Rural Clinical School - Research Publications

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    Candida and the Gram-positive trio: testing the vibe in the ICU patient microbiome using structural equation modelling of literature derived data.
    Hurley, JC (Springer Science and Business Media LLC, 2022-08-18)
    BACKGROUND: Whether Candida interacts with Gram-positive bacteria, such as Staphylococcus aureus, coagulase negative Staphylococci (CNS) and Enterococci, to enhance their invasive potential from the microbiome of ICU patients remains unclear. Several effective anti-septic, antibiotic, anti-fungal, and non-decontamination based interventions studied for prevention of ventilator associated pneumonia (VAP) and other ICU acquired infections among patients receiving prolonged mechanical ventilation (MV) are known to variably impact Candida colonization. The collective observations within control and intervention groups from numerous ICU infection prevention studies enables tests of these postulated microbial interactions in the clinical context. METHODS: Four candidate generalized structural equation models (GSEM), each with Staphylococcus aureus, CNS and Enterococci colonization, defined as latent variables, were confronted with blood culture and respiratory tract isolate data derived from 460 groups of ICU patients receiving prolonged MV from 283 infection prevention studies. RESULTS: Introducing interaction terms between Candida colonization and each of S aureus (coefficient + 0.40; 95% confidence interval + 0.24 to + 0.55), CNS (+ 0.68; + 0.34 to + 1.0) and Enterococcal (+ 0.56; + 0.33 to + 0.79) colonization (all as latent variables) improved the fit for each model. The magnitude and significance level of the interaction terms were similar to the positive associations between exposure to topical antibiotic prophylaxis (TAP) on Enterococcal (+ 0.51; + 0.12 to + 0.89) and Candida colonization (+ 0.98; + 0.35 to + 1.61) versus the negative association of TAP with S aureus (- 0.45; - 0.70 to - 0.20) colonization and the negative association of anti-fungal exposure and Candida colonization (- 1.41; - 1.6 to - 0.72). CONCLUSIONS: GSEM modelling of published ICU infection prevention data enables the postulated interactions between Candida and Gram-positive bacteria to be tested using clinically derived data. The optimal model implies interactions occurring in the human microbiome facilitating bacterial invasion and infection. This interaction might also account for the paradoxically high bacteremia incidences among studies of TAP in ICU patients.
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    Discrepancies in Control Group Mortality Rates Within Studies Assessing Topical Antibiotic Strategies to Prevent Ventilator-Associated Pneumonia: An Umbrella Review.
    Hurley, JC (Ovid Technologies (Wolters Kluwer Health), 2020-01)
    OBJECTIVES: To test the postulate that concurrent control patients within ICUs studying topical oropharyngeal antibiotics to prevent ventilator-associated pneumonia and mortality would experience spillover effects from the intervention. DATA SOURCES: Studies cited in 15 systematic reviews of various topical antibiotic and other infection prevention interventions among ICU patients. STUDY SELECTION: Studies of topical antibiotics, stratified into concurrent control versus nonconcurrent control designs. Studies of nondecontamination-based infection prevention interventions provide additional points of reference. Studies with no infection prevention intervention provide the mortality benchmark. Data from additional studies and data reported as intention to treat were used within sensitivity tests. DATA EXTRACTION: Mortality incidence proportion data, mortality census, study characteristics, group mean age, ICU type, and study publication year. DATA SYNTHESIS: Two-hundred six studies were included. The summary effect sizes for ventilator-associated pneumonia and mortality prevention derived in the 15 systematic reviews were replicated. The mean ICU mortality incidence for concurrent control groups of topical antibiotic studies (28.5%; 95% CI, 25.0-32.3; n = 41) is higher versus the benchmark (23.7%; 19.2-28.5%; n = 34), versus nonconcurrent control groups (23.5%; 19.3-28.3; n = 14), and versus intervention groups (24.4%; 22.1-26.9; n = 62) of topical antibiotic studies. In meta-regression models adjusted for group-level characteristics such as group mean age and publication year, concurrent control group membership within a topical antibiotic study remains associated with higher mortality (p = 0.027), whereas other group memberships, including membership within an antiseptic study, are each neutral (p = not significant). CONCLUSIONS: Within topical antibiotic studies, the concurrent control group mortality incidence proportions are inexplicably high, whereas the intervention group mortality proportions are paradoxically similar to a literature-derived benchmark. The unexplained ventilator-associated pneumonia and mortality excess in the concurrent control groups implicates spillover effects within studies of topical antibiotics. The apparent ventilator-associated pneumonia and mortality prevention effects require cautious interpretation.
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    Structural equation modelling the relationship between anti-fungal prophylaxis and Pseudomonas bacteremia in ICU patients
    Hurley, JC (SPRINGER, 2022-01-21)
    PURPOSE: Animal models implicate candida colonization facilitating invasive bacterial infections. The clinical relevance of this microbial interaction remains undefined and difficult to study directly. Observations from studies of anti-septic, antibiotic, anti-fungal, and non-decontamination-based interventions to prevent ICU acquired infection collectively serve as a natural experiment. METHODS: Three candidate generalized structural equation models (GSEM), with Candida and Pseudomonas colonization as latent variables, were confronted with blood culture and respiratory tract isolate data derived from 464 groups from 279 studies including studies of combined antibiotic and antifungal exposures within selective digestive decontamination (SDD) interventions. RESULTS: Introducing an interaction term between Candida colonization and Pseudomonas colonization substantially improved GSEM model fit. Model derived coefficients for singular exposure to anti-septic agents (- 1.23; - 2.1 to - 0.32), amphotericin (- 1.78; - 2.79 to - 0.78) and topical antibiotic prophylaxis (TAP; + 1.02; + 0.11 to + 1.93) versus Candida colonization were similar in magnitude but contrary in direction. By contrast, the model-derived coefficients for singular exposure to TAP, as with anti-septic agents, versus Pseudomonas colonization were weaker or non-significant. Singular exposure to amphotericin would be predicted to more than halve candidemia and Pseudomonas bacteremia incidences versus literature benchmarks for absolute differences of approximately one percentage point or less. CONCLUSION: GSEM modelling of published data supports the postulated interaction between Candida and Pseudomonas colonization towards promoting bacteremia among ICU patients. This would be difficult to detect without GSEM modelling. The model indicates that anti-fungal agents have greater impact in preventing Pseudomonas bacteremia than TAP, which has no impact.
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    Selective digestive decontamination, a seemingly effective regimen with individual benefit or a flawed concept with population harm?
    Hurley, JC (BMC, 2021-09-01)
    Selective digestive decontamination (SDD) regimens, variously constituted with topical antibiotic prophylaxis (TAP) and protocolized parenteral antibiotic prophylaxis (PPAP), appear highly effective for preventing ICU-acquired infections but only within randomized concurrent control trials (RCCT's). Confusingly, SDD is also a concept which, if true, implies population benefit. The SDD concept can finally be reified  in humans using the broad accumulated evidence base, including studies of TAP and PPAP that used non-concurrent controls (NCC), as a natural experiment. However, this test implicates overall population harm with higher event rates associated with SDD use within the ICU context.
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    Asymmetric Effects of Decontamination Using Topical Antibiotics for the ICU Patient
    Hurley, JC (MDPI, 2021-06)
    There are several antiseptic, antibiotic and non-decontamination-based interventions for preventing intensive care unit (ICU) acquired infection. These have been evaluated in >200 studies. Infection prevention using topical antibiotic prophylaxis (TAP) appears to be the most effective. Whether antibiotic use in the ICU may influence the risk of infection among concurrent control patients within the same ICU and result in asymmetrical herd effects cannot be resolved with individual studies examined in isolation. The collective observations within control and intervention groups from numerous ICU infection prevention studies simulates a multi-center natural experiment enabling the herd effects of antibiotics to be evaluated. Among the TAP control groups, the incidences for both ventilator associated pneumonia (VAP) and mortality are unusually high in comparison to literature-derived benchmarks. Paradoxically, amongst the TAP intervention groups, the incidences of mortality are also unusually high and the VAP incidences are similar (i.e., not lower) compared to the incidences among studies of other interventions. By contrast, the mortality incidences among the intervention groups of other studies are similar to those among the intervention groups of TAP studies. Using topical antibiotics to prevent infections acquired within the ICU environment may result in profoundly asymmetrical effects.
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    Could simulation methods solve the curse of sparse data within clinical studies of antibiotic resistance?
    Hurley, JC ; Brownridge, D (OXFORD UNIV PRESS, 2021-03)
    Infectious disease (ID) physicians and ID pharmacists commonly confront therapeutic questions relating to antibiotic resistance. Randomized controlled trial data are few and meta-analytic-based approaches to develop the evidence-base from several small studies that might relate to an antibiotic resistance question are not simple. The overriding challenge is the sparsity of data which is problematic for traditional frequentist methods, being the paradigm underlying the derivation of 'P value' inferential statistics. In other sparse data contexts, simulation methods enable answers to key questions that are meaningful, quantitative and potentially relevant. How these simulation methods 'work' and how Bayesian-based methods, being not 'P value based', can facilitate simulation are reviewed. These methods are becoming increasingly accessible. This review highlights why sparse data is less of an issue within Bayesian versus frequentist paradigms. A fictional pharmacokinetic study with sparse data illustrates a simplistic application of Bayesian and simulation methods to antibiotic dosing. Whether within epidemiological projections or clinical studies, simulation methods are likely to play an increasing role in antimicrobial resistance research within both hospital and community studies of either rare infectious disease or infections within specific population groups.
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    Forrest plots or caterpillar plots?
    Hurley, JC (ELSEVIER SCIENCE INC, 2020-05)
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    Candida-Acinetobacter-Pseudomonas Interaction Modelled within 286 ICU Infection Prevention Studies
    Hurley, JC (MDPI, 2020-12)
    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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    Incidence of coagulase-negative staphylococcal bacteremia among ICU patients: decontamination studies as a natural experiment
    Hurley, JC (SPRINGER, 2020-04)
    The epidemiology of coagulase-negative staphylococcal (CNS) bacteremia among adult ICU patients remains unclear. Decontamination studies among ICU patients provide a unique opportunity to study the impacts of different diagnostic criteria, exposure to various decontamination interventions, and various other factors, on its incidence over three decades. Decontamination studies among ICU patients reporting CNS bacteremia incidence data were obtained mostly from recent systematic reviews. The CNS bacteremia incidence within component (control and intervention) groups of decontamination studies was benchmarked versus studies without intervention (observational groups). The impacts of antibiotic versus chlorhexidine decontamination interventions, control group concurrency, publication year, and diagnostic criteria were examined in meta-regression models. Among non-intervention (observational) studies which did versus did not specify stringent (≥ 2 positive blood cultures) diagnostic criteria, the mean CNS bacteremia incidence per 100 patients (and 95% CI; n) is 1.3 (0.9-2.0; n = 23) versus 3.6 (1.8-6.9; n = 8), respectively, giving an overall benchmark of 1.8 (1.2-2.4; n = 31). Versus the benchmark incidence, the mean incidence is high among concurrent control (5.7; 3.6-9.1%) and intervention (5.2; 3.6-6.9%), but not non-concurrent control (1.0; 0.4-3.9%) groups of 21 antibiotic studies, nor among eleven component groups of chlorhexidine studies. This high incidence remained apparent (p < 0.01) in meta-regression models adjusting for group wide factors such as diagnostic criteria and publication year. The incidence of CNS bacteremia within both intervention and concurrent (but not non-concurrent) control groups of antibiotic-based decontamination studies are unusually high even accounting for variable diagnostic criteria and other factors.
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    Estimated Treatment Effects of Tight Glycaemic Targets in Mild Gestational Diabetes Mellitus: A Multiple Cut-Off Regression Discontinuity Study Design
    Song, D ; Hurley, JC ; Lia, M (MDPI, 2020-11)
    Background: We investigated the treatment effects of tight glycaemic targets in a population universally screened according to the International Association of Diabetes and Pregnant Study Groups (IADPSG)/World Health Organisation (WHO) gestational diabetes mellitus (GDM) guidelines. As yet there, have been no randomized control trials evaluating the effectiveness of treatment of mild GDM diagnosed under the IADPSG/WHO diagnostic thresholds. We hypothesize that tight glycaemic control in pregnant women diagnosed with GDM will result in similar clinical outcomes to women just below the diagnostic thresholds. Methods: A multiple cut-off regression discontinuity study design in a retrospective observational cohort undergoing oral glucose tolerance tests (OGTT) (n = 1178). Treatment targets for women with GDM were: fasting capillary blood glucose (CBG) of ≤5.0 mmol/L and the 2-h post-prandial CBG of ≤6.7 mmol/L. Regression discontinuity study designs estimate treatment effects by comparing outcomes between a treated group to a counterfactual group just below the diagnostic thresholds with the assumption that covariates are similar. The counterfactual group was selected based on a composite score based on OGTT plasma glucose categories. Results: Women treated for GDM had lower rates of newborns large for gestational age (LGA), 4.6% versus those just below diagnostic thresholds 12.6%, relative risk 0.37 (95% CI, 0.16-0.85); and reduced caesarean section rates, 32.2% versus 43.0%, relative risk 0.75 (95% CI, 0.56-1.01). This was at the expense of increases in induced deliveries, 61.8% versus 39.3%, relative risk 1.57 (95% CI, 1.18-1.9); notations of neonatal hypoglycaemia, 15.8% versus 5.9%, relative risk 2.66 (95% CI, 1.23-5.73); and high insulin usage 61.1%. The subgroup analysis suggested that treatment of women with GDM with BMI ≥30 kg/m2 drove the reduction in caesarean section rates: 32.9% versus 55.9%, relative risk 0.59 (95%CI, 0.4-0.87). Linear regression interaction term effects between non-GDM and treated GDM were significant for LGA newborns (p = 0.001) and caesarean sections (p = 0.015). Conclusions: Tight glycaemic targets reduced rates of LGA newborns and caesarean sections compared to a counterfactual group just below the diagnostic thresholds albeit at the expense of increased rates of neonatal hypoglycaemia, induced deliveries, and high insulin usage.