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ICU Nurses’ Perceptions of Patients with Co-Morbid Mental Health Disorders: An Integrative Review
No full textUse of medications with pharmacogenomic guidelines and adverse outcomes in hospitalised older patients: a retrospective cross-sectional study
Get PDFThis study aimed to assess the prevalence of the use of medications with pharmacogenomic guidelines upon hospital admission in patients aged 65 and over and evaluate its association with adverse outcomes, including length of stay, unplanned admissions, and repeat hospital admissions. A retrospective cross-sectional study was conducted using hospital admissions data from 2018–2019 in one NHS hospital trust in England, focusing on patients aged 65 and over. The usage of medications with pharmacogenomic guidelines was examined, and comparisons were made between their prevalence in unplanned and planned admissions. Multivariable models assessed whether the use of medications with pharmacogenomic guidelines were associated with adverse outcomes, considering frailty status. Analysis of 59,973 admissions revealed 67 pharmacogenomics medicines as per the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines, with 11 classified as high-risk among 1438 unique medicines identified from 560,179 recorded medications. Notably, unplanned admissions exhibited a higher prevalence of medications with pharmacogenomic guidelines (84% versus 64%, p < 0.001) compared to planned admissions. The models demonstrated the usage of these medications was associated with adverse outcomes (length of stay in hospital, unplanned admission and repeat hospital admission) with substantial evidence (Delta_AICc < 2) particularly in patients with high frailty status. This study highlights the association between medications with pharmacogenomic guidelines and adverse outcomes, particularly among patients with high frailty. The findings emphasise the importance of integrating pharmacogenomic-guided care into the management of older individuals with frailty to mitigate adverse outcomes and enhance medication safety
Newborn screening for spinal muscular atrophy in the UK: use of modelling to identify priorities for ongoing evaluation
Get PDFSpinal muscular atrophy (SMA) is a genetic condition that causes the degeneration of motor neurons in the spinal cord. Newborn blood spot (NBS) screening can potentially enable diagnosis before symptoms, and presymptomatic treatment is considered to be more effective than symptomatic treatment. In this paper, we present an overview of a cost-effectiveness model of NBS screening for SMA in the UK, informed by key clinical trials and the relevant published literature. Our analyses suggest that implementing screening could result in better outcomes and lower costs compared to the current approach of no screening plus treatment. However, several uncertainties and limitations of the model remain. These include uncertainty in the reimbursement status of nusinersen and risdiplam in the future; the ‘actual’ costs of treatments, as they are under confidential commercial agreements; uncertainty in the long-term effectiveness of presymptomatic and symptomatic treatment; and uncertainty around the incidence of SMA and the costs and the accuracy of NBS screening. An SMA in-service evaluation (ISE) that could capture data specific to the UK is under consideration, and an appropriately designed ISE with ongoing data collection could support periodic updates of clinical and cost-effectiveness estimates of NBS screening for SMA in the UK
Aspergillus fumigatus PolX1 is an early ancestor of vertebrate terminal deoxynucleotidyl transferases
Get PDFX-family DNA polymerases (PolXs) perform essential roles in repair and maintenance of the genome. One branch of the PolXs have evolved to function as terminal transferases, extending DNA ends in a template-independent manner, unusual for polymerases. To date, template independence has been shown exclusively in metazoans. We analysed PolXs to determine the phylogenetic evolution of the terminal transferase function in fungal PolXs. We have identified and characterised a PolX from the saprophytic fungus Aspergillus fumigatus, named AfPolX1, that demonstrates inherent terminal transferase ability under physiologically relevant conditions. This is the first report for a fungal terminal deoxynucleotidyl transferase (TdT). Our findings indicate that template-independent ‘creative’ synthesis evolved earlier than previously thought and can be traced as far back as the early Polµ’s of multicellular fungi. We further show that like TdT, AfPolX1 is capable of introducing ribonucleotides and various nucleotides with 2′ ribose modifications, giving credence to the idea that the structural features necessary for PolXs observed promiscuous behaviour during template independence existed in the PolXs of early eukaryotes. Our findings suggest AfPolX1 as a promising candidate for use in enzymatic oligonucleotide synthesis
ChIP happens:from biochemical origins to the modern omics toolbox for understanding steroid hormone receptors
Get PDFNuclear steroid hormone receptors (SHRs) are ligand-activated transcription factors that mediate cellular responses to steroid hormones (SHs) through regulating gene expression. Understanding the SHR function is crucial for elucidating SH-driven physiology and pathology, including their roles in normal development, metabolism and reproduction, alongside their aberrant function in cancer, endocrine disorders and inflammatory diseases. Investigating the mechanisms that underscore SHR signalling and regulation is therefore essential for advancing our knowledge of both normal physiology and disease and is vital to the development of novel therapeutic strategies. In this review, we examine a range of methods for studying SHR interactions with chromatin and coregulator proteins, from classical biochemical assays to more advanced approaches such as PL-MS, RIME and ChIP. We also highlight potential future innovations in the field, including in situ Calling Cards and UV-induced photocross-linking RIME (UVXL-RIME), that may overcome current methodological limitations, in turn enabling the study of SHRs in increasingly physiologically relevant contexts
The euro after quarter of a century: a post-Keynesian perspective
Get PDFThe paper starts by reviewing the post-Keynesian analysis of the formation of the euro, indicating the concerns over the imposition of common fiscal policies across the Economic and Monetary Union (EMU) countries, the likely deflationary effects, and constraints on counter-cyclical fiscal policy. Scepticism was expressed over the role of the European Central Bank (ECB) and its relationships with national governments in terms of the financing of government expenditure and its abilities to achieve a harmonised inflation target across all countries. It is argued that the issues identified by post-Keynesian (and other) authors have haunted the governance of the euro area and in a number of cases and that corresponding policy shifts have intensified these problems. The developments over budget deficits and national debt in the EMU are mapped out. It broadly suggests a tightening of the deflationary nature of the rules, particularly regarding the excessive deficit procedures, and the shift of emphasis from deficit to debt. The adoption of the ‘structural budget’ and its reliance on ‘potential output’ raise further problematics. Section 5 relates to the role of the ECB and monetary policy, and the relationship between ECB and national governments. Section 6 explores the responses of the authorities to the euro and other crises. Section 7 is a concluding section in which we discuss how far our fears on the euro were realised, and the struggles to address issues
Alkyl chain length governs structure, conformation and antimicrobial activity in poly(alkylene biguanide)
Get PDFPoly(hexamethylene biguanide) (PHMB) is a polycationic antimicrobial polymer exhibiting broad-spectrum activity against bacteria, fungi, and viruses, and is widely used in medical settings for infection prevention and control. However, the relationship between chemical structure and antimicrobial activity remains unclear. In this study, we synthesised and characterised a series of polymeric biguanides with systematically varied alkyl chain lengths to examine the effects of structural variation on physicochemical properties and antimicrobial activity. H NMR spectroscopy and FTIR confirmed successful polymerisation. Solubility measurements revealed a progressive decrease in aqueous solubility with increasing alkyl chain length, consistent with increased hydrophobicity. Dynamic light scattering indicated reversible folding and unfolding of polymer chains in aqueous solution, with stabilisation at higher concentrations. Diffusion-ordered spectroscopy was used to calculate hydrodynamic diameters and polydispersity indices. Antimicrobial assays against Staphylococcus aureus and Pseudomonas aeruginosa showed that polymers containing heptamethylene and octamethylene chains exhibited the highest antibacterial activity, whereas tetramethylene- and pentamethylene-containing polymers showed greater fungicidal activity against Candida albicans. Highly hydrophobic polymers showed increased aggregation, resulting in reduced antimicrobial efficacy. Overall, these results indicate that both charge density and alkyl chain length are key determinants of antimicrobial activity. This polymeric biguanide series provides a platform for further investigation of structure–activity relationships and mechanisms of action against pathogenic microorganisms and their biofilms
Explainable temporal graph-based CNNs for predicting hip replacement risk using EHR data
Get PDFObjective
To develop and compare four explainable artificial intelligence methods to visualise the influence of electronic health records (EHRs) on predicting hip replacement risk.
Methods and analysis
We used a pretrained temporal graph-based convolutional neural networks (TGCNN) model to generate explainable graph visualisations through four methods: the original gradient-weighted class activation mapping (Grad-CAM) applied to graphs, a modified Grad-CAM using absolute weights (Grad-CAM (abs)), sliding element-wise multiplication of feature maps with patient graph inputs (fm-act) and of 3D convolutional neural networks filters/kernels with patient graph inputs (edge-act). These methods visually explain the TGCNN model’s predictions regarding a person’s risk of needing a hip replacement within 5 years, based on clinical codes from EHRs. We evaluated these models through human qualitative analysis studies, sensitivity quantification, edge detection bias and sparsity.
Results
The edge-act methods performed best in terms of graph sparsity and model sensitivity. Subgraph analysis indicated that prescriptions highly influenced predictions. Clinicians found the visualisations useful for explaining model predictions but too complex for clinical decision-making, particularly with extensive patient EHRs.
Conclusions
The fm-act and Grad-CAM (abs) methods led to graphs with zero sparsity; these graphs could be difficult to interpret if the patient has a long EHR history. The edge-act median method had the highest sparsity; therefore, this method might be the easiest to interpret for long EHR histories. We improved the explainability of hip replacement risk predictions using four post hoc methods on the TGCNN model. Further refinement could enhance their utility in clinical decision-making
The time course of exercise-induced expiratory and inspiratory muscle fatigue
Get PDFInspiratory muscle fatigue develops during exercise prior to intolerance. The expiratory muscles are less resistant to fatigue compared to the inspiratory muscles, but the time-course of inspiratory and expiratory muscle fatigue during exercise has not been compared. Ten healthy adults (25 ± 5 years; 2 females) cycled on three separate occasions at 25% of the difference between estimated critical power and peak ramp incremental power (severe-intensity domain) for: 1) 100% of time to the limit of tolerance (T LIM ; 10.2 ± 2.6 min); 2) 75% T LIM (7.7 ± 1.9 min); and 3) 50% T LIM (5.1 ± 1.3 min). Expiratory and inspiratory muscle fatigue were quantified as the pre- to post-exercise reduction in the gastric (Pga tw ) and diaphragm (Pdi tw ) twitch pressure response to magnetic stimulation of the thoracic and cervical nerves, respectively. Pga tw and Pdi tw were reduced from baseline values after 50% T LIM (11.9 ± 8.2% and 9.5 ± 9.2%, both P 0.05). Expiratory and inspiratory muscle fatigue develops relatively early during severe intensity exercise and increases progressively in magnitude by exercise intolerance. The onset and progression of respiratory muscle fatigue during exercise is not different between the expiratory and inspiratory muscles
Artificial Intelligence technologies for assessing skin lesions for referral on the urgent suspected cancer pathway to detect benign lesions and reduce secondary care specialist appointments:early value assessment
Get PDFBackground Skin cancers are some of the most common types of cancer. Dermatology services receive about 1.2 million referrals a year, but only a small minority are confirmed skin cancer. Artificial intelligence may be helpful in the diagnosis of skin cancer by identifying lesions that are or are not cancerous. Objectives To investigate the clinical and cost-effectiveness of two artificial intelligence technologies: DERM (Deep Ensemble for Recognition of Malignancy, Skin Analytics) and Moleanalyzer Pro (FotoFinder), as decision aids following a primary care referral. Methods A rapid systematic review of evidence on the two technologies was conducted. A narrative synthesis was performed, with a meta-analysis of diagnostic accuracy data. Published and unpublished cost-effectiveness evidence on the named technologies, as well as other diagnostic technologies were reviewed. A conceptual model was developed that could form the basis of a full economic evaluation. Results Four studies of DERM and two of Moleanalyzer Pro were subject to full synthesis. DERM had a sensitivity of 96.1% to detect any malignant lesion (95% confidence interval 95.4 to 96.8); at a specificity of 65.4% (95% confidence interval 64.7 to 66.1). For detecting benign lesions, the sensitivity was 71.5% (95% confidence interval 70.7 to 72.3) for a specificity of 86.2% (95% confidence interval 85.4 to 87.0). Moleanalyzer Pro had lower sensitivity, but higher specificity for detecting melanoma than face-to-face dermatologists. DERM might lead to around half of all patients being discharged without assessment by a dermatologist, but a small number of malignant lesions would be missed. Patient and clinical opinions showed substantial resistance to using artificial intelligence without any assessment of lesions by a dermatologist. No published assessments of the cost-effectiveness of the technologies were identified; three assessments related to skin cancer more broadly in a National Health Service setting were identified. These studies employed similar model structures, but the mechanism by which diagnostic accuracy influenced costs and health outcomes differed. An unpublished cost–utility model was provided by Skin Analytics. Several issues with the modelling approach were identified, particularly the mechanisms by which value is driven and how diagnostic accuracy evidence was used. The conceptual model presents an alternative approach, which aligns more closely with the National Institute for Health and Care Excellence reference case and which more appropriately characterises the long-term consequences of basal cell carcinoma. Limitations The rapid review approach meant that some relevant material may have been missed, and capacity for synthesis was limited. The proposed conceptual model does not capture non-cash benefits associated with demand on dermatologist time. An assessment of the likely budget impact and resource use could not be provided. Conclusions DERM shows promising diagnostic accuracy for triage and diagnosis of suspicious cancer lesions in selected patients referred from primary care. Its impact on the diagnostic pathway and patient care is, however, uncertain. Moleanalyzer Pro shows promising accuracy for diagnosing melanoma, but its evidence base is limited. Future work While artificial intelligence has the potential to be cost-effective for the identification of benign lesions, further research addressing the limitations in the diagnostic accuracy evidence is necessary. Without comparative evidence on the diagnostic accuracy of artificial intelligence technologies, their value will remain uncertain. Study registration This study is registered as PROSPERO CRD42023475705. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR136014) and is published in full in Health Technology Assessment; Vol. 30, No. 10. See the NIHR Funding and Awards website for further award information
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