, 0.30 for risk thresholds 0.1, 0.2 and 0.3; respective false positive rate values were 0.84, 0.25, 0.10.

CONCLUSIONS

We found that PSP showed a very good discriminative ability for both investigated study endpoints ICU mortality and infection severity; better in comparison to CRP, similar to PCT. Combinations of biomarkers did not improve their predictive ability.
Handle
https://boris-portal.unibe.ch/handle/20.500.12422/169991
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Zuercher_Infection_2023.pdftextAdobe PDF1.07 MBpublishedOpen
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