Evidence map›Paper›PMID 21539743›Full record

Trial reportBMC infectious diseases2011

Enhancement of CURB65 score with proadrenomedullin (CURB65-A) for outcome prediction in lower respiratory tract infections: derivation of a clinical algorithm.

Werner C Albrich, Frank Dusemund, Kristina Rüegger, Mirjam Christ-Crain, Werner Zimmerli, Thomas Bregenzer, Sarosh Irani, Ulrich Buergi, Barbara Reutlinger, Beat Mueller and 1 more

Registry-linked trialOpen access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC infectious diseases, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03651635 (To Assess and Validate the Use of MR-proADM and the CT-proET-1/MR-proADM Ratio as Prognostic Markers During the First 7 Days of ICU Treat-ment), which is not on this map. Cited by 38 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 1 pooled it
11.0field-weighted citation impact, top 1% 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.

NCT03651635 completednot on this mapstarted 2018, after this paper: background citation

To Assess and Validate the Use of MR-proADM and the CT-proET-1/MR-proADM Ratio as Prognostic Markers During the First 7 Days of ICU Treat-ment

TypeobservationalSponsorUniversity of ZurichRan2018 to 2019Enrolled533ConditionsAcute Phase Biomarkers, Medical ICU Admitted PatientsArmsBlood sampling for MR-proADM & CT-proET-1
3 · Its place in the literature

Who cites it

38 citing papers in PubMed, 1 synthesis or guideline pooled it, 121 citations in OpenAlex.

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  15. Proadrenomedullin Predicts Severe Disease in Children With Suspected Community-acquired Pneumonia.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021
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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

11 authors at 5 institutions in 2 countries.

Werner C AlbrichMedical University Department of the University of Basel, Kantonsspital Aarau, Switzerland.
Frank Dusemund
Kristina Rüegger
Mirjam Christ-Crain
Werner Zimmerli
Thomas Bregenzer
Sarosh Irani
Ulrich Buergi
Barbara Reutlinger
Beat Mueller
Philipp Schuetz
Kantonsspital Aarau · CHHarvard University · USKantonsspital Baselland · CHUniversity Hospital of Basel · CHUniversity of Basel · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProadrenomedullin (ProADM) confers additional prognostic information to established clinical risk scores in lower respiratory tract infections (LRTI). We aimed to derive a practical algorithm combining the CURB65 score with ProADM-levels in patients with community-acquired pneumonia (CAP) and non-CAP-LRTI.

methodsWe used data of 1359 patients with LRTI enrolled in a multicenter study. We chose two ProADM cut-off values by assessing the association between ProADM levels and the risk of adverse events and mortality. A composite score (CURB65-A) was created combining CURB65 classes with ProADM cut-offs to further risk-stratify patients.

resultsCURB65 and ProADM predicted both adverse events and mortality similarly well in CAP and non-CAP-LRTI. The combined CURB65-A risk score provided better prediction of death and adverse events than the CURB65 score in the entire cohort and in CAP and non-CAP-LRTI patients. Within each CURB65 class, higher ProADM-levels were associated with an increased risk of adverse events and mortality. Overall, risk of adverse events (3.9%) and mortality (0.65%) was low for patients with CURB65 score 0-1 and ProADM ≤0.75 nmol/l (CURB65-A risk class I); intermediate (8.6% and 2.6%, respectively) for patients with CURB65 score of 2 and ProADM ≤1.5 nmol/l or CURB classes 0-1 and ProADM levels between 0.75-1.5 nmol/L (CURB65-A risk class II), and high (21.6% and 9.8%, respectively) for all other patients (CURB65-A risk class III). If outpatient treatment was recommended for CURB65-A risk class I and short hospitalization for CURB65-A risk class II, 17.9% and 40.8% of 1217 hospitalized patients could have received ambulatory treatment or a short hospitalization, respectively.

conclusionsThe new CURB65-A risk score combining CURB65 risk classes with ProADM cut-off values accurately predicts adverse events and mortality in patients with CAP and non-CAP-LRTI. Additional prospective cohort or intervention studies need to validate this score and demonstrate its safety and efficacy for the management of patients with LRTI.

trial registrationProcalcitonin-guided antibiotic therapy and hospitalisation in patients with lower respiratory tract infections: the prohosp study; isrctn.org Identifier: ISRCTN: ISRCTN95122877.

Indexed as

AdrenomedullinProtein PrecursorsAgedAged, 80 and overAlgorithmsCohort StudiesFemaleHumansMaleMiddle AgedPredictive Value of TestsPrognosisRespiratory Tract InfectionsAdrenomedullinproadrenomedullinProtein Precursors

Identifiers

PMID21539743
PMCPMC3119069
OpenAlexW2109068302

What OpenQuestion holds

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LicenceCC BY
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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.