Conectar
by Robert Parisien, Alexander Drost, Amin Razi, Sina Ramtin, David Ring, Stein J. Janssen
ObjectivesTo inform efforts to promote regular and normalized Bayesian reasoning, we studied factors associated with the degree to which surgeons use Bayesian reasoning to navigate uncertainty across different clinical scenarios.
MethodsScience of Variation Group members (153; 58% North America, 30% Europe, 69% over 15 years of experience) completed an online survey reading 8 scenarios of test and treatment decisions and chose one of 4 answer options with higher scores indicating more Bayesian reasoning. Internal consistency of the survey was assessed using Cronbach alpha.
ResultsThe average Bayesian reasoning score across all scenarios was 3.0 (IQR 2.7–3.2) on a 4-point scale, indicating a relative context-dependent variability. Completely non-Bayesian reasoning was selected least often (8.6%, 90 of 1,044) and fully Bayesian reasoning represented 29% (301 of 1,044) of responses. Most surgeons showed mixed patterns (defined as reasoning in which prior probability is acknowledged but underweighted, without explicit probabilistic updating): 85% (121 of 142) used fully Bayesian reasoning at least once (121 of 142) while 42% (60 of 142) used completely non-Bayesian reasoning at least once. The Cronbach alpha was 0.43 suggesting the scenarios measured different aspects of clinical reasoning rather a unified construct.
ConclusionsThe finding that surgeons use relatively context-dependent reasoning suggests an opportunity for surgeons to develop and practice Bayesian reasoning strategies both in training programs and in practice.
Although implementing evidence-based interventions has been shown to improve the quality of care, there is limited evidence evaluating how these interventions are implemented. In intensive care settings, the use of evidence-based protocols, guidelines and care bundles has been associated with enhanced care quality and reduced burden on patients.
To identify and map existing evidence on the evaluation of evidence-based intervention implementation in adults' intensive care.
A scoping review was conducted by including original published and unpublished studies in English and Finnish.
The studies were retrieved from five databases (CINAHL, Scopus, Ovid Medline, Medic ja Mednar) from January 2000 to December 2024. The data search was performed on 29 November 2022 and updated on 10 December 2024. The results were synthesized and presented in a tabular and descriptive form.
A total of 19 studies were included in the review. These studies evaluated the implementation of evidence-based interventions, focusing on nurse and patient outcomes. Nurse outcomes included measures such as compliance, knowledge and self-confidence. Patient outcomes included indicators such as body temperature, blood glucose, incidence of pressure ulcers and length of stay.
The evaluation of evidence-based intervention implementation does not consistently extend to the evaluation of the entire implementation process. More consistent research reporting would improve disseminating the evidence. The evaluation implementation makes it possible to show the impact of nurse and patient outcomes. The evaluation results can reveal the success of the implementation. Further research on evaluation implementation, development of systematic and comprehensive evaluation implementation methods, or evaluation matrix is needed.
The review will be useful for nursing professionals in planning evidence of implementation, developing or researching evaluation implementation. Promoting evaluation of evidence-based intervention implementation in Nursing can improve the quality of patient care, improve disseminating evidence and uniformities of care practice.
What Problem Did the Study Address? There is limited evidence of evaluation of evidence-based interventions of implementation. Evaluating evidence-based implementation is important to ensure the quality of patient care and patient safety.
What Were the Main Findings? Evaluation of implementation of evidence-based interventions focused on nurse and patient outcomes. Evaluation of the entire implementation process was not identified, and implementation strategies were not evaluated.
Where and on Whom Will the Research Have an Impact? Evidence-based practice implementation in nursing for researchers, developers, nursing leaders and clinical nursing practitioners who implement and evaluate evidence-based practice implementation.
PRISMA 2020 statement.
No Patient of Public Contribution: This study did not include patient or public involvement in its design, conduct or reporting.
Randomised clinical trials (RCTs) are gold standard in evidence-based medicine, but follow-up typically relies on clinic visits and trial-specific data collection. Much of this information overlaps with routinely collected healthcare systems data (HSD), such as electronic health records and national registries. Leveraging HSD for trial follow-up has the potential to reduce cost, time and resource burden. However, concerns remain about data quality and evidence is needed to show that HSD-based outcomes are reported to an equivalent standard to trial-specific data.
The Blood Cancer Clinical Trials Long-term Follow-up Using Integrated Healthcare Systems platform will link data collected from multiple myeloma clinical trials with HSD to create a research database supporting extended follow-up and further methodological and clinical research.
This data-linkage study includes participants from multiple myeloma RCTs conducted by the University of Leeds between 2008 and 2021. NHS (National Health Service) England will link these participants to HSD, including deaths and cancer registrations, systemic anticancer therapy, radiotherapy and Hospital Episode Statistics.
We will compare trial-collected outcomes with those derived from HSD, including mortality, treatment, second cancer incidence and major adverse events. Long-term overall survival will be estimated using national mortality data. HSD-derived demographic and clinical variables will be used to assess population representativeness relative to the wider myeloma population. Time to next treatment will be derived and evaluated as a surrogate for progression-free survival. HSD-derived frailty measures will be examined for prognostic utility, and radiotherapy and hospital records will be analysed to characterise bone-related treatments and skeletal complications.
Ethical approval has been obtained from the East of England–Cambridge Central Research Ethics Committee, with Section251 support from the Health Research Authority on advice from the Confidentiality Advisory Group. Findings will be disseminated through publications, conference presentations and engagement with stakeholders and patient groups.
by Ratinan Dangwilailert, Somboon Lekmak, Duangtida Promlee, Tanyaporn Pongkunakorn, Parichart Permpikul
BackgroundHemoglobin (Hb) assessment is crucial to prevent blood donation from anemic donors. Most measurements are invasive and painful; however, an alternative, non-invasive hemoglobin measurement is available. This study aimed to compare non-invasive and point-of-care invasive hemoglobin test results with those from an automated blood analyzer in blood donors.
MethodsQualified blood donors were enrolled at a tertiary care hospital in Bangkok, Thailand. Hemoglobin was initially measured by the non-invasive device (Rad-67 Pulse CO-Oximeter) and a point-of-care invasive hemoglobin screening device (Mission HemoPro). Participants with point-of-care invasive hemoglobin ≥ 12.5 g/dL were eligible to donate, and during donation, standard hemoglobin measurements were obtained using an automated analyzer, XN-550. Those who were ineligible with point-of-care invasive hemoglobin Results
Of 300 participants, 295 had complete data. Of these, 169 were male (57.28%). Average non-invasive, point-of-care, and automated hemoglobin levels were 14.38 ± 1.12 g/dL, 13.65 ± 0.70 g/dL, and 13.90 ± 1.16 g/dL, respectively. The ICC between non-invasive, point-of-care, and automated hemoglobin measurement was 0.600 (95% CI: 0.522–0.668) and 0.897 (95% CI: 0.872–0.957). The sensitivity of the non-invasive Hb measurement was poor for detecting anemic donors when the Hb cut-off was set at 12.5 g/dL. This method received significantly higher satisfaction than the routinely used invasive device.
ConclusionThe non-invasive Hb measurement in blood donors showed moderate agreement with the standard test, but the sensitivity was poor when the cut-off hemoglobin was set at 12.5 g/dl. Since donor satisfaction was higher, this method may be used as an alternative screening tool, provided a higher Hb cut-off value is used.
by Miriam Mohatar-Barba, Ángel Fernández-Aparicio, Javier S. Perona, Jacqueline Schmidt-RioValle, Carmen Enrique-Mirón, Emilio González-Jiménez
Different indirect methods have been developed to assess insulin resistance (IR), though their validation has been limited to adult populations. In this sense, the study aim is to compare the predictive capacity of the McAuley, QUICKI, SPISE indices, and glucose-insulin ratio against insulin resistance (IR) in Spanish adolescents and to establish reliable cut-off values for these indices in this population. A cross-sectional study was conducted with 981 adolescents aged 11–16 years, from Southern Spain. Anthropometric measurements and fasting biochemical parameters, were assessed. IR indices, such as HOMA-IR, QUICKI, the McAuley index, SPISE, and the glucose-insulin ratio, were calculated. The ability of each index to predict IR was evaluated using multivariate regression analysis and receiver operating characteristic (ROC) curves. Boys exhibited higher waist circumference, triglyceride levels, and fasting insulin levels, while girls had a higher percentage of body fat (pTo identify and synthesise the ethical, feasibility and acceptability challenges associated with implementing eye-tracking research with clinicians in acute care settings and to explore strategies to address these concerns.
Scoping review using the Joanna Briggs Institute methodology.
Six databases (MEDLINE, CINAHL, EMBASE, Web of Science, APA PsycInfo and ProQuest Dissertations & Theses Global) were searched for peer-reviewed articles. Reference lists of included studies were also hand-searched.
Eligible studies involved clinicians using or interacting with eye-tracking devices in acute care environments and addressed at least one ethical, feasibility, or acceptability consideration. Data were extracted and thematically analysed. Knowledge users, including clinicians, ethicists and a patient partner, were engaged during protocol development and findings synthesis.
Twenty-five studies published from 2010 to 2024 were included. Seven challenges were identified: obtaining ethical approval, managing consent, privacy and confidentiality concerns, collecting data in unpredictable environments, interference with care, participant comfort and data loss or unreliability. Knowledge users highlighted the importance of early institutional engagement, clear protocols, continuous consent and context-sensitive ethical reflection.
Eye-tracking offers valuable insights into clinician behaviour and cognition, but its implementation in acute care raises complex ethical and methodological issues. Responsible use requires anticipatory planning, stakeholder engagement and flexible yet rigorous protocols.
By informing the development of ethically sound study protocols and consent practices, this work contributes to safer, more transparent and patient-centred research that respects participant autonomy and protects clinical workflows.
The protocol was registered with the Open Science Framework (https://osf.io/jn4yx).
Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA; Page et al., 2021) and its Extension for Scoping Reviews (Tricco et al., 2018).
A patient partner was involved in protocol development, interpretation of findings and development of study recommendations. Their contributions included participating in advisory groups and providing feedback alongside clinicians and ethicists during focus groups. This input helped ensure the research addressed patient-relevant priorities and informed the development of ethically responsible practices for conducting eye-tracking research in clinical care settings.
Respiratory syncytial virus (RSV) is a leading cause of hospitalisation in infants worldwide. New immunoprophylactic products, including long-acting monoclonal antibodies and maternal vaccines, have demonstrated high efficacy in prelicensure clinical trials. Understanding how these interventions perform outside controlled trials, and how viral evolution or host factors influence protection, is essential for sustaining confidence in RSV prevention programmes.
We will conduct a 5-year, test-negative case–control study among infants ≤12 months of age who present with acute respiratory illness (ARI) within a large healthcare delivery network serving a demographically diverse population. Cases will be infants testing positive for RSV by PCR, and controls will be RSV-negative infants meeting the same ARI criteria. Data will be obtained from electronic health records, structured caregiver surveys and state immunization registries to ensure accurate classification of exposures and covariates. Vaccine effectiveness will be estimated using multivariable logistic regression controlling for potential confounding. RSV-positive specimens will undergo full-genome sequencing to identify variant lineages and potential immune-escape mutations. A subset of participants will provide acute and convalescent blood samples for single-cell immune profiling to define innate and adaptive responses associated with breakthrough infection.
The study protocol has been approved by the Yale Human Investigation Committee (HIC #2000036550). Written informed consent will be obtained from all parents or legal guardians prior to participation. Study findings will be disseminated through peer-reviewed publications, scientific meetings and public repositories, with fully de-identified participant data to protect privacy and confidentiality. Viral genomic data will be shared in accordance with the National Institutes of Health Genomic Data Sharing Policy, and analytical code will be made publicly available to ensure reproducibility.
Colorectal cancer (CRC) is one of the most common cancers worldwide. Stage II/III patients undergo curative-intent surgery yet still face the recurrence risk. Detecting recurrences early provides the best opportunity for optimal treatment. We aimed to develop a microsimulation model to evaluate CRC management-associated outcomes based on current guidelines, including the performance of guideline-recommended surveillance in detecting recurrences.
Two separate individual-level state transition (microsimulation) models for colon and rectal cancer were built with a lifetime horizon using monthly cycles. The models integrated treatment and surveillance strategies per current guidelines.
The currently recommended surveillance modalities by National Comprehensive Cancer Network guidelines for surveilling patients with CRC after curative-intent surgery.
65-year-old patients with stage II and stage III CRC who underwent curative-intent surgery in the USA.
Cumulative recurrences, detected recurrences, detection rate, overall survival and recurrence-free survival in a 5-year horizon, as well as average life expectancy, were the outcome measures used.
Over 5 years, disease recurrence was observed in 9.5% of patients with stage II–III colon cancer and in 38.0% of patients with stage II–III rectal cancer. Of these, 82.5% and 85.5% were detected via surveillance, respectively, within 5 years. The predicted 5-year overall survival was 86.0% for colon cancer and 69.3% for rectal cancer, with corresponding recurrence-free survival rates of 78.9% and 53.8%. Based on current guidelines-recommended surveillance, detecting one colon cancer recurrence requires 148 carcinoembryonic antigen (CEA) tests, 37 CT scans and 21 colonoscopies. In contrast, detecting one rectal cancer recurrence requires 31 CEA tests, 8 CT scans and 4 colonoscopies.
Our validated model suggests that relative to an optimal benchmark in which all recurrences are detected, recurrence detection under current guidelines may be suboptimal, indicating room for improvement. As new tests emerge, this model could be a valuable tool for evaluating existing clinical practices and the potential of new tests to enhance patient outcomes.
Post-COVID-19 syndrome (PCS) is characterised by persistent symptoms, such as fatigue, dyspnoea, depression and sleep problems, following SARS-CoV-2 infection. The long-term course and impact on quality of life remain unclear. This review aims to synthesise evidence on longitudinal changes in symptom prevalence, severity and health-related quality of life (HRQoL) in adults with PCS.
This systematic review will include longitudinal studies (randomised controlled trials, non-randomised trials, prospective and retrospective cohort studies) of adults (≥18 years) with PCS, defined by symptoms persisting beyond 4 weeks after acute infection. Eligible studies must report changes in prevalence or severity of fatigue, dyspnoea, depression, sleep problems or HRQoL from baseline to at least one follow-up visit.
We will systematically search MEDLINE, Embase, PsycINFO, Web of Science, Scopus, CINAHL and Epistemonikos, with no restrictions on language, date or publication status. Two reviewers will independently screen studies, extract data and assess risk of bias using validated tools appropriate to study design. Disagreements will be resolved by consensus or a third reviewer.
A narrative synthesis will summarise study characteristics and symptom trajectories. Where sufficient data are available, random-effects meta-analyses will be conducted to estimate pooled changes in symptom prevalence (ORs), severity ((standardised) mean differences) and HRQoL ((standardised) mean differences). Meta-regression and subgroup analyses will explore potential effect modifiers. Certainty of evidence will be evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.
No ethical approval is required. Findings will be disseminated via peer-reviewed publication, conference presentations and plain language summaries.
CRD420251011612.
Medication administration errors are high-risk patient safety issues that could potentially cause harm to patients, thereby delaying recovery and increasing length of hospital stay with additional healthcare costs. Nurses are pivotal to the medication administration process and are considered to be in the position to recognize and prevent these errors. However, the effectiveness of interventions implemented by nurses to reduce medication administration errors in acute hospital settings is less reported.
To identify and quantify the effectiveness of interventions by nurses in reducing medication administration errors in adults' inpatient acute hospital.
A systematic review and meta-analysis was conducted up to 03/24. Six databases were searched. Study methodology quality assessment was conducted using the Joanna Briggs Institute (JBI) critical appraisal tools, and data extraction was conducted. Meta-analysis was performed to combine effect sizes from the studies, and synthesis without meta-analysis was adopted for studies that were not included in the meta-analysis to aggregate and re-examine results from studies.
Searches identified 878 articles with 26 studies meeting the inclusion criteria. Five types of interventions were identified: (1) educational program, (2) workflow smart technologies, (3) protocolised improvement strategy, (4) low resource ward-based interventions, and (5) electronic medication management. The overall results from 14 studies included in meta-analysis showed interventions implemented by nurses are effective in reducing medication administration errors (Z = 2.15 (p = 0.03); odds ratio = 95% CI 0.70 [0.51, 0.97], I 2 = 94%). Sub-group analysis showed workflow smart technologies to be the most effective intervention compared to usual care. Findings demonstrate that nurse-led interventions can significantly reduce medication administration errors compared to usual care. The effectiveness of individual interventions varied, suggesting a bundle approach may be more beneficial. This provides valuable insights for clinical practice, emphasizing the importance of tailored, evidence-based approaches to improving medication safety.
PRISMA guided the review and JBI critical appraisal tools were used for quality appraisal of included studies.
Global discussions surrounding the medical use of marijuana have gained momentum; yet in Malaysia, cannabis remains strictly prohibited under the Dangerous Drugs Act 1952. Despite its legal status, there is growing public discourse on its potential therapeutic benefits. Understanding public acceptance is critical for informing future health policies and public education efforts.
This study used a cross-sectional design, web-based survey among Malaysians aged 18 years and above using convenience and snowball sampling methods. The survey collected data on sociodemographic characteristics, lifestyle factors (eg, smoking and drug use), awareness of medical marijuana and perceived risk. Multivariable logistic regression analysis was performed to identify factors associated with acceptance of medical marijuana decriminalisation.
Out of 2047 respondents, 88.4% supported medical marijuana decriminalisation based on clinical evidence. Key predictors of acceptance included male gender (adjusted OR (AOR) 1.71; 95% CI 1.29 to 2.26), higher education (Bachelor’s degree AOR 1.56; 95% CI 1.09 to 2.23 and Master’s/PhD AOR 2.04; 95% CI 1.34 to 3.10), self-employment (AOR 1.84; 95% CI 1.22 to 2.77) and private sector employment (AOR 1.40; 95% CI 1.03 to 1.89). Behavioural factors, such as smoking (AOR 1.58; 95% CI 1.10 to 2.27), prior drug use (AOR 1.86; 95% CI 1.30 to 2.67) and low perceived risk (AOR 5.82; 95% CI 3.48 to 9.73), were also significantly associated with acceptance.
A large proportion of Malaysian adults supported the clinical use of medical marijuana. Acceptance was strongly associated with demographic and behavioural factors, particularly gender, education and perceived risk. These findings may guide the development of targeted public health education and inform future discussions on regulatory approaches in Malaysia.
by Plotine Jardat, Alexandra Destrez, Fabrice Damon, Noa Tanguy-Guillo, Anne-Lyse Lainé, Céline Parias, Fabrice Reigner, Vitor H. B. Ferreira, Ludovic Calandreau, Léa Lansade
Olfaction is the most widespread sensory modality animals use to communicate, yet much remains to be discovered about its role. While most studies focused on intraspecific interactions and reproduction, new evidence suggests chemosignals may influence interspecific interactions and emotional communication. This study explores this possibility, investigating the potential role of olfactory signals in human-horse interactions. Cotton pads carrying human odours from fear and joy contexts, or unused pads (control odour) were applied to 43 horses’ nostrils during fear tests (suddenness and novelty tests) and human interaction tests (grooming and approach tests). Principal component analysis showed that overall, when exposed to fear-related human odours, horses exhibited significantly heightened fear responses and reduced interaction with humans compared to joy-related and control odours. More precisely, when exposed to fear-related odours, horses touched the human less in the human approach test (effect size: Rate Ratio(RR)=0.60 ± 0.24), gazed more at the novel object (RR = 1.32 ± 0.14), and were more startled (startle intensity – Cohen’s d = −0.88 ± 0.39; and maximum heart rate – Cohen’s d = 1.16 ± 0.47) by a sudden event. These results highlight the significance of chemosignals in interspecific interactions and provide insights into questions about the impact of domestication on emotional communication. Moreover, these findings have practical implications regarding the significance of handlers’ emotional states and its transmission through odours during human-horse interactions.by Giacinto Angelo Sgarro, Paride Vasco, Domenico Santoro, Luca Grilli, Marco Giglio, Natale Daniele Brunetti, Luigi Traetta, Giuseppe Cibelli, Anna Antonia Valenzano
Sudden Cardiac Death (SCD) is a critical and unexpected condition that occurs due to cardiac causes within one hour of the onset of acute cardiovascular symptoms or twenty-four hours in unwitnessed cases. Despite advancements in cardiovascular medicine, practical methods for predicting SCD are still lacking, and there are no standardized systems to identify individuals at risk, especially in seemingly healthy populations such as athletes. In this study, we employed hierarchical clustering and principal component analysis (PCA) on data from 711 competitive athletes, revealing distinct patterns and cluster distributions in PCA space. Specifically, Clustering revealed characteristic feature combinations associated with increased SCD risk in athletes. Notably, certain clusters shared traits, including participation in Class C sports, sinus tachycardia, ventricular pre-excitation, personal or family history of heart disease, T-wave inversions, and prolonged QTc intervals. PCA helped visualize these patterns in distinct spatial regions, highlighting underlying structures and aiding intuitive risk interpretation. These results enable scientists to derive cluster metrics that serve as reference points for classifying new individuals and visually representing risk patterns in a clear graphical format. These findings establish a foundation for predictive tools that, with additional clinical validation, could aid in the prevention of SCD. The dataset used in this study, along with the clustering and PCA results, is available to the scientific community in an open format, together with the necessary tools and scripts to enable independent experimentation and further analysis.by Carmen Villagrasa, Giorgio Baiocco, Zine-El-Abidine Chaoui, Michael Dingfelder, Sébastien Incerti, Pavel Kundrát, Ioanna Kyriakou, Yusuke Matsuya, Takeshi Kai, Alessio Parisi, Yann Perrot, Marcin Pietrzak, Jan Schuemann, Hans Rabus
Biological effects induced by diverse types of ionizing radiation are known to show important variations. Nanodosimetry is suitable for studying the link between these variations and the patterns of radiation interactions within nanometer-scale volumes, using experimental techniques complemented by Monte Carlo track structure (MCTS) simulations. However, predicted nanodosimetric quantities differ among MCTS codes, primarily because each code employs distinct molecular-scale particle interaction models. This multi-code study examines these variations for low-energy electrons (20–10,000 eV), which play a critical role in energy deposition and biological effects by virtually all types of ionizing radiation. Specifically, the hypothesis tested in this work is that inter-code variability in nanodosimetry results is mainly caused by differences in assumptions regarding total interaction cross sections. Ionization cluster size distributions and derived nanodosimetric parameters were simulated with seven MCTS codes (PARTRAC, PHITS-TS, MCwater, PTra, and three Geant4-DNA options) in liquid water as a surrogate for biological tissue. Significant inter-code differences were observed, especially at the lowest energies. They were substantially reduced upon replacing the original cross sections in each code with a common, averaged dataset, created ad-hoc for this study and not based on theoretical assumptions. For example, for 50 eV electrons in 8 nm spheres, the variability in the predicted mean ionization numbers decreased from 23% to 5%, and in the probability of inducing two or more ionizations from 34% to 7% (relative standard deviations). This quantification demonstrates that total interaction cross sections are the primary source of uncertainty at low electron energies. A sensitivity test using DNA damage simulations with the PARTRAC code revealed that cross section variations notably affect biological outcome predictions. Replacing the code’s original cross sections with the averaged ones increased the predicted double-strand break yield by up to 15%. These findings underscore the urgent need for improved characterization of low-energy electron interaction cross sections to reduce uncertainties in MCTS simulations and enhance mechanistic understanding of radiation-induced biological effects.To evaluate the impact of various antihypertensive drugs on secondary stroke prevention in a real-life setting.
Nationwide historic cohort study.
French healthcare system data (SNDS).
Adults hospitalised for ischaemic stroke between 2014 and 2015 were followed up until December 2021 and stratified based on the presence of atrial fibrillation (AF).
Risk of stroke recurrence was assessed using a time-dependent Cox cause-specific model accounting for changes in drug exposure. We also investigated the risk of major adverse cardiovascular events (MACE) or all-cause death. Models were adjusted on stroke characteristics, coprescriptions and co-morbidities, at inclusion and across follow-up.
Among 54 764 patients without AF (median age 71; 46% women) and 17 960 with AF (median age 79; 51% women), stroke recurrence occurred in 11% and 13%, respectively. In non-AF patients, reduced recurrence risk was associated only with use of calcium channel blockers (adjusted HR (aHR) 0.91, 95% CI 0.86 to 0.97), thiazide diuretics (aHR 0.90, 95% CI 0. 83 to 0.97), loop diuretics (aHR 0.86, 95% CI 0.77 to 0.95) and potassium-sparing agents (aHR 0.83, 95% CI 0.70 to 0.98). In AF patients, only potassium-sparing agents (aHR 0.82, 95% CI 0.69 to 0.99) were associated with reduced recurrence risk. All antihypertensive drugs, apart from loop diuretics, were associated with a reduced risk of MACE or all-cause death.
In this large cohort, only diuretics and calcium channel blockers were associated with a reduced risk of recurrent stroke. Most antihypertensive drugs, however, may be more effective in overall cardiovascular prevention.
To examine the association between nurse–patient mutuality (i.e., a good quality of the relationship between the nurse and the patient) and nurse professional quality of life.
A cross-sectional, multi-centre study was conducted across four tertiary hospitals in Italy.
Data collection took place from November 2023 to June 2024, enrolling 517 nurses. Both medical and surgical departments, as well as inpatients and outpatients departments were included. Data were collected on nurses caring for patients with chronic illness. Mutuality was measured with the Nurse–Patient Mutuality in Chronic Illness scale, which includes three dimensions: Developing and Going Beyond, Being a Point of Reference, Deciding and Sharing Care; Professional Quality of Life was measured with the Professional Quality of Life version 5, which includes three dimensions: Compassion Satisfaction, Secondary Traumatic Stress, Burnout. A Bayesian path analysis was employed to evaluate the contribution of mutuality dimensions to the dimensions of professional quality of life.
Nurses' sample consisted of 517 participants. The three dimensions of mutuality showed different associations with the three dimensions of professional quality of life. Specifically, Being a Point of Reference, along with Deciding and Sharing Care, was significantly associated with Compassion Satisfaction. The dimensions Developing and Going Beyond and Deciding and Sharing Care were significantly and negatively associated with Secondary Traumatic Stress. Additionally, Deciding and Sharing Care was significantly and negatively associated with Burnout.
As all the dimensions of mutuality were significantly associated with different aspects of professional quality of life, future interventions to improve nurses' professional quality of life may also consider nurse–patient mutuality.
Nurse–patient mutuality may be a novel area of research to enhance nurses' professional quality of life, with implications for clinical practice and organisational development.
Nurse–patient mutuality is a key indicator of a high-quality relationship, enabling shared goals and shared decision-making. Nurses' professional quality of life is one of the most important factors that influence their intention to leave. Little is known about the association between nurse–patient mutuality and nurses' professional quality of life. Mutuality influences nurses' and patients' outcomes. Understanding mutuality could enhance the professional quality of life for nurses, improving their compassion satisfaction and reducing their burnout.
We adhered to STROBE guidelines.
Patients were not included in the sample. Health workers were involved in the study.
To develop prediction models for short-term outcomes following a first acute myocardial infarction (AMI) event (index) or for past AMI events (prevalent) in a national primary care cohort.
Retrospective cohort study using logistic regression models to estimate 1-year and 5-year risks of all-cause mortality and composite cardiovascular outcomes.
Primary care practices in England contributing data to the Clinical Practice Research Datalink (CPRD) Aurum and CPRD GOLD databases between 2006 and 2019.
Patients with an incident (index) or prevalent AMI event. Models were trained on a random 80% sample of CPRD Aurum (n=1018 practices), internally validated on the remaining 20% (n=255) and externally validated using CPRD GOLD (n=248).
Discrimination assessed using sensitivity, specificity and area under the receiver operating characteristic curve (AUC). Calibration assessed using calibration plots.
In the index (prevalent) cohorts, 94 241 (64 789) patients were included in the training and internal validation sets, and 16 832 (7479) in the external validation set. For the index cohort, AUCs for 1-year [5-year] all-cause mortality were 0.802 (95% CI 0.793 to 0.812) [0.847 (0.841 to 0.853)] internally and 0.800 (0.790 to 0.810) [0.841 (0.835 to 0.847)] externally. For the primary composite outcome (stroke, heart failure and all-cause death), AUCs were 0.763 (0.756 to 0.771) [0.824 (0.818 to 0.830)] internally and 0.748 (0.739 to 0.756) [0.808 (0.801 to 0.815)] externally. Discrimination was higher in the prevalent cohort, particularly for 1-year mortality (AUC: 0.896, 95% CI 0.887 to 0.904). Models excluding treatment variables showed slightly lower but comparable performance. Calibration was acceptable across models.
These models can support clinicians in identifying patients at increased risk of short-term adverse outcomes following AMI, whether newly diagnosed or with a prior history. This can inform monitoring strategies and secondary prevention and guide patient counselling on modifiable risk factors.
Epidemics pose significant challenges for fragile health systems, particularly in humanitarian emergencies. Recent responses to epidemics such as cholera in Yemen and Ebola virus disease in the Democratic Republic of the Congo have highlighted the lack of effective and integrated coordination. We review existing global models for addressing large-scale epidemics in humanitarian emergencies, identify gaps and inefficiencies, and propose operational recommendations to enhance response mechanisms.
A two-pronged approach was used to identify and critically assess current response coordination frameworks. Using the Arksey and O’Malley framework, a scoping review was undertaken, which was complemented by key informant interviews with humanitarian emergency response experts. The interviews focused on identifying the existing challenges and potential strategies to improve epidemic response in humanitarian contexts.
The scoping review included 51 documents (13 peer-reviewed articles and 38 grey literature documents). We conducted in-depth interviews with 28 respondents representing 17 different agencies and donors.
We focused on two major response architectures: the Incident Management System (IMS) and the cluster system. IMS is an important coordination and response instrument increasingly being used to respond to infectious disease threats.
Outcome measures of interest included the gaps in the current mechanisms to address infectious disease threats in complex humanitarian emergencies.
Unlike the cluster system model, which relies on consensus decision-making, IMS has a command-and-control approach, ensuring rapid decision-making. However, it can also lead to vertical responses that neglect the cross-sectoral and complex needs of affected communities. In addition, we found that the absence of context-specific response coordination mechanisms, with clear roles and responsibilities for involved stakeholders, was a common shortcoming. Fragmented response efforts that sidelined national and local stakeholders and a lack of reliable funding were also identified as important weaknesses.
We recommend the integration of coordination mechanisms into a sufficiently flexible framework that can be adapted to local contexts, while empowering national and local actors and ensuring the continuity of essential humanitarian services. We propose a paradigm shift towards mechanisms that respect humanitarian principles, effectively addressing the epidemic threats while remaining focused on deploying community-centric response efforts.
To examine the association between maternal and neonatal biochemical variables in babies born to mothers with hypertensive disorders of pregnancy (HDP) and admitted to the neonatal unit within 24 hours of delivery.
Retrospective chart review study.
Specialised antenatal hypertension clinic and neonatal unit in a tertiary unit referral hospital.
Pregnancies complicated with HDP (N=282) and their neonates if admitted to the neonatal unit within 24 hours of delivery.
We examined the association between maternal and neonatal biochemical variables, after controlling for maternal, neonatal and pregnancy characteristics.
There were strong associations and independent prediction of neonatal levels by maternal levels for urea, creatinine, sodium and calcium. The highest associations were between neonatal and maternal urea and creatinine, where the only predictor was the respective maternal variable (model R2= 0.61 and 0.60, respectively). Similarly, maternal sodium and calcium were the strongest predictors for neonatal sodium and calcium (model R2= 0.36 and 0.22, respectively). On the contrary, the strongest predictor for neonatal total protein, albumin and globulin was the gestational age (model R2= 0.43, 0.35 and 0.48, respectively) with no maternal contribution for total protein and albumin.
Maternal levels of urea, creatinine, sodium and calcium, in a pregnancy complicated by HDP, should be taken into consideration by both the obstetric and neonatal teams when deciding on timing of delivery and providing intensive monitoring.
FreshRSS 