Rural Clinical School - Research Publications
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ItemCandida and the Gram-positive trio: testing the vibe in the ICU patient microbiome using structural equation modelling of literature derived data.(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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ItemDiscrepancies in Control Group Mortality Rates Within Studies Assessing Topical Antibiotic Strategies to Prevent Ventilator-Associated Pneumonia: An Umbrella Review.(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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ItemStructural equation modelling the relationship between anti-fungal prophylaxis and Pseudomonas bacteremia in ICU patients(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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ItemSelective digestive decontamination, a seemingly effective regimen with individual benefit or a flawed concept with population harm?(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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ItemRecommended pre-analytical plasma glucose sampling methodology may distort gestational diabetes mellitus prevalence: implications for diagnostic thresholds(WILEY, 2019-10)AIM: Current International Association of the Diabetes and Pregnancy Study Groups/World Health Organization gestational diabetes mellitus (GDM) diagnostic thresholds are based on a landmark study in which the pre-analytical plasma glucose sampling methodology is unclear. Worldwide, plasma glucose pre-analytical sampling methodology practices are divergent. We considered the effects of pre-analytical plasma glucose sampling methodology on GDM prevalence and gestational outcomes. METHODS: This is a retrospective observational cohort study of 1178 pregnant women undergoing an oral glucose tolerance test (OGTT). Of the 1178 pregnant women, a subset of 892 non-GDM women with singleton births undergoing OGTT between 24 and 28 weeks' gestation were investigated for large for gestation age (LGA) outcomes. OGTT were determined using traditional methods (sodium fluoride tubes batched at roomed temperature). We modelled the potential effects of using a recommended pre-analytical plasma glucose methodology (lyophilized citrate tubes) on GDM prevalence. RESULTS: The GDM prevalence in our cohort was 13.5%. The incidence of LGA showed a linear association with maternal plasma glucose that was similar to the association observed in the Hyperglycemia and Adverse Pregnancy Outcome study. Frequency of LGA exceeded 10% at HAPO glucose category 4 (fasting, 4.8 to 4.9 mmol/l; 1-h, 8.7 to 9.5 mmol/l) for fasting and 1-h plasma glucose. The use of a recommended pre-analytical method is projected to increase the prevalence of GDM to 39.2%. CONCLUSION: We challenge the consensus that recommended pre-analytical plasma glucose methodologies are optimal for the accurate diagnosis of GDM. Recommended pre-analytical plasma glucose methods may profoundly over-diagnose GDM. Centres using recommended pre-analytical plasma glucose methodologies may need to reappraise their diagnostic thresholds.
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ItemNon-invasive ventilation of patients with acute asthma(WILEY, 2019-02)A retrospective observational study of 21 patients admitted to the Intensive Care Unit (ICU) of Frankston Hospital with acute asthma between 2011 and 2014 was undertaken. We report the outcomes for three groups of patients; those that did (n = 7) or did not (n = 6) receive initial therapy with non-invasive ventilation (NIV) together with those that received invasive ventilation (n = 8). Patients successfully managed with NIV alone experienced a shorter ICU and hospital stay versus those who required invasive ventilation.
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ItemAsymmetric Effects of Decontamination Using Topical Antibiotics for the ICU Patient(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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ItemCould simulation methods solve the curse of sparse data within clinical studies of antibiotic resistance?(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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ItemForrest plots or caterpillar plots?(ELSEVIER SCIENCE INC, 2020-05)
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ItemCandida-Acinetobacter-Pseudomonas Interaction Modelled within 286 ICU Infection Prevention Studies(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.