Colonisation of hospital surfaces from low- and middle-income countries by extended spectrum ß-lactamase- and carbapenemase-producing bacteria.

Hospital surfaces can harbour bacterial pathogens, which may disseminate and cause nosocomial infections, contributing towards mortality in low- and middle-income countries (LMICs). During the BARNARDS study, hospital surfaces from neonatal wards were sampled to assess the degree of environmental surface and patient care equipment colonisation by Gram-negative bacteria (GNB) carrying antibiotic resistance genes (ARGs). Here, we perform PCR screening for extended-spectrum ß-lactamases (blaCTX-M-15) and carbapenemases (blaNDM, blaOXA-48-like and blaKPC), MALDI-TOF MS identification of GNB carrying ARGs, and further analysis by whole genome sequencing of bacterial isolates. We determine presence of consistently dominant clones and their relatedness to strains causing neonatal sepsis. Higher prevalence of carbapenemases is observed in Pakistan, Bangladesh, and Ethiopia, compared to other countries, and are mostly found in surfaces near the sink drain. Klebsiella pneumoniae, Enterobacter hormaechei, Acinetobacter baumannii, Serratia marcescens and Leclercia adecarboxylata are dominant; ST15 K. pneumoniae is identified from the same ward on multiple occasions suggesting clonal persistence within the same environment, and is found to be identical to isolates causing neonatal sepsis in Pakistan over similar time periods. Our data suggests persistence of dominant clones across multiple time points, highlighting the need for assessment of Infection Prevention and Control guidelines.

The incidence, clinical features, and management of essential infantile esotropia in the United Kingdom. A British Ophthalmology Surveillance Unit (BOSU) study.

BACKGROUND/OBJECTIVES: A national study was undertaken through the British ophthalmology surveillance unit (BOSU) to determine the incidence, presenting features and management of essential infantile esotropia (EIE) in the UK. METHODS: Data from a prospective national observational study of newly diagnosed EIE presenting to clinicians in the United Kingdom over a 12-month period were collected. Cases with a confirmed diagnosis by a clinician of a constant, non-accommodative esotropia ≥20 prism dioptres (PD), presenting at ≤12 months, with no neurological or ocular abnormalities were identified through BOSU. Follow-up data were collected at 12 months. RESULTS: A total of 57 cases were reported giving an incidence of EIE of 1 in 12,828 live births. The mean age of diagnosis and intervention were 7.05 ± 2.6 months (range 2-12) and 14.7 ± 4.9 months (range 6.5-28.1), respectively. Management was surgical in 59.6%, botulinum toxin alone in 22.8%, and 17.5% were observed. The preoperative angle of esotropia was smaller in the observation group (P = 0.04). The postoperative angle of esotropia was not statistically significant between botulinum toxin or surgery (P = 0.3), although the age of intervention was earlier in the botulinum group (P = 0.007). Early intervention (before 12 months of age) did not influence the post-intervention motor outcomes between 0 and 10 prism dioptres of esotropia (P = 0.78). CONCLUSIONS: The incidence of EIE in the UK is considerably lower than reported in other population-based studies. The preferred method of treatment was surgical with earlier intervention in those treated with botulinum toxin. An early age of intervention (<12 months) did not influence motor outcomes.

Combination protein biomarkers predict multiple sclerosis diagnosis and outcomes.

Establishing biomarkers to predict multiple sclerosis diagnosis and prognosis has been challenging using a single biomarker approach. We hypothesised that a combination of biomarkers would increase the accuracy of prediction models to differentiate multiple sclerosis from other neurological disorders and enhance prognostication for people with multiple sclerosis. We measured 24 fluid biomarkers in the blood and cerebrospinal fluid of 77 people with multiple sclerosis and 80 people with other neurological disorders, using ELISA or Single Molecule Array assays. Primary outcomes were multiple sclerosis versus any other diagnosis, time to first relapse, and time to disability milestone (Expanded Disability Status Scale 6), adjusted for age and sex. Multivariate prediction models were calculated using the area under the curve value for diagnostic prediction, and concordance statistics (the percentage of each pair of events that are correctly ordered in time for each of the Cox regression models) for prognostic predictions. Predictions using combinations of biomarkers were considerably better than single biomarker predictions. The combination of cerebrospinal fluid [chitinase-3-like-1 + TNF-receptor-1 + CD27] and serum [osteopontin + MCP-1] had an area under the curve of 0.97 for diagnosis of multiple sclerosis, compared to the best discriminative single marker in blood (osteopontin: area under the curve 0.84) and in cerebrospinal fluid (chitinase-3-like-1 area under the curve 0.84). Prediction for time to next relapse was optimal with a combination of cerebrospinal fluid[vitamin D binding protein + Factor I + C1inhibitor] + serum[Factor B + Interleukin-4 + C1inhibitor] (concordance 0.80), and time to Expanded Disability Status Scale 6 with cerebrospinal fluid [C9 + Neurofilament-light] + serum[chitinase-3-like-1 + CCL27 + vitamin D binding protein + C1inhibitor] (concordance 0.98). A combination of fluid biomarkers has a higher accuracy to differentiate multiple sclerosis from other neurological disorders and significantly improved the prediction of the development of sustained disability in multiple sclerosis. Serum models rivalled those of cerebrospinal fluid, holding promise for a non-invasive approach. The utility of our biomarker models can only be established by robust validation in different and varied cohorts.

Low circulatory levels of total cholesterol, HDL-C and LDL-C are associated with death of patients with sepsis and critical illness: systematic review, meta-analysis, and perspective of observational studies.

BACKGROUND: Mechanistic studies have established a biological role of sterol metabolism in infection and immunity with clinical data linking deranged cholesterol metabolism during sepsis with poorer outcomes. In this systematic review we assess the relationship between biomarkers of cholesterol homeostasis and mortality in critical illness. METHODS: We identified articles by searching a total of seven electronic databases from inception to October 2023. Prospective observational cohort studies included those subjects who had systemic cholesterol (Total Cholesterol (TC), HDL-C or LDL-C) levels assessed on the first day of ICU admission and short-term mortality recorded. Meta-analysis and meta-regression were used to evaluate overall mean differences in serum cholesterol levels between survivors and non-survivors. Study quality was assessed using the Newcastle-Ottawa Scale. FINDINGS: From 6469 studies identified by searches, 24 studies with 2542 participants were included in meta-analysis. Non-survivors had distinctly lower HDL-C at ICU admission -7.06 mg/dL (95% CI -9.21 to -4.91, p < 0.0001) in comparison with survivors. Corresponding differences were also seen less robustly for TC -21.86 mg/dL (95% CI -31.23 to -12.49, p < 0.0001) and LDL-C -8.79 mg/dL (95% CI, -13.74 to -3.83, p = 0.0005). INTERPRETATION: Systemic cholesterol levels (TC, HDL-C and LDL-C) on admission to critical care are inversely related to mortality. This finding is consistent with the notion that inflammatory and metabolic setpoints are coupled, such that the maladaptive-setpoint changes of cholesterol in critical illness are related to underlying inflammatory processes. We highlight the potential of HDL-biomarkers as early predictors of severity of illness and emphasise that future research should consider the metabolic and functional heterogeneity of HDLs. FUNDING: EU-ERDF-Welsh Government Ser Cymru programme, BBSRC, and EU-FP7 ClouDx-i project (PG).