Structural equation modeling the “control of gut overgrowth” in the prevention of ICU-acquired Gram-negative infection

Hurley, James C.

doi:10.1186/s13054-020-02906-6

Cited by 19 publications

(17 citation statements)

References 46 publications

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“…To elucidate the relative, complex association between factors and PIICS, we used a generalized structural equation model (GSEM) [ 11 , 12 ]. The model structure was developed based on prior knowledge [ 9 , 13 , 14 , 15 ].…”

Section: Methodsmentioning

confidence: 99%

Disseminated Intravascular Coagulopathy Is Associated with the Outcome of Persistent Inflammation, Immunosuppression and Catabolism Syndrome

Nakamura

Ogura

Nakano

et al. 2020

JCM

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Persistent inflammation, immunosuppression and catabolism syndrome (PIICS) often occur after critical care. Disseminated intravascular coagulation (DIC) is expected to be associated independently with PIICS development. We retrospectively analyzed 5397 patients admitted to the Hitachi General Hospital emergency and critical care center during four years. We classified PIICS as C-reactive protein > 3.0 mg/dL or albumin < 3.0 g/dL or lymphocyte count < 800/μL on day 14. Prolonged hospital stay (>14 days) without PIICS and early recovery (discharged alive within 14 days) were assigned as non-PIICS. Early death (death within 14 days) was identified. We analyzed the association between the International Society on Thrombosis and Haemostasis overt DIC and PIICS outcomes. Results revealed 488 PIICS, 416 early death and 4493 non-PIICS cases. Analyses showed DIC as associated significantly with mortality, the Barthel index at discharge and PIICS development. Multivariate regression analysis and a generalized structural equation model identified DIC on admission as an independent risk factor for PIICS in surviving patients.

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Section: Methodsmentioning

confidence: 99%

Disseminated Intravascular Coagulopathy Is Associated with the Outcome of Persistent Inflammation, Immunosuppression and Catabolism Syndrome

Nakamura

Ogura

Nakano

et al. 2020

JCM

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“…A snowballing search strategy [ 32 ] using the “Related articles” function within Google Scholar was undertaken for additional studies not identified within key systematic reviews. The key inclusion and exclusion criteria described previously [ 27 ], being a patient group requiring prolonged (>24 h) ICU stay with group-level data for any of Pseudomonas or Acinetobacter infection data available, was expanded to include Candida infection data and studies of single anti-fungal prophylaxis [ 28 , 29 ]. All eligible studies were then collated, and any duplicate studies were removed.…”

Section: Methodsmentioning

confidence: 99%

“…Scatter plots of the Candida , Pseudomonas and Acinetobacter infection data were generated to facilitate a visual survey of the entire data as derived from the literature. To facilitate this visual survey, a benchmark for each outcome of interest was generated from the groups of the observational studies as described previously [ 27 ].…”

Section: Methodsmentioning

confidence: 99%

“…The prevention of VAP and other ICU acquired infections is of great interest and various anti-septic, antibiotic, anti-fungal, or non-decontamination-based interventions have been studied [ 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ]. These methods variably target colonization with Gram-negative bacteria such as Pseudomonas and Acinetobacter bacteria and also Candida [ 26 , 27 ]. Topical antibiotic prophylaxis (TAP)-based methods appear to be the most effective for the overall prevention of VAP and bacteraemia among ICU patients [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

“…These methods variably target colonization with Gram-negative bacteria such as Pseudomonas and Acinetobacter bacteria and also Candida [ 26 , 27 ]. Topical antibiotic prophylaxis (TAP)-based methods appear to be the most effective for the overall prevention of VAP and bacteraemia among ICU patients [ 27 ]. Surprisingly, the incidences of infection with Candida [ 28 , 29 ] and likewise incidences of both Acinetobacter [ 30 ] and Pseudomonas bacteraemia [ 31 ] are unusually high among studies of methods using TAP.…”

Section: Introductionmentioning

confidence: 99%

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Candida–Acinetobacter–Pseudomonas Interaction Modelled within 286 ICU Infection Prevention Studies

Hurley

2020

JoF

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Background: Whether Candida interacts to enhance the invasive potential of Acinetobacter and Pseudomonas bacteria cannot be resolved within individual studies. There are several anti-septic, antibiotic, anti-fungal, and non-decontamination-based interventions to prevent ICU acquired infection. These effective prevention interventions would be expected to variably impact Candida colonization. The collective observations within control and intervention groups from numerous ICU infection prevention studies simulates a multi-centre natural experiment with which to evaluate Candida, Acinetobacter and Pseudomonas interaction (CAPI). Methods: Eight Candidate-generalized structural equation models (GSEM), with Candida, Pseudomonas and Acinetobacter colonization as latent variables, were confronted with blood culture and respiratory tract isolate data derived from >400 groups derived from 286 infection prevention studies. Results: Introducing an interaction term between Candida colonization and each of Pseudomonas and Acinetobacter colonization improved model fit in each case. The size of the coefficients (and 95% confidence intervals) for these interaction terms in the optimal Pseudomonas (+0.33; 0.22 to 0.45) and Acinetobacter models (+0.32; 0.01 to 0.5) were similar to each other and similar in magnitude, but contrary in direction, to the coefficient for exposure to topical antibiotic prophylaxis (TAP) on Pseudomonas colonization (−0.45; −0.71 to −0.2). The coefficient for exposure to topical antibiotic prophylaxis on Acinetobacter colonization was not significant. Conclusions: GSEM modelling of published ICU infection prevention data supports the CAPI concept. The CAPI model could account for some paradoxically high Acinetobacter and Pseudomonas infection incidences, most apparent among the concurrent control groups of TAP studies.

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Staphylococcus aureus hitchhiking from colonization to bacteremia via Candida within ICU infection prevention studies: a proof of concept modelling

Hurley

2023

Eur J Clin Microbiol Infect Dis

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Whether Candida within the patient microbiome drives the pathogenesis of Staphylococcus aureus bacteremia, described as microbial hitchhiking, cannot be directly studied. Group-level observations from studies of various decontamination and non-decontamination-based ICU infection prevention interventions and studies without study interventions (observational groups) collectively enable tests of this interaction within causal models. Candidate models of the propensity for Staphylococcus aureus bacteremia to arise with versus without various antibiotic, anti-septic, and antifungal exposures, each identified as singleton exposures, were tested using generalized structural equation modelling (GSEM) techniques with Candida and Staphylococcus aureus colonization appearing as latent variables within the models. Each model was tested by confrontation against blood and respiratory isolate data, obtained from 467 groups within 284 infection prevention studies. Introducing an interaction term between Candida colonization and Staphylococcus aureus colonization substantially improved GSEM model fit. Model-derived coefficients for singular exposure to anti-septic agents (− 1.28; 95% confidence interval; − 2.05 to − 0.5), amphotericin (− 1.49; − 2.3 to − 0.67), and topical antibiotic prophylaxis (TAP; + 0.93; + 0.15 to + 1.71) as direct effects versus Candida colonization were similar in magnitude but contrary in direction. By contrast, the coefficients for singleton exposure to TAP, as with anti-septic agents, versus Staphylococcus colonization were weaker or non-significant. Topical amphotericin would be predicted to halve both candidemia and Staphylococcus aureus bacteremia incidences versus literature derived benchmarks for absolute differences of < 1 percentage point. Using ICU infection prevention data, GSEM modelling validates the postulated interaction between Candida and Staphylococcus colonization facilitating bacteremia.

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Structural equation modeling the “control of gut overgrowth” in the prevention of ICU-acquired Gram-negative infection

Cited by 19 publications

References 46 publications

Disseminated Intravascular Coagulopathy Is Associated with the Outcome of Persistent Inflammation, Immunosuppression and Catabolism Syndrome

Disseminated Intravascular Coagulopathy Is Associated with the Outcome of Persistent Inflammation, Immunosuppression and Catabolism Syndrome

Candida–Acinetobacter–Pseudomonas Interaction Modelled within 286 ICU Infection Prevention Studies

Staphylococcus aureus hitchhiking from colonization to bacteremia via Candida within ICU infection prevention studies: a proof of concept modelling

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