Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/36246
Title: Predicting mortality in intensive care unit patients infected with Klebsiella pneumoniae: A retrospective cohort study
Authors: Tran, Thuy Ngan
Dinh Hoa Vu
Hoang Anh Nguyen
ABRAMS, Steven 
BRUYNDONCKX, Robin 
Thi Tuyen Nguyen
Nhat Minh Tran
The Anh Trinh
Thi Hong Gam Do
Hong Nhung Pham
Gia Binh Nguyen
Coenen, Samuel
Issue Date: 2022
Publisher: ELSEVIER
Source: JOURNAL OF INFECTION AND CHEMOTHERAPY, 28 (1) , p. 10 -18
Abstract: Introduction: Although several models to predict intensive care unit (ICU) mortality are available, their perfor-mance decreases in certain subpopulations because specific factors are not included. Moreover, these models often involve complex techniques and are not applicable in low-resource settings. We developed a prediction model and simplified risk score to predict 14-day mortality in ICU patients infected with Klebsiella pneumoniae. Methodology: A retrospective cohort study was conducted using data of ICU patients infected with Klebsiella pneumoniae at the largest tertiary hospital in Northern Vietnam during 2016-2018. Logistic regression was used to develop our prediction model. Model performance was assessed by calibration (area under the receiver operating characteristic curve-AUC) and discrimination (Hosmer-Lemeshow goodness-of-fit test). A simplified risk score was also constructed. Results: Two hundred forty-nine patients were included, with an overall 14-day mortality of 28.9%. The final prediction model comprised six predictors: age, referral route, SOFA score, central venous catheter, intracerebral haemorrhage surgery and absence of adjunctive therapy. The model showed high predictive accuracy (AUC = 0.83; p-value Hosmer-Lemeshow test = 0.92). The risk score has a range of 0-12 corresponding to mortality risk 0-100%, which produced similar predictive performance as the original model. Conclusions: The developed prediction model and risk score provide an objective quantitative estimation of individual 14-day mortality in ICU patients infected with Klebsiella pneumoniae. The tool is highly applicable in practice to help facilitate patient stratification and management, evaluation of further interventions and allo-cation of resources and care, especially in low-resource settings where electronic systems to support complex models are missing.
Notes: Tran, TN (corresponding author), Univ Antwerp, Fac Med & Hlth Sci, Family Med & Populat Hlth FAMPOP, Univ Pl 1, B-2610 Antwerp, Belgium.
thuyngan.tran@uantwerpen.be
Keywords: Klebsiella pneumoniae; Intensive care unit; Mortality; Prediction;;Prognosis
Document URI: http://hdl.handle.net/1942/36246
ISSN: 1341-321X
e-ISSN: 1437-7780
DOI: 10.1016/j.jiac.2021.09.001
ISI #: WOS:000719451000003
Category: A1
Type: Journal Contribution
Validations: ecoom 2023
Appears in Collections:Research publications

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