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James C Hurley
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Background: Conceptually, the ‘control of gut overgrowth’ (COGO) is key to the mediation of infection prevention with ‘abnormal Gram-negative bacilli’ (AGNB) by Selective Digestive Decontamination (SDD). However, the relative importance of the SDD components; topical (TAP), enteral (EAP) and protocolized parenteral antibiotic prophylaxis (PPAP), versus other methods of infection prevention and versus other contextual exposures cannot be resolved within individual studies.
Methods: Seven candidate generalized structural equation models (GSEM) founded on COGO concepts were confronted with Pseudomonas and Acinetobacter bacteremia as well as ventilator associated pneumonia (VAP) data derived from >200 infection prevention studies. The following group level exposures were included in the GSEM models; use of TAP, EAP, PPAP, antiseptic and non-decontamination methods of infection prevention; proportion receiving mechanical ventilation (MV); trauma ICU; mean length of ICU stay and concurrency versus non-concurrency of TAP study control groups.
Results: In GSEM modelling of Pseudomonas and Acinetobacter gut overgrowth (GO) as latent variables, anti-septic interventions had the strongest negative effect against Pseudomonas GO but no intervention was significantly negative against Acinetobacter GO. Strikingly, PPAP and concurrency each have positive effects in the model, EAP is neutral and Acinetobacter bacteremia incidences are high within TAP studies, moreso with PPAP exposure. Paradoxically, TAP (moreso with PPAP) appears to provide the strongest summary prevention effects against overall bacteremia and overall VAP.
Conclusions: GSEM modelling of published AGNB infection data enables a test of the COGO concept. Paradoxically, Acinetobacter and Pseudomonas bacteremia incidences are unusually high among studies of TAP.
Keywords
Bacteremia, Acinetobacter, Pseudomonas, Antibiotic prophylaxis, Study design, Intensive care, Mechanical ventilation, Selective Digestive Decontamination, Polymyxin generalized structural equation model
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CURRENT STATUS: Published
View the published article at Critical Care.
No community comments so far
Editor assigned
On 14 Apr, 2020
Editorial decision: Accept
On 14 Apr, 2020
Submission checks complete
On 13 Apr, 2020
Editor invited
On 13 Apr, 2020
Version 2
Posted 17 Mar, 2020
No comments provided
Editorial decision: Minor revision
On 04 Apr, 2020
Review #1 received
Received 16 Mar, 2020
Editor assigned
On 11 Mar, 2020
Reviewers invited
Invitations sent on 11 Mar, 2020
Reviewer #1 agreed
On 11 Mar, 2020
Submission checks complete
On 10 Mar, 2020
Editor invited
On 10 Mar, 2020
No comments provided
Editorial decision: Minor revision
On 28 Feb, 2020
Review #3 received
Received 23 Feb, 2020
Review #2 received
Received 14 Feb, 2020
Reviewer #3 agreed
On 13 Feb, 2020
Reviewer #2 agreed
On 11 Feb, 2020
Review #1 received
Received 09 Feb, 2020
Reviewer #1 agreed
On 30 Jan, 2020
Reviewers invited
Invitations sent on 30 Jan, 2020
Editor assigned
On 26 Jan, 2020
Editor invited
On 25 Jan, 2020
Submission checks complete
On 23 Jan, 2020
First submitted
On 13 Jan, 2020
Metrics
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PDF Downloads: ...
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Subject Areas
Critical Care & Emergency Medicine
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A new preprint design is coming!
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See the published version of this preprint at Critical Care.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
James C Hurley
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Critical Care.
No community comments so far
Editor assigned
On 14 Apr, 2020
Editorial decision: Accept
On 14 Apr, 2020
Submission checks complete
On 13 Apr, 2020
Editor invited
On 13 Apr, 2020
Version 2
Posted 17 Mar, 2020
No comments provided
Editorial decision: Minor revision
On 04 Apr, 2020
Review #1 received
Received 16 Mar, 2020
Editor assigned
On 11 Mar, 2020
Reviewers invited
Invitations sent on 11 Mar, 2020
Reviewer #1 agreed
On 11 Mar, 2020
Submission checks complete
On 10 Mar, 2020
Editor invited
On 10 Mar, 2020
No comments provided
Editorial decision: Minor revision
On 28 Feb, 2020
Review #3 received
Received 23 Feb, 2020
Review #2 received
Received 14 Feb, 2020
Reviewer #3 agreed
On 13 Feb, 2020
Reviewer #2 agreed
On 11 Feb, 2020
Review #1 received
Received 09 Feb, 2020
Reviewer #1 agreed
On 30 Jan, 2020
Reviewers invited
Invitations sent on 30 Jan, 2020
Editor assigned
On 26 Jan, 2020
Editor invited
On 25 Jan, 2020
Submission checks complete
On 23 Jan, 2020
First submitted
On 13 Jan, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Critical Care & Emergency Medicine
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Critical Care.
Background: Conceptually, the ‘control of gut overgrowth’ (COGO) is key to the mediation of infection prevention with ‘abnormal Gram-negative bacilli’ (AGNB) by Selective Digestive Decontamination (SDD). However, the relative importance of the SDD components; topical (TAP), enteral (EAP) and protocolized parenteral antibiotic prophylaxis (PPAP), versus other methods of infection prevention and versus other contextual exposures cannot be resolved within individual studies.
Methods: Seven candidate generalized structural equation models (GSEM) founded on COGO concepts were confronted with Pseudomonas and Acinetobacter bacteremia as well as ventilator associated pneumonia (VAP) data derived from >200 infection prevention studies. The following group level exposures were included in the GSEM models; use of TAP, EAP, PPAP, antiseptic and non-decontamination methods of infection prevention; proportion receiving mechanical ventilation (MV); trauma ICU; mean length of ICU stay and concurrency versus non-concurrency of TAP study control groups.
Results: In GSEM modelling of Pseudomonas and Acinetobacter gut overgrowth (GO) as latent variables, anti-septic interventions had the strongest negative effect against Pseudomonas GO but no intervention was significantly negative against Acinetobacter GO. Strikingly, PPAP and concurrency each have positive effects in the model, EAP is neutral and Acinetobacter bacteremia incidences are high within TAP studies, moreso with PPAP exposure. Paradoxically, TAP (moreso with PPAP) appears to provide the strongest summary prevention effects against overall bacteremia and overall VAP.
Conclusions: GSEM modelling of published AGNB infection data enables a test of the COGO concept. Paradoxically, Acinetobacter and Pseudomonas bacteremia incidences are unusually high among studies of TAP.
Figure 1
Figure 2
This is a list of supplementary files associated with this preprint. Click to download.
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