Modern Pathology

Accurate, reproducible interpretation of kidney allograft biopsies is critical for diagnosis of graft injury to guide prognosis and management. The international Banff classification is a consensus diagnostic system based on semiquantitative histological lesion scoring on either extent or severity of kidney transplant biopsies. However, pathologist scoring is limited by substantial interobserver variability, constrained scalability, and the inherent nature of the scoring system itself. Here we present BanffNET, a weakly supervised, probabilistic deep learning framework that combines self-supervised feature extraction with a novel Bayesian multiple-instance learning framework to predict (continuously) the full spectrum of Banff lesion scores directly from whole-slide images (WSIs). Using lesion-specific aggregation functions tailored to localized (modeling lesion severity) and diffuse pathologies (modeling lesion extent), BanffNET generates interpretable, patch-level probability maps and calibrated slide-level scores. BanffNET's performance was assessed relative to consensus, biological correlates of rejection and clinical outcome, demonstrating superior consistency, transportability and generalization. Trained on 7,249 WSIs from three cohorts, BanffNET demonstrates consistent performance on 11,028 WSIs across five external test sets, performing on par or exceeding expert consensus across lesions. BanffNET scores align more closely than pathologist Banff scores with molecular profiles of rejection, offering a transparent, biologically grounded framework for computational pathology with relevance beyond transplantation.

Background: Biochemical recurrence (BCR) occurs in 20-40% of men after radical prostatectomy. Existing postoperative recurrence risk tools based on PSA and pathology are clinically useful but show only moderate and variable discrimination, highlighting the need for biomarkers that improve risk stratification and consequent treatment decisions. We hypothesized that the prostate microenvironment, including both the tumor and non-cancerous adjacent tissue, may contain prognostic features associated with adverse postoperative PSA outcomes. Methods: We assembled a cohort of matched tumor-adjacent benign and tumor prostate tissue from 243 men across three institutions to establish a discovery cohort (n=123; 43 postoperative PSA events, 35%) and validation cohort (n=120; 46 events, 38%). For primary binary analyses, a postoperative PSA event included BCR, defined as two consecutive postoperative PSA values >=0.2 ng/mL, or PSA persistence. We performed RNA sequencing of matched tumor-adjacent benign and tumor tissues, quantified immune signatures, and developed an integrated model combining the adjacent-tissue B-cell signature, preoperative PSA, and radical prostatectomy Gleason score (BRIGADE). CAPRA-S-adjusted Cox analyses excluding recurrence-time-0 cases evaluated time to BCR, and CD19 multiplex immunofluorescence provided tissue-level confirmation (n=10). Results: In prostatectomy specimens, tumors from patients without a postoperative PSA event were enriched for B-cell transcriptional programs, whereas tumors from event-positive patients showed elevated proliferation signatures. B-cell-related transcriptional programs were correlated between tumor and adjacent tissue. Tumor-adjacent benign B-cell scores were higher in no-event cases and discriminated postoperative PSA-event status in PCBN discovery (AUC 0.63) and BM validation (AUC 0.81) cohorts, outperforming numerous other immune-related signatures. In CAPRA-S-adjusted Cox sensitivity analyses excluding recurrence-time-0 cases, higher adjacent-tissue B-cell activity was associated with reduced recurrence risk in PCBN (HR 0.42, 95% CI 0.19-0.94; BH-adjusted p=0.035) and BM (HR 0.54, 95% CI 0.30-0.95; BH-adjusted p=0.034). Tissue-based validation showed that CD19+ B-cell density in adjacent benign tissue was higher in no-event than event-positive patients (median 0.1145 vs 0.0471; p=0.008). BRIGADE achieved an AUC of 0.68 in cross-validation and 0.83 in independent validation, compared to AUCs of 0.54-0.63 and 0.44-0.78 for the tested clinical predictors, respectively. At the fixed classification threshold, the validation-cohort odds ratio for BRIGADE was 2.75. The adjacent B-cell score remained associated with lower odds of a postoperative PSA event after adjustment for PSA and Gleason score. Conclusions: B-cell infiltration in tumor-adjacent benign prostate tissue may complement existing clinicopathologic models for stratifying adverse postoperative PSA outcomes and subsequent BCR after radical prostatectomy. The transcriptomic signal was recapitulated by CD19-based tissue staining, supporting further development of a pathology-based assay.

To evaluate the cost-utility and 5-year budget impact of first-line olaparib plus abiraterone versus abiraterone alone for metastatic castration-resistant prostate cancer (mCRPC) in China after the eleventh round of volume-based procurement (VBP). The intention-to-treat (ITT) population was assigned primary decision-analytic weight; the prespecified BRCA1/2-mutated (BRCAm) subgroup was a supporting analysis.

Next-generation sequencing (NGS) for the detection of somatic variants has become the method of choice in a variety of molecular oncology fields and in the clinic. Its use ranges from sequencing entire tumor genomes and transcriptomes to targeted clinical diagnostic gene panels. The NYU Langone Genome PACT (Profiling of Actionable Cancer Targets, LG-PACT) assay is a qualitative in vitro diagnostic test that uses targeted next generation sequencing (NGS) of formalin-fixed paraffin-embedded (FFPE) tumor tissue matched with normal specimens from patients to detect gene alterations in a targeted panel covering 606 genes and the TERT promoter. Indications for testing are cancer (solid tumors and hematological malignancies) where a mutational profile from multiple genes would be informative for disease stratification, prognosis, or treatment options including targeted therapies and eligibility for clinical trials. The test is intended to provide information on somatic mutations including point mutations, small insertions/deletions (indels), and copy number aberrations for diagnostic and treatment decisions. LG-PACT is a United States Food and Drug Administration (FDA) cleared diagnostic test (510K: K202304). The clinical interpretation of sequencing data of molecular tumor markers from NGS encompasses automated variant calling tools with human interpretation. This final mostly manual review of data step is intensive, involving highly trained scientists, encompassing literature review, interpretation and clinical tier classification by pathologists, who then provide a complete molecular diagnostic report to the treating oncologists. We provide analysis of 1339 clinical genomic profiles from 31 different cancers and their subtypes, comprising of central nervous system (CNS) 792 (59%) cases (incl. meningioma, glioma and glioblastoma), with 267 (20%) cases predominantly of lung, pancreatic and colorectal and 280 of others (21%). Here, we present the technical challenges of validating an NGS oncological diagnostic targeted assay for clinical grade accuracy and sensitivity for patient care. We show how copy number alterations provide a more comprehensive description of the tumors genomic profile. We then outline the utility of targeted panel sequencing based on certified pathologist selection of reportable variants for our current patient cohort. Where analysis of variant detection has led to 49.4% (661/1339) of our clinical tumor samples containing mutations in known therapy targeted genes, 35.6% (477/1339) with mutation detected in other genes, and 15% (201/1339) cases being negative.

BACKGROUND: Cerebral ischemia following subarachnoid hemorrhage (SAH) has traditionally been considered transient because functional alterations of the cerebral microcirculation are thought to be self-limiting. However, we identified a previously unrecognized vasculopathy, perivascular fibrosis of the cerebral microcirculation (PFCM), characterized by excessive type I collagen deposition after SAH. This study investigated the mechanisms underlying PFCM and its subsequent effects on cerebral hemodynamics. METHODS: In vivo SAH was modeled in mice by autologous blood injection, whereas oxygenated hemoglobin (OxyHb) exposure was used to mimic SAH in vitro. Pericyte-deficient mice (Pdgfr{beta}+/-) and pericyte-specific vestigial-like family member 3 (VGLL3) conditional knockout mice (Vgll3{Delta}PC) were generated. Pericyte contractility was measured by nanoindentation and traction force microscopy. Molecular mechanisms were examined using Western blotting, immunofluorescence, CUT&Tag, RNA-seq, transmission electron microscopy, and molecular docking. PFCM, impaired dilation of the cerebral microcirculation, and cerebral autoregulation were assessed by two-photon imaging, transcranial Doppler with continuous blood pressure monitoring, super-resolution ultrasound imaging, and photoacoustic imaging. RESULTS: After SAH, mice developed long-term cerebral autoregulation dysfunction marked by impaired dilation of the cerebral microcirculation, with the abnormality being most evident within the relatively lower blood pressure range. The marked reduction in PFCM in Pdgfr{beta}+/- mice indicated that pericytes were the principal cellular contributors. Mechanistically, OxyHb-induced cytoskeletal remodeling in vitro increased pericyte contractility and promoted nuclear translocation of SAH-upregulated VGLL3. This was followed by increased genomic occupancy, Col1a1 transcriptional activation, and type I collagen deposition. Pericyte-specific VGLL3 knockout abolished PFCM and, consequently, significantly alleviated long-term cerebral autoregulation dysfunction. CONCLUSIONS: Our findings identify PFCM mediated by pericytic VGLL3 as a novel vasculopathy leading to long-term cerebral autoregulation dysfunction after SAH.

Background: Immunochemotherapy (ICT) is considered standard in regards to care for small-cell lung cancer (SCLC) in extensive stages, yet reliable biomarkers for treatment response remain elusive. While previous univariate analyses suggest specific peripheral lymphocyte subsets correlate with survival, the systemic immune response involves complex, multivariate interactions that require advanced analytical approaches. Methods: This paper analysed high-dimensional flow cytometry data from 32 patients with stage IV SCLC treated with carboplatin, etoposide, and atezolizumab. Peripheral blood was analysed at baseline (V0) and longitudinally during treatment. To identify potential early predictive biomarkers and mitigate sample attrition in later cycles, we focused on baseline and measurements after two cycles of ICT (V1). We employed a rigorous machine learning framework utilising nested cross-validation, bootstrapping, and permutation-based statistical testing to evaluate eleven different regression and survival models. Results: Under model-appropriate metrics, regressors did not generalise (R2 <0); conversely, censoring-aware Random Survival Forests (RSF) successfully extracted robust prognostic signatures. Baseline immune profiles (V0) achieved a concordance index (C-index) of 0.66 (p= 0.015), while dynamic changes from V0 to V1 ({triangleup}V) achieved a C-index of 0.65 (p= 0.022). Crucially, absolute values measured after two cycles of ICT (V1) yielded no significant signal (p= 0.445). Feature importance analysis confirmed the prognostic value of Th17 normalisation and identified Naive Regulatory T cells and Memory B cells as candidate components. Conclusion: Machine learning validation confirms a predictive signal in the peripheral immune profile of SCLC patients. Early dynamic shifts in the balance between regulatory and effector immune arms are associated with prognosis, contrasting with the lack of signal in absolute counts after two cycles of ICT. These findings establish a proof of concept for multivariate liquid biopsy immune profiling, warranting confirmation in larger cohorts and highlighting the necessity of integrating systemic and tumour-intrinsic data.

BACKGROUND: Subarachnoid hemorrhage (SAH) induces inflammatory responses and subsequent immune cell activation, which may contribute in cerebral vasospasm, microcirculatory impairment and poor neurological outcomes. Although cerebral vasospasm has traditionally been considered a major cause of delayed cerebral ischemia after SAH, therapies targeting angiographic vasospasm have not consistently improved functional outcomes. Early inflammatory responses may contribute to microcirculatory impairment, cerebral vasospasm, and subsequent neurological injury. Herein, we investigated whether interleukin-10 (IL-10), an anti-inflammatory cytokine, improves these outcomes in an experimental SAH model. METHODS: Mice received intramuscular injections of either an adeno-associated virus encoding IL-10 (AAV/IL-10) vector or an AAV expressing green fluorescent protein (AAV/GFP) vector (control). India ink angiography was performed to assess the diameter of the sphenoidal segment of the middle cerebral artery (MCA), the total length of the visible cortical arteries, and cortical staining intensity, as indices of cerebral vasospasm, microcirculatory impairment, and cerebral perfusion, respectively. Perivascular inflammatory cell infiltration and cytokine levels were assessed using immunohistochemistry and ELISA. We also evaluated the therapeutic efficacy of the AAV/IL-10 vector when administered immediately after SAH induction. RESULTS: IL-10 overexpression significantly improved neurological outcomes after SAH and was associated with attenuated cerebral vasospasm and microcirculatory impairment, as well as preservation of cerebral perfusion. It also significantly reduced neutrophil and macrophage infiltration around the internal carotid artery and attenuated SAH-induced elevations in IL-6 and matrix metalloproteinase-3 levels. Mice treated with the AAV/IL-10 vector immediately after SAH induction showed significant improvements in neurological scores and cerebral perfusion. CONCLUSIONS: AAV-mediated IL-10 overexpression improves neurological outcomes after SAH, likely by attenuating inflammatory responses, cerebral vasospasm, and microcirculatory impairment. These findings suggest that IL-10-based anti-inflammatory therapy is a promising therapeutic strategy for SAH.

Background: Primary malignant cardiac tumors (PMCTs) are rare and histologically heterogeneous. Objective: To compare demographics, specific ICD-O-3 morphologies, first-course treatment patterns, annual registered case counts, and unadjusted overall survival between soft-tissue and hematologic PMCTs. Methods: We identified 730 PMCT cases diagnosed from 2000 to 2021 in SEER 18 (ICD-O-3 topography C38.0). Histologic lineage was assigned from ICD-O-3 morphology. Comparative analyses included soft-tissue (n=458) and hematologic (n=212) tumors. First-course variables were primary-site surgery, chemotherapy (yes versus no/unknown), and radiotherapy (radiation versus none/unknown). Groups were compared with chi-square tests. Overall survival was estimated with Kaplan-Meier methods; follow-up was truncated at 120 months. Results: Soft-tissue PMCTs occurred predominantly at ages 45-64 years (67.9%), whereas hematologic PMCTs occurred predominantly at age [&ge;]65 years (63.2%; p<0.001). Men comprised 59.9% of hematologic and 49.3% of soft-tissue cases (p=0.014). The leading soft-tissue morphology was hemangiosarcoma/angiosarcoma (ICD-O-3 9120/3; 201/458, 43.9%); synovial sarcoma accounted for 20/458 cases (4.4%). Diffuse large B-cell lymphoma, NOS, accounted for 131/212 hematologic tumors (61.8%). Any primary-site surgery was recorded in 66.6% of soft-tissue versus 15.6% of hematologic cases (p<0.001). Chemotherapy was recorded in 67.5% versus 51.1% (p<0.001), and radiotherapy in 9.0% versus 20.5% (p<0.001). In exploratory Kaplan-Meier analyses, hematologic patients with recorded chemotherapy had higher unadjusted 120-month overall survival than those without recorded chemotherapy (42.0% versus 12.2%; log-rank p=7.5x10-). Radiation-associated survival differences were not statistically significant in either lineage. Conclusions: Soft-tissue and hematologic PMCTs have distinct age distributions, named histologies, and first-course treatment patterns in SEER. These findings describe registry coding and do not establish treatment effectiveness or population incidence.

Antimicrobial resistance is a public health challenge, driving the need for rapid, cost-effective diagnostic support tools. Artificial intelligence (AI) may enable prediction of susceptibility to untested antibiotics from known susceptibility results, but prospective clinical validation is required before routine use. We evaluated an AI-based decision support method, trained on invasive isolates from the European Surveillance System (TESSy), for prediction of antibiotic susceptibility in clinical Escherichia coli urine isolates. The evaluation included 99 E. coli isolates from urine samples with diversity in age, sex, and antibiotic susceptibility. Predictions were evaluated for 14 antibiotics using patient metadata and susceptibility results for 4-8 antibiotics as input. Prediction uncertainty was handled using conformal prediction, allowing abstention when confidence was insufficient. EUCAST disk diffusion test results were used as reference and genomic sequence data was used to explore mechanisms of the AI performance. Without conformal prediction, 84% of predictions were correct when susceptibility results of six antibiotics were used to predict susceptibility to eight additional antibiotics. Across all predictions generated using susceptibility results for six antibiotics as input, the major and very major error rates were 19% and 12%, respectively. Prediction errors varied between antibiotics and were associated with certain phenotypic and genotypic resistance patterns. Conformal prediction reduced errors but increased abstentions; at confidence levels of 90%, 95%, and 97.5%, the model abstained in 9.6%, 14%, and 22% of instances. The method showed promising performance, but its clinical use remains limited and may require diagnostic data beyond susceptibility test results and demographic variables.

The 17th Ebola outbreak in the Democratic Republic of the Congo, announced on 15 May 2026, was attributed to Bundibugyo ebolavirus (BDBV). Although case isolation is the main control strategy, its effectiveness is compromised when patients escape isolation facilities before recovery. Between 14 May and 17 June 2026, 175 individuals reportedly left isolation facilities without formal discharge across Ituri Province. We assessed how this "isolation leakage" affects community transmission. We refined the SEIHFR framework to distinguish undetected community infections, detected but not-yet-isolated cases, isolated individuals, leakage, funeral-associated transmission, and removals. Using Bayesian inference, we fitted the model to daily Ituri surveillance data, escapee counts, and isolation census records. We estimated the leakage rate, reporting and detection probabilities, and the transmission rate, while fixing other parameters based on the BDBV literature. The model reproduced confirmed cases, deaths, discharges, and escapees. We estimated R_0=3.67 (95% HDI: 2.0-5.7), a leakage rate of {rho} {approx} 0.034 day^-1 (0.022-0.051), and high contact-tracing-driven detection (p_d {approx} 0.91-0.99). Leakage increased the detection-dependent reproduction number [R](p_d) from approximately 3.2 to above 5. Eliminating leakage reduced cumulative infections by about one-third, from 1,120 to 764, while the minimum detection level required for control increased from p_d [&ge;] 0.73 without leakage to p_d [&ge;] 0.87 at the fitted leakage rate. Shortening time to isolation prevented the most infections (73.4%; 59-84), followed by reducing leakage (29.7%; 14-52) and re-isolating escapees (12.6%; 6-24). Delaying leakage reduction until week 4 reduced its benefit from about 27% to below 2%. Isolation leakage represents a major transmission pathway that has until now gone largely unmeasured. While rapid initiation of isolation is highly beneficial, it cannot compensate for permeable isolation; therefore, early, community-driven efforts to control leakage, embedded within a multilayered response, are critical.

Background: Fibrosis, characterised by excessive accumulation of collagen type I (COL1), is a common feature of chronic diseases, including liver diseases (LDs), chronic kidney disease (CKD) and heart failure (HF). COL1 degradation products can be detected in urine by proteomics/ peptidomics analyses and may serve as non-invasive biomarkers of fibrosis. We aimed to identify a common molecular signature of fibrosis across these diseases that may ultimately guide interventions to slow disease progression and prevent organ damage. Methods: Using capillary electrophoresis coupled to mass spectrometry (CE-MS), naturally occurring COL1 degradation products (peptides) in the urine of patients with fibrotic disease, LDs (n=127), CKD (n=263) or HF (n=187), were investigated and compared with the same number of matched controls. Disease-associated COL1 peptides were identified separately for each condition, and peptides showing consistent associations across the three diseases were selected to define a common fibrosis signature. A support vector machine model based on the selected peptides was developed and validated in independent cohorts of patients with LDs (n=110), CKD (n=93), HF (n=32) and controls (n=643). Results: We identified a common fibrotic signature consisting of 50 COL1 degradation products, mainly downregulated in fibrosis. A model based on these peptides achieved a strong performance, with an area under the receiver operating characteristic curve (AUC) of 0.935 (95% confidence interval (CI) 0.917-0.953, p<0.0001) in an external validation cohort comprising pooled disease groups (LDs, CKD, and HF) and controls. Performance was maintained in LDs, CKD and HF, with AUCs of 0.917 (95% CI 0.890-0.944, p<0.0001), 0.951 (95% CI 0.931-0.971, p<0.0001) and 0.950 (95% CI 0.903-0.997, p<0.0001), respectively. The model scores were significantly associated with fibrosis stage in LDs (p=0.0097) and with interstitial fibrosis and tubular atrophy in CKD (p=0.045). Conclusion: A model of urinary COL1 peptides captures a shared collagen degradation signature across organs and diseases, enabling the non-invasive assessment of fibrosis irrespective of its origin. As these peptides exclusively reflect collagen degradation, the findings suggest impaired collagen degradation as a driver in fibrosis. Future clinical studies are warranted to evaluate the utility of this model for early fibrosis detection and earlier implementation of anti-fibrotic interventions.

Biological aging occurs heterogeneously across individuals and organs. However, current measures of biological age incompletely capture organ-specific differences in health and disease risk. Because chest CT visualizes multiple thoracic organs, it offers an opportunity to quantify structural aging across organ systems. Here, we developed MOSAIC-Age, a framework characterizing eight organ-specific aging clocks on chest CT. The clocks were developed and validated using 9,971 CT scans from CT-RATE and MIDRC, and subsequently locked and applied to two independent prospective cohorts with 35,293 participants from the National Lung Screening Trial and Genetic Epidemiology of COPD study. CT-derived biological age gaps (BAGs) were examined in relation to lifestyle and socioeconomic factors, prevalent comorbidities, incident chronic diseases, and all-cause and cause-specific mortality. Higher BAGs, indicating organs that appeared older on CT than expected for their chronological age, were broadly associated with adverse health characteristics, chronic disease burden, and increased mortality risk. Multiple disease outcomes were associated with aging across several organs, whereas in multivariable analyses including all eight organ-specific BAGs, the remaining associations were more organ specific. A greater number of markedly older-appearing organs and a faster pace of aging were each associated with higher mortality. Together, these findings demonstrate that routine chest CT captures both shared and organ-specific patterns of biological aging and establish CT-derived organ aging as a quantitative imaging biomarker for assessing multi-organ health and long-term disease risk.

Stroke remains a leading cause of mortality and long-term disability worldwide, yet rapid diagnosis is often limited by the shortage of trained radiologists, particularly in resource-constrained settings. Automated analysis of CT imaging offers a potential solution, but existing methods often struggle to achieve clinically generalisable performance while jointly addressing multiple diagnostic tasks. Here we present the Intelligent Integrated Stroke Diagnosis System IISDS, an end-to-end deep learning framework built upon StrokeGNN, a graph-based architecture that integrates 3D contextual feature extraction with U-Net-based 2D lesion segmentation to enable comprehensive stroke analysis from non-contrast CT scans. IISDS performs stroke subtype classification, lesion segmentation and lesion volume estimation within a unified pipeline. To develop and validate the system, we collected and curated BGD-ISD through a collaboration between AI researchers, neurologists, radiologists and clinicians, resulting in a large multi-centre dataset comprising 1,507 CT scans from 597 stroke cases acquired across six hospitals and medical centres in Bangladesh. Across BGD-ISD and multiple publicly available datasets, IISDS achieves state-of-the-art performance on all tasks, improving segmentation accuracy by [&ge;]0.011 Dice score, reducing lesion volume estimation error by [&ge;]0.3 average symmetric surface distance (ASSD), and increasing classification performance by [&ge;]0.018 area under the receiver operating characteristic curve (AUC) compared with existing approaches. These results demonstrate the potential of graph-based deep learning to enable clinically generalisable, automated and scalable stroke diagnosis from CT imaging, supporting rapid clinical decision-making, particularly in healthcare environments with limited access to expert radiological interpretation.

Background: Aerobic exercise is recommended during stroke rehabilitation to improve cardiorespiratory fitness and support recovery; however, participation rates remain low. While institutional and system-level barriers have been widely examined, less is known about how individual patient factors influence engagement in aerobic exercise during rehabilitation. Objectives: We aimed to determine whether depressive symptoms, apathy, self-efficacy and outcome expectations for exercise, perceived barriers, or past exercise history were associated with aerobic exercise participation in stroke rehabilitation. Methods: In this prospective cohort sub-study, adults admitted to in- or out-patient stroke rehabilitation at three urban hospitals completed validated questionnaires assessing depressive symptoms, apathy, exercise self-efficacy, outcome expectations for exercise, perceived barriers to being active, and premorbid exercise history. Participants were separated into two groups for analysis: those who completed aerobic exercise during rehabilitation and those who did not. Equivalence testing and between-group comparisons were performed. Results: Sixty-two participants were enrolled; 16 participated in aerobic exercise and 46 did not. Groups were not equivalent on any individual-level factors. Compared to non-participants, those who performed aerobic exercise had significantly higher depressive symptom scores (p=0.0025) and lower self-efficacy for exercise (p=0.0087). Non-participants demonstrated significantly higher apathy (p=0.0007). No significant differences were found for outcome expectations, perceived barriers, or exercise history. Conclusion: Depressive symptoms and lower self-efficacy did not impede aerobic exercise participation during rehabilitation. Increased apathy, however, was associated with non-participation. Findings highlight the need for individually tailored aerobic exercise prescriptions that consider motivational and affective factors to optimize engagement during stroke rehabilitation.

Background and Objectives: Recurrence following burr-hole drainage of chronic subdural haematoma (cSDH) occurs in 10-25% of cases, sustained by neovascularisation of the subdural neomembrane supplied by the middle meningeal artery (MMA). MMA embolisation reduces recurrence; whether incidental burr-hole intersection of MMA branches during drainage confers similar benefit is unknown. Methods: We performed a multicentre retrospective cohort study of consecutive adults undergoing burr-hole drainage for cSDH at two UK tertiary neurosurgical centres. Postoperative thin-slice CT was used to classify burr-hole intersection of the underlying MMA groove (no hit, distal-branch hit or main-branch hit) and measure perpendicular burr-hole-to-MMA-groove distance. Co-primary outcomes were radiological recurrence and recurrence requiring intervention. Patient-clustered multivariable logistic regression adjusted for prespecified clinical covariates and treating site. Results: 227 patients (284 operated hemispheres) were included. Radiological recurrence decreased from 34.4% with no branch hit to 22.9% with main-branch intersection, with the gradient confined predominantly to unilateral cSDH. Main-branch intersection was associated with lower adjusted odds of radiological recurrence in unilateral cSDH (adjusted OR 0.30, 95% CI 0.11- 0.81; P = .018), with a similar but non-significant association in the overall cohort (adjusted OR 0.53, 95% CI 0.26-1.07; P = .075). Burr-hole-to-MMA-groove distance demonstrated a more consistent association: in the overall cohort, each 5-mm increase independently increased the odds of radiological recurrence (adjusted OR 1.38, 95% CI 1.04-1.82; P = .025). In unilateral cSDH, each 5-mm increase was independently associated with both radiological recurrence (adjusted OR 1.45, 95% CI 1.03-2.04; P = .034) and recurrence requiring intervention (adjusted OR 1.52, 95% CI 1.05-2.20; P = .027). Conclusion: Main-branch intersection of the middle meningeal artery during routine burr-hole surgery is associated with lower recurrence of unilateral cSDH, while the accompanying burr-hole-to-MMA-groove distance gradient provides biologically plausible support for a dose-response relationship. Together, these findings provide mechanistic rationale for prospective evaluation of intentional neuronavigation-guided MMA targeting (BURR-MMA; NCT07549893).

Disseminating study results to participants is an ethical responsibility for researchers but remains uncommon in low- and middle-income countries, and participants preferences for receiving study results are poorly understood. This study examined study result dissemination preferences among pregnant women in a phase III malaria prevention trial in Papua New Guinea (PNG). Participants completed an interviewer-administered questionnaire (survey) assessing their interest in and motivation for receiving trial results and preferences for dissemination methods and content. Associations between participants characteristics and dissemination preferences were explored using multivariable logistic regression analysis. Of 1172 trial participants, 96.0% (1125/1172) completed the survey, and of these 99.6% (1121/1125) wanted to learn about the trial results. The main motivation factors driving participants interest were an acknowledgment of their contribution to research (51.7%; n=579) and a better understanding of the study (45.0%; n=505). Most participants (78.9%; n=884) wanted to learn about the trial findings through written summary and a group meeting with other participants at the nearest clinic (31.1%, n=349). Multivariable regression analysis indicated that participants from rural/peri-urban clinics were more likely to choose non-electronic media dissemination approaches such as a group meeting as compared to urban-dwelling participants. Frequently selected items (>50% of participants) for content included information regarding good results of the study, purpose of the study, medical treatment advances, results specific to me, and how study was conducted. There was heterogenicity in the preference for dissemination content: compared to urban clinics rural clinics are less likely to want to learn about how and why study was conducted and medical and scientific advances. Overall, the majority wanted to learn about trial results, highlighting the importance of integrating dissemination into research activities in PNG. Variation in preferences for mode and content of dissemination between study clinics suggests that dissemination activities could be tailored to local context and preferences.

Objective: To determine whether paradoxical relief, feeling unusually better after a seizure compared to before it, is more common after functional/dissociative seizures (FDS) than epileptic seizures (ES), quantify its diagnostic accuracy, and explore its relationship with preictal symptoms. Methods: Consecutive patients admitted to a tertiary epilepsy unit for prolonged inpatient EEG monitoring underwent a structured clinical interview on admission, before final multidisciplinary diagnostic classification. Preictal dissociative and autonomic/somatic symptom burden was assessed using items adapted from established questionnaires. Diagnostic classification incorporated clinical history, seizure semiology, video electroencephalography findings, and collateral information. Patients with dual or indeterminate diagnoses were excluded. Associations with paradoxical relief were examined using logistic regression, followed by an exploratory mediation analysis. Results: Of 176 patients assessed, 66 with FDS and 65 with ES were included. Paradoxical relief was reported by 46/66 patients with FDS (69.7%) and 10/65 with ES (15.4%; unadjusted odds ratio [OR] 12.65, 95% confidence interval [CI] 5.57 to 31.09). As a diagnostic signal for FDS, paradoxical relief had 69.7% sensitivity (95% CI 57.1 to 80.4), 84.6% specificity (95% CI 73.5 to 92.4), a positive likelihood ratio of 4.53 (2.51 to 8.19), and a negative likelihood ratio of 0.36 (0.24 to 0.52). FDS diagnosis remained independently associated with paradoxical relief after adjustment (OR 10.59, 95% CI 3.42 to 38.06). In a parallel mediation analysis, dissociative symptom burden showed a significant indirect effect, accounting for 19.5% of the association between diagnostic group and relief, whereas the indirect effect through somatic/autonomic symptom burden was not significant. Significance: Paradoxical relief is substantially more common after FDS than ES and may provide a simple, clinically useful diagnostic signal. Its absence does not exclude FDS, and the finding requires external validation. The association with dissociative symptoms is exploratory and supports prospective investigation of whether relief reflects transient resolution of a disturbed, disembodied preictal state.

Background: In Tanzania, over 10,000 women aged 15-44 are diagnosed with cervical cancer annually, and more than 6525 die. The majority are diagnosed at an advanced stage, which contributes to delays in treatment enrollment and illness complications. Multiple factors can affect womens willingness and ability to access cervical pre-cancer screening. Purpose: To explore the barriers and facilitators to attending cervical pre-cancer screening among women living in a resource-constrained area of Southern Tanzania Methods: A qualitative study of 17 focus group discussions and 12 in-depth interviews was conducted from December 2023 to July 2024. Data collection took place in the community and health centers of a town and the surrounding rural areas in Kilombero district. The study used purposive sampling to recruit 112 women and 23 men aged 18- 50+ years. Results: Fear of death emerged as a central theme in the data, acting as both a barrier to and a facilitator of womens screening behavior. Women linked death with the screening procedure, receiving results and undergoing treatment. Participants mistrusted the speculum itself and linked it to pain, vaginal infection, and infertility. Conversely, fear of physical and social death motivated other women to attend the screening to learn about their health and prevent the consequences of a positive diagnosis. Public trust in the healthcare system and the role of health information sources were also identified as influencing women's decisions to undergo or not undergo screening. Conclusion: Our findings showed that cervical cancer screening uptake is influenced by fear of death and other co-factors. To improve early cervical cancer screening, programs and policy interventions are needed to raise awareness of the disease while also addressing womens specific concerns. Also, strengthening structural dimensions such as the availability of the healthcare workforce, healthcare facilities, and ensuring equitable service availability are essential to reducing cervical cancer complications and avoidable mortality.

Objective: Whether a scheduled antiseizure medication (ASM) continues on schedule across the ICU-to-floor transfer has not been characterized. We quantified ASM administration-gap frequency across this transfer and compared it with gap frequency during matched non-transfer intervals in the same patient and drug. Methods: In this retrospective MIMIC-IV (version 3.1) cohort study, we identified epilepsy and status-epilepticus admissions with an ICU stay followed by floor transfer and a scheduled ASM order active at ICU departure. A gap was defined as an interval exceeding 1.5 times the expected dosing interval between the last ICU dose and first floor dose, or no further dose before discharge, and compared with a matched non-transfer control interval in the same patient and drug (paired McNemar test). A multivariable model evaluated six prespecified clinical predictors; sociodemographic variables were summarized descriptively. Results: Among 2,469 ASM transition-by-drug observations (1,583 admissions, 1,335 patients), an administration gap occurred in 251 (10.2%; 95% CI, 8.7%-11.7%). Gap frequency across the transfer exceeded frequency during matched non-transfer control intervals in the same patient and drug: a paired rate difference of 5.8 percentage points (95% CI, 4.4-7.1; 7.5% vs 1.7%; P = 7.3 x 10^-22) before the transfer and 6.4 percentage points (95% CI, 4.9-7.9; 8.9% vs 2.5%; P = 1.9 x 10^-23) after. Gap rates were similar for intravenous-available (9.9%) and oral-only (11.4%) drugs (rate difference, 1.5 percentage points; 95% CI, -1.6 to 4.5; P = .34). None of six prespecified predictors reached significance after correction. Significance: An antiseizure medication administration gap occurred in approximately 1 of every 10 drug-transition observations at the ICU-to-floor transfer, exceeding matched non-transfer gap rates by 5.8 to 6.4 percentage points. This transfer-associated excess, rather than any single medication or patient characteristic, supports a structured medication-continuity check.

Background: Fluctuations in pain intensity are intrinsic to non-specific chronic low back pain (nsCLBP). Nevertheless, pain fluctuations have rarely been considered when investigating pathophysiological mechanisms. Therefore, a novel study protocol was developed and implemented to systematically assess the impact of fluctuating pain states on pain-related measures. Methods: The final study cohort consisted of 45 nsCLBP patients and 47 age- and sex-matched healthy controls (HCs). Patients participated in three visits, conducted during different pain states (i.e. clinically relevant pain, low-intensity clinical pain / pain-free, clinically irrelevant pain induced using a Qutenza 8% capsaicin patch). Pain fluctuations were monitored through online assessments every four days and guided the pseudorandomized visit scheduling. HCs participated in a single visit. Each study visit comprised a multimodal battery of pain-related measures. Results: 93.33% of patients completed all three visit types in a pseudorandomized order (chi-squared=1.50, p=0.826). Visit scheduling was possible due to the high self-report adherence (median=93.48%), unrelated to self-report burden (rho=-0.097, p=0.53). Study visits were conducted during different pain states, as indicated by: i) the significantly higher low back pain intensity in the clinically relevant pain visit (mean[SD]: 3.98[0.90]), compared to the low-intensity clinical pain (1.03[0.86]) and clinically irrelevant pain (1.13[0.82]) visits (p-values<0.001), as well as by ii) the successful induction of a moderate-to-high clinically irrelevant pain across assessments. Conclusion: Despite scheduling complexity and pain state transition uncertainty, a pain state-dependent pseudorandomized study design is feasible and could improve the understanding of nsCLBP mechanisms.