A pilot study of an integrated mental health, social and medical model for diabetes care in an inner‐city setting: three dimensions for diabetes (3DFD)

Aims We examined the effectiveness of a service innovation, Three Dimensions for Diabetes (3DFD), that consisted of a referral to an integrated mental health, social care and diabetes treatment model, compared with usual care in improving biomedical and health economic outcomes. Methods Using a non‐randomized control design, the 3DFD model was offered in two inner‐city boroughs in London, UK, where diabetes health professionals could refer adult residents with diabetes, suboptimal glycaemic control [HbA1c ≥ 75 mmol/mol (≥ 9.0%)] and mental health and/or social problems. In the usual care group, there was no referral pathway and anonymized data on individuals with HbA1c ≥ 75 mmol/mol (≥ 9.0%) were collected from primary care records. Change in HbA1c from baseline to 12 months was the primary outcome, and change in healthcare costs and biomedical variables were secondary outcomes. Results 3DFD participants had worse glycaemic control and higher healthcare costs than control participants at baseline. 3DFD participants had greater improvement in glycaemic control compared with control participants [−14 mmol/mol (−1.3%) vs. −6 mmol/mol (−0.6%) respectively, P < 0.001], adjusted for confounding. Total follow‐up healthcare costs remained higher in the 3DFD group compared with the control group (mean difference £1715, 95% confidence intervals 591 to 2811), adjusted for confounding. The incremental cost‐effectiveness ratio was £398 per mmol/mol unit decrease in HbA1c, indicating the 3DFD intervention was more effective and costed more than usual care. Conclusions A biomedical, psychological and social criteria‐based referral system for identifying and managing high‐cost and high‐risk individuals with poor glycaemic control can lead to improved health in all three dimensions

The Patient Health Questionnaire-9 for detection of major depressive disorder in primary care: consequences of current thresholds in a crosssectional study

<p>Abstract</p> <p>Background</p> <p>There is a need for brief instruments to ascertain the diagnosis of major depressive disorder. In this study, we present the reliability, construct validity and accuracy of the PHQ-9 and PHQ-2 to detect major depressive disorder in primary care.</p> <p>Methods</p> <p>Cross-sectional analyses within a large prospective cohort study (PREDICT-NL). Data was collected in seven large general practices in the centre of the Netherlands. 1338 subjects were recruited in the general practice waiting room, irrespective of their presenting complaint. The diagnostic accuracy (the area under the ROC curve and sensitivities and specificities for various thresholds) was calculated against a diagnosis of major depressive disorder determined with the Composite International Diagnostic Interview (CIDI).</p> <p>Results</p> <p>The PHQ-9 showed a high degree of internal consistency (ICC = 0.88) and test-retest reliability (correlation = 0.94). With respect to construct validity, it showed a clear association with functional status measurements, sick days and number of consultations. The discriminative ability was good for the PHQ-9 (area under the ROC curve = 0.87, 95% CI: 0.84-0.90) and the PHQ-2 (ROC area = 0.83, 95% CI 0.80-0.87). Sensitivities at the recommended thresholds were 0.49 for the PHQ-9 at a score of 10 and 0.28 for a categorical algorithm. Adjustment of the threshold and the algorithm improved sensitivities to 0.82 and 0.84 respectively but the specificity decreased from 0.95 to 0.82 (threshold) and from 0.98 to 0.81 (algorithm). Similar results were found for the PHQ-2: the recommended threshold of 3 had a sensitivity of 0.42 and lowering the threshold resulted in an improved sensitivity of 0.81.</p> <p>Conclusion</p> <p>The PHQ-9 and the PHQ-2 are useful instruments to detect major depressive disorder in primary care, provided a high score is followed by an additional diagnostic work-up. However, often recommended thresholds for the PHQ-9 and the PHQ-2 resulted in many undetected major depressive disorders.</p

Sex differences in the impact of ozone on survival and alveolar macrophage function of mice after Klebsiella pneumoniae infection

<p>Abstract</p> <p>Background</p> <p>Sex differences have been described in a number of pulmonary diseases. However, the impact of ozone exposure followed by pneumonia infection on sex-related survival and macrophage function have not been reported. The purpose of this study was to determine whether ozone exposure differentially affects: 1) survival of male and female mice infected with <it>Klebsiella pneumoniae</it>, and 2) the phagocytic ability of macrophages from these mice.</p> <p>Methods</p> <p>Male and female C57BL/6 mice were exposed to O₃or to filtered air (FA) (control) and then infected intratracheally with <it>K. pneumoniae </it>bacteria. Survival was monitored over a 14-day period, and the ability of alveolar macrophages to phagocytize the pathogen <it>in vivo </it>was investigated after 1 h.</p> <p>Results</p> <p>1) Both male and female mice exposed to O₃are significantly more susceptible to <it>K. pneumoniae </it>infection than mice treated with FA; 2) although females appeared to be more resistant to <it>K. pneumoniae </it>than males, O₃exposure significantly increased the susceptibility of females to <it>K. pneumoniae </it>infection to a greater degree than males; 3) alveolar macrophages from O₃-exposed male and female mice have impaired phagocytic ability compared to macrophages from FA-exposed mice; and 4) the O₃-dependent reduction in phagocytic ability is greater in female mice.</p> <p>Conclusion</p> <p>O₃exposure reduces the ability of mice to survive <it>K. pneumoniae </it>infection and the reduced phagocytic ability of alveolar macrophages may be one of the contributing factors. Both events are significantly more pronounced in female mice following exposure to the environmental pollutant, ozone.</p

The Formation and Evolution of the First Massive Black Holes

The first massive astrophysical black holes likely formed at high redshifts (z>10) at the centers of low mass (~10^6 Msun) dark matter concentrations. These black holes grow by mergers and gas accretion, evolve into the population of bright quasars observed at lower redshifts, and eventually leave the supermassive black hole remnants that are ubiquitous at the centers of galaxies in the nearby universe. The astrophysical processes responsible for the formation of the earliest seed black holes are poorly understood. The purpose of this review is threefold: (1) to describe theoretical expectations for the formation and growth of the earliest black holes within the general paradigm of hierarchical cold dark matter cosmologies, (2) to summarize several relevant recent observations that have implications for the formation of the earliest black holes, and (3) to look into the future and assess the power of forthcoming observations to probe the physics of the first active galactic nuclei.Comment: 39 pages, review for "Supermassive Black Holes in the Distant Universe", Ed. A. J. Barger, Kluwer Academic Publisher

REDUCE (Reviewing long-term antidepressant use by careful monitoring in everyday practice) internet and telephone support to people coming off long-term antidepressants: protocol for a randomised controlled trial.

BACKGROUND: Around one in ten adults take antidepressants for depression in England, and their long-term use is increasing. Some need them to prevent relapse, but 30-50% could possibly stop them without relapsing and avoid adverse effects and complications of long-term use. However, stopping is not always easy due to withdrawal symptoms and a fear of relapse of depression. When general practitioners review patients on long-term antidepressants and recommend to those who are suitable to stop the medication, only 6-8% are able to stop. The Reviewing long-term antidepressant use by careful monitoring in everyday practice (REDUCE) research programme aims to identify safe and cost-effective ways of helping patients taking long-term antidepressants taper off treatment when appropriate. METHODS: Design: REDUCE is a two-arm, 1:1 parallel group randomised controlled trial, with randomisation clustered by participating family practices. SETTING: England and north Wales. POPULATION: patients taking antidepressants for longer than 1 year for a first episode of depression or longer than 2 years for repeated episodes of depression who are no longer depressed and want to try to taper off their antidepressant use. INTERVENTION: provision of 'ADvisor' internet programmes to general practitioners or nurse practitioners and to patients designed to support antidepressant withdrawal, plus three patient telephone calls from a psychological wellbeing practitioner. The control arm receives usual care. Blinding of patients, practitioners and researchers is not possible in an open pragmatic trial, but statistical and health economic data analysts will remain blind to allocation. OUTCOME MEASURES: the primary outcome is self-reported nine-item Patient Health Questionnaire at 6 months for depressive symptoms. SECONDARY OUTCOMES: depressive symptoms at other follow-up time points, anxiety, discontinuation of antidepressants, social functioning, wellbeing, enablement, quality of life, satisfaction, and use of health services for costs. SAMPLE SIZE: 402 patients (201 intervention and 201 controls) from 134 general practices recruited over 15-18 months, and followed-up at 3, 6, 9 and 12 months. A qualitative process evaluation will be conducted through interviews with 15-20 patients and 15-20 practitioners in each arm to explore why the interventions were effective or not, depending on the results. DISCUSSION: Helping patients reduce and stop antidepressants is often challenging for practitioners and time-consuming for very busy primary care practices. If REDUCE provides evidence showing that access to internet and telephone support enables more patients to stop treatment without increasing depression we will try to implement the intervention throughout the National Health Service, publishing practical guidance for professionals and advice for patients to follow, publicised through patient support groups. TRIAL REGISTRATION: ISRCTN:12417565. Registered on 7 October 2019

Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants

BACKGROUND: Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS) will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through clinical practice. Computer-aided decision-support tools would benefit inexperienced clinicians, especially during peak neonatal intensive care unit (NICU) census. METHODS: A five-step procedure was developed to identify predictive variables. Clinical expert (CE) thought processes comprised one model. Variables from that model were used to develop two mathematical models for the decision-support tool: an artificial neural network (ANN) and a multivariate logistic regression model (MLR). The ranking of the variables in the three models was compared using the Wilcoxon Signed Rank Test. The best performing model was used in a web-based decision-support tool with a user interface implemented in Hypertext Markup Language (HTML) and the mathematical model employing the ANN. RESULTS: CEs identified 51 potentially predictive variables for extubation decisions for an infant on mechanical ventilation. Comparisons of the three models showed a significant difference between the ANN and the CE (p = 0.0006). Of the original 51 potentially predictive variables, the 13 most predictive variables were used to develop an ANN as a web-based decision-tool. The ANN processes user-provided data and returns the prediction 0–1 score and a novelty index. The user then selects the most appropriate threshold for categorizing the prediction as a success or failure. Furthermore, the novelty index, indicating the similarity of the test case to the training case, allows the user to assess the confidence level of the prediction with regard to how much the new data differ from the data originally used for the development of the prediction tool. CONCLUSION: State-of-the-art, machine-learning methods can be employed for the development of sophisticated tools to aid clinicians' decisions. We identified numerous variables considered relevant for extubation decisions for mechanically ventilated premature infants with RDS. We then developed a web-based decision-support tool for clinicians which can be made widely available and potentially improve patient care world wide

Sigma-2 receptor ligand as a novel method for delivering a SMAC mimetic drug for treating ovarian cancer

BACKGROUND: The sigma-2 receptor has been validated as a biomarker for proliferating tumours. Second mitochondria-derived activator of caspase (Smac) is a protein released from mitochondria into the cytosol, leading to apoptosis. In this study, we investigated a sigma-2 ligand as a tumour-targeting drug delivery agent for treating ovarian cancer. METHODS: A sigma-2 ligand, SW 43, was conjugated with a Smac mimetic compound (SMC), SW IV-52s, to form SW III-123. The delivery function of the sigma-2 moiety and cell killing mechanisms of SW III-123 were examined in human ovarian cancer cell lines. RESULTS: SW III-123 internalisation into ovarian cancer cells was mediated by sigma-2 receptors. SW III-123, but not SW IV-52s or SW 43, exhibited potent cytotoxicity in human ovarian cancer cell lines SKOV-3, CaOV-3 and BG-1 after 24-h treatment, suggesting that the sigma-2 ligand successfully delivered SMC into ovarian cancer cells. SW III-123 induced rapid degradation of inhibitor of apoptosis proteins (cIAP1 and cIAP2), accumulation of NF-κB-inducing kinase (NIK) and phosphorylation of NF-κB p65, suggesting that SW III-123 activated both canonical and noncanonical NF-κB pathways in SKOV-3 cells. SW III-123 cleaved caspase-8, -9 and -3. Tumour necrosis factor alpha (TNFα) antibody markedly blocked SW III-123-induced cell death and caspase-3 activity in SKOV-3 cells, indicating that SW III-123 activated both intrinsic and extrinsic apoptotic pathways and induced TNFα-dependent cell death in SKOV-3 cells. CONCLUSION: Sigma-2 ligands are a promising tumour-targeting drug delivery agent. Sigma-2-conjugated SMC exemplifies a novel class of therapeutic drugs for treating ovarian cancer