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Abstract Intensive malaria control and elimination efforts have led to substantial reductions in malaria incidence over the past two decades. However, the reduction in Plasmodium falciparum malaria cases has led to a species shift in some geographic areas, with P. vivax predominating in many areas outside of Africa. Despite its wide geographic distribution, P. vivax vaccine development has lagged far behind that for P. falciparum, in part due to the inability to cultivate P. vivax in vitro, hindering traditional approaches for antigen identification. In a prior study, we have used a positive-unlabeled random forest (PURF) machine learning approach to identify P. falciparum antigens based on features of known antigens for consideration in vaccine development efforts. Here we integrate systems data from P. falciparum (the better-studied species) to improve PURF models to predict potential P. vivax vaccine antigen candidates. We further show that inclusion of known antigens from the other species is critical for model performance, but the inclusion of only the unlabeled proteins from the other species can result in misdirection of the model toward predictors of species classification, rather than antigen identification. Beyond malaria, incorporating antigens from a closely related species may aid in vaccine development for emerging pathogens having few or no known antigens.

Abstract Background Uncontrolled blood pressure is a significant public health problem associated with a high rate of mortality and morbidity worldwide. In Ethiopia, 48% of hypertensive patients have Uncontrolled blood pressure. Therefore, this study aimed to identify the determinants of uncontrolled blood pressure among adult hypertensive patients on follow-up at the Negele and Adola General Hospitals in the Guji Zone, Oromia, Ethiopia. Methods A facility-based, unmatched case–control study was conducted in Negelle and Adola General Hospitals, Guji Zone, from January-01–30, 2023, on 384 samples. Study participants were selected consecutively as they came for treatment until the required sample size was obtained. The data were collected using an interview-administered structured questionnaire and medical chart review. The data were entered into Epi-data version 3.1 and exported to SPSS version 25 for analysis. Binary logistic regression analysis was used to model the association between the dependent and independent variables. The candidate variables with p

Due to COVID-19, schools closed in Finland for eight weeks in the spring of 2020, and teaching was conducted using distance education. Teachers used their professional agency to ensure a continuation of their students' learning. This study focuses on the experiences of teachers who taught pupils with intellectual disabilities during the distance education period. The research question is: What kind of experiences did the teachers have with distance education? The data were collected via an electronic questionnaire and analysed using qualitative content analysis. The results were examined using teachers' professional agency as a theoretical lens. The results showed that teachers encountered many challenges and emotions at the beginning, but during distance education, they learnt new ways to teach and support pupils and families. Teachers' agency was spread between supporting the agency of pupils and guardians. These are discussed in the article.

ABSTRACT Plasmodium parasites, the causative organism of malaria, caused over 600,000 deaths in 2022. In Mali, Plasmodium falciparum causes the majority of malaria cases and deaths and is transmitted seasonally. Anti-malarial immunity develops slowly over repeated exposures to P. falciparum and some aspects of this immunity (e.g., antibody titers) wane during the non-transmission, dry season. Here, we sequenced RNA from 33 pediatric blood samples collected during P. falciparum infections at the beginning or end of a transmission season, and characterized the host and parasite gene expression profiles for paired, consecutive infections. We found that human gene expression changes more over the course of one transmission season than between seasons, with signatures of partial development of an adaptive immune response during one transmission season and stability in gene expression during the dry season. Additionally, we found that P. falciparum gene expression did not vary with timing during the season and remained stable both across and between seasons, despite varying human immune pressures. Our results provide insights into the dynamics of anti-malarial immune response development over short time frames that could be exploited by future vaccine and prevention efforts.IMPORTANCEOur work seeks to understand how the immune response to Plasmodium falciparum malaria changes between infections that occur during low and high malaria transmission seasons, and highlights that immune gene expression changes more during the high transmission season. This provides important insight into the dynamics of the anti-malarial immune response that are important to characterize over these short time frames to better understand how to exploit this immune response with future vaccine efforts.

Summary: Background: The inflammatory response in patients with traumatic brain injury (TBI) offers opportunities for stratification and intervention. Previous unselected approaches to immunomodulation in patients with TBI have not improved patient outcomes. Methods: Serum and plasma samples from two prospective, multi-centre observational studies of patients with TBI were used to discover (Collaborative European NeuroTrauma Effectiveness Research [CENTER-TBI], Europe) and validate (Transforming Research and Clinical Knowledge in Traumatic Brain Injury [TRACK-TBI] Pilot, USA) individual variations in the immune response using a multiplex panel of 30 inflammatory mediators. Mediators that were associated with unfavourable outcomes (Glasgow outcome score-extended [GOS-E] ≤ 4) were used for hierarchical clustering to identify patients with similar signatures. Findings: Two clusters were identified in both the discovery and validation cohorts, termed early-inflammatory and pauci-inflammatory. The early-inflammatory phenotype had higher concentrations of interleukin-6 (IL-6), IL-15, and monocyte chemoattractant protein 1 (MCP1). Patients with the early-inflammatory phenotype were older and more likely to have an unfavourable GOS-E at 6 months. There were no differences in the baseline injury severity scores between patients in each phenotype. A combined IL-15 and MCP1 signature identified patients with the early-inflammatory phenotype in both cohorts. Inflammatory processes mediated outcomes in older patients with moderate-severe TBI. Interpretation: Our findings offer a precision medicine approach for future clinical trials of immunomodulation in patients with TBI, by using inflammatory signatures to stratify patients. Funding: CENTER-TBI study was supported by the European Union 7th Framework Programme. TRACK-TBI is supported by the National Institute of Neurological Disorders and Stroke.

Abstract Despite clinical benefits of tyrosine kinase inhibitors (TKIs) in cancer, most tumors can reactivate proliferation under TKI therapy. Here we present transcriptional profiling of HER2+ breast cancer cells transitioning from dormant drug tolerant cells to re-proliferating cells under continuous HER2 inhibitor (HER2i) therapy. Focusing on phosphatases, expression of dual-specificity phosphatase DUSP6 was found inhibited in dormant cells, but strongly induced upon regrowth. DUSP6 expression also selectively associated with poor patient survival in HER2+ breast cancers. DUSP6 overexpression conferred apoptosis resistance, whereas its pharmacological blockade prevented therapy tolerance development under HER2i therapy. DUSP6 targeting also synergized with clinically used HER2i combination therapies. Mechanistically DUSP6 is a positive regulator of HER3 expression, and its impact on HER2i tolerance was mediated by neuregulin-HER3 axis. In vivo, genetic targeting of DUSP6 reduced tumor growth in brain metastasis model, whereas its pharmacological targeting induced synthetic lethal therapeutic effect in combination with HER2i. Collectively this work demonstrates that DUSP6 drives escape from HER2i-induced dormancy, and that DUSP6 is a druggable target to overcome HER3-driven TKI resistance.

Abstract Bacteria must constantly probe their environment for rapid adaptation, a crucial need most frequently served by two-component systems (TCS). As one component, sensor histidine kinases (SHK) control the phosphorylation of the second component, the response regulator (RR). Downstream responses hinge on RR phosphorylation and can be highly stringent, acute, and sensitive because SHKs commonly exert both kinase and phosphatase activity. With a bacteriophytochrome TCS as a paradigm, we here interrogate how this catalytic duality underlies signal responses. Derivative systems exhibit tenfold higher red-light sensitivity, owing to an altered kinase-phosphatase balance. Modifications of the linker intervening the SHK sensor and catalytic entities likewise tilt this balance and provide TCSs with inverted output that increases under red light. These TCSs expand synthetic biology and showcase how deliberate perturbations of the kinase-phosphatase duality unlock altered signal-response regimes. Arguably, these aspects equally pertain to the engineering and the natural evolution of TCSs.

Abstract Malaria vaccine development is hampered by extensive antigenic variation and complex life stages of Plasmodium species. Vaccine development has focused on a small number of antigens, many of which were identified without utilizing systematic genome-level approaches. In this study, we implement a machine learning-based reverse vaccinology approach to predict potential new malaria vaccine candidate antigens. We assemble and analyze P. falciparum proteomic, structural, functional, immunological, genomic, and transcriptomic data, and use positive-unlabeled learning to predict potential antigens based on the properties of known antigens and remaining proteins. We prioritize candidate antigens based on model performance on reference antigens with different genetic diversity and quantify the protein properties that contribute most to identifying top candidates. Candidate antigens are characterized by gene essentiality, gene ontology, and gene expression in different life stages to inform future vaccine development. This approach provides a framework for identifying and prioritizing candidate vaccine antigens for a broad range of pathogens.

Abstract Background Understanding the dynamics of gametocyte production in polyclonal Plasmodium falciparum infections requires a genotyping method that detects distinct gametocyte clones and estimates their relative frequencies. Here, a marker was identified and evaluated to genotype P. falciparum mature gametocytes using amplicon deep sequencing. Methods A data set of polymorphic regions of the P. falciparum genome was mined to identify a gametocyte genotyping marker. To assess marker resolution, the number of unique haplotypes in the marker region was estimated from 95 Malawian P. falciparum whole genome sequences. Specificity of the marker for detection of mature gametocytes was evaluated using reverse transcription-polymerase chain reaction of RNA extracted from NF54 mature gametocytes and rings from a non-gametocyte-producing strain of P. falciparum. Amplicon deep sequencing was performed on experimental mixtures of mature gametocytes from two distinct parasite clones, as well as gametocyte-positive P. falciparum field isolates to evaluate the quantitative ability and determine the limit of detection of the genotyping approach. Results A 400 bp region of the pfs230 gene was identified as a gametocyte genotyping marker. A larger number of unique haplotypes was observed at the pfs230 marker (34) compared to the sera-2 (18) and ama-1 (14) markers in field isolates from Malawi. RNA and DNA genotyping accurately estimated gametocyte and total parasite clone frequencies when evaluating agreement between expected and observed haplotype frequencies in gametocyte mixtures, with concordance correlation coefficients of 0.97 [95% CI: 0.92–0.99] and 0.92 [95% CI: 0.83–0.97], respectively. The detection limit of the genotyping method for male gametocytes was 0.41 pfmget transcripts/µl [95% CI: 0.28–0.72] and for female gametocytes was 1.98 ccp4 transcripts/µl [95% CI: 1.35–3.68]. Conclusions A region of the pfs230 gene was identified as a marker to genotype P. falciparum gametocytes. Amplicon deep sequencing of this marker can be used to estimate the number and relative frequency of parasite clones among mature gametocytes within P. falciparum infections. This gametocyte genotyping marker will be an important tool for studies aimed at understanding dynamics of gametocyte production in polyclonal P. falciparum infections.

Abstract Trees are natural objects that carry practical, cultural and spiritual meanings to humans. Trees are an elemental part of human daily life, both in urban and rural environments, and even in locations where forests are distant. Conflicts related to tree removal in the close environments of humans indicate that individual trees may have special significance. Despite that, we have little knowledge of the ways these relationships are formed and the meanings they carry. To examine how the properties of trees and humans influence the type of relationships that are formed between them, we conducted a large‐scale survey (n = 1758). We used cluster analysis to identify typical groups of trees and human–tree relationships and conducted cross‐tabulation to correlate human and tree types in the relationships. In studying the human–tree relationship, we applied the framework of natureculture to address how the lives of humans and trees are bound together in interspecies relationships. Our results show that the strongest influence on tree–human relationships originates from human lifestyles and nature connections. Consequently, we identified three main types of human–tree relationships: (1) Admiring relationships towards large, old and charismatic trees, primarily grounded in sensory and emotional experiences, are common among urban nature‐loving people. (2) Nurturing relationships that occur with young trees in people's own gardens, which is most typical for rural outdoorspeople owning houses. (3) Nostalgic relationships are associated with trees with symbolic value in the memories of people who no longer have a material connection to an important environment. Our study revealed that the affection of humans for trees in their close environment strongly varied in emotional intensity and practical actions related to trees. We provide new knowledge of the correlations between human and tree characteristics in forming their interspecies relationship and how this relationship affects human emotional well‐being. Based on our findings, we suggest that understanding human–nature interdependence helps to sustain and create emotionally supportive multispecies environments through green design and management. Read the free Plain Language Summary for this article on the Journal blog.

Summary: Background: Traumatic brain injury is conventionally categorised as mild, moderate, or severe on the Glasgow Coma Scale (GCS). Recently developed biomarkers can provide more objective and nuanced measures of the extent of brain injury. Methods: Exposure–response relationships were investigated in 2479 patients aged ≥16 enrolled in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) prospective observational cohort study. Neurofilament protein-light (NFL), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), and glial fibrillary acidic protein (GFAP) were assayed from serum sampled in the first 24 h; concentrations were divided into quintiles within GCS severity groups. Relationships with the Glasgow Outcome Scale-Extended were examined using modified Poisson regression including age, sex, major extracranial injury, time to sample, and log biomarker concentration as covariates. Findings: Within severity groups there were associations between biomarkers and outcomes after adjustment for covariates: GCS 13–15 and negative CT imaging (relative risks [RRs] from 1.28 to 3.72), GCS 13–15 and positive CT (1.21–2.81), GCS 9–12 (1.16–2.02), GCS 3–8 (1.09–1.94). RRs were associated with clinically important differences in expectations of prognosis. In patients with GCS 3 (RRs 1.51–1.80) percentages of unfavourable outcome were 37–51% in the lowest quintiles of biomarker levels and reached 90–94% in the highest quintiles. Similarly, for GCS 15 (RRs 1.83–3.79), the percentages were 2–4% and 19–28% in the lowest and highest biomarker quintiles, respectively. Interpretation: Conventional TBI severity classification is inadequate and underestimates heterogeneity of brain injury and associated outcomes. The adoption of circulating biomarkers can add to clinical assessment of injury severity. Funding: European Union 7th Framework program (EC grant 602150), Hannelore Kohl Stiftung, One Mind, Integra LifeSciences, Neuro-Trauma Sciences, NIHR Rosetrees Trust.

Abstract Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD), yet strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we use simulations, a true IBD inference algorithm, and empirical data sets from different malaria transmission settings to investigate the extent of this bias and explore potential correction strategies. We analyze whole genome sequence data generated from 640 new and 3089 publicly available Plasmodium falciparum clinical isolates. We demonstrate that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discover that the removal of IBD peak regions partially restores the accuracy of IBD-based inferences, with this effect contingent on the population’s background genetic relatedness and extent of inbreeding. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.

Abstract Systematically assessing asthma during follow-up contacts is important to accomplish comprehensive treatment. No previous long-term studies exist on how comorbidities, lifestyle factors, and asthma management details are documented in scheduled asthma contacts in primary health care (PHC). We showed comorbidities and lifestyle factors were poorly documented in PHC in this real-life, 12-year, follow-up study. Documented information on rhinitis was found in 8.9% and BMI, overweight, or obesity in ≤1.5% of the 542 scheduled asthma contacts. Of the 145 patients with scheduled asthma contacts, 6.9% had undergone revision of their inhalation technique; 16.6% had documentation of their asthma action plan. Screening of respiratory symptoms was recorded in 79% but nasal symptoms in only 15.5% of contacts. Lifestyle guidance interventions were found in

Abstract In Bandiagara, Mali, children experience on average two clinical malaria episodes per year. However, even in the same transmission area, the number of uncomplicated symptomatic infections, and their parasitemia, can vary dramatically among children. We simultaneously characterize host and parasite gene expression profiles from 136 Malian children with symptomatic falciparum malaria and examine differences in the relative proportion of immune cells and parasite stages, as well as in gene expression, associated with infection and or patient characteristics. Parasitemia explains much of the variation in host and parasite gene expression, and infections with higher parasitemia display proportionally more neutrophils and fewer T cells, suggesting parasitemia-dependent neutrophil recruitment and/or T cell extravasation to secondary lymphoid organs. The child’s age also strongly correlates with variations in gene expression: Plasmodium falciparum genes associated with age suggest that older children carry more male gametocytes, while variations in host gene expression indicate a stronger innate response in younger children and stronger adaptive response in older children. These analyses highlight the variability in host responses and parasite regulation during P. falciparum symptomatic infections and emphasize the importance of considering the children’s age when studying and treating malaria infections.

OBJECTIVE: This study provides the global-, regional- and country-level estimates on the work-related burden of diseases and accidents for 2019, including deaths, disability adjusted life years (DALY) and economic losses. METHODS: Data on occupational illnesses and injuries from international organizations, institutions, and public websites were used. Risk ratios (RR) and population attributable fractions (PAF) for the risk factor-outcome pairs were derived from the literature. Estimated mortality and DALY for a group of seven major diseases covering 120 risk-outcome pairs attributable to work were calculated for 181 countries. RESULTS: Globally, 2.9 million deaths were attributed to work, with 2.58 million deaths due to work-related diseases and 0.32 million related to occupational injuries. Globally, work-related diseases with a long latency period are increasing, while the number of occupational injuries has decreased. Work-related circulatory diseases were the major cause of 912 000 deaths globally, followed by 843 000 work-related malignant neoplasms. In high-income, American, Eastern European and Western Pacific World Health Organization (WHO) regions, however, work-related malignant neoplasms comprised the biggest disease group. DALY attributable to work were estimated to be 180 million in 2019, with an associated economic loss of 5.8% of global GDP. New estimates of psychosocial factors increased the global loss. CONCLUSIONS: The burden of work-related diseases and injuries increased by 26% from 2.3 million annual deaths in 2014 to 2.9 million in 2019. The DALY attributable to work have also substantially increased from 123 million in 2014 to 180 million in 2019 (47% increase). We found large regional and country variations.

Introduction: The COVID-19 pandemic turned biological hazards in the working environment into a global concern. This systematized review of published reviews aimed to provide a comprehensive overview of the specific jobs and categories of workers exposed to biological hazards with the related prevention. Methods: We extracted reviews published in English and French in PubMed, Embase, and Web of Science. Two authors, working independently, subsequently screened the potentially relevant titles and abstracts recovered (step 1) and then examined relevant full texts (step 2). Disagreements were resolved by consensus. We built tables summarizing populations of exposed workers, types of hazards, types of outcomes (types of health issues, means of prevention), and routes of transmission. Results: Of 1426 studies initially identified, 79 studies by authors from every continent were selected, mostly published after 2010 (n = 63, 79.7%). About half of the reviews dealt with infectious hazards alone (n = 38, 48.1%). The industrial sectors identified involved healthcare alone (n = 16), laboratories (n = 10), agriculture (including the animal, vegetable, and grain sectors, n = 32), waste (n = 10), in addition of 11 studies without specific sectors. The results also highlighted a range of hazards (infectious and non-infectious agents, endotoxins, bioaerosols, organic dust, and emerging agents). Conclusion: This systematized overview allowed to list the populations of workers exposed to biological hazards and underlined how prevention measures in the healthcare and laboratory sectors were usually well defined and controlled, although this was not the case in the agriculture and waste sectors. Further studies are necessary to quantify these risks and implement prevention measures that can be applied in every country.

Introduction: Biological risks are a major global problem in the workplace. The recent COVID-19 pandemic has highlighted the need for a more comprehensive understanding of the biological risks at work. This study presents data on both communicable infectious biological agents and noncommunicable factors leading to death and disability for the year 2021. Methods: We followed the methodology established by the International Labour Organization (ILO) in their past global estimates on occupational accidents and work-related diseases. We used relevant ILO estimates for hazardous substances and related population attributable fractions derived from literature, which were then applied to World Health Organization mortality data. The communicable diseases included in the estimates were tuberculosis, pneumococcal diseases, malaria, diarrheal diseases, other infectious diseases, neglected tropical diseases, influenza associated respiratory diseases and COVID-19. Noncommunicable diseases and injuries considered were Chronic Obstructive Diseases (COPD) due to organic dusts, asthma, allergic reactions and risks related to animal contact. We estimated death attributable to biological risk at work and disability in terms of disability adjusted life years (DALYs). Results: We estimated that in 2022, 550,819 deaths were caused by biological risk factors, with 476,000 deaths attributed to communicable infectious diseases and 74,000 deaths caused by noncommunicable factors. Among these, there were 223,650 deaths attributed to COVID-19 at work. We calculated the rate of 584 DALYs per 100,000 workers, representing an 11% increase from the previous estimate of the global burden of work-related disabilities measured by DALYs. Conclusion: This is a first update since previous 2007 ILO estimates, which has now increased by 74% and covers most biological risks factors. However, it is important to note that there may be other diseases and deaths are missing from the data, which need to be included when new information becomes available. It is also worth mentioning that while deaths caused by major communicable diseases including COVID-19 are relatively rare within the working population, absences from work due to these diseases are likely to be very common within the active workforce.

ABSTRACTModelling climate change impact is very important to reduce the crisis behind food security, drought, and loss of energy sectors. The impact on streamflow and hydrological components due to climate change was aimed to investigate by the SWAT model for this study. Two regional climate models (RCM) were selected according to their performance to calibrate and validate the streamflow. The Regional Climate Models’ performance in simulation of flow and the hydrological cycle was evaluated by statistical performance criteria. Digital elevation model (DEM), land use land cover and soil map, and streamflow data were collected and used as raw input for the model. Bias correction was made by using power transformation and variance scaling method for RCM against observed data. The result simulated with RACMO22T was best with (PBIAS = 0.23, NSE = 0.84, R2 = 0.79) for calibration, (PBIAS = 0.11, NSE = 0.88, R2 = 0.81) for validation. RCA4 model underperformed in simulating streamflow compared to RACMO22T with (PBIAS = 0.28, NSE = 0.78, R2 = 0.74) and (PBIAS = 0.18, NSE = 0.85, R2 = 0.78) for calibration and validation of the models respectively. The streamflow was projected and shows a slightly increasing trend respectively with 13.8 and 21.3 % for the 2030s and 2050s simulation years. But in the 2080s simulation periods, the simulated streamflow indicates a decreasing trend under representative concentration pathways (RCP4.5) by 12.5%. The overall result indicates both streamflow and runoff show a decreasing pattern in the end of this century under both scenarios. The spatial variability of hydrological components which contributes to streamflow was dependent on the subbasin characteristics. Furthermore, the simulated groundwater recharge (GW_Q), rainfall, water yields (WYLD), surface runoff (SUR_Q) and evapotranspiration (ET) were decreased by 4%, 17.7%, 20.8%, 27.7%, and 8.6% respectively for the baseline period.

This study evaluated the performance of five Global Climate Model (GCM) outputs from the Coupled Model Intercomparison Project phase 6 (CMIP6) in reproducing the historical precipitation and temperature. Observational data from the National Meteorological Agency are used for model evaluation and bias correction. Then, the projections from representative GCMs are used to understand the future climate (2031–2060) of the Baro River Basin under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5) with respect to the historical datasets (1985–2014). Statistical metrics (percent of bias, root mean square error, and coefficient of determination) are used to assess the model's performance in reproducing precipitation and temperature and Compromise Programming (CP) was used in ranking GCMs. GFDL-CM4, INM-CM5-0, and INM-CM4-8 models for precipitation; CMCC-ESM2, MRI-ESM2-0, and INM-CM4-8 for maximum temperature; and GFDL-CM4, INM-CM4-8, and INM-CM5-0 for minimum temperature were selected based on their better simulation. The projected annual precipitation shows increases of 6% under SSP2-4.5 and 16.46% under SSP5-8.5. The mean annual maximum and minimum temperature show increases of 1.43 and 1.96 °C under SSP2-4.5, and 1.81 and 3.11 °C under SSP5-8.5, respectively. Overall, the ensemble of three models outperforms the ensemble of all models for the Baro River Basin when utilising the representative GCMs. HIGHLIGHTS Multi-model GCM outputs help in reducing model discrepancies.; Multi-criteria evaluation enables the development of proactive approach to facilitate evaluation.; Relying solely on the ensemble of all models is not suitable for climate impact studies.; Careful model selection in climate impact studies should be emphasized.; Comprehensive understanding of climate dynamics helps to explore the future outlook of regions.;

Abstract Background It is known that blood levels of neurofilament light (NF-L) and diffusion-weighted magnetic resonance imaging (DW-MRI) are both associated with outcome of patients with mild traumatic brain injury (mTBI). Here, we sought to examine the association between admission levels of plasma NF-L and white matter (WM) integrity in post-acute stage DW-MRI in patients with mTBI. Methods Ninety-three patients with mTBI (GCS ≥ 13), blood sample for NF-L within 24 h of admission, and DW-MRI ≥ 90 days post-injury (median = 229) were included. Mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated from the skeletonized WM tracts of the whole brain. Outcome was assessed using the Extended Glasgow Outcome Scale (GOSE) at the time of imaging. Patients were divided into CT-positive and -negative, and complete (GOSE = 8) and incomplete recovery (GOSE

Abstract Background Several classification systems for medication errors (MEs) have been established over time, but none of them apply optimally for classifying severe MEs. In severe MEs, recognizing the causes of the error is essential for error prevention and risk management. Therefore, this study focuses on exploring the applicability of a cause-based DRP classification system for classifying severe MEs and their causes. Methods This was a retrospective document analysis study on medication-related complaints and authoritative statements investigated by the Finnish National Supervisory Authority for Welfare and Health (Valvira) in 2013–2017. The data was classified by applying a previously developed aggregated DRP classification system by Basger et al. Error setting and harm to the patient were identified using qualitative content analysis to describe the characteristics of the MEs in the data. The systems approach to human error, error prevention, and risk management was used as a theoretical framework. Results Fifty-eight of the complaints and authoritative statements concerned MEs, which had occurred in a wide range of social and healthcare settings. More than half of the ME cases (52%, n = 30) had caused the patient’s death or severe harm. In total, 100 MEs were identified from the ME case reports. In 53% (n = 31) of the cases, more than one ME was identified, and the mean number of MEs identified was 1.7 per case. It was possible to classify all MEs according to aggregated DRP system, and only a small proportion (8%, n = 8) were classified in the category “Other,” indicating that the cause of the ME could not be classified to specific cause-based category. MEs in the “Other” category included dispensing errors, documenting errors, prescribing error, and a near miss. Conclusions Our study provides promising preliminary results for using DRP classification system for classifying and analyzing especially severe MEs. With Basger et al.’s aggregated DRP classification system, we were able to categorize both the ME and its cause. More research is encouraged with other ME incident data from different reporting systems to confirm our results.

Introduction The empty pelvis syndrome is a significant source of morbidity following pelvic exenteration surgery. It remains poorly defined with research in this field being heterogeneous and of low quality. Furthermore, there has been minimal engagement with patient representatives following pelvic exenteration with respect to the empty pelvic syndrome. ‘PelvEx—Beating the empty pelvis syndrome’ aims to engage both patient representatives and healthcare professionals to achieve an international consensus on a core outcome set, pathophysiology and mitigation of the empty pelvis syndrome.Methods and analysis A modified-Delphi approach will be followed with a three-stage study design. First, statements will be longlisted using a recent systematic review, healthcare professional event, patient and public engagement, and Delphi piloting. Second, statements will be shortlisted using up to three rounds of online modified Delphi. Third, statements will be confirmed and instruments for measurable statements selected using a virtual patient-representative consensus meeting, and finally a face-to-face healthcare professional consensus meeting.Ethics and dissemination The University of Southampton Faculty of Medicine ethics committee has approved this protocol, which is registered as a study with the Core Outcome Measures in Effectiveness Trials Initiative. Publication of this study will increase the potential for comparative research to further understanding and prevent the empty pelvis syndrome.Trial registration number NCT05683795.