Evidence map›Paper›PMID 34843551›Full record

Observational studyPloS one2021

Central nervous system infection in the intensive care unit: Development and validation of a multi-parameter diagnostic prediction tool to identify suspected patients.

Hugo Boechat Andrade, Ivan Rocha Ferreira da Silva, Justin Lee Sim, José Henrique Mello-Neto, Pedro Henrique Nascimento Theodoro, Mayara Secco Torres da Silva, Margareth Catoia Varela, Grazielle Viana Ramos, Aline Ramos da Silva, Fernando Augusto Bozza and 5 more

Abstract readObservational Study
In one paragraph

Observational study in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Hugo Boechat AndradeIntensive Care Unit, Evandro Chagas National Institute of Infectious Diseases (INI), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, RJ, Brazil.ORCID 0000-0001-6781-6125
Ivan Rocha Ferreira da SilvaDepartment of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States of America.ORCID 0000-0001-8572-9631
Justin Lee SimDepartment of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States of America.
José Henrique Mello-NetoIntensive Care Unit, Evandro Chagas National Institute of Infectious Diseases (INI), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, RJ, Brazil.
Pedro Henrique Nascimento TheodoroIntensive Care Unit, Evandro Chagas National Institute of Infectious Diseases (INI), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, RJ, Brazil.ORCID 0000-0003-3197-2999
Mayara Secco Torres da SilvaIntensive Care Unit, Evandro Chagas National Institute of Infectious Diseases (INI), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, RJ, Brazil.
Margareth Catoia VarelaImmunization and Health Surveillance Research Laboratory, Evandro Chagas National Institute of Infectious Diseases (INI), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, RJ, Brazil.ORCID 0000-0002-8161-1158
Grazielle Viana RamosDepartment of Critical Care, D'Or Institute for Research and Education, Rio de Janeiro, RJ, Brazil.
Aline Ramos da SilvaDepartment of Critical Care, D'Or Institute for Research and Education, Rio de Janeiro, RJ, Brazil.
Fernando Augusto BozzaIntensive Care Unit, Evandro Chagas National Institute of Infectious Diseases (INI), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, RJ, Brazil.ORCID 0000-0003-4878-0256
Jesus SoaresDivision of High-Consequence Pathology and Pathogens, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States of America.ORCID 0000-0002-8640-8618
Ermias D BelayDivision of High-Consequence Pathology and Pathogens, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States of America.
James J SejvarDivision of High-Consequence Pathology and Pathogens, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States of America.
José Cerbino-NetoImmunization and Health Surveillance Research Laboratory, Evandro Chagas National Institute of Infectious Diseases (INI), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, RJ, Brazil.ORCID 0000-0001-9254-917X
André Miguel JapiassúIntensive Care Unit, Evandro Chagas National Institute of Infectious Diseases (INI), Oswaldo Cruz Foundation (Fiocruz), Rio de Janeiro, RJ, Brazil.ORCID 0000-0002-9444-9890

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCentral nervous system infections (CNSI) are diseases with high morbidity and mortality, and their diagnosis in the intensive care environment can be challenging. Objective: To develop and validate a diagnostic model to quickly screen intensive care patients with suspected CNSI using readily available clinical data.

methodsDerivation cohort: 783 patients admitted to an infectious diseases intensive care unit (ICU) in Oswaldo Cruz Foundation, Rio de Janeiro RJ, Brazil, for any reason, between 01/01/2012 and 06/30/2019, with a prevalence of 97 (12.4%) CNSI cases. Validation cohort 1: 163 patients prospectively collected, between 07/01/2019 and 07/01/2020, from the same ICU, with 15 (9.2%) CNSI cases. Validation cohort 2: 7,270 patients with 88 CNSI (1.21%) admitted to a neuro ICU in Chicago, IL, USA between 01/01/2014 and 06/30/2019. Prediction model: Multivariate logistic regression analysis was performed to construct the model, and Receiver Operating Characteristic (ROC) curve analysis was used for model validation. Eight predictors-age <56 years old, cerebrospinal fluid white blood cell count >2 cells/mm3, fever (≥38°C/100.4°F), focal neurologic deficit, Glasgow Coma Scale <14 points, AIDS/HIV, and seizure-were included in the development diagnostic model (P<0.05).

resultsThe pool data's model had an Area Under the Receiver Operating Characteristics (AUC) curve of 0.892 (95% confidence interval 0.864-0.921, P<0.0001).

conclusionsA promising and straightforward screening tool for central nervous system infections, with few and readily available clinical variables, was developed and had good accuracy, with internal and external validity.

Indexed as

AdultAgedBrazilCentral Nervous System InfectionsChicagoCritical CareFemaleGlasgow Coma ScaleHumansIntensive Care UnitsLogistic ModelsMaleMiddle AgedMultivariate AnalysisPrognosisRetrospective Studies

Identifiers

PMID34843551
PMCPMC8629274

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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.