Journal of Clinical Pathology

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.

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.

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.

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: Pregnancy is a uniquely complex ethical and clinical context in which precision medicine approaches, including genomics-driven risk prediction tools, biomarker-based stratification, and data-intensive analytics, are rapidly evolving. There is a need for community consultation on the ethical, social, and practical implications of precision medicine in pregnancy research and healthcare. Aim: The primary aim of this study was to engage healthcare consumers to build consensus on the acceptability of precision medicine approaches in pregnancy research and healthcare. We also sought to identify consumer priorities for future research. Methods: A two-round modified Delphi study was conducted to determine consumer opinions on the use of precision medicine approaches in pregnancy research and healthcare. Seven in-person workshops (round one) were held, with purposeful recruitment to ensure a representative group of healthcare consumers who engage with the healthcare system during pregnancy. These included first-time parents, culturally and linguistically diverse women, Aboriginal and Torres Strait Islander women, and women and their partners who had experienced previous pregnancy complications. Recruitment was conducted through established advocacy networks, and each workshop was facilitated by representatives from each organization. A second-round online survey, based on workshop content, was completed to assess the acceptability of precision medicine and to determine consumer priorities for future precision medicine research on pregnancy health. Results: Precision medicine research and the implementation of new technologies in clinical care were acceptable to participants; however, the need for transparency and trust between participants and researchers regarding the use and storage of genetic material was highlighted, particularly among Aboriginal and culturally and linguistically diverse participants. Outcomes related to survival and perinatal complications (stillbirth, preterm birth, and labor complications) were the highest-rated consumer research priorities, along with maternal mental health and breastfeeding. When asked whether participants would like to see PM available as part of routine pregnancy care for conditions with available treatments, complete consensus (100%) was reached. Conclusion: Healthcare consumers strongly support the use of precision medicine in pregnancy research and its translation into routine clinical care, particularly when effective interventions are available. However, implementation must be underpinned by transparency, trust, culturally appropriate governance, and clear communication about the collection, storage, and use of genetic material. These findings provide a consumer-informed framework for prioritizing future precision medicine research and guiding its responsible translation into pregnancy care.

Background: Murine models are widely used to investigate cardiovascular disease (CVD), yet many established models rely on invasive surgery or genetic manipulation to induce hyperlipidemia and therefore may not fully capture the gradual cardiovascular consequences of mutant hematopoiesis. Tie2-Cre/-FF1/- (Tie2FF1) mice express JAK2V617F mutation in both hematopoietic and endothelial cells and develop spontaneous CVD on a standard chow diet. Methods: We applied a comprehensive, non-invasive cardiovascular phenotyping protocol to 1-year-old Tie2FF1 mice and age-matched controls. Assessments included transthoracic echocardiography, coronary flow reserve by Doppler ultrasound, quantitative analysis of coronary arteriolar structure and perivascular fibrosis, endocardial histology and subendocardial collagen deposition, and histologic evaluation of pulmonary and hepatic congestion. Results: Tie2FF1 mice demonstrated left ventricular dilation, increased cardiac mass, and mildly reduced systolic function without obstructive epicardial coronary disease. Coronary microvascular remodeling was evident by arteriolar narrowing and increased perivascular fibrosis, while coronary flow reserve was markedly reduced in an exploratory cohort. Endocardial endothelial disruption and increased subendocardial fibrosis were also observed. In addition, Tie2FF1 mice showed increased lung and liver weights, pulmonary fluid accumulation, alveolar septal thickening, pulmonary vascular fibrosis, hepatic sinusoidal dilatation, and centrilobular hepatocyte swelling, providing objective evidence of clinically relevant heart failure. Significance: These findings establish Tie2FF1 mice as a spontaneous, non-invasive model with features of coronary microvascular and endocardial endothelial dysfunction and heart failure with mildly reduced left ventricular ejection fraction. The integrated approach described here provides a practical framework for comprehensive murine cardiovascular phenotyping beyond traditional atherosclerosis- and surgery-based models.

Background: Pre-operative triage of adnexal masses with serum CA-125, HE4, and ultrasound (O-RADS) has limited accuracy, contributing to unnecessary surgery. We develop and validate a first of its kind, biomarker panel-free plasma proteomic classifier that distinguishes malignant from benign adnexal masses from a single blood draw, operating directly on discovery-mode mass spectrometry. Methods: In this multicenter prospective observational study, plasma from women with adnexal masses and from healthy controls at a large urban academic center (discovery and four validation cohorts) and an external academic center from another Urban-suburban area (external validation) was analyzed by data-independent-acquisition mass spectrometry (Orbitrap Astral), quantifying >1,000 proteins per sample. Cancerous (malignant, borderline adnexal mass, or metastasis to ovary) versus benign adnexal masses were classified with ADAPT-MS (Adaptive Diagnostic Architecture for Personalized Testing by Mass Spectrometry), which retrains an ElasticNet model for each sample based on the proteins measured. The primary outcome was discrimination (area under the receiver operating characteristic curve [AUC]). Pre-operative O-RADS scores and serum CA-125 were compared and combined with proteomics on matched subsets. Findings: Using a discovery cohort (n=1062), an ADAPT-MS classifier, validated across five independent cohorts (n=623), achieved a summary AUC of 0.835 (cohort range 0.779-0.904). Among patients with pre-operative O-RADS (n=231), proteomics (AUC 0.852) was comparable to O-RADS alone (0.863) and combining them raised discrimination to 0.922. Proteomics outperformed serum CA-125 (0.915 versus 0.777; n=125) and proteome-derived ROMA-like and two-marker surrogates. Biologically, the classification-relevant proteins are enriched for host response proteins rather than tumor cell associated protein changes, comprising ECM remodeling, complement and innate immune response pathways. This explains good detection of tumor with heterogenous pathology and also metastasis to ovary. Interpretation: A single plasma proteomic measurement interpreted using adaptive machine learning discriminates malignant from benign adnexal masses with good internal and external validation, and is complementary to ultrasound, warranting prospective evaluation as a panel-free diagnostic adjunct to imaging.

Background: The Greater Manchester Care Record (GMCR) integrates health and social care data for 2.8 million individuals. While it contains maternity information, identifying individual pregnancies, including timing and outcomes, is complex due to variations in healthcare interactions and recording practices. This study develops open-source code to create a pregnancy register within the GMCR using diagnosis- and procedure-based algorithm established in other databases. Methods: 1,448 maternity SNOMED clinical codes identified pregnancy-related primary care records among women aged 14-49 years between March 2012 and August 2023. Codes were grouped by pregnancy outcome, with a hierarchical ruling approach where multiple outcomes appeared within one episode. Pregnancy start dates were derived from hierarchical coded events or imputed using biologically plausible duration based on outcome type. Internal validation compared GMCR register episodes against Hospital Episode Statistics (HES) hospital maternity admissions; external validation compared outcome rates against published UK estimates. Results: The algorithm was developed across 379,832 women, identifying 880,926 pregnancies. Internal validation showed nearly half of register deliveries had a corresponding HES record, with a positive predictive value (PPV) of 48.1%and a median date difference of 17 days (IQR 1-30). External comparison revealed live birth (927.8 vs. 995.6 per 1,000 deliveries) and stillbirth (2.12 vs. 3.9 per 1,000 births) rates close to national estimates but a notable discrepancy for miscarriage (8.00 vs. 15.3 per 100 pregnancies) and termination of pregnancy (5.36 vs. 25.1 per 1,000 women). Demographic alignment was strong for maternal age (31 vs. 29.8 years) and deprivation (IMD10 median: 3 vs. 2.6), though ethnic minority representation was expectedly higher in the GMCR (37.0% vs. 28.7%). Conclusions: This pregnancy register enriches the GMCR for maternal health research, enabling more comprehensive and regionally tailored studies to inform healthcare delivery and policy. This work represents an important first step in developing a scalable, open-source algorithmic tool to support pregnancy research across diverse populations. By making the code openly available, it can be adapted for use in federated data environments, enhancing reproducibility and collaboration.

Background: Clinical registries and institutional quality control (QC) in pathology heavily depend on complex histopathological data. However, critical tumor characteristics are mostly locked in unstructured free-text reports. We hypothesize that locally deployed, resource-efficient language models operating within a secure institutional network can reliably extract relevant variables from German reports of hepatocellular carcinoma (HCC), thereby enabling automated data curation without transferring sensitive patient data. Methods: We developed a local, privacy-preserving open-weight Large Language Model (LLM) pipeline consisting of two consecutive stages: Stage 1 utilizes a lightweight gatekeeper model to isolate the target cohort of confirmed Hepatocellular Carcinoma cases from a screening pool of N = 2,864 reports. Stage 2 deploys a high-capacity model to extract 15 predefined histopathological variables, including tumor-node-metastasis staging, histological grading, vascular invasion, and selected immunohistochemical features into structured JSON format. For both Stages, pipeline performance was evaluated using Accuracy, Macro F1-scores, and Cohen's kappa compared to expert-curated reference annotations. Results: The top-performing Stage 1 gatekeeper isolated the target patient cohort with zero classification errors, effectively reaching complete agreement with the reference standard (ground truth) and correcting inaccurate administrative metadata. For Stage 2 feature extraction, current-generation models demonstrated robust structural reliability, reducing the burden of manual post-processing. The 31B model configuration (Gemma 4) virtually eliminated objective factual errors, achieving near-perfect agreement with the reference standard (Macro F1 > 0.99). Conclusion: Local two-stage pipelines offer a highly accurate, resource-efficient, and secure solution for clinical text processing. This framework serves as a privacy-preserving engine for institutional quality control and the scalable curation of pathology registries.

Background: Pharmacogenomic point-of-care testing (PGx POCT) enables genotype-informed prescribing at the bedside, but implementation is limited by the lack of suitable reference materials and standardised external quality assessment (EQA). Methods: Fixed lymphoblastoid cell lines were formulated as swab-based materials at defined cellular inputs for MTRNR1 POCT. Materials were evaluated using Genedrive MTRNR1 assays, quantitative PCR, acceptance quality limit batch release, workflow perturbation testing and stability studies, then deployed in an international EQA programme. Results: Materials were homogeneous, workflow-compatible and reproducible, with 100% correct genotype calls at the lowest intended manufacturing cell load. Seven EQA surveys yielded 253 participant results, with full-mark rates between 87.5 and 100%, and six test failures. Most failures occurred with low cell-input materials near the assay limit of detection. The materials supported genotype concordance, performance monitoring and identification of workflow and sample-related variability. Conclusions: Workflow-compatible cell-based reference materials combined with EQA provide a scalable framework for quality-assured PGx POCT beyond specialist laboratories. International MT-RNR1 PGx POCT EQA programme deployment demonstrated feasibility in decentralised settings. The framework may provide a model for the implementation, verification and ongoing quality assessment of PGx POCT. Further evaluation across platforms, analytes, settings and participant groups is required to establish broader applicability.

Obstetric anal sphincter injury (OASI) requires immediate postpartum recognition for primary repair. Diagnosis relies primarily on clinical examination, as endoanal ultrasound (EAUS) is rarely a bedside option. Therefore, objective diagnostic assessment is most needed during the first postpartum hours. However, it is challenging to obtain the anatomically verified data needed to develop diagnostic technologies for this clinical window. We evaluated the translation of a machine-learning-assisted impedance spectroscopy model into its intended immediate postpartum setting. The model lifecycle comprised three sequential phases: V1 development using anatomically verified data from a prospective multicenter study (N=152); V2 real-world adaptation, comprising post-market data collection, retraining (N=144) to adapt to acute physiological tissue changes, and subsequent separate evaluation (N=125); and prospective external validation of V2 in an unseen cohort (N=70). During this separate evaluation, V2 achieved 89.6% accuracy. In external validation, all examinations occurred within 4 hours of birth (94.3% within the first hour). Against subsequent EAUS, V2 achieved 86.2% sensitivity, 92.7% specificity, and 90.0% overall accuracy. The V2 model was prospectively externally validated in its intended immediate-postpartum setting, supporting ML-assisted impedance spectroscopy as an objective adjunct, and not a replacement, to clinical OASI assessment. Further validation is required to confirm generalizability.

BACKGROUND Twin pregnancies have a two- to three-fold higher risk of preeclampsia (PE), but early prediction remains poor because current biomarkers and prediction models are largely derived from singleton pregnancies. Defining the biological changes that precede PE in twins may facilitate the development of more effective risk assessment approaches. OBJECTIVE We aimed to characterize maternal plasma protein changes preceding PE in twin pregnancies and to explore whether early circulating proteins could serve as improved risk stratification for twin PE. STUDY DESIGN We performed a nested case-control study within a prospective twin pregnancy cohort at Peking University Third Hospital. A total of 84 women with twin pregnancies were included, comprising 40 pregnancies complicated by PE and 44 normotensive controls. Longitudinal maternal plasma samples were collected in the first, second, and third trimesters. In the discovery cohort, maternal plasma proteins were profiled by mass spectrometry to identify trimester-specific protein changes associated with PE. Candidate proteins were then validated in an independent validation set. We further assessed the functional relevance of selected proteins in trophoblast and endothelial cell models and constructed prediction models integrating biomarkers with maternal clinical characteristics. RESULTS Twin pregnancies complicated by PE showed distinct trimester-dependent protein alterations, with first- and second-trimester changes mainly involving immune regulation and glycolipid metabolism, and later changes enriched in cardiovascular-related pathways. Several proteins demonstrated early discriminatory patterns, including increased annexin A3, chitotriosidase-1, and ferritin light chain (FTL), together with decreased annexin A2 in the first trimester, whereas the conventional singleton markers (sFlt-1 and PAPP-A) did not differ. ELISA validation of these candidate biomarkers yielded an AUC of 0.93 for twin preeclampsia prediction; integration with standard maternal clinical factors further improved discriminatory performance to an AUC of 0.97. Accordingly, a multivariable model combining annexin A2, annexin A3, chitotriosidase-1, FTL, and maternal clinical factors achieved strong internal performance for early discrimination of PE in twin pregnancies (AUC, 0.97; 95% CI, 0.93-1.00). Moreover, annexin A2 knockdown impaired trophoblast migration and invasion and reduced inflammatory cytokine secretion in endothelial cells, supporting a role in placental development and maternal vascular adaptation. CONCLUSION Twin pregnancies that later develop PE exhibit early and progressive maternal plasma protein alterations that can be detected before clinical disease onset. These findings identify candidate biomarkers and biologically relevant pathways that may help explain why PE in twins differs from singleton disease and may support future twin-specific risk stratification strategies. These results require external validation before clinical application.

Objective: To test the hypothesis that selected SIRS and SOFA criteria measured at ICU admission have divergent associations with (1) the development of new culture-confirmed infections and (2) early empiric broad-spectrum antibiotic receipt in critically ill patients with cirrhosis. Design: Retrospective, observational study using electronic health record (EHR) data. Setting: Both community and academic ICUs within a five-hospital health system between July 2017 and December 2025. Subjects: Adult patients >18 years of age diagnosed with cirrhosis admitted to the ICU within 96 hours of hospital admission. Patients transferred from outside facilities and those with positive cultures collected >24 hours before ICU admission were excluded. Interventions: None. Measurements: Multivariable logistic regression tested the association of the most aberrant values in nine SIRS/SOFA vital sign and laboratory parameters measured during the 24 hours prior to ICU admission with (1) the development a newly positive culture collected during the 24 hours before through the 96 hours after ICU admission and (2) receipt of broad-spectrum antibiotics during the 24 hours before through the 24 hours after ICU admission. Main Results: The presence of hyperthermia, hypothermia, hypoxia, or hypotension at ICU admission was associated with both culture positivity and antibiotic receipt. The presence of leukocytosis was associated with antibiotic receipt but not culture positivity. Among patients in the 21.6% of encounters with newly positive cultures, normothermia and normal WBC were common (respectively present in 97.2% and 77.5% of encounters) and associated with antibiotic omission at ICU admission despite the subsequent development culture positivity. Conclusions: Traditional physiologic markers of infection are often absent in critically ill patients with cirrhosis who develop new culture-confirmed infections at ICU admission, possibly contributing to delayed antibiotics. There may be opportunities to improve antibiotic delivery and stewardship at ICU admission in this high-risk population.

Funding and publishing scientific research has become increasingly competitive, highlighting a growing need for clear and accurate scientific communication. Scientific editors are professionals who help ensure that grant proposals and research manuscripts meet the standards of funding agencies and peer-reviewed journals while effectively communicating research significance to diverse audiences. However, detailed information characterizing the scientific editing profession is scarce. While some organizations have conducted salary surveys, to our knowledge, no comprehensive survey of the scientific editing field has been conducted. Here, we report findings from a 2024 comprehensive survey of 132 scientific editors. We collected data on demographics and education, career experience and current employment, skills and types of editing, and outcomes and satisfaction. Our data reveal that scientific editors have homogenous demographic characteristics but considerable variability in job titles, employment mechanisms, and career pathways. As the responsibilities of many scientific editors, including supporting proposal development, applying best practices in grantsmanship, and identifying strategies to enhance competitiveness for research funding, overlap with those of research development professionals, our findings provide considerations for further incorporating or defining the role of scientific editors within research development offices. Our results also suggest avenues for scientific editors to start or advance their careers. We anticipate that our results will serve as a foundation for discussions on the future directions of the scientific editing profession as well as areas for future research and professional development.

Background Despite being originally developed to support labour monitoring in low-resource and rural settings, the partograph has remained the standard tool for labour management and continues to be used by obstetricians and midwives across diverse settings worldwide. However, inappropriate use and non-use of the partograph persist and have been associated with increased odds of adverse perinatal outcomes, including perinatal death. To address these limitations, the World Health Organization introduced the Labour Care Guide in 2020 as a comprehensive tool to standardise and improve the quality of care during childbirth. Henceforth, some countries such as Rwanda and Uganda have since implemented its use. This study aimed to assess the effect of WHO Labour Care Guide implementation, compared with the traditional partograph, on selected maternal and perinatal outcomes across participating facilities. Methods This was a quasi-experimental implementation study conducted in selected referral hospitals in Zambia, comparing maternal and perinatal outcomes before and after implementation of the WHO Labour Care Guide. Facilities were grouped into implementation and comparison sites. Routine HMIS/DHIS2 data were used to assess selected outcomes across the pre- and post-implementation periods. Descriptive statistics were used to summarise outcome trends, while a difference-in-differences analytical approach was applied using Stata version 18 to compare changes over time between implementation and comparison sites. Results The analysis included 12 hospitals, 192 facility-month observations, 89,122 total births, and 87,004 live births. Overall, the stillbirth rate was 23.8 per 1,000 total births, birth asphyxia rate was 40.1 per 1,000 live births, caesarean section rate was 34.6 per 100 live births, low-birthweight rate was 168.6 per 1,000 live births, and maternal mortality ratio was 313.8 per 100,000 live births. The implementation sites reporting higher birth asphyxia rates (42.7 versus 38.0 per 1,000 live births). Difference-in-differences analysis showed no statistically significant effect of LCG implementation on stillbirths, IRR 1.07 (95% CI: 0.69-1.67, p=0.752); fresh stillbirths, IRR 1.23 (95% CI: 0.74-2.05, p=0.431); birth asphyxia, IRR 0.65 (95% CI: 0.34-1.27, p=0.207); or caesarean section, IRR 1.02 (95% CI: 0.80-1.30, p=0.892). Conclusion Implementation of the WHO Labour Care Guide was not associated with statistically significant changes in stillbirths, fresh stillbirths, birth asphyxia, or caesarean section rates during the study period. Despite the higher birth asphyxia rates in the implementation sites the difference remained statistically not significant. Scale-up of the LCG should be accompanied by sustained training, mentorship, audit and feedback, and strengthening of emergency obstetric and newborn care systems.

Background Implantable loop recorders (ILRs) provide continuous rhythm monitoring. Professional society guidelines and expert consensus statements recommend ILR use for patients with recurrent syncope and cryptogenic stroke, but recommendations are weaker for other indications. We assessed ILR use over time and concordance between indication and clinical guidance. Methods We conducted a retrospective cohort study using Epic Cosmos data from 1/1/2020-12/31/2025. Among active patients with at least one of 13 diagnoses potentially eligible for ILR placement, we identified ILR placements and classified them by concordance with professional society guidance: concordant, possibly, or non-addressed. Annual incidence was estimated overall and by indication. We also described the proportion of patients who received longer-term (>7 days) rhythm monitoring in the year prior to placement. Results Of 47,046,706 patients with diagnoses potentially eligible for ILR placement, 201,103 (0.4%) had an ILR placed. ILR placements increased from 3.08 ILRs per 100,000 patient-days in 2020 to 4.13 in 2025 (5.9% annual growth). The most common indications were cryptogenic stroke (28.6%) and atrial fibrillation without prior ablation (21.4%). Overall, 43.9% were guidance concordant, 28.5% possibly concordant, and 24.8% non-addressed. Relative annual growth in ILR placements per 100,000 patient-days was significant across all guidance categories: concordant (1.3%, 95% CI, 0.9%-1.7%), possibly concordant (5.5%, 95% CI, 5.0%-6.0%) and non-addressed (7.4%, 95% CI, 6.8%-8.0%). Among 125,631 outpatient placements, 50,181 (39.9%) had any prior long-term rhythm monitoring. Conclusion ILR placements are uncommon but increasing, with faster annual growth for indications that may not be guidance concordant. More than half of patients lacked long-term rhythm monitoring prior to outpatient ILR placement.