Conectar
by Zoe Dellaert, Hollie M. Putnam
Reef-building coral polyps contain multiple specialized tissue types with distinct functions, from feeding and defense to symbiosis and skeleton formation. While these cell types have been characterized microscopically and more recently via single-cell RNA sequencing, spatially resolved high-throughput gene expression profiling remains limited in corals. Here we combine Laser Capture Microdissection with RNA sequencing to characterize tissue-specific gene expression in the reef building coral Pocillopora acuta. Oral tissues, adjacent to the seawater, exhibited 1,253 upregulated genes enriched for amino acid synthesis, transmembrane transport, signaling, environmental sensing, and secretion. These tissues showed high expression of immune and microbial-recognition genes consistent with their interface with seawater microbiota: mucins, lectins, toll-like receptors (TLRs), and MyD88 that connects TLRs to the NF-κB pathway. Aboral tissues, which build the coral’s skeleton, exhibited 552 upregulated genes enriched for developmental processes, cell adhesion, and stimulus response. We identified strong differential expression of biomineralization- associated genes, including Chitin Synthase and Wnt pathway members, suggesting previously underdescribed roles in skeleton formation. Critically, many genes implicated in specialized functions were expressed in multiple tissues. This lack of location specificity suggests functional biomarkers will likely entail multi-gene expression patterns rather than single genes. Collectively, we highlight the need for greater spatial resolution (e.g., single cell/nuclei and spatial transcriptomics) to fully resolve coral responses within their native tissue complexity. As anthropogenic climate change increasingly threatens coral reefs, spatially resolved molecular insight into coral biology will be critical for interpreting stress response mechanisms, forecasting their limits, and applying human interventions.
by Kerong Wang, Guoliang Li, Xiuci Yang, Meiling Ji, Shuainan Hong, Cong Liu, Mengyao An, Jiangning Yin
ObjectiveThis study aims to find a quick bedside ultrasonography evaluation technique that evaluates the optic nerve sheath diameter to eyeball transverse diameter (ONSD/ETD) ratio and middle cerebral artery (MCA) flow parameters at 6 hours post-return of spontaneous circulation (ROSC) for early neurological prognosis.
MethodsThis retrospective study included 49 patients who achieved return of spontaneous circulation (ROSC) and were admitted to our emergency department between September 2023 and September 2025. Collected data encompassed baseline characteristics, GCS-M scores, APACHE-II scores, and bedside ultrasound measurements of ONSD, ONSD/ETD at 6, 24, and 48 hours post‑ROSC and middle cerebral artery hemodynamic parameters at 6, 24 hours post‑ROSC. The statistical analyses included the Mann-Whitney U test, t-test, and Receiver Operating Characteristic (ROC) curve analysis.
ResultsThe ONSD/ETD ratio at 6 hours post-ROSC was a robust predictor of unfavorable neurological outcomes (AUC 0.922, P = 0.001), outperforming ONSD alone (AUC 0.866, P = 0.003), with an optimum threshold of 0.256 (sensitivity 76.5%, specificity 100%). The ONSD/ETD ratio was a significant predictor of CPC scores (OR = 1.979, P = 0.010). Although the majority of middle cerebral artery hemodynamic measures revealed no significant changes, all patients displaying cerebral circulatory arrest (CCA) waveforms or advancing to such waveforms demonstrated a dismal neurological prognosis. The alteration in Pulsatility Index (PI) was borderline significant (P = 0.05), with a threshold of 0.269 (AUC 0.90, sensitivity 80%, specificity 100%).
ConclusionThe ONSD/ETD ratio assessed six hours after cardiac arrest accurately forecasts neurological prognosis, especially for unfavorable results (CPC 4–5). Transcranial Doppler can continuously monitor patients exhibiting an increased pulsatility index or identified cerebral circulatory arrest waveforms. The integration of various methodologies for dynamic evaluation enhances risk categorization and aids clinical decision-making for patients who attain ROSC. However, these findings are preliminary and require validation in larger cohorts.
by Michael Kalinoski, Leah Bolden, Qi Wang, R. Adams Dudley, Nathan Mesfin, Nicholas E. Ingraham
IntroductionPersistent critical illness (PerCI) describes patients with prolonged intensive care unit (ICU) dependence after their acute phase of illness and affects 5–20% of the general ICU population. PerCI has been studied in the general ICU cohort, but prevalence and outcomes remain unclear among mechanically ventilated patients with acute hypoxic respiratory failure (AHRF), a high-risk cohort that is more prone to ICU-associated complications. The objective of this study is to quantify PerCI prevalence, identify risk factors for PerCI development, and describe one-year mortality in this population.
MethodsWe conducted a retrospective study of patients with AHRF (PaO2/FiO2 ratio < 300) requiring mechanical ventilation within 72 hours of ICU admission across a 12-hospital health system (2011–2022). PerCI was defined as ICU length of stay ≥ 10 days. The primary outcome was one-year mortality, modeled using a Cox proportional hazards model with PerCI as a time-varying exposure. To identify risk factors for PerCI while accounting for competing early mortality, we used a dual-model approach: logistic regression comparing PerCI to early death (≤ 10-day mortality) and PerCI to early ICU discharge, with factors associated with both models considered robust predictors.
ResultsAmong 10,626 eligible patients, 3,107 (29.2%) met criteria for PerCI. One-year survival was 64.2% in the PerCI group compared to 73.8% in the non-PerCI group. After PerCI onset, mortality risk increased threefold (hazard ratio 3.01; 95% CI 2.72–3.33). Factors consistently associated with PerCI across both models included ARDS, pneumonia, aspiration pneumonitis, heart failure, septic shock, weight loss, surgical admission, and postprocedural respiratory and circulatory failure.
ConclusionNearly one in three mechanically ventilated AHRF patients developed PerCI, far exceeding rates in the general ICU populations and was associated with worse one-year survival. Identifiable clinical risk factors may support earlier goals-of-care conversations and post-ICU care planning in this high-risk population.
by Xinyi Qiu, Limei Guan, Hui Liu
BackgroundAdolescent diabetes mellitus (DM) constitutes a significant global public health challenge. This study seeks to quantify the burden of DM in adolescents aged 10–19 years from 1990 to 2023 and to forecast trends in incidence, prevalence, mortality, and disability-adjusted life years (DALYs) through 2040.
MethodsEpidemiological data for DM among adolescents in 204 countries and territories were obtained from the Global Burden of Disease (GBD) 2023 database. The global burden was evaluated using age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), age-standardized mortality rate (ASMR), and age-standardized DALY rate (ASDR), stratified by region, sex, age, and Socio-demographic Index (SDI). Health inequality was assessed using the slope index of inequality (SII) and concentration index (CI). Future trends were forecast using an autoregressive integrated moving average (ARIMA) model with model-specific validation (AICc, Ljung-Box test).
ResultsFrom 1990 to 2023, global adolescent DM burden increased substantially. ASIR, ASPR, and ASDR rose consistently, whereas ASMR remained relatively stable with a slight decline. In 2023, an estimated 6.07 million adolescents were living with DM (ASPR: 458.07 per 100,000). The highest ASPR was observed in low-SDI regions (482.25 per 100,000), followed by high-SDI regions (442.81 per 100,000). Low-SDI regions also carried the highest DALY and mortality burdens. Males progressively exceeded females in both incidence and prevalence by 2023, although this observed sex reversal may partly reflect changes in screening and diagnostic practices. The overall burden increase was primarily driven by adolescents aged 15–19 years. ARIMA forecasts indicate that ASIR, ASPR, and ASDR are projected to continue increasing through 2040, while ASMR is expected to remain low and stable.
ConclusionsThe burden of adolescent DM increased considerably from 1990 to 2023, with marked heterogeneity by age, sex, and geography. The rising non-fatal burden (incidence, prevalence, DALYs) contrasts with stable mortality, suggesting improvements in acute care alongside growing morbidity. Persistent health disparities and projected increases underscore the need for age-, sex-, and region-specific public health strategies.
by Yankuba Singhateh, Tshepiso Mechele Matoko, Mannini Shaabe, Selloane Amelia Maepe, Francis Dumobong Ngmenasong Abobo, Sarah Waithera Wanyoike
BackgroundLesotho, a lower middle-income country in southern Africa, has historically had relatively high routine immunization coverage over the last three decades. Since 1996, the country has been implementing measles elimination strategies. This manuscript evaluates Lesotho’s performance, from 2011 to 2025, against the World Health Organization’s criteria for measles and rubella elimination.
MethodsWe conducted a retrospective review of Lesotho’s immunization and surveillance data during 2011–2025. This included Lesotho’s annual WHO/UNICEF Estimates of National Immunization Coverage (WUENIC) for routine measles-containing vaccine (MCV) doses; performance in the periodic measles rubella vaccination campaigns and case-based surveillance; and the trends of measles and rubella incidences.
ResultsDuring 2011–2025, MCV1 coverage generally remained ≥90% but failed to reach the 95% elimination target. MCV2 coverage reached 80% in 2011 and 2012 before declining in subsequent years. Lesotho has mostly attained the targets for surveillance performance according to the two principal performance indicators – non-measles febrile rash illness rate and the proportion of districts that report a minimum of one suspected case. From 2011 to 2015, measles incidence stayed below one per 1 million population in Lesotho. However rubella incidence ranged between 33.4 in 2012 to 142.3 in 2014, and declined significantly after MR introduction in 2017.
ConclusionLesotho has made significant progress in measles and rubella elimination efforts. To sustain the gains made, the country should work to strengthen vaccination in the second year of life, reinforce demand generation during preventive campaigns, address population denominator inaccuracies that hinder accurate coverage tracking, and systematically document measles and rubella virus genotypes.
by Laura van Dussen, Emilie V. Albers, Saskia N. van der Crabben, Ronald H. Lekanne Deprez, Astrid S. Plomp, Mirjam Langeveld
Fabry disease (FD) is the most common lysosomal storage disorder in which a severe, classical phenotype as well as a milder, non-classical phenotype can be distinguished. In this study we investigated the impact of the introduction of broader DNA sequencing techniques and subsequently the addition of the GLA-gene to NGS or WES based panels on the type of FD patient that is diagnosed by analyzing changes in the composition of the Dutch Fabry cohort over time. The current study confirms that Fabry disease is a genetically heterogeneous disorder with 64 different GLA variants established in a cohort of 319 patients. The introduction of broader DNA sequencing techniques, applied to a broader range of individuals with less specific symptoms, results in the identification of a higher proportion of individuals with less deleterious GLA variants and consequently a milder clinical phenotype. For the majority of individuals identified using the broader sequencing techniques cardiomyopathy is the presenting and only symptom of the disorder, in contrast to the multisystem classical Fabry disease phenotype. This phenotypic shift should be taken into account when comparing current to historical clinical and treatment effect data and requires tailored genetic counseling and clinical follow-up to prevent both over- and undertreatment.
by Thomas Muehlbauer, Reinhold Kliegl, Katharina Borgmann, Sam Limpach, Dirk Krombholz, Stefan Panzer
BackgroundThe effects of training interventions on interlimb balance performance have been recently investigated. However, no comparison was conducted between the impact of a single-mode versus combined training modality, whereby complementary adaptations are suggested for the latter.
ObjectiveThus, we investigated the effects of a single-mode versus combined training modality on interlimb static and dynamic balance performance in soccer players.
MethodsYoung male soccer players (N = 57, Tier level 3) were randomly allocated to a unilateral single-mode balance training (BT) group (n = 17, age: 13.8 ± 1.5 years), a unilateral combined balance and plyometric jump training (BT + PT) group (n = 20, age: 14.1 ± 1.5 years) or an active control (CON) group (n = 20, age: 14.2 ± 1.6 years). Training was conducted in-season for nine weeks (two sessions per week) using the non-dominant leg. Pre- and post-intervention, unipedal balance performance was assessed for both legs under static (unipedal stance only) and dynamic (unipedal stance with continuous leg swing) task conditions while increasing the difficulty level (i.e., gradual reduction of the base of support). Binary (success rate) and metric (center of pressure [CoP] indices, limb symmetry index [LSI]) parameters of postural control were calculated.
ResultsBoth training modalities yielded significant improvements in interlimb static and dynamic postural control, with greater effects in the single-mode BT group for the parameter success rate and in the combined BT + PT group for the CoP-based indices. Significant improvements in the LSI occurred irrespective of the training modality.
ConclusionBoth, single-mode BT (binary outcome) and combined BT + PT (metric outcome) appear to be effective in improving interlimb static and dynamic postural control in young male soccer players. Due to the floor and ceiling effects across outcome domains, it cannot be concluded that one training mode is superior to the other. However, the more in-depth analysis (i.e., CoP-based indices) yields findings in favor of the combined BT + PT and suggests that regulatory processes, in particular, benefit from this training modality.
by Qunting Chen, Xinhui Chen, Geng Chen
In this paper, a low-cost, high-precision, high-degree-of-freedom intelligent manipulator was developed. Specifically, a 15-DOF palm-scale bionic manipulator integrated with a vision-based gesture mapping framework is presented. The system consists of a power management module, palm module, joint module, and gesture recognition module, and can be controlled via smart devices. Experimental results demonstrate gesture-driven control with an average end-to-end response time of approximately 2s, including perception, communication, and execution delays. In addition, the system is lightweight and compact, with dimensions comparable to those of a human palm. The work demonstrates the feasibility of integrating established gesture-recognition components with a compact robotic manipulator for embedded and portable human-robot interaction.
by Carla Laria, Nicola Serra, Annarosa Trofa, Angelica Rodio, Giuseppe Chiarella, Pasquale Viola, Federica D’Ambrosio Geremicca, Emma Landolfi, Rita Malesci, Anna Rita Fetoni
IntroductionMathematical competencies are essential for both academic achievement and everyday functioning. Research investigating mathematical skills in deaf and hard of hearing (DHH) individuals has produced heterogeneous findings, indicating domain-specific performance patterns and the influence of linguistic and cognitive factors. Recent evidence further suggests that these differences may emerge early in development. This systematic review aims to evaluate mathematical competencies in DHH individuals and to contextualize their mathematical profile in relation to developmental dyscalculia.
MethodsA systematic review of observational studies was conducted in accordance with PRISMA 2020 guidelines. Studies were selected based on the PICOS framework, including participants under 18 years of age with congenital or acquired hearing loss. Comparisons involved hearing peers with or without specific learning disorders, and outcomes were based on direct assessments of mathematical abilities or related cognitive processes. A comprehensive literature search was performed in PubMed, Scopus, and Web of Science between March 31 and April 3, 2026, including all studies published up to the search date. In addition, relevant studies were identified through manual screening of reference lists. Methodological quality was assessed using the Joanna Briggs Institute (JBI) critical appraisal tools. Due to the heterogeneity of the included studies, results were synthesised narratively rather than through meta-analysis.
ResultsThe twelve included studies showed substantial variability in mathematical performance among DHH individuals. Lower achievement was more consistently observed in tasks with high linguistic demands, such as word problem solving, measurement, and mathematical reasoning, whereas procedural and visually supported tasks were relatively preserved. Evidence from both preschool and school-aged populations suggests that these differences may emerge early in development and remain observable across different developmental stages. Linguistic proficiency and access to a fully accessible language emerged as key factors associated with mathematical outcomes. Additional sources of variability included educational setting, communication modality, age of language acquisition, and hearing-related characteristics. Overall methodological quality was generally characterized by moderate methodological concerns, most commonly related to limited control of confounding variables, incomplete reporting of measurement validity, and small sample sizes.
ConclusionMathematical difficulties in deaf and hard of hearing (DHH) individuals appear to be domain-specific rather than global and appear to be associated with linguistic access and educational experiences. Evidence from both preschool and school-aged populations suggests that these differences may emerge early in development and remain evident across studies involving different age groups. These findings highlight the importance of considering language-related factors in both the assessment and instruction of mathematics in DHH learners.
by Haojie Wang, Mengxiang Li, Xiaomeng Liang, Weijian Wang, Pengren Luo, Jiaji Zhang, Yuxuan Du, Tan Liu, Boyu Zhang, Xu Wang, Zhefeng Jin, Yilin Zhu, Tao Han
Background & objectivePrevious biomechanical studies on pediatric flexible flatfoot have treated the subject as a single analytical unit, thus failing to elucidate mechanical transmission within the lower extremity closed kinetic chain. This study investigates the impact of distal arch collapse on macroscopic gait parameters, static joint alignment, and dynamic kinematic deviation by integrating a dual-level analytical strategy at both the subject and individual limb levels.
Methods153 children with pediatric flexible flatfoot (25 unilateral, 128 bilateral) were included, and 3D gait data from 306 lower extremities were analyzed. At the subject level, macroscopic spatiotemporal parameters were compared using the Mann-Whitney U test. At the limb level, linear mixed-effects models (LMMs) compared static 3D joint angles and Gait Variable Scores (GVS) between normal feet and flatfeet, treating subject as a random effect and adjusting for age, body mass index (BMI), and unilateral leg length.
ResultsAt both the subject and limb levels, no significant between-group differences were observed in any core spatiotemporal parameters (e.g., Mean Velocity, Frequency, and Step Width) (P > 0.05). Regarding static joint alignment at the limb level, the static Hip Rotation angle on the flatfoot side exhibited significantly less external rotation (i.e., relative internal rotation) compared to the normal side (−2.11° ± 0.67° vs. −5.79° ± 1.79°, P = 0.043). During dynamic walking, the Hip Abduction/Adduction GVS on the flatfoot side was significantly elevated (P = 0.032). However, comprehensive gait indices, including the GDI and GPS, showed no significant overall between-group differences.
ConclusionPediatric flexible flatfoot was associated with subtle proximal biomechanical alterations despite preserved macroscopic gait characteristics. Changes in static hip alignment and dynamic frontal-plane hip kinematics may therefore provide complementary information beyond conventional gait measures, supporting a broader kinetic-chain assessment in clinical evaluation and follow-up.
by Sean Hartmann, Andrew Sharp, Heather Johnston, Michael S. Gee, Susie Y. Huang, Mukesh G. Harisinghani, Jens Gühring, Wei-Ching Lo, Vibhas Deshpande, Oleg S. Pianykh
PurposeHigh complexity of modern processes renders manual process optimization impossible. The main goal of our work was to formalize and to demonstrate the practical efficiency of explainable rule-learning AI in complex process optimization.
Materials and methodsProcess optimization methodology was based on globally-optimal Boolean rule-learning AI models, capable of identifying multiple inefficiency patterns, and supporting process-oriented optimization metrics. To illustrate this approach in real-word environment, the study used 3994 liver and prostate Magnetic Resonance Imaging (MRI) exams performed on five 3T scanners at three outpatient facilities from January 2019 to January 2024. Imaging exams longer than 25 minutes were labeled as requiring optimization, which applied to 35.4% of liver and 52.6% of prostate cases. Rule-learning AI was applied to the MRI scanner log data to discover short and interpretable process optimization rules. The selected Boolean rules were used to implement improved exam protocols, and a permutation test was used to measure the statistical significance of the resulting change in average exam duration.
ResultsN=1000 top rules, identifying the most significant processing delay patterns, were discovered by rule-learning AI from the scanner log data based on F1 score. A smaller set of 20 top rules was selected using the secondary operational impact metric, an estimate of each rule’s impact on average scan duration. A change in liver MRI protocols based on findings from the top rule resulted in a 10.9% reduction of median scan time. The proportion of long liver exams was reduced from 35.4% to 23.9% (p < 0.001). Similar optimizations in prostate protocols were used to add a new scanning sequence, improving exam quality.
ConclusionsGlobally optimal, multi-model rule-learning AI can transform feature-rich device logs into concise, interpretable, and operationally meaningful rules. When combined with domain expertise, this approach can support measurable and sustainable improvements in complex clinical workflows.
by Aline Veras Morais Brilhante, Christina César Praça Brasil, Raimunda Magalhães da Silva, Marjan Askari, Luciana Andrade da Mota Sampaio, Jonas Loiola Gonçalves, Layane Sabóia, Lucas Alessandro Macedo Cruz, Helena Rodrigues Dias, Luciel Almeida Cavalcanti, Maria Julya Albuquerque Parente, Mariana Tavares Rocha, Melania Maria Ramos de Amorim
Autistic women experience increased obstetric and perinatal risks, partly driven by communication barriers within maternity care. Evidence on how these barriers are experienced in low- and middle-income countries remains scarce. This study aimed to analyze communication barriers in perinatal care based on narratives of autistic women who experienced pregnancy, childbirth, and postpartum care in Brazil. A qualitative study was conducted using the Hermeneutic-Dialectic Circle (HDC) approach. Thirty-four autistic women (22 with support level 1 and 12 with support level 2, including three non-speaking participants with complex communication needs) were recruited through convenience sampling, supplemented by active recruitment through participant referral, and participated in semi-structured interviews conducted in multiple accessible formats (video call, real-time messaging, in-person, and augmentative and alternative communication). Data were analyzed using constant comparative methods within the hermeneutic-dialectic framework, guided by the social model of disability and the neurodiversity paradigm. Three central categories were constructed: (1) communicational demands of autistic women and their non-recognition, including alexithymia, sensory hypersensitivity, and need for predictability; (2) institutional and interpersonal communication failures, encompassing symptom invalidation, disrespectful care, and exclusion of non-speaking women; and (3) experiences of respectful and effective communication, demonstrating that adapted strategies promote safety and autonomy. Participants’ narratives indicate that communication barriers in perinatal care for autistic women operate systemically rather than individually. Training healthcare professionals and implementing accessible communication strategies are essential to promote respectful, safe, and inclusive maternity care.
by Yeliz Yilmaz Bozok, Nihan Acar, Murat Kemal Atahan, Cem Karaali
BackgroundBreast cancer, the most common malignancy among women, remains a major global public health concern. With the rapid growth of artificial intelligence–based language models, it is essential to evaluate their potential roles in patient education. This study compared ChatGPT and Gemini in responding to patient-oriented questions about breast cancer and its surgical treatment regarding scientific accuracy, clarity, and unnecessary detail.
MethodsForty frequently asked questions were collected from Turkish online sources. Both models were queried under identical conditions on August 13, 2025, and the responses were anonymized for blinded evaluation. Four general surgeons experienced in breast surgery independently assessed each response using a five-point Likert scale across three domains: scientific accuracy, clarity, and unnecessary detail.
ResultsResponse lengths were recorded and compared. ChatGPT achieved significantly higher median scores than Gemini in scientific accuracy [4.75 (3.50–5.00) vs. 4.25 (3.50–5.00); p < 0.001], clarity [4.75 (3.50–5.00) vs. 4.25 (3.25–5.00); p = 0.005], and unnecessary detail [5.00 (5.00–5.00) vs. 4.50 (3.50–5.00); p < 0.001]. The overall median score was 4.83 (4.08–5.00) for ChatGPT and 4.33 (3.50–4.92) for Gemini (p < 0.001). Gemini’s responses were significantly longer (244 ± 84 vs. 170 ± 47 words; p < 0.001).
ConclusionBoth models demonstrated acceptable overall performance. However, ChatGPT’s higher scores and shorter, more focused responses indicate that it may be a more efficient tool for addressing breast cancer–related patient questions. In their current form, these models should not be used for diagnostic or clinical decision-making purposes. AI-generated health information should be used only under expert supervision and for educational or supportive purposes.
by Subhanwita Manna, Bijaya Kumar Mishra, Krishna Kant Yadav, Pratibha Dhiman, Smiteerekha Sahoo, Chiranjeet Mishra, Tanveer Rehman, Ranjan Kumar Prusty, Ragini Kulkarni, Mahadev Bhise, Ashok Kumar Pandey, Ravikumar B. S., Ipsita Pal Bhowmick, Subrata Kumar Palo, Narayana Swamy D. M., Neha Srivastava, Umaer Alam, Reeta Singh, Manish Barvaliya, Vani Kandpal, Barsha Gadapani Pathak, Reema Mukherjee, Sanghamitra Pati
BackgroundUnsafe abortion continues to be a significant cause of avoidable maternal morbidity and mortality especially in low- and middle-income countries. Despite India’s permissive Medical Termination of Pregnancy (MTP) Act, operational gaps continue to prevent women from accessing safe abortion services. There is still a dearth of multi-centric mixed-methods research from rural areas on women’s experiences, provider perspectives, and facility readiness. This study aims to assess the status of comprehensive abortion care (CAC) in rural India by evaluating public-sector facility preparedness, provider experiences, care-seeking pathways, and identifying key barriers and facilitators as per CAC guidelines (2023). The findings will guide the development of a preliminary implementation approach (Model 0+) as well as future phases focused on testing, adaptation, and scale up to strengthen CAC availability, quality, and uptake.
MethodsThis study employs a convergent mixed-methods design across six geographically varied rural blocks in India (North, South, East, West, Central, and Northeast). There will be two participant groups: married women aged 18–49 years who are current, previous, or potential abortion service users, and public health system stakeholders involved in Comprehensive Abortion Care (CAC). A multistage cluster survey will enroll approximately 854 married women per site across 20 clusters. The qualitative component will comprise interviews with women who have had abortions in the last two years and healthcare practitioners, for a total of around 240 interviews. Additionally, 18 focus group discussions with Accredited Social Health Activists and Anganwadi Workers (three per site), will capture frontline worker’s perspectives. Quantitative data will be collected using KoboCollect and analysed using STATA (or an equivalent statistical software). Qualitative data will undergo combined phenomenological and thematic analysis using NVivo or equivalent software.
DiscussionThis study constitutes the first phase of a multi-stage implementation research programme. The study builds upon national CAC guidelines as a foundation of implementation of “Model 0” for abortion care and assesses their functioning in routine public-sector settings. Insights from women, frontline workers, and providers will inform development of a refined implementation strategy (“Model 0+”) grounded in real-world contexts. This evidence-driven approach is expected to yield a practical, acceptable, and scalable model for subsequent piloting, adaptation, and wider health system uptake.
by Kelly L. Penz, Erin Barker, Julie G. Kosteniuk, Norma J. Stewart, Steinunn Jónatansdóttir, Martha L. P. MacLeod
BackgroundThe availability of palliative health care professionals is considered a global concern, especially within rural/remote practice settings. Nurses across all domains of practice are expected to advocate for high-quality hospice, palliative, and end of life (H/P/EOL) care. However, within many rural/remote geographical areas, formal palliative care services are non-existent, leaving generalist nurses to take on this complex responsibility.
MethodsExamining results from a Pan-Canadian cross-sectional survey of rural and remote nurses (N = 3,822), this paper explores a subset (n = 295) of nurses who provided hospice, palliative and/or end of life care as part of their practice. Analyses examined job demands and job resources, predictors of work engagement, and a summary of open-ended responses.
ResultsThe rural and remote nurses who worked in hospice, palliative, and/or end of life care had significantly higher satisfaction with practice demands related to their safety, lower practice resources related to staffing and time, and higher levels of work engagement compared to nurses in other areas. Multiple regression analyses demonstrated that seven variables accounted for 40% of the variance in their work engagement, including: perceived mental health, job satisfaction, interprofessional collaboration, affective organizational commitment, continuance organizational commitment, normative organizational commitment, and lower job demands related to working conditions. Open-ended data revealed that rural nurses felt privileged to provide H/P/EOL care, however, faced barriers related to blurred personal/professional boundaries when dealing with death/dying and lack of access to palliative resources.
ConclusionsThis is the first Canadian national profile of rural and remote nurses who provide hospice, palliative and end of life care and highlights key areas related to their professional quality of life (e.g., work engagement, organizational commitment, job resources/demands). The results of this analysis may inform practice and policy development for health human resource planning and recruitment/retention in hospice, palliative and/or end of life care across rural and remote settings.
Hyperbaric oxygen therapy (HBOT) is an established adjunctive treatment for selected diabetic foot ulcers, although evidence regarding its effectiveness remains heterogeneous. We conducted a retrospective, single-center, observational study of adult diabetic patients receiving HBOT (2.5 ATA, 100% oxygen) for a lower-limb wound at the only hyperbaric center in Guadeloupe, a French Caribbean territory, between January 2020 and June 2023. Among 257 patients treated with HBOT, 71 diabetic patients met inclusion criteria (mean age 63.1 ± 12.7 years; 69% male). Peripheral arterial disease and osteitis were highly prevalent, while the proportion of current smokers (7.9%) was notably lower than in previously published HBOT cohorts, a distinctive feature of this population. HBOT was considered a last resort, after failure of prolonged conventional therapy, in 63% of patients, likely contributing to the modest six-month healing rate of 34% (18/53 evaluable patients) and 19% rate of major amputation occurring during or after HBOT. Patients referred through the multidisciplinary Diabetic Foot Care Unit had fewer major amputations despite older age and greater vascular burden, though this comparison may reflect referral-related selection bias. No candidate factor, including glycemic control, referral pathway, or delay to HBOT, reached statistical significance in univariable analysis. This descriptive, single-arm finding cannot establish HBOT efficacy but is consistent with a role for HBOT within coordinated multidisciplinary diabetic foot care, highlighting the importance of earlier referral and optimised patient selection.
Venous leg ulcers are a common manifestation of chronic venous disease and are associated with substantial morbidity and impaired health-related quality of life (HRQoL). Patient-reported outcome measures are essential for capturing the patient perspective of disease burden and treatment outcomes in wound care management. The Sheffield Preference-based Venous Ulcer questionnaire (SPVU-5D) is a concise preference-based instrument designed to assess the quality of life in individuals with venous leg ulcers and to support health-economic evaluation. However, its measurement properties have not been extensively examined in different linguistic contexts. This study aimed to evaluate the psychometric properties of the Spanish version of the SPVU-5D in patients with venous leg ulcers. A methodological validation study was conducted involving 132 patients (264 observations from pre- and post-treatment assessments) with a mean age of 63.76 ± 10.02 years. Cross-cultural adaptation followed the established guidelines for translation and cultural equivalence. Content validity was assessed using Aiken's V coefficient. Structural validity and reliability were examined using multilevel confirmatory factor analysis and measurement performance was further evaluated using a multilevel graded response model based on item response theory. Floor and ceiling effects, minimum detectable change and convergent validity with the RESVECH 2.0 clinical scale were also evaluated. Confirmatory factor analysis supported a unidimensional structure with excellent fit indices and satisfactory internal consistency. Item response theory analyses showed high item discrimination and well-distributed difficulty thresholds for the items. The floor and ceiling effects were minimal, indicating adequate sensitivity across the latent trait continuum. The Spanish version of the SPVU-5D demonstrates satisfactory validity, reliability and measurement precision and represents a useful instrument for assessing the health-related quality of life in patients with venous leg ulcers.
This study examines factors associated with deep tissue pressure injury and develops interpretable machine learning models for early risk prediction in adult ICU patients. This retrospective observational cohort study included 336 adult intensive care unit patients, of whom 211 developed deep tissue pressure injury and 125 remained pressure injury-free. For patients who developed deep tissue pressure injury, haemodynamic, laboratory and nursing variables from the 24 h before injury onset were analysed using a physiological time-at-risk framework. For pressure injury-free patients, corresponding variables from the first 24 h after intensive care unit admission were used. Six supervised machine learning classifiers were developed and internally validated using cross-validation and hyperparameter optimization. All models showed good predictive performance. Extreme gradient boosting achieved the highest discriminative ability, with an area under the receiver operating characteristic curve of 0.976. The most influential predictors across feature selection methods were low-molecular-weight heparin use, norepinephrine duration, lower blood pressure values, immobility, nutritional risk, antiplatelet therapy and chronic disease profile. Routinely documented nursing and haemodynamic indicators obtained within a clinically relevant 24-h risk window can support accurate early risk stratification for deep tissue pressure injury in adult intensive care unit patients. A physiology-informed and interpretable machine learning approach may improve recognition of patients at imminent risk.
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