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Background: Establishing and sustaining enteral feeding in critically ill children is challenging and has met with many problems. Aims and objectives: The aim of this study was to investigate (a) how actual calorie intake compared with estimated caloric requirements and (b) whether feeding guideline adherence resulted in improved nutritional intake. Design and methods: A prospective observational study was undertaken over 1 month in a tertiary referral paediatric intensive care unit (PICU) in the northwest of England. Results: Forty-seven children were studied, with a wide range of diagnoses in a 1-month period. Only 47% of the children had enteral feeds started within our 6 h post-admission target. Over half (55%) of the children received less than half of their estimated calorie requirements, but if feeding guidelines were followed, this resulted in a significantly higher ( p = 0·004) delivery of the child's estimated requirements. Conclusions: This study found that many children are not receiving adequate nutrition in PICU and that the use of feeding guidelines significantly improves calorie delivery in PICU patients. Relevance to clinical practice: This paper highlights the dearth of research related to enteral feeding in critically ill children. We found that the use of feeding guidelines improved calorie delivery and so units should be encouraged to develop their own guidelines based on the best evidence available. [ABSTRACT FROM AUTHOR]

Objectives: Current British HIV Association (BHIVA) guidelines recommend the use of FRAX for the routine assessment of bone fracture risk in people living with HIV over 50 years of age every 3 years. Bone mineral density measurement with dual‐energy X‐ray absorptiometry (DXA) scan is recommended for those with increased fracture risk (FRAX major > 10%). Our objectives were to estimate the prevalence of and risk factors for osteoporosis in a population of PLWH aged > 50 years and assess the utility of FRAX in predicting the presence of DXA‐proven osteoporosis in this cohort. Methods: This was a cross‐sectional study of a cohort of PLWH aged > 50 years attending the Chelsea and Westminster Hospital and who had a DXA scan between January 2009 and December 2018. FRAX scores were calculated using the Sheffield algorithm. Multiple regression models and Cohen's kappa values were used to assess risk factors for osteoporosis and agreement between FRAX and DXA scan results, respectively. Results: In all, 744 patients were included (92.9% male, mean age 56 ± 5 years). The prevalence rates of osteoporosis (at DXA scans) and osteopenia were 12.2% and 63.7%, respectively. FRAX major was > 10% in only two patients, while 90/91 (98.9%) patients with osteoporosis had a normal FRAX score. The presence of osteoporosis was significantly associated with low body mass index and estimated glomerular filtration rate (p < 0.05). Conclusion: Our results indicate that FRAX scores did not predict the presence of osteoporosis in our population of PLWH over 50 years of age and therefore FRAX scores may not be the appropriate tool to define eligibility to perform DXA scans in PLWH. [ABSTRACT FROM AUTHOR]

Background: Red blood cells are essential for modern medicine but managing their collection and supply to cope with fluctuating demands represents a major challenge. As deterministic models based on predicted population changes have been problematic, there remains a need for more precise and reliable prediction of use. Here, we develop three new time-series methods to predict red cell use 4 to 52 weeks ahead.Study Design and Methods: From daily aggregates of red blood cell (RBC) units issued from 2005 to 2011 from the NHS Blood and Transplant, we generated a new set of non-overlapping weekly data by summing the daily data over 7 days and derived the average blood use per week over 4-week and 52-week periods. We used three new methods for linear prediction of blood use by computing the coefficients using Minimum Mean Squared Error (MMSE) algorithm.Results: We optimized the time-window size, order of the prediction, and order of the polynomial fit for our data set. By exploiting the annual periodicity of the data, we achieved significant improvements in long-term predictions, as well as modest improvements in short-term predictions. The new methods predicted mean RBC use with a standard deviation of the percentage error of 2.5% for 4 weeks ahead and 3.4% for 52 weeks ahead.Conclusion: This paradigm allows short- and long-term prediction of RBC use and could provide reliable and precise prediction up to 52 weeks ahead to improve the efficiency of blood services and sufficiency of blood supply with reduced costs. [ABSTRACT FROM AUTHOR]

Background: Blood products are essential for modern medicine, but managing their collection and supply in the face of fluctuating demands represents a major challenge. As deterministic models based on predicted changes in population have been problematic, there remains a need for more precise and reliable prediction of demands. Here, we propose a paradigm incorporating four different time-series methods to predict red blood cell (RBC) issues 4 to 24 weeks ahead.Study Design and Methods: We used daily aggregates of RBC units issued from 2005 to 2011 from the National Health Service Blood and Transplant. We generated a new set of nonoverlapping weekly data by summing the daily data over 7 days and derived the average blood issues per week over 4-week periods. We used four methods for linear prediction of blood demand by computing the coefficients with the minimum mean squared error and weighted least squares error algorithms.Results: We optimized the time-window size, order of the prediction, and order of the polynomial fit for our data set. The four time-series methods, essentially using different weightings to data points, gave very similar results and predicted mean RBC issues with a standard deviation of the percentage error of 3.0% for 4 weeks ahead and 4.0% for 24 weeks ahead.Conclusion: This paradigm allows prediction of demand for RBCs and could be developed to provide reliable and precise prediction up to 24 weeks ahead to improve the efficiency of blood services and sufficiency of blood supply with reduced costs. [ABSTRACT FROM AUTHOR]

Background: The co‐occurrence of internalizing disorders is a common form of psychiatric comorbidity, raising questions about the boundaries between these diagnostic categories. We employ network psychometrics in order to: (a) determine whether internalizing symptoms cluster in a manner reflecting DSM diagnostic criteria, (b) gauge how distinct these diagnostic clusters are and (c) examine whether this network structure changes from childhood to early and then late adolescence. Method: Symptom‐level data were obtained for service users in publicly funded mental health services in England between 2011 and 2015 (N = 37,162). A symptom network (i.e. Gaussian graphical model) was estimated, and a community detection algorithm was used to explore the clustering of symptoms. Results: The estimated network was densely connected and characterized by a multitude of weak associations between symptoms. Six communities of symptoms were identified; however, they were weakly demarcated. Two of these communities corresponded to social phobia and panic disorder, and four did not clearly correspond with DSM diagnostic categories. The network structure was largely consistent by sex and across three age groups (8–11, 12–14 and 15–18 years). Symptom connectivity in the two older age groups was significantly greater compared to the youngest group and there were differences in centrality across the age groups, highlighting the age‐specific relevance of certain symptoms. Conclusions: These findings clearly demonstrate the interconnected nature of internalizing symptoms, challenging the view that such pathology takes the form of distinct disorders. [ABSTRACT FROM AUTHOR]

Patient-reported outcome measures (PROMs) are now routinely collected in the English National Health Service and used to compare and reward hospital performance within a high-powered pay-for-performance scheme. However, PROMs are prone to missing data. For example, hospitals often fail to administer the pre-operative questionnaire at hospital admission, or patients may refuse to participate or fail to return their post-operative questionnaire. A key concern with missing PROMs is that the individuals with complete information tend to be an unrepresentative sample of patients within each provider and inferences based on the complete cases will be misleading. This study proposes a strategy for addressing missing data in the English PROM survey using multiple imputation techniques and investigates its impact on assessing provider performance. We find that inferences about relative provider performance are sensitive to the assumptions made about the reasons for the missing data. [ABSTRACT FROM AUTHOR]

Multiple drug intolerance to antihypertensive medications (MDI-HTN) is an overlooked cause of nonadherence. In this study, 55 patients with MDI-HTN were managed with a novel treatment algorithm utilizing sequentially initiated monotherapies or combinations of maximally tolerated doses of fractional tablet doses, liquid formulations, transdermal preparations, and off-label tablet medications. A total of 10% of referred patients had MDI-HTN, resulting in insufficient pharmacotherapy and baseline office blood pressure (OBP) of 178±24/94±15 mm Hg. At baseline, patients were intolerant to 7.6±3.6 antihypertensives; they were receiving 1.4±1.1 medications. After 6 months on the novel MDI-HTN treatment algorithm, both OBP and home blood pressure (HBP) were significantly reduced, with patients receiving 2.0±1.2 medications. At 12 months, OBP was reduced from baseline by 17±5/9±3 mm Hg (P<.01, P<.05) and HBP was reduced by 11±5/12±3 mm Hg (P<.01 for both) while patients were receiving 1.9±1.1 medications. Application of a stratified medicine approach allowed patients to tolerate increased numbers of medications and achieved significant long-term lowering of blood pressure. [ABSTRACT FROM AUTHOR]