In:
PLOS ONE, Public Library of Science (PLoS), Vol. 16, No. 11 ( 2021-11-29), p. e0260551-
Abstract:
Central 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. Methods Derivation 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/mm 3 , 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). Results The 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). Conclusions A 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.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0260551
DOI:
10.1371/journal.pone.0260551.g001
DOI:
10.1371/journal.pone.0260551.g002
DOI:
10.1371/journal.pone.0260551.g003
DOI:
10.1371/journal.pone.0260551.t001
DOI:
10.1371/journal.pone.0260551.t002
DOI:
10.1371/journal.pone.0260551.t003
DOI:
10.1371/journal.pone.0260551.s001
DOI:
10.1371/journal.pone.0260551.s002
DOI:
10.1371/journal.pone.0260551.s003
DOI:
10.1371/journal.pone.0260551.s004
DOI:
10.1371/journal.pone.0260551.s005
DOI:
10.1371/journal.pone.0260551.r001
DOI:
10.1371/journal.pone.0260551.r002
DOI:
10.1371/journal.pone.0260551.r003
DOI:
10.1371/journal.pone.0260551.r004
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2021
detail.hit.zdb_id:
2267670-3
