Crossroads of Antimicrobial and Diagnostic Stewardship : Assessing Risks to Develop Clinical Decision Support to Combat Multidrug-Resistant Pseudomonas
© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:10 |
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| Enthalten in: |
Open forum infectious diseases - 10(2023), 10 vom: 06. Okt., Seite ofad512 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Zou, Iris [VerfasserIn] |
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| Links: |
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| Themen: |
Antibiotic resistance |
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| Anmerkungen: |
Date Revised 31.10.2023 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1093/ofid/ofad512 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM363931333 |
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| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a © The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America. | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Pseudomonas aeruginosa | |
| 650 | 4 | |a antibiotic resistance | |
| 650 | 4 | |a antimicrobial stewardship | |
| 650 | 4 | |a diagnostic stewardship | |
| 700 | 1 | |a Abate, Daniel |e verfasserin |4 aut | |
| 700 | 1 | |a Newman, Michelle |e verfasserin |4 aut | |
| 700 | 1 | |a Heil, Emily L |e verfasserin |4 aut | |
| 700 | 1 | |a Leekha, Surbhi |e verfasserin |4 aut | |
| 700 | 1 | |a Claeys, Kimberly C |e verfasserin |4 aut | |
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