Journal of Clinical Pathology

Background: Early access to pregnancy assessment units now detects many tubal ectopic pregnancies (TEP) at a stage when they could resolve spontaneously, creating a management dilemma. Methods: We performed a hypothesis-generating exploratory analysis in a retrospective study to assess whether serum progesterone (P4) levels in women with TEP are associated with management outcome. Results: Ninety-one cases of TEP managed in a single centre over three years were analysed. Receiver operating characteristic (ROC) curve analysis was used to explore serum levels of progesterone (P4), first human chorionic gonadotropin (hCG) and peak hCG (alone and in combination) in relation with successful completion of expectant management. Decision-tree analysis using first hCG and P4 was additionally performed to explore clinical sequential risk stratification. 23% (n=21) successfully completed expectant management. P4 concentrations in the expectant management group (median 3 nmol/L, IQR 2.00 to 8.50) were significantly lower than in those requiring surgical or medical management (median 17 nmol/L, IQR 5.75 to 29.25; p=0.0002). Area under the ROC curve (AUC) values for P4, log10 first hCG, log10 peak hCG and P4 with log10 first hCG were 0.766, 0.814, 0.811 and 0.835, respectively, for predicting successful expectant management. However, hCG was not significantly outperformed. Nonetheless, Youden optimised thresholds for hCG and P4 are reported, alongside decision-tree analysis that identified sequential first hCG and P4 thresholds associated with successful expectant management. Conclusion: Lower P4 levels are associated with successful expectant management of TEP but they do not outperform hCG either alone or as an adjunctive marker.

Background: Pregnancies complicated by fetal growth restriction are at increased risk of fetal demise and adverse neonatal outcomes. Distinguishing growth-restricted fetuses from constitutionally small ones remains challenging. Given the variability in current diagnostic criteria and the importance of identifying at-risk fetuses, fetal growth velocity has emerged as a predictor of adverse neonatal outcomes. Objective: To evaluate whether percentile-based fetal growth velocity, defined as change in estimated fetal weight percentile per week, predicts adverse neonatal outcomes in pregnancies affected by fetal growth restriction or small-for-gestational-age neonates. The primary aim was to determine the relationship between growth velocity and a composite of adverse neonatal outcomes. Study Design: This was a retrospective cohort study of pregnant patients 18 - 45 years old who delivered between August 2017 to December 2022 in a single healthcare system. Patients were excluded who had fewer than 2 ultrasounds after 16 weeks gestation, genetic or anatomic abnormalities, or a multiple gestation. Results: 300 patients met all inclusion criteria, and most patients (n=199) delivered at the tertiary care center. Three had an intrauterine fetal demise at a mean gestational age of 35w3d. 74 neonates were admitted to the NICU with a mean length of stay of 8.5 days; 29 required respiratory support. No neonatal deaths occurred. In fetuses with initial estimated fetal weight <3rd percentile (n=33), the probability of composite outcome was increased (50%, 95% CI 44.8-55.2) compared to those >50th percentile (5%, 95% CI 3.7-6.6). In the 3-10th and 10 - 50th percentile subgroups with decelerated growth, composite outcome rates were also increased (56.2% and 44.1%) compared to those with neutral or increased growth velocity. Conclusion: Percentile-based fetal growth velocity is a simple calculation that correlates with adverse neonatal outcomes regardless of initial estimated fetal weight. As fetal growth velocity decreased, our cohort saw increased rates of adverse outcomes. Change in EFW percentile normalizes for gestational age and allows ease of clinical interpretation. Decelerated growth identified fetuses at highest risk, suggesting growth velocity as a useful metric in routine surveillance.

Introduction: Thyroid diseases are major health problems and among the most common endocrine disorders worldwide, including in Ethiopia. They are characterized by alterations in hormone secretion, enlargement of the thyroid gland, or both. Fine needle aspiration cytology is an important initial screening tool, and histopathologic examination is essential for the definitive diagnosis of thyroid disease. This study aimed to compare the diagnostic accuracy of fine needle aspiration cytology with histopathology in identifying thyroid diseases. Methods: A cross-sectional study was conducted at three health facilities in Hawassa City, Ethiopia, involving 304 patients who underwent both thyroid fine needle aspiration cytology and histopathologic examination of the same site between 30th October 2024 and 29th October 2025. FNAC results were classified using the Bethesda system, with histopathology as the gold standard. Data were entered into Kobo Toolbox, exported to SPSS version 27, and analyzed using cross-tabulation and chi-square ({chi}{superscript 2}) tests to determine diagnostic accuracy. Result: 304 patient records were included in the study. The fine needle aspiration cytology was determinate/diagnostic in 81.6% of cases. The study revealed the sensitivity and specificity of fine needle aspiration cytology to be 88.2% (CI 77.6-95.1%) and 94.4% (CI 90.6-97.1%), respectively. The false negative and false positive rates in this study were 2.4% and 4.4%, respectively. The positive predictive value was 80.3% (CI 68.7-89.3%), and the negative predictive value was 96.8% (CI 93.8-98.7%). The accuracy of fine needle aspiration cytology in differentiating benign from malignant thyroid lesions was 93.1%. Conclusion: FNAC demonstrated strong agreement with histopathology and remains a reliable, cost-effective first-line diagnostic tool for thyroid disease, particularly in resource-limited settings. Strengthening sample handling, ultrasound guidance, and adherence to Bethesda criteria may further improve diagnostic precision

Background: General-purpose large language models (LLMs) are increasingly evaluated in diagnostic pathology, but prior studies have largely emphasized diagnostic accuracy rather than how models fail. We evaluated four LLMs for diagnostic performance, pathology-relevant errors and hallucinations, their burden, and potential clinical impact across multi-organ pathology cases. Design: In this retrospective multicenter study, 153 pathology cases from two institutions spanning 20 organs were evaluated using ChatGPT-5.3 (LLM1), Gemini 3 (LLM2), Grok 4.20 (LLM3), and Claude Opus 4.6 (LLM4). Each LLM received multi-magnification histologic images with clinical context and generated a microscopic description and diagnosis. No data splitting, training, or fine-tuning was performed. Twenty-one pathologists assessed 612 outputs for diagnostic correctness, error and hallucination type and burden, clinical impact (0-4), and overall performance (1-5). Results: Strict diagnostic accuracy was 48.9% overall (60.1% including partially correct diagnoses) and ranged from 36.6% to 58.2% across LLMs. Errors occurred in 82.0% of outputs and hallucinations in 76.6%; 90.2% contained at least one error or hallucination. Misinterpretation was the most frequent error (72.1%), while fabricated histologic features were the dominant hallucination type (74.5%). LLM2 had significantly lower misinterpretation rates than the other three LLMs, while LLM3 had significantly higher fabricated-feature hallucination rates than LLM1 and LLM2. Errors were more frequent in incorrect than correct diagnoses (97.5% vs 66.2%), as were hallucinations (95.1% vs 59.9%; both p < 0.001). Every strictly incorrect diagnosis contained an error and/or hallucination, while 79.9% of strictly correct diagnoses also contained at least one. In multivariable analysis, LLM3 was independently associated with higher odds of an incorrect diagnosis. Diagnostic correctness was the strongest determinant of high clinical impact; each one-point increase in hallucination burden increased the odds by 63% (adjusted OR, 1.63). Conclusion: Diagnostic accuracy alone substantially underestimates the safety limitations of general-purpose LLMs in histopathology. Errors and hallucinations were common even when the final diagnosis was correct, and their burden was independently associated with clinical impact. Evaluation frameworks should therefore assess both diagnostic correctness and the reliability and potential consequences of accompanying generated content.

Background: Lung cancer is leading cause of cancer related death globally. It is second most prevalent cancer among women worldwide and ranks third among females in Nepal. Contributing factors are smoking, tobacco use, air pollution, and delayed diagnosis. Image-guided fine needle aspiration cytology (FNAC) is rapid diagnostic technique for evaluating lung lesions. It is minimally invasive procedure with less complications. This study examine histocytologic makeup of lung lesions and link the results. Materials and Methods: This cross-sectional observational study included 65 patients irrespective of age and sex presenting with lung masses at Chitwan Medical College and Teaching Hospital from April 2023 to September 2024. After clinical and radiologic evaluation, all cases underwent image-guided FNAC and biopsy. Only specimens with unequivocal malignant features were classified positive. Histopathology served as diagnostic reference standard. Results: FNAC diagnosed 90.8% as malignant and 9.2% as benign. Biopsy confirmed malignancy in 92.3% of cases. FNAC demonstrated a sensitivity of 98.33%, specificity of 100%, positive predictive value(PPV) of 100%, and negative predictive value (NPV) of 83.33%. Concordance between FNAC and histopathological subtyping was 98.46%. Adenocarcinoma was most common subtype, followed by Squamous cell carcinoma(SCC) and small cell carcinoma. Smoking was most common contributing factor associated with malignancy. Conclusion and implications: Image-guided FNAC is an excellent diagnostic accuracy tool which possess higher level of concordance with biopsy in evaluating lung masses. It should be considered as frontline diagnostic tool, especially in resource limited settings. Keywords: FNAC, Lung cancer, Biopsy, SCC, Adenocarcinoma, Small cell carcinoma, Nepal

Objective: Hyperthyroidism and hypothyroidism related to iodine deficiency are major public health concerns in Afghanistan. This study aimed to assess the frequency of thyroid dysfunction among male patients referred for thyroid testing and its association with age, and to examine monthly trends in thyroid dysfunction at Asia Med Laboratory in Herat, Afghanistan, from July 2021 to January 2022. Methods: A retrospective analysis was conducted on 250 male patients aged 0-69 years. We measured Serum TSH, total T4, and total T3 levels, and thyroid status was classified using age specific reference ranges. In addition, the frequency of thyroid dysfunction was analyzed across age groups with monthly trends of thyroid state. Results: Overall, the euthyroid state consisted of 69.2% of participants, 24.8% with overt hypothyroidism, 3.2% with overt hyperthyroidism, and 2.8% with subclinical hyperthyroidism. Thyroid status differed significantly by age (p = 0.0135), with hypothyroidism increasing in older age groups and reaching its highest proportion among men aged 60-69 years (55.6%). Euthyroidism predominated in patients aged 10-39 years, while hyperthyroidism across age groups remained relatively infrequent. After September 2021, a threefold increase was observed in the total number of male patients referred for thyroid testing. During this period, the proportion of hyperthyroidism increased slightly, whereas hypothyroidism cases declined. Conclusion: In conclusion, hypothyroidism was more frequent with older age. The rise in absolute case numbers after September 2021 likely reflects increased patient referrals, underscoring the need for ongoing monitoring of thyroid function. The study may assist in the early management of thyroid disorders and in reducing their complications.

RationaleOxidative stress, resulting from an imbalance between the production of reactive oxygen species (ROS) and antioxidant defence mechanisms, disrupts cellular redox homeostasis and contributes to damage of biomolecules, including nucleic acids, proteins and lipids. Such disturbances can impair intracellular signalling pathways and have been implicated in the pathophysiology of female reproductive disorders. Nitroblue Tetrazolium (NBT) is a distinctive dye that assesses cellular redox activity in neutrophils through the detection of superoxide anion (O2-). However, the relationship between neutrophil-derived oxidative stress and women infertility remains to be fully elucidated. Aim of the study: We aimed to investigate the role of neutrophil oxidative stress in women infertility using a novel Nitroblue Tetrazolium (NBT) method developed in our laboratory. Materials and methodsBlood and serum specimens were obtained from a total of 100 Libyan women, comprising healthy fertile women (n = 21; controls) and infertile women (n = 79). Superoxide anion (O2-) generation in neutrophils was assessed using the novel NBT method, while malondialdehyde (MDA), a marker of lipid peroxidation, was determined using the thiobarbituric acid reactive substances (TBARS) assay. ResultsA significant increase in both NBT-reactivity levels and the percentage of NBT-positive neutrophils was observed in infertile women compared with healthy fertile controls (P < 0.0001). In addition, MDA levels were significantly higher in infertile women than in the control group, indicating enhanced lipid peroxidation. MDA levels were positively correlated with NBT-reactivity levels (r = 0.410, P = 0.0001) and the percentage of NBT-positive neutrophils (r = 0.21, P = 0.047). A significant positive correlation was also observed between NBT-reactivity levels and the percentage of NBT-positive neutrophils (r = 0.510, P = 0.0001), demonstrating a close association between neutrophil oxidative activity and lipid peroxidation in women infertility. ConclusionThe present study demonstrates the utility of a novel NBT method for detecting reactive oxygen species (ROS), a marker of oxidative stress, in neutrophils from both blood and serum specimens. The findings demonstrate increased neutrophil-derived oxidative stress in infertile women and suggest that this method may have potential as a diagnostic tool for the assessment of women infertility. ImpactThis study provides evidence that neutrophil-derived oxidative stress is significantly increased in women infertility and demonstrates the application of a novel Nitroblue Tetrazolium (NBT) assay for assessing oxidative stress in both blood and serum specimens. The significant associations between NBT-reactivity, NBT-positive neutrophils and malondialdehyde levels provide further insight into the contribution of oxidative stress to female reproductive pathophysiology. These findings support the potential utility of the novel NBT method as a simple and reliable diagnostic approach for evaluating oxidative stress in women infertility and provide a foundation for future studies investigating oxidative stress biomarkers in reproductive medicine.

Background. In Europe, first-trimester combined screening with the Fetal Medicine Foundation (FMF) algorithm identifies women at increased risk of preeclampsia who may benefit from personalized aspirin prophylaxis. However, a substantial proportion of early-onset preeclampsia (EOPE) remains undetected at clinically acceptable specificity. Objective. To evaluate the first-trimester performance of MaiRa for early-onset preeclampsia (EOPE) risk stratification by benchmarking it against FMF screening in the same women, characterizing discordant patient-level classification profiles and exploring potential implementation strategies. Study Design. This secondary case-control analysis was nested within the prospective, multicentre PREMOM cohort [NCT04990141], which enrolled women with singleton pregnancies across 14 tertiary hospitals in Spain. First-trimester MaiRa and FMF risk estimates were evaluated in the same 126 pregnant women, comprising 99 uncomplicated controls and 27 EOPE cases, defined by disease onset before 34 weeks. Discrimination was compared using a stratified paired bootstrap analysis of the areas under the receiver-operating-characteristic curves. Performance was assessed at prespecified clinical thresholds, and detection rates were evaluated at fixed false-positive rates. Universal and contingent MaiRa implementation strategies were also evaluated. Results. MaiRa showed greater first-trimester discrimination for EOPE than FMF combined screening (AUC, 0.974 vs 0.900; P=.040) and consistently achieved higher detection rates across fixed false-positive rates. At false-positive rates of 5% and 10%, MaiRa detected 85.2% and 92.6% of EOPE cases, compared with 44.4% and 70.4% for FMF, respectively. Patient-level analysis demonstrated that MaiRa identified 12 of 27 EOPE cases (44.4%) classified as low risk by FMF; these pregnancies generally exhibited less abnormal conventional first-trimester profiles, including fewer maternal risk factors, lower mean arterial pressure and lower uterine artery pulsatility index, yet 8 of 12 (66.7%) subsequently developed severe EOPE. Exploratory implementation analyses showed that universal MaiRa screening achieved the highest EOPE detection, whereas a contingent strategy using FMF for triage and reflex MaiRa testing reduced molecular testing to 35.7% of pregnancies while maintaining 77.8% sensitivity and 97.0% specificity. Conclusion. MaiRa provided greater first-trimester discrimination for EOPE than conventional combined screening and detected additional pregnancies that later developed severe disease despite less abnormal conventional screening profiles. The findings suggest that maternal plasma cfRNA profiling captures biological alterations not fully reflected by combined first-trimester screening and support further prospective evaluation in an independent, unselected obstetric population. Key words: early-onset preeclampsia; first-trimester screening; cell-free RNA; liquid biopsy; Fetal Medicine Foundation algorithm; combined screening; risk stratification; aspirin prophylaxis.

Objective: The purpose of this study was to estimate the negative predictive value (NPV) of screening for group B streptococcus (GBS) colonization in pregnant patients undergoing antepartum hospitalization for GBS colonization status at the time of preterm delivery. Study Design: This prospective, observational cohort study compared GBS colonization status upon initial hospital admission to that at the time of delivery. Pregnant patients at 22 to 35 weeks gestation admitted to the antepartum unit at a tertiary care hospital underwent standard screening for GBS colonization. When preterm labor progressed or iatrogenic preterm delivery was indicated, the GBS colonization test was repeated. Comparison of the sequential test results was performed to determine the NPV of the antepartum screening test for the intrapartum status. Results: 159 eligible patients were enrolled in the study, and 100 completed the study and were included in the analysis. The average gestational age at admission was 30 weeks 1 day (95% confidence interval [CI] 29w4d to 30w6d) and the average duration of pregnancy latency in the study group was 17.5 days (95% CI 15.1 to 19.8). GBS colonization rate at the time of admission was 18% and at the time of delivery was 20%. The NPV of GBS screening at admission was 91.5% (95% CI 83.2 to 96.5%) and the positive predictive value (PPV) was 72.2% (95% CI 46.4 to 90.3%). Conclusion: In a cohort of pregnant patients with preterm pregnancy complications, GBS screening at the time of antepartum hospital admission has an NPV of 91.5% (95% CI 83.2 to 96.5%) for GBS colonization at the time of preterm delivery. This is comparable to the published NPV of routine GBS screening for colonization status at term delivery.

Objective: To evaluate the added diagnostic value of immediate postpartum impedance spectroscopy (IS) when used alongside clinical assessment for obstetric anal sphincter injury (OASI), using subsequent three-dimensional endoanal ultrasound (3D EAUS) as the anatomical reference assessment. Methods: This prospective observational cohort study included women following vaginal birth with at least one predefined OASI risk factor or clinical uncertainty regarding sphincter injury. Participants underwent postpartum clinical assessment, including digital rectal examination and senior obstetric reassessment when required, followed by immediate postpartum IS. Women who subsequently completed 3D EAUS were included in the paired diagnostic analysis. Diagnostic performance, agreement with EAUS and clinically relevant discordant findings were evaluated. Results: Of 151 women enrolled, 70 completed EAUS and were included in the paired analysis; 29/70 (41.4%) were OASI-positive on the EAUS-based reference assessment. IS had a sensitivity of 86.2% (95% CI 69.4-94.5), specificity of 92.7% (95% CI 80.6-97.5) and overall accuracy of 90.0% (95% CI 80.8-95.1), compared with 75.9% (95% CI 57.9-87.8), 70.7% (95% CI 55.5-82.4) and 72.9% (95% CI 61.5-81.9), respectively, for clinical assessment. In paired analysis, IS was correct and clinical assessment incorrect in 17 women, whereas clinical assessment was correct and IS incorrect in five (McNemar P=0.017). Seven women with confirmed OASI were not identified clinically, and all seven generated an IS REFER result. Conversely, among 12 women clinically diagnosed with OASI who underwent primary repair but were subsequently classified as OASI-negative, 10 (83.3%) generated an IS PASS result. IS was performed within the first hour postpartum in 94.3% of women, and 70.0% of examinations were performed by midwives. Conclusions: Immediate postpartum IS provided additional objective information complementary to clinical assessment, particularly when clinical findings did not reliably identify or exclude sphincter injury. These findings support prospective evaluation of IS within postpartum diagnostic pathways to determine whether its use reduces diagnostic errors and improves clinically meaningful outcomes.

Background: Gastric carcinoma remains a major cause of cancer related mortality worldwide, with tumor progression increasingly recognized as a consequence of complex interactions within the tumor microenvironment. Hypoxia induced signaling, cancer associated fibroblast (CAF) heterogeneity, and immune checkpoint activation play critical roles in tumor progression and immune evasion. However, their integrated relationship in gastric carcinoma remains insufficiently characterized. Objectives: To evaluate the expression of Hypoxia inducible factor 1 alpha and its association with cancer-associated fibroblast subtypes and Programmed death-ligand 1 expression in gastric carcinoma. Methods: This cross sectional analytical study included 100 histologically confirmed gastric carcinoma cases from Satkhira Medical College. Immunohistochemistry was performed for HIF 1 alpha, smooth muscle actin (SMA), fibroblast activation protein (FAP), and PD L1. CAFs were subclassified into myofibroblastic CAFs (myCAFs) and inflammatory CAFs (iCAFs). Associations between biomarkers and clinicopathological variables were analyzed using chi square test, Spearman correlation, and multivariate logistic regression. Receiver operating characteristic (ROC) curve analysis was used to assess model performance. Result: High HIF 1 alpha expression was observed in 55% of cases and demonstrated significant association with poor differentiation (p = 0.001), advanced tumor stage (p = 0.002), and lymph node metastasis (p = 0.001). iCAF predominance was significantly associated with poor differentiation (p = 0.003), advanced stage (p = 0.004), and nodal metastasis (p = 0.004). High PD L1 expression was significantly associated with poor differentiation (p = 0.03), advanced stage (p = 0.001), and lymph node metastasis (p = 0.002). Multivariate logistic regression identified high HIF 1 alpha expression (OR = 3.8, p = 0.001), iCAF dominance (OR = 4.5, p < 0.001), and advanced tumor stage (OR = 2.9, p = 0.004) as independent predictors of high PD L1 expression. Combined high HIF 1 alpha expression and CAF activation demonstrated the highest rate of PD L1 positivity (76.7%, p < 0.001). ROC curve analysis demonstrated good predictive performance of the model with an area under the curve of 0.81. Conclusion: The present study demonstrates a significant interaction between hypoxia, stromal remodeling, and immune checkpoint activation in gastric carcinoma. High HIF 1 alpha expression and inflammatory CAF predominance are strongly associated with aggressive clinicopathological features and increased PD L1 expression, supporting the existence of a coordinated hypoxia stroma immune axis in gastric carcinoma progression. These findings may have potential implications for prognostic stratification and combined targeted therapeutic strategies.

Assessment of tumour infiltrating lymphocytes (TILs) is a robust prognostic biomarker for HER2-positive and triple negative breast cancer. We aimed to update a previously established pipeline for automated TIL assessment to align to clinical scoring guidelines (tumour region identification guided scoring), foundation model-based lymphocyte detection (SAM-TIL) and compare with alternative methods (HoVerNet, muTILs) and gold standard clinical assessment. TRIGS and SAM-TIL had an odds ratio of 1.95 (95% confidence interval(ci): 1.22-3.03, p=0.005) and 2.32 (95% ci:1.43-3.77, p=0.001) for predicting pathological complete response (pCR) rate in 166 neoadjuvantly treated patients in the TransNEO cohort. Hazard ratios for overall survival in 277 triple negative and HER2-positive patients in The Cancer Genome Atlas were 0.79 (95% ci: 0.63-1.00, p=0.05) and 0.80 (95% ci: 0.67-0.97, p=0.02) for TRIGS and SAM-TIL. Comparator methods showed similar results. Correlation with gold standard clinical assessment in 285 patients from the PARTNER randomized trial ranged from 0.59-0.69, which is substantially more than interobserver variability for the gold standard. Despite differences with gold standard assessment, no substantial difference in predicting pCR (AUC 0.60-0.64) or event free survival (Integrated Brier score approximately 0.10) were observed between the tested methods and gold standard assessment, suggesting AI tools that do not follow manual scoring guidelines could be validated and subsequently used. Although we reached prognostic performance similar to published literature and gold standard assessment, the lymphocyte detections produced by the models are not interchangeable with gold standard clinical assessment (correlation 0.59-0.69) and therefore cannot support pathologist assessment. Further studies to validate independent use and/or to improve prognostication are required.

Cardiotocography (CTG) is the standard of care for intrapartum fetal monitoring, yet its poor specificity drives unnecessary intervention without reducing hypoxic-ischemic encephalopathy (HIE). Most artificial intelligence (AI) models are trained exclusively on the final hour before delivery, a window only identifiable retrospectively. We hypothesized that this framework prevents models from learning the early evolving signs of HIE. We analyzed 174,186 deliveries, with gestational age GA[&ge;]35 weeks, from Kaiser Permanente Northern California. Forty CTG features were extracted from 20-minute epochs to train Random Forest classifiers targeting severe acidosis (N=2,636) and clinically validated HIE (N=304). The training window was progressively extended from the final hour to the full duration of labor, and time from labor onset (TLO) was added as a feature. Models were evaluated continuously throughout labor at a fixed 15% false positive rate. Our results showed that the early identification of fetuses at risk of HIE improved as the training window was extended, plateauing at 18 hours. Adding TLO gave the highest early-warning performance: 40.3% of HIE cases identified at least 3 hours and 27.3% at least 6 hours before delivery, absolute gains of 8.4% and 10.7% over the last-hour classifier. Finally, 55.7% of HIE cases were identified at least 40 minutes before delivery. In conclusion, classifiers trained only on the last hour may identify HIE patterns that occur near delivery; time-aware models trained across labor map the temporal evolution of these patterns and provide actionable early warnings. Thus, AI systems for intrapartum monitoring must account for the temporal evolution of labor to shift from end-of-labor diagnosis to early-warning decision support.

Background Pre-implantation biopsy utility for deceased-donor kidney acceptance is controversial due to processing limitations and interpretive variability. We evaluated whether systematic histological assessment, including expert evaluation and quantification with the BanffNET automated deep learning system (17 lesions), predicts post-transplant failure under optimal laboratory conditions. Methods Biopsies from deceased donor kidneys (N=733) underwent optimized laboratory processing, whole slide imaging, expert Banff 2024 pathologic assessment, and BanffNET lesion quantification. We assessed their incremental predictive value beyond clinical characteristics for early graft dysfunction, longitudinal eGFR/UPCR trajectories, need for indication biopsies, and death-censored graft failure. Results Histopathology improved clinical model discrimination by 1-4% and increased explained variance for longitudinal trajectories by 1-2%. Continuous bivariate surface analysis, however, revealed that while histology adds marginal overall predictive accuracy, mapping continuous composite and individual BanffNET scores against the Kidney Donor Risk Index (KDRI) uncovers distinct topological risk gradients for early graft dysfunction and long-term graft failure. Conclusion While pre-implantation biopsies add minimal overall prognostic value, continuous bivariate mapping of KDRI and BanffNET scores uncovers distinct synergistic risk gradients for graft failure. These continuous clinical-histological surfaces could optimize organ salvage by precisely identifying viable high-KDRI kidneys lacking critical compounded damage and vice versa.

Gestational diabetes mellitus (GDM) is associated with significant maternal and neonatal morbidity. Screening strategies vary internationally and the diagnostic performance of the 50g glucose challenge test (50g GCT) as a universal screening tool remains uncertain across diverse populations. This retrospective cohort study included 18,213 singleton pregnancies at a London tertiary hospital between 2010 and 2023. Women routinely underwent the universal two-step GDM screening pathway: a 50g GCT at 24 - 32 weeks' gestation, followed by a diagnostic 75-g oral glucose tolerance test if the 50g GCT result was greater than or equal to 7.8 mmol/L. We evaluated the use of universal two-step screening in detecting GDM, how its prevalence varies with maternal characteristics, including ethnicity, body mass index, age, and in those who would not have been included in risk factor-indicated screening, and the association between the 50g GCT and adverse outcomes. 2,015 women had an abnormal GCT, and 406 (20.1%) had an abnormal 75g OGTT, with GDM diagnosed at 24-28 weeks. We also found 87 women, despite a normal GCT and/or normal OGTT, developed late-onset GDM. The overall prevalence of GDM was 4.4% (810/18,213). Universal screening will therefore identify a significant number of GDM cases, notably including those in a low-risk cohort who would not have been screened using a risk factor-based approach. When we examined glucose as a continuous variable, there was an association between increasing 50g GCT values and adverse maternal and neonatal outcomes. Universal screening with a GCT is a feasible and safe approach and addresses a significant health disparity gap, in that women without risk factors are screened and may be diagnosed with GDM. Given the long-term cardiometabolic implications of GDM, pregnancy diagnosis is important to allow for longer-term targeting of cardiometabolic risk factors to improve long-term health screening for type 2 diabetes and obesity.

Abstract Background: Chronic subdural hematoma (cSDH) remains a significant and increasingly prevalent cause of morbidity in older adults. Disease progression is sustained by de novo formed highly vascularized pseudomembranes and a persistent cycle of fluid accumulation and hematoma expansion. Although inflammatory and angiogenic pathways have been implicated in cSDH pathogenesis, the endothelial mechanisms underlying persistent vascular leak remain poorly understood. We investigated the cSDH vascular microenvironment in human patients and examined the role of vascular endothelial cadherin (VECAD) remodeling in cSDH endothelial dysfunction. Methods: Human cSDH membranes and fluid were evaluated by multiplex profiling, histology, immunofluorescence, immunoprecipitation, western blotting and exploratory bulk RNA sequencing. A human brain endothelial cell (HBEC) line was exposed to patient-derived cSDH fluid to assess VECAD remodeling, endothelial barrier permeability, and proliferation. Results: Multiplex profiling of patient-derived cSDH fluid detected mediators associated with endothelial cell (EC) activation, extracellular matrix remodeling, inflammation, and angiogenesis. In patient pseudomembranes, discontinuous VECAD coincided with erythrocyte extravasation. Two hyperdense (high-risk) specimens showed more extensive disruption than the hypodense (low-risk) specimen while vessel counts appeared similar. Bulk RNA sequencing identified an angiogenic environment and enrichment in cadherin regulation. A soluble VECAD (sVECAD) isoform was detected in cSDH fluid. Exposure of HBECs to patient-derived cSDH fluid increased EC proliferation, cytoplasmic VECAD (cVECAD) accumulation, and EC barrier permeability. Concurrent dexamethasone or minocycline treatment attenuated VECAD cleavage. Conclusions: VECAD disruption is a prominent feature of cSDH and is associated with EC barrier dysfunction. These findings support further evaluation of soluble VECAD as a candidate biomarker and of junction-preserving pathways as potential therapeutic targets.

Background: Patient-facing AI intake chatbots can enter clinical use without regulatory review, so their errors may first surface with actual patients. Objective: To develop and pilot a remote, voice-based standardized patient (SP) method for evaluating an intake chatbot's history-taking, documentation, and patient-centeredness. Methods: Four primary care cases had Easy and Difficult variants. In Phase 1, five SPs completed 40 encounters with internal medicine residents rating portrayal fidelity. In Phase 2, SPs completed 80 encounters with a ChatGPT 4o chatbot, recorded whether critical elements were asked about and addressed satisfactorily, and rated summaries; four debriefing interviews were analyzed. In Phase 3, two blinded clinicians rated transcripts and summaries from 101 encounters (32 resident-led, 69 chatbot-led). Results: Portrayal fidelity averaged 4.52 of 5. The chatbot asked about 59.3% of critical elements in Easy versus 50.2% in Difficult variants (adjusted OR 1.49; 95% CI, 1.15 to 1.93) and addressed 73.3% versus 64.6% (OR 1.47; 1.12 to 1.93); near-ceiling summary quality did not differ. SPs reported missed information and rushed pacing. Reviewer agreement was moderate to substantial for element judgments (AC1 0.49 to 0.70) but poor for totals (ICC 0.10 and 0.21). In exploratory comparisons, residents asked about more elements (adjusted difference 12.5 percentage points; 95% CI, 7.0 to 18.1) and satisfactorily addressed more (9.2 points; 3.8 to 14.6); totals did not differ. Conclusions: SP portrayal was consistent enough for pre-clinical chatbot evaluation, and the method detected lower coverage in harder cases. Documentation ratings alone may miss conversational gaps, which require direct measurement.

Background: Artificial intelligence (AI) is increasingly used in healthcare, but data on its real-world use and perceptions among obstetricians and gynecologists remain limited. Objectives: To assess familiarity, use, perceptions, and expectations regarding AI among physicians practicing obstetrics and gynecology in France. Study Design: We conducted a cross-sectional survey between June 2 and July 30, 2025, mainly distributed through professional organizations or associations and social media. Participation was voluntary and self-selected. AI use was defined as any use of an AI tool in routine clinical practice, regardless of type or frequency. Comparisons were made between AI users and non-users and between junior and senior physicians. Results: Among 469 respondents, representing approximately 5% of the target population, 199 of 466 (42.7%) reported AI use in practice; three respondents were excluded from this analysis because of discordant questionnaire responses. AI use was associated with male gender and professional status, with residents more represented among users. Junior physicians reported greater AI use than senior physicians and expressed greater concern regarding medical confidentiality. Current applications primarily involved administrative tasks, medical writing, literature retrieval, and translation; anticipated future uses centered on clinical decision support and medical data interpretation. Perceptions of several AI applications differed between groups. Conclusions: AI was reported to be used by a substantial proportion of respondents, primarily for supportive and informational tasks. These findings support further evaluation of training, validation, governance, and safe implementation of AI in obstetrics and gynecology.

Background: While critical care pharmacists (CCPs) are broadly associated with improvements in outcomes for critically ill patients, operationalizing staffing in the intensive care unit (ICU) requires further study. The purpose of this evaluation was to determine the relationship of a CCP on interprofessional rounds for weekday admissions of ICU patients on patient-centered outcomes. Methods: This post-hoc analysis of the Optimizing Pharmacist-Team Integration for ICU Patient Management (OPTIM) study included adults admitted to an ICU on a weekday in the multicenter observational study. The primary outcome was in-hospital mortality. The primary exposure was level of comprehensive medication management (CMM) during the first 24 hours of ICU stay. A secondary exposure was pharmacist-to-patient ratio. Multivariable generalized estimating equations (GEE) were used to estimate associations between mortality and patient, ICU, and institution variables. Fine-Gray sub-distribution hazards regression estimated hazard of discharge alive (HDA) from the ICU and hospital and hazard of extubation alive. Results: 21,835 patients met inclusion criteria, and 76.1% of patients had CMM delivered on interprofessional rounds. Patients who had no CMM on the first ICU day had an increased risk of mortality of 23% (Odds Ratio (OR) 1.23, 95% Confidence Interval (CI) 1.04-1.46, p=0.02) compared to those who received CMM on interprofessional rounds. Patients with no CMM also had decreased HDA from the ICU and hospital and decreased hazard of extubation alive. No difference was seen in any outcomes when comparing other levels of CMM (CMM delivered outside of interprofessional rounds or abbreviated CMM) compared to CMM delivered on rounds. Conclusions: Absence of pharmacist CMM on the first day of ICU stay for patients with weekday admission was associated with an increased risk of in-hospital mortality, but no difference was seen in other levels of CMM: this signal supports further investigation in prospective analysis.

Objective: To perform internal and external validation of a gradient-boosted decision tree (GBDT) fusion model that integrates zygote morphokinetic parameters with conventional embryo assessment features for blastocyst prediction, and to compare its discriminative performance against senior embryologists. Methods: This retrospective cohort study included 631 normally fertilized zygotes from 218 treatment cycles. A GBDT fusion model integrating 84 zygote morphokinetic parameters and 8 conventional assessment features was evaluated internally (5-fold cross-validation) and externally on a public dataset of 523 embryos with blastocyst outcomes. Model performance was assessed using area under the ROC curve (AUC), area under the precision-recall curve (AUPRC), F1 score, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Discrimination was compared with embryologist consensus using the DeLong test; agreement was assessed with Cohen's kappa. Results: The model achieved an internal AUC of 0.78 (95% CI 0.74-0.82), AUPRC 0.72, F1 0.73, sensitivity 0.74, specificity 0.77, PPV 0.72, and NPV 0.79. External validation on the public dataset demonstrated acceptable generalizability (AUC 0.76, 95% CI 0.71-0.81). The model significantly outperformed embryologist consensus (AUC 0.70, P<0.001) with moderate agreement (kappa=0.56). Decision curve analysis confirmed clinical net benefit at threshold probabilities of 0.15-0.55. Conclusions: The GBDT fusion model integrating zygote morphokinetics with conventional assessment demonstrates good discrimination and external generalizability for blastocyst prediction, providing an interpretable decision-support tool for embryo selection in IVF practice.