Lithium alters brain activation in bipolar disorder in a task- and state-dependent manner: an fMRI study

BACKGROUND: It is unknown if medications used to treat bipolar disorder have effects on brain activation, and whether or not any such changes are mood-independent. METHODS: Patients with bipolar disorder who were depressed (n = 5) or euthymic (n = 5) were examined using fMRI before, and 14 days after, being started on lithium (as monotherapy in 6 of these patients). Patients were examined using a word generation task and verbal memory task, both of which have been shown to be sensitive to change in previous fMRI studies. Differences in blood oxygenated level dependent (BOLD) magnitude between the pre- and post-lithium results were determined in previously defined regions of interest. Severity of mood was determined by the Hamilton Depression Scale for Depression (HAM-D) and the Young mania rating scale (YMRS). RESULTS: The mean HAM-D score at baseline in the depressed group was 15.4 ± 0.7, and after 2 weeks of lithium it was 11.0 ± 2.6. In the euthymic group it was 7.6 ± 1.4 and 3.2 ± 1.3 respectively. At baseline mean BOLD signal magnitude in the regions of interest for the euthymic and depressed patients were similar in both the word generation task (1.56 ± 0.10 and 1.49 ± 0.10 respectively) and working memory task (1.02 ± 0.04 and 1.12 ± 0.06 respectively). However, after lithium the mean BOLD signal decreased significantly in the euthymic group in the word generation task only (1.56 ± 0.10 to 1.00 ± 0.07, p < 0.001). Post-hoc analysis showed that these differences were statistically significant in Broca's area, the left pre-central gyrus, and the supplemental motor area. CONCLUSION: This is the first study to examine the effects of lithium on brain activation in bipolar patients. The results suggest that lithium has an effect on euthymic patients very similar to that seen in healthy volunteers. The same effects are not seen in depressed bipolar patients, although it is uncertain if this lack of change is linked to the lack of major improvements in mood in this group of patients. In conclusion, this study suggests that lithium may have effects on brain activation that are task- and state-dependent. Given the small study size and the mildness of the patient's depression these results require replication

Looking for the “Little Things”: A Multi-Disciplinary Approach to Medicines Monitoring for Older People Using the ADRe Resource

As prescribing has become the dominant modality of medical treatment, the “pharmaceuticalization” of practice has often resulted in treatment “at a distance”, with doctors having limited contact with patients. Older and poorer people, who are socially distanced from medical prescribers, suffer more adverse drug reactions (ADRs) than the general population. This paper advocates a team approach to checking patients in care homes systematically for ADRs, using information from manufacturers’ guidelines. It explains the benefits of medicines monitoring to protect older patients from iatrogenic harm, such as over-sedation and falls. The ADRe profile is a sophisticated paper-based check-list, which helps nurses and carers play an active role in monitoring signs symptoms that indicate problems. Better monitoring allows doctors and pharmacists to adjust prescribing and respond to identified ADRs. We argue that Implementation of tools like ADRe can be accelerated by changes to the regulatory regime and better inter-professional cooperation

Developing the Diagnostic Adherence to Medication Scale (the DAMS) for use in clinical practice

There is a need for an adherence measure, to monitor adherence services in clinical practice, which can distinguish between different types of non-adherence and measure changes over time. In order to be inclusive of all patients it needs to be able to be administered to both patients and carers and to be suitable for patients taking multiple medications for a range of clinical conditions. A systematic review found that no adherence measure met all these criteria. We therefore wished to develop a theory based adherence scale (the DAMS) and establish its content, face and preliminary construct validity in a primary care population

Quality of medication use in primary care - mapping the problem, working to a solution: a systematic review of the literature

Background: The UK, USA and the World Health Organization have identified improved patient safety in healthcare as a priority. Medication error has been identified as one of the most frequent forms of medical error and is associated with significant medical harm. Errors are the result of the systems that produce them. In industrial settings, a range of systematic techniques have been designed to reduce error and waste. The first stage of these processes is to map out the whole system and its reliability at each stage. However, to date, studies of medication error and solutions have concentrated on individual parts of the whole system. In this paper we wished to conduct a systematic review of the literature, in order to map out the medication system with its associated errors and failures in quality, to assess the strength of the evidence and to use approaches from quality management to identify ways in which the system could be made safer. Methods: We mapped out the medicines management system in primary care in the UK. We conducted a systematic literature review in order to refine our map of the system and to establish the quality of the research and reliability of the system. Results: The map demonstrated that the proportion of errors in the management system for medicines in primary care is very high. Several stages of the process had error rates of 50% or more: repeat prescribing reviews, interface prescribing and communication and patient adherence. When including the efficacy of the medicine in the system, the available evidence suggested that only between 4% and 21% of patients achieved the optimum benefit from their medication. Whilst there were some limitations in the evidence base, including the error rate measurement and the sampling strategies employed, there was sufficient information to indicate the ways in which the system could be improved, using management approaches. The first step to improving the overall quality would be routine monitoring of adherence, clinical effectiveness and hospital admissions. Conclusion: By adopting the whole system approach from a management perspective we have found where failures in quality occur in medication use in primary care in the UK, and where weaknesses occur in the associated evidence base. Quality management approaches have allowed us to develop a coherent change and research agenda in order to tackle these, so far, fairly intractable problems

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice