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Background: Within the UK, COVID-19 has contributed towards over 103,000 deaths. Although multiple risk factors for COVID-19 have been identified, using this data to improve clinical care has proven challenging. The main aim of this study is to develop a reliable, multivariable predictive model for COVID-19 in-patient outcomes, thus enabling risk-stratification and earlier clinical decision-making. Methods: Anonymised data consisting of 44 independent predictor variables from 355 adults diagnosed with COVID-19, at a UK hospital, was manually extracted from electronic patient records for retrospective, case–control analysis. Primary outcomes included inpatient mortality, required ventilatory support, and duration of inpatient treatment. Pulmonary embolism sequala was the only secondary outcome. After balancing data, key variables were feature selected for each outcome using random forests. Predictive models were then learned and constructed using Bayesian networks. Results: The proposed probabilistic models were able to predict, using feature selected risk factors, the probability of the mentioned outcomes. Overall, our findings demonstrate reliable, multivariable, quantitative predictive models for four outcomes, which utilise readily available clinical information for COVID-19 adult inpatients. Further research is required to externally validate our models and demonstrate their utility as risk stratification and clinical decision-making tools.

IntroductionWithin the UK, COVID-19 has contributed towards over 103,000 deaths. Multiple risk factors for COVID-19 have been identified including various demographics, co-morbidities, biochemical parameters, and physical assessment findings. However, using this vast data to improve clinical care has proven challenging.Aimsto develop a reliable, multivariable predictive model for COVID-19 in-patient outcomes, to aid risk-stratification and earlier clinical decision-making.MethodsAnonymized data regarding 44 independent predictor variables of 355 adults diagnosed with COVID-19, at a UK hospital, was manually extracted from electronic patient records for retrospective, case-controlled analysis. Primary outcomes included inpatient mortality, level of ventilatory support and oxygen therapy required, and duration of inpatient treatment. Secondary pulmonary embolism was the only secondary outcome. After balancing data, key variables were feature selected for each outcome using random forests. Predictive models were created using Bayesian Networks, and cross-validated.ResultsOur multivariable models were able to predict, using feature selected risk factors, the probability of inpatient mortality (F1 score 83.7%, PPV 82%, NPV 67.9%); level of ventilatory support required (F1 score varies from 55.8% “High-flow Oxygen level” to 71.5% “ITU-Admission level”); duration of inpatient treatment (varies from 46.7% for “≥ 2 days but < 3 days” to 69.8% “≤ 1 day”); and risk of pulmonary embolism sequelae (F1 score 85.8%, PPV of 83.7%, and NPV of 80.9%).ConclusionOverall, our findings demonstrate reliable, multivariable predictive models for 4 outcomes, that utilize readily available clinical information for COVID-19 adult inpatients. Further research is required to externally validate our models and demonstrate their utility as clinical decision-making tools.HighlightsUsing COVID-19 risk-factor data to assist clinical decision making is a challengeAnonymous data from 355 COVID-19 inpatients was collected & balancedKey independent variables were feature selected for 4 different outcomesAccurate, multi-variable predictive models were computed, using Bayesian NetworksFuture research should externally validate our models & demonstrate clinical utility

Enteroviruses (EV) and human parechoviruses (HPeV) are known and emerging cause of sepsis-like illnesses in infants; however, testing is not yet routine. We retrospectively evaluated the number of diagnosed EV/HPeV infections in children under the age of 5 years who presented with sepsis-like illness or meningitis in Cornwall, UK, before and after routine implementation of viral screening of cerebrospinal fluid samples. During the 4-year period prior to routine testing, we identified 20 cases of EV meningitis and no cases of HPeV. In the year after introduction of routine screening, 27 cases of EV and 14 cases of HPeV were identified in 1 year. The majority of EV/HPeV infections occurred among children under 3 months old between May and August. Clinical and laboratory characteristics of EV and HPeV infections were mostly indistinguishable. We found that CSF pleocytosis and biochemistry-based testing strategy could miss 48.1 and 78.5% of EV and HPeV cases, respectively. With routine viral screening, the mean length of hospital stay (3.8 vs 5.9 days, P 0.001) and antibiotic days (2.8 vs 4.7 days, P 0.001) were significantly reduced in EV/HPeV-positive cases compared to a similar cohort without any detectable microbial aetiology.Routine EV and HPeV testing of CSF samples in children has the potential to reduce length of stay and antibiotic use. What is Known: • EV and HPeV are frequent cause of meningitis and sepsis-like illness among young children. • There is increasing evidence supporting routine EV and HPeV testing of paediatric CSF. What is New: • Outcome of routine EV and HPeV testing in Cornwall, UK. • The value of testing all paediatric CSF without any screening criteria. • A rapid diagnosis of EV/HPeV can significantly reduce length of hospital stay and unnecessary antibiotics.

Campylobacter are common zoonotic food borne pathogens but infrequent causes of disseminated human infection. Campylobacter fetus is an unusual cause of human infection and spondylodiscitis. We describe a case of C. fetus infection in a 72-year-old woman who presented with indolent onset lumbar spondylodiscitis. The literature is reviewed and the presentation of spondylodiscitis is contrasted with the usual aggressive nature of bacteremia with this pathogen. Keywords: Spondylodiscitis, Campylobacter, Fetus

Background and aims Meningitis due to Enterovirus infection is usually mild and self-limiting, particularly affecting young infants. We found that we were increasingly diagnosing the condition and undertook a retrospective review, exploring case characteristics and whether increasing use of virology detection reduced antibiotic course length, having previously rarely employed these techniques. Methods All cases identified as being diagnosed with meningitis with a positive enterovirus polymerase chain reaction (PCR) result between January 2012 and December 2012, below 16 years of age, were retrospectively reviewed. Results Nine cases of enterovirus meningitis were identified in the time period. Seven were infants aged 3 months or less, with two patients aged 11 and 15 years respectively. There were five females and four males. The infants presented with fever, lethargy or irritability. The older children presented with fever and headache. Following full infection screens, all of the infants were treated with intravenous antibiotics. One patient had raised inflammatory markers and one patient had a significant cerebrospinal fluid (CSF) pleocytosis, the majority had a normal or minimally raised CSF white cell count. Eight patients had positive CSF Enterovirus PCR results and one patient had a Coxsackievirus positive serum PCR (having not undergone lumbar puncture). In three patients a prolonged course of antibiotics was discontinued following the PCR result. One patient had episodes of tachycardia with subsequent diagnosis of supraventricular tachycardia requiring treatment. Conclusion Positive enterovirus PCR results appear to have reduced antibiotic course length, limiting unnecessary antibiotic administration, and we advocate increasing use of this investigation.

Brain abscess due to disseminated nocardia infection is an acute medical emergency among immunocompromised patients. We report a case of rapidly progressive nocardia brain abscess in an apparently healthy diabetic individual. The close similarity of the radiological features with those of malignancy and tuberculosis may delay the diagnosis of central nervous system (CNS) nocardiosis. A high index of suspicion and early intervention like stereotactic brain biopsy remain the cornerstone to increase the chance of positive clinical outcome.