Do children with neurological disabilities use more inpatient resources: an observational study.

BACKGROUND: Advances in healthcare have improved the survival of children with neurological disabilities (ND). Studies in the US have shown that children with ND use a substantial proportion of resources in children's hospitals, however, little research has been conducted in the UK. We aimed to test the hypothesis that children with neurological disabilities use more inpatient resources than children without neurological disabilities, and to quantify any significant differences in resource use. METHODS: A retrospective observational study was conducted, looking at the number of hospital admissions, total inpatient days and the reason for admissions for paediatric inpatients from January 1st to March 31st 2015. Inpatients were assigned into one of three groups: children without ND, children with one ND, and children with more than one ND. RESULTS: The sample population included 942 inpatients (mean age 6y 6mo). Children with at least one ND accounted for 15.3% of the inpatients, 17.7% of total hospital inpatient admission episodes, and 27.8% of the total inpatients days. Neurological disability had a statistically significant effect on total hospital admissions (p < 0.001). Neurological disability also had a statistically significant effect on total inpatient days (p < 0.001). Neurological disability increased the length of inpatient stay across medicine, specialties, and surgery. CONCLUSIONS: Children with ND had more frequent hospital admission episode and longer inpatient stays. We identified a smaller group within this population, with arguably more complex neurological disabilities, children with more than one ND. This group had the highest number of admissions and longest inpatient stays. More frequent hospital admissions and longer inpatient stays may place children with ND at greater risk of the adverse effects of hospitalisations. We recommend further investigations looking at each the effects of the different categories of ND on inpatient resource use, and repeat of this study at a national level and over a longer period of time

Myocardial infarction with unusual presentation of otalgia: a case report

A rare case of a patient with unusual symptoms of earache and sore throat for cardiac ischemia is presented. A diagnosis of non-ST-segment elevation myocardial infarction (NSTEMI) was made based on initial elevation of troponin and an abnormal electrocardiograph (ECG). Percutaneous coronary intervention (PCI) performed with stent placement in the occluded coronary vessel was followed by a decrease in troponin level and complete resolution of the ear and throat pain and patient recovery from cardiac ischemia

Entanglement-free Heisenberg-limited phase estimation

Measurement underpins all quantitative science. A key example is the measurement of optical phase, used in length metrology and many other applications. Advances in precision measurement have consistently led to important scientific discoveries. At the fundamental level, measurement precision is limited by the number N of quantum resources (such as photons) that are used. Standard measurement schemes, using each resource independently, lead to a phase uncertainty that scales as 1/sqrt(N) - known as the standard quantum limit. However, it has long been conjectured that it should be possible to achieve a precision limited only by the Heisenberg uncertainty principle, dramatically improving the scaling to 1/N. It is commonly thought that achieving this improvement requires the use of exotic quantum entangled states, such as the NOON state. These states are extremely difficult to generate. Measurement schemes with counted photons or ions have been performed with N <= 6, but few have surpassed the standard quantum limit and none have shown Heisenberg-limited scaling. Here we demonstrate experimentally a Heisenberg-limited phase estimation procedure. We replace entangled input states with multiple applications of the phase shift on unentangled single-photon states. We generalize Kitaev's phase estimation algorithm using adaptive measurement theory to achieve a standard deviation scaling at the Heisenberg limit. For the largest number of resources used (N = 378), we estimate an unknown phase with a variance more than 10 dB below the standard quantum limit; achieving this variance would require more than 4,000 resources using standard interferometry. Our results represent a drastic reduction in the complexity of achieving quantum-enhanced measurement precision.Comment: Published in Nature. This is the final versio

Ion-pairing chromatography and amine derivatization provide complementary approaches for the targeted LC-MS analysis of the polar metabolome.

Liquid chromatography coupled to mass spectrometry is a key metabolomics/metabonomics technology. Reversed-phase liquid chromatography (RPLC) is very widely used as a separation step, but typically has poor retention of highly polar metabolites. Here, we evaluated the combination of two alternative methods for improving retention of polar metabolites based on 6-aminoquinoloyl-N-hydroxysuccinidimyl carbamate derivatization for amine groups, and ion-pairing chromatography (IPC) using tributylamine as an ion-pairing agent to retain acids. We compared both of these methods to RPLC and also to each other, for targeted analysis using a triple-quadrupole mass spectrometer, applied to a library of ca. 500 polar metabolites. IPC and derivatization were complementary in terms of their coverage: combined, they improved the proportion of metabolites with good retention to 91%, compared to just 39% for RPLC alone. The combined method was assessed by analyzing a set of liver extracts from aged male and female mice that had been treated with the polyphenol compound ampelopsin. Not only were a number of significantly changed metabolites detected, but also it could be shown that there was a clear interaction between ampelopsin treatment and sex, in that the direction of metabolite change was opposite for males and females

COVID‐19 and its cardiovascular effects: a systematic review of prevalence studies

BACKGROUND: A small minority of people with coronavirus disease 2019 (COVID-19) develop a severe illness, characterised by inflammation, microvascular damage and coagulopathy, potentially leading to myocardial injury, venous thromboembolism (VTE) and arterial occlusive events. People with risk factors for or pre-existing cardiovascular disease may be at greater risk. OBJECTIVES: To assess the prevalence of pre-existing cardiovascular comorbidities associated with suspected or confirmed cases of COVID-19 in a variety of settings, including the community, care homes and hospitals. We also assessed the nature and rate of subsequent cardiovascular complications and clinical events in people with suspected or confirmed COVID-19. SEARCH METHODS: We conducted an electronic search from December 2019 to 24 July 2020 in the following databases: the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, covid-19.cochrane.org, ClinicalTrials.gov and EU Clinical Trial Register. SELECTION CRITERIA: We included prospective and retrospective cohort studies, controlled before-and-after, case-control and cross-sectional studies, and randomised controlled trials (RCTs). We analysed controlled trials as cohorts, disregarding treatment allocation. We only included peer-reviewed studies with 100 or more participants, and excluded articles not written in English or only published in pre-print servers. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the search results and extracted data. Given substantial variation in study designs, reported outcomes and outcome metrics, we undertook a narrative synthesis of data, without conducting a meta-analysis. We critically appraised all included studies using the Joanna Briggs Institute (JBI) checklist for prevalence studies and the JBI checklist for case series. MAIN RESULTS: We included 220 studies. Most of the studies originated from China (47.7%) or the USA (20.9%); 9.5% were from Italy. A large proportion of the studies were retrospective (89.5%), but three (1.4%) were RCTs and 20 (9.1%) were prospective. Using JBI's critical appraisal checklist tool for prevalence studies, 75 studies attained a full score of 9, 57 studies a score of 8, 31 studies a score of 7, 5 studies a score of 6, three studies a score of 5 and one a score of 3; using JBI's checklist tool for case series, 30 studies received a full score of 10, six studies a score of 9, 11 studies a score of 8, and one study a score of 5 We found that hypertension (189 studies, n = 174,414, weighted mean prevalence (WMP): 36.1%), diabetes (197 studies, n = 569,188, WMP: 22.1%) and ischaemic heart disease (94 studies, n = 100,765, WMP: 10.5%)  are highly prevalent in people hospitalised with COVID-19, and are associated with an increased risk of death. In those admitted to hospital, biomarkers of cardiac stress or injury are often abnormal, and the incidence of a wide range of cardiovascular complications is substantial, particularly arrhythmias (22 studies, n = 13,115, weighted mean incidence (WMI) 9.3%), heart failure (20 studies, n = 29,317, WMI: 6.8%) and thrombotic complications (VTE: 16 studies, n = 7700, WMI: 7.4%). AUTHORS' CONCLUSIONS: This systematic literature review indicates that cardiometabolic comorbidities are common in people who are hospitalised with a COVID-19 infection, and cardiovascular complications are frequent. We plan to update this review and to conduct a formal meta-analysis of outcomes based on a more homogeneous selected subsample of high-certainty studies

Morphological and Bactericidal Effects of Different Antibiotics on Helicobacter pylori

Background: Helicobacter pylori (H. pylori) is a spiral Gram negative bacteria that can transform to the coccoid form in adverse conditions. Objectives: The aim of this study was to determine the in vitro morphological and bactericidal effects of metronidazole, amoxicillin and clarithromycin on H. pylori. Materials and Methods: The standard strain 26695 of H. pylori was cultured on Brucella agar (BA) and the minimum inhibitory concentrations (MICs) of three antibiotics were determined by E-test method. The bacteria were exposed to antibiotics at 1/2 MIC, MIC and 2X MIC concentrations in Brucella broth (BB). Induced coccoid forms were confirmed by Gram staining and light microscopy. The viability of cells as well as the susceptibility of viable coccoids to antibiotics were examined using the flow cytometry method. Results: All of the three antibiotics at sub-MIC induced coccoid forms. The highest rates of coccoids (> 90%) were induced at 0.008 μg/ mL concentration (1/2 MIC) of amoxicillin, 72 hours postexposure. Metronidazole and clarithromycin with 1/2 MIC (0.5 and 0.125 µg/mL respectively) induced lower rates of coccoid forms (60% and 40% respectively). Potent bactericidal effects on coccoids were observed with Metronidazole at 2X MIC and clarithromycin at MIC (0.25 µg/mL) (80 - 90%). Amoxicillin with MIC and 2X MIC had no bactericidal effect on coccoid forms. Conclusions: Despite the good in vitro bactericidal effect of amoxicillin on spiral forms of H. pylori, this antibiotic has little effect on induced coccoids that may develop after the inappropriate in vivo antibacterial treatment. Hence, for successful therapy, it is essential not only to eradicate the spiral forms, but to eliminate the viable coccoids

A review of RCTs in four medical journals to assess the use of imputation to overcome missing data in quality of life outcomes

Background: Randomised controlled trials (RCTs) are perceived as the gold-standard method for evaluating healthcare interventions, and increasingly include quality of life (QoL) measures. The observed results are susceptible to bias if a substantial proportion of outcome data are missing. The review aimed to determine whether imputation was used to deal with missing QoL outcomes. Methods: A random selection of 285 RCTs published during 2005/6 in the British Medical Journal, Lancet, New England Journal of Medicine and Journal of American Medical Association were identified. Results: QoL outcomes were reported in 61 (21%) trials. Six (10%) reported having no missing data, 20 (33%) reported ≤ 10% missing, eleven (18%) 11%–20% missing, and eleven (18%) reported >20% missing. Missingness was unclear in 13 (21%). Missing data were imputed in 19 (31%) of the 61 trials. Imputation was part of the primary analysis in 13 trials, but a sensitivity analysis in six. Last value carried forward was used in 12 trials and multiple imputation in two. Following imputation, the most common analysis method was analysis of covariance (10 trials). Conclusion: The majority of studies did not impute missing data and carried out a complete-case analysis. For those studies that did impute missing data, researchers tended to prefer simpler methods of imputation, despite more sophisticated methods being available.The Health Services Research Unit is funded by the Chief Scientist Office of the Scottish Government Health Directorate. Shona Fielding is also currently funded by the Chief Scientist Office on a Research Training Fellowship (CZF/1/31)

A review of RCTs in four medical journals to assess the use of imputation to overcome missing data in quality of life outcomes

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