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ABSTRACT: Background
Early detection of multidrug-resistant Pseudomonas aeruginosa (MDRP) remains challenging. Existing risk prediction tools are difficult to translate to bedside application. The goal of this study was to develop a simple electronic medical record (EMR)-integrated tool for prediction of MDRP infection.Methods
This was a mixed-methods study. We conducted a split-sample cohort study of adult critical care patients with P aeruginosa infections. Two previously published tools were validated using c-statistic. A subset of variables based on strength of association and ease of EMR extraction was selected for further evaluation. A simplified tool was developed using multivariable logistic regression. Both c-statistic and theoretical trade-off of over- versus underprescribing of broad-spectrum MDRP therapy were assessed in the validation cohort. A qualitative survey of frontline clinicians assessed understanding of risks for MDRP and potential usability of an EMR-integrated tool to predict MDRP.Results
The 2 previous risk prediction tools demonstrated similar accuracy in the derivation cohort (c-statistic of 0.76 [95% confidence interval {CI}, .69-.83] and 0.73 [95% CI, .66-.8]). A simplified tool based on 4 variables demonstrated reasonable accuracy (c-statistic of 0.71 [95% CI, .57-.85]) without significant overprescribing in the validation cohort. The risk factors were prior MDRP infection, ≥4 antibiotics prior to culture, infection >3 days after admission, and dialysis. Fourteen clinicians completed the survey. An alert providing context regarding individual patient risk factors for MDRP was preferred.Conclusions
These results can be used to develop a local EMR-integrated tool to improve timeliness of effective therapy in those at risk of MDRP infections.
SUBMITTER: Zou I
PROVIDER: S-EPMC10603593 | biostudies-literature | 2023 Oct
REPOSITORIES: biostudies-literature
Zou Iris I Abate Daniel D Newman Michelle M Heil Emily L EL Leekha Surbhi S Claeys Kimberly C KC
Open forum infectious diseases 20231012 10
<h4>Background</h4>Early detection of multidrug-resistant <i>Pseudomonas aeruginosa</i> (MDRP) remains challenging. Existing risk prediction tools are difficult to translate to bedside application. The goal of this study was to develop a simple electronic medical record (EMR)-integrated tool for prediction of MDRP infection.<h4>Methods</h4>This was a mixed-methods study. We conducted a split-sample cohort study of adult critical care patients with <i>P aeruginosa</i> infections. Two previously p ...[more]