Evidence map›Paper›PMID 33675432›Full record

ArticleAnnals of intensive care2021

Ability of procalcitonin to distinguish between bacterial and nonbacterial infection in severe acute exacerbation of chronic obstructive pulmonary syndrome in the ICU.

Cédric Daubin, François Fournel, Fabrice Thiollière, Fabrice Daviaud, Michel Ramakers, Andréa Polito, Bernard Flocard, Xavier Valette, Damien Du Cheyron, Nicolas Terzi and 4 more

Open access · goldAbstract read
In one paragraph

Article in Annals of intensive care, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

8 citing papers in PubMed, 13 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

14 authors at 8 institutions in 2 countries.

Cédric DaubinDepartment of Medical Intensive Care, CHU de Caen, 14000, Caen, France. daubin-c@chu-caen.fr.ORCID https://orcid.org/0000-0002-3898-6296
François FournelDepartment of Biostatistics and Clinical Research, CHU de Caen, 14000, Caen, France.
Fabrice ThiollièreIntensive Care Unit, Centre Hospitalier Lyon Sud, Pierre Bénite, Hospices Civils de Lyon, France.
Fabrice DaviaudDepartment of Medial Intensive Care, Cochin University Hospital, Paris, France.
Michel RamakersDepartment of Intensive Care Medicine, General Hospital, Saint Lô, France.
Andréa PolitoService de Médecine Intensive Et Réanimation, General Intensive Care Unit, Hôpital Raymond Poincaré (APHP), Raymond Poincaré Hospital, Garches, France.
Bernard FlocardDepartment of Anesthesiology and Critical Care Medicine, Edouard Herriot Hospital, Hospices Civils de Lyon, Lyon, France.
Xavier ValetteDepartment of Medical Intensive Care, CHU de Caen, 14000, Caen, France.
Damien Du CheyronDepartment of Medical Intensive Care, CHU de Caen, 14000, Caen, France.
Nicolas TerziDepartment of Medical Intensive Care, CHU de Grenoble Alpes, 38000, Grenoble, France.
Muriel FartoukhService de Medecine Intensive Reanimation, AP-HP, Sorbonne université, Hôpital Tenon, Groupe de Recherche Clinique CARMAS, collegium Gallilée, Paris, France.
Stephane AlloucheUniversite Caen Normandie, Medical School, EA 4650, Signalisation, Electrophysiologie et Imagerie des lésions d'Ischemie-reperfusion Myocardique, 14000, Caen, France.
Jean-Jacques ParientiDepartment of Biostatistics and Clinical Research, CHU de Caen, 14000, Caen, France.
from the PROCALCIVIR and BPCTrea study group
Centre Hospitalier Universitaire de Caen Normandie · FRHôpital Cochin · FRHospices Civils de Lyon · FRInserm · FRCentre Hospitalier Universitaire de Grenoble · FRInstitut thématique Immunologie, inflammation, infectiologie et microbiologie · FRNormandie Université · FRSorbonne Université · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo assess the ability of procalcitonin (PCT) to distinguish between bacterial and nonbacterial causes of patients with severe acute exacerbation of COPD (AECOPD) admitted to the ICU, we conducted a retrospective analysis of two prospective studies including 375 patients with severe AECOPD with suspected lower respiratory tract infections. PCT levels were sequentially assessed at the time of inclusion, 6 h after and at day 1, using a sensitive immunoassay. The patients were classified according to the presence of a documented bacterial infection (including bacterial and viral coinfection) (BAC + group), or the absence of a documented bacterial infection (i.e., a documented viral infection alone or absence of a documented pathogen) (BAC- group). The accuracy of PCT levels in predicting bacterial infection (BAC + group) vs no bacterial infection (BAC- group) at different time points was evaluated by receiver operating characteristic (ROC) analysis.

resultsRegarding the entire cohort (n = 375), at any time, the PCT levels significantly differed between groups (Kruskal-Wallis test, p < 0.001). A pairwise comparison showed that PCT levels were significantly higher in patients with bacterial infection (n = 94) than in patients without documented pathogens (n = 218) (p < 0.001). No significant difference was observed between patients with bacterial and viral infection (n = 63). For example, the median PCT-H

conclusionDespite higher PCT levels in severe AECOPD caused by bacterial infection, PCT had a poor accuracy to distinguish between bacterial and nonbacterial infection. Procalcitonin might not be sufficient as a standalone marker for initiating antibiotic treatment in this setting.

Indexed as

Antibiotic stewardshipChronic obstructive pulmonary diseaseCommunity-acquired pneumoniaProcalcitoninRespiratory tract infectionViral infection

Identifiers

PMID33675432
PMCPMC7936235
OpenAlexW3135448413

What OpenQuestion holds

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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 OpenQuestion graph.