Guided digital health intervention for depression in Lebanon: randomised trial

<jats:sec><jats:title>Background</jats:title><jats:p>Most people with mental disorders in communities exposed to adversity in low-income and middle-income countries (LMICs) do not receive effective care. Digital mental health interventions are scalable when digital access is adequate, and can be safely delivered during the COVID-19 pandemic.</jats:p></jats:sec><jats:sec><jats:title>Objective</jats:title><jats:p>To examine the effects of a new WHO-guided digital mental health intervention, Step-by-Step, supported by a non-specialist helper in Lebanon, in the context of concurring economic, humanitarian and political crises, a large industrial disaster and the COVID-19 pandemic.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We conducted a single-blind, two-arm pragmatic randomised trial, comparing guided Step-by-Step with enhanced care as usual (ECAU) among people suffering from depression and impaired functioning. Primary outcomes were depression (Patient Health Questionnaire 9 (PHQ-9)) and impaired functioning (WHO Disability Assessment Schedule-12 (WHODAS)) at post-treatment.</jats:p></jats:sec><jats:sec><jats:title>Findings</jats:title><jats:p>680 people with depression (PHQ-9>10) and impaired functioning (WHODAS>16) were randomised to Step-by-Step or ECAU. Intention-to-treat analyses showed effects on depression (standardised mean differences, SMD: 0.71; 95% CI: 0.45 to 0.97), impaired functioning (SMD: 0.43; 95% CI: 0.21 to 0.65), post-traumatic stress (SMD: 0.53; 95% CI: 0.27 to 0.79), anxiety (SMD: 0.74; 95% CI: 0.49 to 0.99), subjective well-being (SMD: 0.37; 95% CI: 0.12 to 0.62) and self-identified personal problems (SMD: 0.56; 95% CI 0.29 to 0.83). Significant effects on all outcomes were retained at 3-month follow-up.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Guided digital mental health interventions can be effective in the treatment of depression in communities exposed to adversities in LMICs, although some uncertainty remains because of high attrition.</jats:p></jats:sec><jats:sec><jats:title>Clinical implications</jats:title><jats:p>Guided digital mental health interventions should be considered for implementation in LMICs.</jats:p></jats:sec><jats:sec><jats:title>Trial registration number</jats:title><jats:p>ClinicalTrials.gov <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="clintrialgov" xlink:href="NCT03720769">NCT03720769</jats:ext-link>.</jats:p></jats:sec&gt

The PROgnostic Value of unrequested Information in Diagnostic Imaging (PROVIDI) Study: rationale and design

We describe the rationale for a new study examining the prognostic value of unrequested findings in diagnostic imaging. The deployment of more advanced imaging modalities in routine care means that such findings are being detected with increasing frequency. However, as the prognostic significance of many types of unrequested findings is unknown, the optimal response to such findings remains uncertain and in many cases an overly defensive approach is adopted, to the detriment of patient-care. Additionally, novel and promising image findings that are newly available on many routine scans cannot be used to improve patient care until their prognostic value is properly determined. The PROVIDI study seeks to address these issues using an innovative multi-center case-cohort study design. PROVIDI is to consist of a series of studies investigating specific, selected disease entities and clusters. Computed Tomography images from the participating hospitals are reviewed for unrequested findings. Subsequently, this data is pooled with outcome data from a central population registry. Study populations consist of patients with endpoints relevant to the (group of) disease(s) under study along with a random control sample from the cohort. This innovative design allows PROVIDI to evaluate selected unrequested image findings for their true prognostic value in a series of manageable studies. By incorporating unrequested image findings and outcomes data relevant to patients, truly meaningful conclusions about the prognostic value of unrequested and emerging image findings can be reached and used to improve patient-care

Short-term health-related quality of life consequences in a lung cancer CT screening trial (NELSON)

Item does not contain fulltextBACKGROUND: In lung cancer CT screening, participants often have an indeterminate screening result at baseline requiring a follow-up CT. In subjects with either an indeterminate or a negative result after screening, we investigated whether health-related quality of life (HRQoL) changed over time and differed between groups in the short term. METHODS: A total of 733 participants in the NELSON trial received four questionnaires: T0, before randomisation; T1, 1 week before the baseline screening; T2, 1 day after the screening; and T3, 2 months after the screening results but before the 3-month follow-up CT. HRQoL was measured as generic HRQoL (the 12-item Short Form, SF-12; the EuroQol questionnaire, EQ-5D), anxiety (the Spielberger State-Trait Anxiety Inventory, STAI-6), and lung-cancer-specific distress (the Impact of Event Scale, IES). For analyses, repeated-measures analysis of variance was used, adjusted for covariates. RESULTS: Response to each questionnaire was 88% or higher. Scores on SF-12, EQ-5D, and STAI-6 showed no clinically relevant changes over time. At T3, IES scores that were clinically relevant increased after an indeterminate result, whereas these scores showed a significant decrease after a negative result. At T3, differences in IES scores between the two baseline result groups were both significant and clinically relevant (P<0.01). CONCLUSION: This longitudinal study among participants of a lung cancer screening programme showed that in the short term recipients of an indeterminate result experienced increased lung-cancer-specific distress, whereas the HRQoL changes after a negative baseline screening result may be interpreted as a relief

Cisplatin and vinorelbine first-line chemotherapy in non-resectable malignant pleural mesothelioma

The aim was to evaluate the activity of cisplatin and vinorelbine in previously untreated, inoperable patients having histologically verified malignant pleural mesothelioma (MPM), normal organ function, and performance status 0–2. Treatment was vinorelbine 25 mg m−2 i.v. weekly and cisplatin 100 mg m−2 i.v. every 4 weeks with hydration and standard prophylactic antiemetic treatment. Patients gave written informed consent. Characteristics of 54 consecutive patients were: males 85%, epithelial subtype 74%, IMIG stages III and IV 35 and 46%, performance status 0, 1, and 2, 26, 69, and 6%, and median age 63 years (31–78 years). CTC grade 3 or 4 toxicity occurred with respect to leukocytopenia (48% of patients, grade 4 in 13%), nausea (13%), neurotoxicity (11%), nephrotoxicity (4%), and other toxicities (9%). There were no toxic deaths. The median number of cycles was four. The fraction of patients alive at 1-, 2-, and 3-years were 61, 31, and 4%, respectively, and median survival and median time to progression were 16.8 months (0.5 to 46.4 +months) and 7.2 months (1.6 to 40.6 + months). There were two CRs and 14 PRs (response rate 29.6%). Cisplatin and intravenous vinorelbine is a highly active regimen in MPM with a response rate and survival comparable to the most active regimens so far reported

FAIR environmental and health registry (FAIREHR)- supporting the science to policy interface and life science research, development and innovation

The environmental impact on health is an inevitable by-product of human activity. Environmental health sciences is a multidisciplinary field addressing complex issues on how people are exposed to hazardous chemicals that can potentially affect adversely the health of present and future generations. Exposure sciences and environmental epidemiology are becoming increasingly data-driven and their efficiency and effectiveness can significantly improve by implementing the FAIR (findable, accessible, interoperable, reusable) principles for scientific data management and stewardship. This will enable data integration, interoperability and (re)use while also facilitating the use of new and powerful analytical tools such as artificial intelligence and machine learning in the benefit of public health policy, and research, development and innovation (RDI). Early research planning is critical to ensuring data is FAIR at the outset. This entails a well-informed and planned strategy concerning the identification of appropriate data and metadata to be gathered, along with established procedures for their collection, documentation, and management. Furthermore, suitable approaches must be implemented to evaluate and ensure the quality of the data. Therefore, the 'Europe Regional Chapter of the International Society of Exposure Science' (ISES Europe) human biomonitoring working group (ISES Europe HBM WG) proposes the development of a FAIR Environment and health registry (FAIREHR) (hereafter FAIREHR). FAIR Environment and health registry offers preregistration of studies on exposure sciences and environmental epidemiology using HBM (as a starting point) across all areas of environmental and occupational health globally. The registry is proposed to receive a dedicated web-based interface, to be electronically searchable and to be available to all relevant data providers, users and stakeholders. Planned Human biomonitoring studies would ideally be registered before formal recruitment of study participants. The resulting FAIREHR would contain public records of metadata such as study design, data management, an audit trail of major changes to planned methods, details of when the study will be completed, and links to resulting publications and data repositories when provided by the authors. The FAIREHR would function as an integrated platform designed to cater to the needs of scientists, companies, publishers, and policymakers by providing user-friendly features. The implementation of FAIREHR is expected to yield significant benefits in terms of enabling more effective utilization of human biomonitoring (HBM) data.Most co-authors were financialy supported with their respective inistitution. Some of the co-authors were financialy supportrd by the Safe and Efficient Chemistry by Design (SafeChem) project (grant no. DIA 2018/11) funded by the Swedish Foundation for Strategic Environmental Research, and by the PARC project (grant no. 101057014) funded under the European Union's Horizon Europe Research and Innovation program

A walk in the PARC:developing and implementing 21st century chemical risk assessment in Europe

Current approaches for the assessment of environmental and human health risks due to exposure to chemical substances have served their purpose reasonably well. Nevertheless, the systems in place for different uses of chemicals are faced with various challenges, ranging from a growing number of chemicals to changes in the types of chemicals and materials produced. This has triggered global awareness of the need for a paradigm shift, which in turn has led to the publication of new concepts for chemical risk assessment and explorations of how to translate these concepts into pragmatic approaches. As a result, next-generation risk assessment (NGRA) is generally seen as the way forward. However, incorporating new scientific insights and innovative approaches into hazard and exposure assessments in such a way that regulatory needs are adequately met has appeared to be challenging. The European Partnership for the Assessment of Risks from Chemicals (PARC) has been designed to address various challenges associated with innovating chemical risk assessment. Its overall goal is to consolidate and strengthen the European research and innovation capacity for chemical risk assessment to protect human health and the environment. With around 200 participating organisations from all over Europe, including three European agencies, and a total budget of over 400 million euro, PARC is one of the largest projects of its kind. It has a duration of seven years and is coordinated by ANSES, the French Agency for Food, Environmental and Occupational Health & Safety

A prediction model for neonatal mortality in low- and middle-income countries: an analysis of data from population surveillance sites in India, Nepal and Bangladesh.

Abstract BACKGROUND: In poor settings, where many births and neonatal deaths occur at home, prediction models of neonatal mortality in the general population can aid public-health policy-making. No such models are available in the international literature. We developed and validated a prediction model for neonatal mortality in the general population in India, Nepal and Bangladesh. METHODS: Using data (49 632 live births, 1742 neonatal deaths) from rural and urban surveillance sites in South Asia, we developed regression models to predict the risk of neonatal death with characteristics known at (i) the start of pregnancy, (ii) start of delivery and (iii) 5 minutes post partum. We assessed the models' discriminative ability by the area under the receiver operating characteristic curve (AUC), using cross-validation between sites. RESULTS: At the start of pregnancy, predictive ability was moderate {AUC 0.59 [95% confidence interval (CI) 0.58-0.61]} and predictors of neonatal death were low maternal education and economic status, short birth interval, primigravida, and young and advanced maternal age. At the start of delivery, predictive ability was considerably better [AUC 0.73 (95% CI 0.70-0.76)] and prematurity and multiple pregnancy were strong predictors of death. At 5 minutes post partum, predictive ability was good [AUC: 0.85 (95% CI 0.80-0.89)]; very strong predictors were multiple birth, prematurity and a poor condition of the infant at 5 minutes. CONCLUSIONS: We developed good performing prediction models for neonatal mortality. Neonatal deaths are highly concentrated in a small group of high-risk infants, even in poor settings in South Asia. Risk assessment, as supported by our models, can be used as a basis for improving community- and facility-based newborn care and prevention strategies in poor settings