The varying effects of a range of preservatives on Myoviridae and Siphoviridae bacteriophages formulated in a semi-solid cream preparation.

Bacteriophages may be formulated into semi-solid bases for therapeutic delivery. This work investigated the effects of a range of preservatives on the viability of Myoviridae and Siphoviridae bacteriophages when these were formulated into a standard semi-solid cream base. The six preservatives tested included: benzoic acid (0·1%), chlorocresol (0·1%), combination hydroxybenzoates (propyl 4-hydroxybenzoates with methyl 4-hydroxybenzoates) (0·1%), methyl 4-hydroxybenzoate (0·08%), 2-phenoxyethanol (1%) and propyl 4-hydroxybenzoate (0·02%). These were each formulated into cetomacrogol cream aqueous to generate six individual semi-solid bases into which Myoviridae and Siphoviridae bacteriophages were added and tested for stability. Optimal bacteriophage stability was seen when the preservative chlorocresol was used. Bacteriophage in the acidic benzoic acid were the least stable, resulting in complete loss of viability after 4-5 weeks. Of the bacteriophages tested, the Myoviridae KOX1 was significantly more stable than the Siphoviridae PAC1 after 91 days in formulations with each of the preservatives. Our results suggest the need for individual testing of specific bacteriophages in pharmaceutical formulations, as their efficacy when exposed to preservatives and excipients in these delivery forms may vary. SIGNIFICANCE AND IMPACT OF THE STUDY: Bacteriophages are being increasingly investigated as alternatives to antibiotics. While bacteriophages can be formulated in diverse ways for therapeutic delivery, there has been scant work on how excipients and preservatives in these formulations affect stability of different bacteriophages. We demonstrate that the nature of preservatives in formulations will affect bacteriophage stability, and that in these formulations, viability of bacteriophage differs according to their morphology. Our work highlights the need for individual testing of specific bacteriophages in pharmaceutical formulations, as efficacy when exposed to preservatives and excipients in these delivery forms may vary.

Temporal development of the oral microbiome and prediction of early childhood caries.

Human microbiomes are predicted to assemble in a reproducible and ordered manner yet there is limited knowledge on the development of the complex bacterial communities that constitute the oral microbiome. The oral microbiome plays major roles in many oral diseases including early childhood caries (ECC), which afflicts up to 70% of children in some countries. Saliva contains oral bacteria that are indicative of the whole oral microbiome and may have the ability to reflect the dysbiosis in supragingival plaque communities that initiates the clinical manifestations of ECC. The aim of this study was to determine the assembly of the oral microbiome during the first four years of life and compare it with the clinical development of ECC. The oral microbiomes of 134 children enrolled in a birth cohort study were determined at six ages between two months and four years-of-age and their mother's oral microbiome was determined at a single time point. We identified and quantified 356 operational taxonomic units (OTUs) of bacteria in saliva by sequencing the V4 region of the bacterial 16S RNA genes. Bacterial alpha diversity increased from a mean of 31 OTUs in the saliva of infants at 1.9 months-of-age to 84 OTUs at 39 months-of-age. The oral microbiome showed a distinct shift in composition as the children matured. The microbiome data were compared with the clinical development of ECC in the cohort at 39, 48, and 60 months-of-age as determined by ICDAS-II assessment. Streptococcus mutans was the most discriminatory oral bacterial species between health and current disease, with an increased abundance in disease. Overall our study demonstrates an ordered temporal development of the oral microbiome, describes a limited core oral microbiome and indicates that saliva testing of infants may help predict ECC risk.

Does Co-morbidity provide significant improvement on age adjustment when predicting medical outcomes?

OBJECTIVE: Using three risk-adjustment methods we evaluated whether co-morbidity derived from electronic hospital patient data provided significant improvement on age adjustment when predicting major outcomes following an elective total joint replacement (TJR) due to osteoarthritis. METHODS: Longitudinal data from 819 elderly men who had had a TJR were integrated with hospital morbidity data (HMD) and mortality records. For each participant, any morbidity or health-related outcome was retrieved from the linked data in the period 1970 through to 2007 and this enabled us to better account for patient co-morbidities. Co-morbidities recorded in the HMD in all admissions preceding the index TJR admission were used to construct three risk-adjustment methods, namely Charlson co-morbidity index (CCI), Elixhauser's adjustment method, and number of co-morbidities. Postoperative outcomes evaluated included length of hospital stay, 90-day readmission, and 1-year and 2-year mortality. These were modelled using Cox proportional hazards regression as a function of age for the baseline models, and as a function of age and each of the risk-adjustment methods. The difference in the statistical performance between the models that included age alone and those that also included the co-morbidity adjustment method was assessed by measuring the difference in the Harrell's C estimates between pairs of models applied to the same patient data using Bootstrap analysis with 1000 replications. RESULTS: Number of co-morbidities did not provide any significant improvement in model discrimination when added to baseline models observed in all outcomes. CCI significantly improved model discrimination when predicting post-operative mortality but not when length of stay or readmission was modelled. For every one point increase in CCI, postoperative 1- and 2-year mortality increased by 37% and 30%, respectively. Elixhauser's method outperformed the other two providing significant improvement on age adjustment in all outcomes. CONCLUSION: The predictive performance of co-morbidity derived from electronic hospital data is outcome and risk-adjustment method specific.

Increased risk of bloodstream and urinary infections in intensive care unit (ICU) patients compared with patients fitting ICU admission criteria treated in regular wards.

Critically ill patients, eligible for admission into intensive care units (ICUs), are often hospitalized in other wards due to a lack of ICU beds. Differences in morbidity between patients managed in ICUs and elsewhere are unknown, specifically the morbidity related to hospital-acquired infection. Patients fitting ICU admission criteria were identified by screening five entire hospitals on four separate days. Hospital infections within a 30-day follow-up period were compared in ICU patients and in patients on other wards using Kaplan-Meier curves. Residual differences in the patients' case mix between ICUs and other wards were adjusted for utilizing multivariate Cox models. Of 13415 patients screened, 668 were critically ill. The overall infection rates (per 100 patient-days) were 1.2 for bloodstream infection (BSI) and 1.9 for urinary tract infection (UTI). The adjusted hazard ratios in ICU patients compared with patients on regular wards were 3.1 (P<0.001) for BSI and 2.5 (P<0.001) for UTI. This increased risk persisted even after adjusting for the disparity in the number of cultures sent from ICUs compared with ordinary wards. No interdepartmental differences were found in the rates of pneumonia, surgical wound infections and other infections. Minimizing the differences between characteristics of patients hospitalized in ICUs and in other wards, and controlling for the higher frequency of cultures sent from ICUs did not eliminate the increased risk of BSI and UTI associated with admission into ICUs.