Yellow fever is a long-standing zoonotic arboviral disease that affects hundreds of thousands of people annually in different regions of the world, even though the vaccine has been available since the 1930s. Thus, studies that synthesize general and current information on yellow fever are relevant, aiming to disseminate knowledge that can contribute to mitigating its impacts. This narrative review synthesizes the general aspects of yellow fever, discusses its impacts on public health, and presents information on the use of the One Health approach in the context of this zoonosis. The databases used to select the articles were PubMed, Scopus, LILACS, and SciELO, using various descriptors related to the study's theme and objectives. It is important to highlight that yellow fever remains a significant public health challenge due to its high mortality rate in severe cases and the continued circulation of the yellow fever virus in tropical areas, especially in South America and Africa. Although many patients recover spontaneously, recurrent outbreaks continue in endemic regions. The initial clinical similarity to other zoonoses makes timely diagnosis difficult, and management remains restricted to clinical support, as there is no specific antiviral treatment. Vaccination and epidemiological surveillance stand out as the main preventive measures. Additionally, considering that the management of yellow fever involves human, animal, and environmental health aspects, the One Health approach stands out as a modern, robust, and effective alternative for addressing this zoonosis. However, the lack of knowledge regarding this approach among public managers and health professionals results in its non-use and, consequently, impacts the fight against yellow fever. Therefore, it is important to widely disseminate knowledge about the One Health approach, aiming at carrying out holistic actions in the human-animal-environmental interface sectors in the context of yellow fever, allowing for coordinated and sustainable responses at different levels and instances.
Bundibugyo ebolavirus (BDBV) is one of the least studied species within the genus Orthoebolavirus (family Filoviridae), despite its capacity to cause severe Ebola virus disease (EVD) with substantial mortality. First identified during a 2007-2008 outbreak in Bundibugyo District, western Uganda (149 reported cases, 37 deaths; case-fatality rate [CFR] approximately 25-36%), BDBV re-emerged in 2012 in Orientale Province, Democratic Republic of the Congo (DRC) (57-59 cases, 29-34 deaths; CFR 34-58%), before resurfacing in Ituri Province, DRC, in April-May 2026. By 11 August 2026, this third outbreak had grown to 4566 laboratory-confirmed cases and 2128 deaths (CFR ≈ 47%) across five DRC provinces and Uganda, becoming the largest, fastest-growing BDBV epidemic on record and the second-largest Ebola-family outbreak overall. This narrative review, not a systematic review or meta-analysis, summarizes peer-reviewed literature, preprints, and official situation reports from WHO, Africa CDC, US CDC, ECDC, and national health ministries, identified through PubMed, Scopus, Web of Science, Google Scholar, and Embase from inception to 12 August 2026, to examine BDBV historical evolution, virology and pathogenesis, drivers of re-emergence, surveillance and response, therapeutic and vaccine gaps, and global health security implications. The 2026 outbreak, unfolding amid conflict and mass displacement in eastern DRC, has been marked by an estimated basic reproduction number of 1.4-2.1 (central estimate 1.71), disproportionate infection among healthcare workers (7.2% of confirmed cases in DRC, 20% in Uganda), and the continued absence of licensed BDBV-specific vaccines or therapeutics. Findings underscore the need for sustained genomic and ecological surveillance, decentralized rapid diagnostics, broadly protective pan-filovirus vaccines, conflict-sensitive response strategies, and strengthened Uganda-DRC collaboration. Because the evidence base for the ongoing outbreak remains preliminary, findings should be interpreted cautiously and revisited as further peer-reviewed data emerge.
Objective:To retrieve, appraise, and synthesize the best available evidence on the prevention of ventilator-associated pneumonia (VAP) from Chinese and international sources, and to provide evidence-based guidance for clinical nursing practice. Methods:Guided by the 6S evidence pyramid model, a comprehensive electronic search was conducted in BMJ Best Practice, UpToDate, the Guidelines International Network, the National Institute for Health and Care Excellence, the Scottish Intercollegiate Guidelines Network, the Registered Nurses' Association of Ontario, the American Association for Respiratory Care, the American Thoracic Society, CHEST, the Cochrane Library, the IBI Evidence-Based Health Care Center database, Embase, PubMed, Medlive, the Chinese Thoracic Society, the Chinese Biomedical Literature Database, China National Knowledge Infrastructure, and Wanfang Database. The search period ranged from January 1, 2016, to January 1, 2026. Evidence summaries, clinical practice guidelines, systematic reviews, and other evidence-based resources related to VAP prevention were retrieved. After quality appraisal and evidence synthesis, the best evidence was summarized. Results:A total of 24 publications were included, comprising 2 clinical decision support resources, 10 systematic reviews, 5 guidelines, and 7 evidence summaries. Thirty-three recommendations were synthesized into eight practical domains covering organizational strategies, prevention bundles, airway management, positioning, nutrition, device management, pharmacologic approaches, and non-recommended interventions. Conclusion:This evidence summary systematically synthesizes the best available evidence regarding VAP prevention and provides evidence-based guidance for standardized clinical management. These findings may support clinical decision-making and the development of nursing practice strategies for VAP prevention; however, further studies are needed to evaluate the effectiveness of implementing these recommendations in specific clinical settings.
Indications for repeat biopsy after an initial negative prostate biopsy remain poorly defined. Therefore, this study aimed to investigate the effectiveness of the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) scoring system as a guide for repeat biopsy. We retrospectively reviewed patients who underwent repeat prostate biopsy and had bpMRI performed before both biopsies between 2013 and 2024. The association of clinically significant prostate cancer (csPCa) detection with initial Prostate Imaging Reporting and Data System (PI-RADS) and PRECISE scores was analyzed. The predictive effects of prostate-specific antigen density before repeat biopsy (re-PSAD) and PSA velocity (PSAV) on csPCa were assessed in patients progressing to or maintaining re-PI-RADS 3. 104 individuals were included with a median follow-up period of 28.58 months and a PSAV of 0.90 ng/mL/year (interquartile range (IQR), −0.17 to 2.57 ng/mL/year). The csPCa detection rate at repeat biopsy was 24.0
Morganella morganii (M. morganii), a member of the Enterobacteriaceae family, and a constituent of the human gut microbiota, has recently emerged as a candidate microbial contributor to the development of adenomatous polyps (AP) and promoting colorectal carcinogenesis. The present study is a narrative review compiled to evaluate the role of M. morganii in the development and progression of AP and colorectal cancer (CRC). A comprehensive literature search was conducted using Google Scholar and PubMed/Medline (2020-2026) using keywords related to the gut microbiota, M. morganii, and its impact on CRC and intestinal polyps. The ability of M. morganii to produce a specific type of genotoxin, indolimine, is a distinguishing feature of this bacterium compared to other intestinal bacteria. Because its production is independent of the pks gene cluster and the clbI and clbP genes, it exhibits a different damage pattern, namely, DNA smearing. According to reports from previous studies, strains lacking the aat gene exhibited no detectable genotoxic activity, supporting the role of aat in genotoxicity. Available data from in vitro experiments, animal models, a limited number of human observational studies, and findings from research groups suggest that M. morganii may, through the production of a highly potent genotoxin, be associated with distinct genetic damage, metabolic changes, and facilitation of polyp growth, and contribute to the development and acceleration of CRC. These findings establish a new theoretical framework in which CRC is not simply caused by gut microbiota dysbiosis, but rather reflects the activation of genotoxic bacteria and their functional interaction within the intestinal epithelial microenvironment. Nevertheless, owing to the scarcity of longitudinal human studies, it cannot yet be conclusively established whether M. morganii plays a predisposing, an initiating, or merely a consequential role in the development of CRC. Larger human studies investigating the association between M. morganii colonization and CRC development are essential for understanding the causal relationship.
Background:Sepsis is characterized by complex immune dysregulation involving innate immune activation, myeloid stress, and adaptive immune exhaustion. Conventional severity scores mainly reflect organ dysfunction and may not fully capture immune heterogeneity. This study aimed to develop and internally validate an immune-based model for predicting 28-day mortality in sepsis. Methods:This prospective cohort study included 695 participants, including 263 patients with sepsis, 160 infection non-sepsis patients, 152 non-infection critically ill patients, and 120 healthy controls. Immune biomarkers, including neutrophil CD64, heparin-binding protein (HBP), membrane-bound neutrophil alkaline phosphatase (mNAP), and PD-1⁺CD4⁺ T cells, were measured within 6 hours of ICU admission. A mortality prediction model was developed exclusively in the sepsis cohort using LASSO logistic regression and multivariable logistic regression. The model was internally validated using bootstrap resampling, Model performance was assessed using discrimination, calibration, decision curve analysis, and bootstrap internal validation. Results:Sepsis patients exhibited significantly higher levels of CD64, HBP, mNAP, and PD-1⁺CD4⁺ T cells than infection non-sepsis patients, non-infection critically ill patients, and healthy controls. Among 263 sepsis patients, 56 died within 28 days. LASSO identified five predictors: CD64, HBP, mNAP, PD-1⁺CD4⁺ T cells, and SOFA score. The combined SOFA-integrated immune model achieved an apparent AUC of 0.930 and a bootstrap-corrected AUC of 0.918, with good calibration. Conclusion:The proposed model provides an exploratory, internally validated framework for 28-day mortality risk stratification in sepsis and requires external validation before clinical application.
Objective:To develop and temporally validate an admission-variable model for estimating the risk of persistent inflammation-immunosuppression-catabolism syndrome (PICS) among patients with sepsis who remained in the intensive care unit (ICU) for ≥14 days. Methods:We conducted an ambispective, single-center cohort study. The retrospective development cohort included patients admitted from January 2023 to May 2025, and the prospective temporal validation cohort included patients admitted from June 2025 to February 2026. Candidate predictors measured at ICU admission were selected using least absolute shrinkage and selection operator (LASSO) regression and entered into a multivariable logistic regression model. Discrimination, calibration, and potential clinical utility were evaluated using the area under the receiver operating characteristic curve (AUC), calibration analyses, and decision curve analysis. Results:The development cohort included 242 patients, of whom 93 (38.4%) met the PICS criteria. Compared with respiratory infection, urinary infection (adjusted odds ratio (aOR 0.07, 95% CI 0.01-0.67), gastrointestinal infection (aOR 0.15, 95% CI 0.05-0.45), and skin or soft-tissue infection (aOR 0.29, 95% CI 0.11-0.77) were associated with lower odds of PICS. Higher lactate was associated with higher odds of PICS (aOR 1.20, 95% CI 1.07-1.34), whereas higher lymphocyte count (aOR 0.46, 95% CI 0.28-0.77), albumin (aOR 0.92, 95% CI 0.86-0.99), and vitamin D (aOR 0.88, 95% CI 0.83-0.94) were associated with lower odds. The AUC was 0.803 (95% CI 0.747-0.859) in the development cohort and 0.791 (95% CI 0.718-0.864) in the temporal validation cohort. Conclusion:Among patients with sepsis who remained in the ICU for ≥14 days, an admission-variable model showed acceptable discrimination in the development and temporal validation cohorts. External multicenter validation and prospective impact evaluation are required before clinical use.
Background:Ciprofloxacin resistance among Gram-negative bacteria causing osteomyelitis is an emerging clinical concern that may negatively influence disease severity and patient outcomes. This study sought to assess the burden, independent predictors, and clinical impact of ciprofloxacin resistance in acute Gram-negative osteomyelitis. Methods:A retrospective analysis was performed on patients with acute Gram-negative osteomyelitis between 2019-2024. Clinical, microbiological, laboratory, and outcome variables were compared between ciprofloxacin-resistant and susceptible cohorts. Univariable binary logistic regression analyses were performed to identify factors associated with ciprofloxacin resistance, followed by multivariable binary logistic regression analysis to identify independent predictors. Statistical significance was considered at p-value <0.05 (two-tailed). Results:Antimicrobial resistance patterns were assessed among 279 Gram-negative isolates, while clinical and outcome analyses were conducted among 256 patients. The overall prevalence of ciprofloxacin resistance was 54.5% among Gram-negative isolates. In the univariable binary logistic regression analysis, ciprofloxacin resistance was significantly associated with chronic heart disease (p = 0.03), lower hemoglobin concentration (p = 0.04), hypoalbuminemia (p = 0.0001), and increased inflammatory biomarkers, including c-reactive protein (CRP; p = 0.001), and neutrophil-to-lymphocyte ratio (NLR; p = 0.04). Osteomyelitis caused by ESBL-producing pathogens was also significantly associated with ciprofloxacin resistance (OR = 3.93, 95% CI: 1.87-8.31; p = 0.0001). In the multivariable analysis, hypoalbuminemia (adjusted odds ratio [AOR] = 0.53, 95% confidence interval [CI]: 0.35-0.79; p = 0.002) and infection with ESBL-producing pathogens (AOR = 0.25, 95% CI: 0.11-0.54; p = 0.0001) remained independently associated with ciprofloxacin resistance. Compared with ciprofloxacin-susceptible cohort, ciprofloxacin-resistant patients required significantly more surgical debridement (p = 0.006) and developed higher rates of chronic osteomyelitis (p = 0.005), septic shock (p = 0.03), and in-hospital mortality (p = 0.02). Conclusion:Ciprofloxacin resistance was prevalent among Gram-negative osteomyelitis cases and was associated with greater surgical complexity and poorer clinical outcomes. Early identification of ciprofloxacin-resistant infections and integration of clinical and inflammatory markers may support risk stratification and therapeutic decision-making. Given the retrospective, observational, single-center design, these findings should be interpreted cautiously and validated in larger multicenter studies.
Purpose:Diagnosing tuberculous osteoarticular infections (TB-OAI) remains challenging due to frequent false-negative or confounding conventional culture results. This study evaluated the diagnostic and therapeutic utility of metagenomic next-generation sequencing (mNGS) for occult TB-OAI in patients presenting with negative or misleading culture outcomes. Patients and Methods:We retrospectively analyzed 13 patients with confirmed TB-OAI, encompassing periprosthetic, fracture-related, and native joint infections. Patients were stratified by conventional culture results into strictly culture-negative (n=8) and culture-confounded (n=5; yielding non-mycobacterial organisms) groups. A composite reference standard of mNGS positivity combined with histopathological or clinical validation established the definitive diagnosis. We assessed diagnostic yield, therapeutic modifications, and clinical outcomes. Results:Conventional culture failed to identify Mycobacterium tuberculosis in all 13 cases (0% sensitivity) and yielded misleading non-mycobacterial flora in 5 cases (38.5%). Conversely, mNGS successfully identified the pathogen in 100% (13/13) of patients, corroborated by histopathology in all cases. Consequently, mNGS results changed clinical management from empirical antibiotics to targeted anti-tuberculosis therapy in all cases (100%). Postoperative erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) levels decreased significantly (P < 0.05). Over a mean follow-up of 17.5 ± 3.0 months, 12 patients achieved durable infection eradication. One patient experienced early recurrence requiring a two-stage revision, ultimately achieving successful infection control. Conclusion:mNGS serves as a promising diagnostic rescue tool for occult TB-OAI when conventional cultures are negative or misleading. While limited by sample size, these preliminary findings suggest mNGS effectively guides the transition from empirical to targeted anti-tuberculosis therapy and limits diagnostic delays.
The relationship between systemic inflammation, plaque vulnerability, and stroke phenotypes in intracranial atherosclerotic stenosis (ICAS) is unclear. This study investigated inflammatory markers’ association with high-risk plaques and their value in differentiating stroke phenotypes and predicting prognosis. 298 symptomatic ICAS patients were classified into acute ischemic stroke (AIS, n = 207) and delayed perfusion (DP, n = 91) groups using multimodal MRI. Plaque vulnerability was graded based on high-resolution vessel wall imaging, inflammatory indices calculated, and associations assessed using regression and mediation analysis. AIS patients had higher systemic inflammation and more high-risk plaques (all p < 0.05). Each Systemic Inflammation Response Index (SIRI) unit increase was associated with 32.4
High workload and inconsistent quality of ultrasound report writing may lead to diagnostic errors. This study aims to ascertain whether fine-tuned open-source large language models (LLMs) can achieve promising performance for automated quality control of Chinese ultrasound reports, when compared to proprietary LLMs. This retrospective, multi-center study included a multi-subspecialty dataset of 1800 Chinese ultrasound reports, comprising 1500 quality-controlled reports injected artificially with six predefined error types and 300 reports with naturally occurring errors. Nine proprietary LLMs (under zero-shot and few-shot paradigms) and seven open-source LLMs (under fine-tuning) were evaluated, with performance compared against that of radiologists of varying seniority. Performance was measured by detection accuracy, Macro-F1 score, precision, recall, and mean absolute error across six categories. Fine-tuned open-source LLMs, notably Qwen3-14B, achieved a detection accuracy of 0.931 and a Macro-F1 of 0.739, approaching the performance of senior radiologists. Some fine-tuned open-source LLMs maintained performance despite smaller parameter sizes and outperformed most proprietary LLMs with vastly larger parameter counts. The fine-tuned Qwen3-14B demonstrated superior recognition capability for semantic errors such as redundancy, spelling, orientation, and unit or value errors. This study demonstrates that task-specific fine-tuning enables open-source LLMs to rival proprietary LLMs and expert radiologists in Chinese ultrasound report error detection, offering a locally deployable and privacy-compliant alternative for AI-assisted clinical quality control workflows.
We developed a national questionnaire to assess radiology reports (RR) physicians’ reading habits and identify their expectations towards RR, focusing on CT and MRI reports. An anonymized 20-item questionnaire was nationally distributed in France via practice and hospital mailing lists and one social media group, and included three sections: respondent’s profile; RR reading (importance and reading of RR sections, advice on key images [i.e., selected summary screenshots for main findings]); use and impact of the RR. Overall and profile-based subgroup analyses were performed. One thousand two hundred fifty physicians responded (58
Background:Central nervous system (CNS) infections caused by Klebsiella pneumoniae harboring hypervirulence-associated genes usually arise from metastatic dissemination from an extracranial focus. Cases lacking an overt extracranial source remain uncommon. Furthermore, the spontaneous development of tension pneumocephalus in this context is exceptionally rare. Case Presentation:We report a fatal case of a 49-year-old female with a 40-year history of polycystic liver and kidney disease who presented with fulminant meningoencephalitis. Despite aggressive systemic meropenem therapy and neuroprotective measures, she developed refractory intracranial hypertension (780 mmH2O) and rapidly progressive tension pneumocephalus without evidence of neurotrauma or external anatomical breach. Blood and cerebrospinal fluid (CSF) cultures, alongside CSF metagenomic next-generation sequencing (mNGS), identified an extended-spectrum β-lactamase (ESBL)-producing K. pneumoniae. The isolate exhibited a hypermucoviscous phenotype and harbored multiple hypervirulence-associated genes (eg, rmpA, iucA, and iroB) alongside resistance determinants (CTX-M-15-like and AAC(6')-Ib-cr), supporting a probable convergent phenotype. The patient ultimately died from irreversible multiple organ dysfunction syndrome on day 7. Conclusion:The rapid evolution of tension pneumocephalus in this case highlights the potential for abrupt neurological deterioration in CNS infections associated with convergent K. pneumoniae phenotypes. While the exact etiology of intracranial gas is likely multifactorial, this case underscores the critical need to integrate phenotypic assays with molecular diagnostics to identify hypervirulence, while maintaining rigorous differential diagnoses for spontaneous pneumocephalus in the neurocritical care setting.
Background:Bloodstream infections, BSIs caused by Escherichia coli are a major healthcare concern due to the increasing emergence of multidrug-resistant and virulent strains. This study aimed to investigate the phenotypic and genotypic characteristics of bloodstream-derived E. coli isolates, with a focus on antimicrobial resistance, biofilm formation, virulence-associated genes, phylogenetic distribution, and clonal diversity. Methods:A total of 150 blood culture samples were collected from patients with suspected BSIs, of which 60 (40%) E. coli isolates were recovered and confirmed using conventional microbiological methods. Antimicrobial susceptibility testing was performed according to the CLSI2026 guidelines, whereas biofilm formation was assessed using a microtiter plate assay. Virulence genes, phylogenetic groups, and clonal relationships were evaluated using polymerase chain reaction-based, PCR methods. Results:High susceptibility rates were observed for colistin (96.7%) and meropenem (93.3%), whereas the highest rates of resistance were detected against ciprofloxacin (93.3%) and co-trimoxazole (61.7%). Multidrug resistance, MDR was detected in 41.7% of the isolates, while 31.7% were phenotypically characterized as Extended-Spectrum Beta-Lactamase, ESBL producers. Biofilm analysis revealed that 75% of the isolates were capable of biofilm formation. Among the investigated virulence genes, fimH (88.3%), ompT (73.3%), and irp2 (58.3%) were most prevalent. Phylogenetic analysis revealed a predominance of groups B2 (26.7%), B1 (23.3%), and D (23.3%). The ERIC-PCR analysis classified the isolates into 26 distinct ERIC types, indicating substantial genetic diversity. Conclusion:The coexistence of virulence-associated genes, biofilm-forming ability, antimicrobial resistance, and genetic diversity among bloodstream-derived E. coli isolates highlights the circulation of potentially high-risk lineages in healthcare environments. These observations underscore the necessity for ongoing molecular epidemiological monitoring and the implementation of effective infection control strategies.
To characterize MRI matrix signal and CT calcification patterns across WHO-IWGE stages, compare them with lesion mimicking cystic echinococcosis (CE), and derive an MRI-based subclassification for inactive cysts. This retrospective multicenter study included 105 patients (174 CE cysts) imaged between 2012 and 2024, plus 30 mimickers. Inclusion required axial T1-weighted imaging with chemical-shift in-phase/opposed-phase acquisitions and at least two T2-weighted sequences. Two radiologists independently reviewed all examinations, and a consensus was reached. Cysts were classified as inactive if no free-fluid T2 hypersignal was present on index MRI and corroborated by follow-up imaging and/or adjunct ultrasound in equivocal cases. Diagnostic performance indices were calculated to identify inactivity. Fatty T1 hyperintensity was more frequent in inactive than active/transitional cysts (20/97 (21
This study aimed to develop a deep learning model (MST-Net) for the segmentation-free automated and precise differentiation between T2 and T3 staging of rectal cancer based on preoperative T2-weighted magnetic resonance imaging (T2WI). Preoperative T2WI images and postoperative pathologically confirmed T2/T3 staging labels from rectal cancer patients were retrospectively collected from two centers between January 2020 and January 2025. The core of MST-Net includes: a pyramid cross-stage feature fusion module to integrate shallow texture details and deep semantic information, mitigating the loss of spatial details in deep networks; and a lightweight spatial attention mechanism to adaptively focus on key radiomics features within the tumor region. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and accuracy (ACC). A total of 309 patients were included in the analysis, comprising a training set (n = 216) and an internal test set (n = 54) from Center 1, and an external independent validation set (n = 39) from Center 2. MST-Net achieved an AUC of 0.95 (ACC = 90
To evaluate the feasibility of high-pitch free-breathing triple rule-out CT angiography (TRO-CTA) by comparing image quality and radiation dose with a standard breath-hold protocol in patients with acute chest pain. This prospective study enrolled 104 patients with acute chest pain who underwent TRO-CTA on a third-generation dual-source CT scanner, sequentially allocated to high-pitch free-breathing TRO-CTA (pitch = 3.2; Group A, n = 52) or standard breath-hold TRO-CTA (standard pitch; Group B, n = 52). Objective image quality (attenuation, noise, signal-to-noise ratio [SNR], and contrast-to-noise ratio [CNR]) was assessed across the coronary, pulmonary, and aortic territories. Subjective image quality (3-point scale), effective dose (ED), acquisition time, and clinical diagnoses were compared between groups. Radiation dose (ED: 1.81 ± 1.33 vs 15.63 ± 6.71 mSv) and acquisition time (0.48 ± 0.05 vs 6.83 ± 1.87 s) were significantly lower in Group A than in Group B (all p < 0.001). Vascular attenuation was significantly higher in Group A in the coronary arteries, main pulmonary artery, and ascending aorta (p < 0.05), whereas CNR was higher in Group B (all p < 0.01). Subjective image quality scores, including coronary diagnostic segment rates (98.0
To establish and validate a noninvasive multiparametric radiomics model based on dual-layer spectral CT (DLCT) for distinguishing preoperatively malignant from benign solid pulmonary nodules (SPNs). This retrospective study enrolled 441 patients with pathologically confirmed SPNs who underwent preoperative DLCT and were divided into training (n = 252), internal test (n = 112), and external test (n = 77) cohorts. Radiomics features were extracted from conventional and virtual monoenergetic images (40 and 70 keV) and material decomposition images (including iodine density (ID), Z-effective atomic number (Zeff), and electron density (ED) maps) in arterial (AP) and venous (VP) phases. Logistic regression was used to construct radiomics models, and a combined clinical-radiomics model was visualized as a nomogram. Subgroup analysis was performed by nodule size (≤ 10 mm vs. > 10 mm), and diagnostic accuracy was compared with that of two radiologists. The optimal radiomics model, comprising features from ID in VP and Zeff in both AP and VP, achieved an area under the curve (AUC) of 0.835, 0.804, and 0.772 in the training, internal, and external cohorts, respectively. The combined model (age, lobulation, and ten radiomic features) outperformed the clinical-radiological model in all cohorts (AUC: 0.889 vs. 0.816; 0.865 vs. 0.795; 0.825 vs. 0.743; p < 0.05). It maintained strong performance for ≤ 10 mm and > 10 mm nodules, with AUCs of 0.875 and 0.888 (internal test) and 1.000 and 0.794 (external test). A DLCT-based multiparametric radiomics model, integrated with clinical-radiological features, enables accurate preoperative, noninvasive differentiation between benign and malignant SPNs, including subcentimeter nodules.
Background:Bloodstream infections (BSI) are a major cause of pediatric morbidity and mortality in low- and middle-income countries, yet microbiological surveillance data remain limited in Central Africa. We aimed to characterize the epidemiology, microbiological spectrum, antimicrobial resistance (AMR) patterns, and predictors of mortality among children with culture-confirmed BSI in eastern Democratic Republic of the Congo (DRC). Methods:We conducted a retrospective cohort study at Hôpital Provincial Général de Référence de Bukavu, a tertiary referral hospital in eastern DRC. Children aged 29 days to 18 years admitted with clinically suspected sepsis between June 2020 and December 2024 were eligible. Blood cultures classified as contaminants according to predefined microbiological criteria were excluded. Clinical, microbiological, and antimicrobial susceptibility data were extracted from hospital and laboratory records. Multivariable logistic regression was used to identify independent predictors of in-hospital mortality. Results:Among 123 children with culture-confirmed bacteremia, 123 clinically significant bacterial isolates were identified and in-hospital mortality was 9.8% (12/123). Gram-negative bacteria predominated (84/123; 68.3%), with Salmonella spp. (27/123; 22.0%) and Enterococcus spp. (25/123; 20.3%) being the most frequently isolated pathogens. Among the main Gram-negative pathogens, resistance to amoxicillin-clavulanate was 100.0% in Salmonella spp. (24/24), K. pneumoniae (11/11), and E. coli (10/10), whereas amikacin resistance ranged from 0.0% (0/24) in Salmonella spp. to 23.1% (3/13) in K. pneumoniae; no meropenem resistance was detected among isolates tested. In multivariable analysis, altered level of consciousness was associated with higher odds of in-hospital mortality (aOR 12.83; 95% CI 1.54-107.09). Model discrimination was acceptable (AUROC 0.71; 95% CI 0.55-0.87). Conclusion:Pediatric BSI in eastern DRC were predominantly caused by Gram-negative pathogens and showed substantial resistance to commonly used antibiotics. Altered level of consciousness was associated with higher odds of in-hospital mortality. Strengthening microbiological surveillance, diagnostic stewardship, and antimicrobial stewardship is essential to optimize empiric therapy and improve pediatric sepsis outcomes.
Plaque-RADS was recently developed to standardize reporting and risk stratification of carotid plaques. This study aimed to evaluate inter-reader agreement of Plaque-RADS across US, CTA, and MRI, and to assess the impact of reader experience. In 250 patients with carotid US, CTA, and MRI, nine readers (three per modality, stratified by experience) independently assessed plaque features and Plaque-RADS scores. Inter-reader agreement was analyzed using κ statistics and intraclass correlation coefficients (ICC). Learning curves were generated by comparing reader performance against MRI expert reference across five sequential case subsets. Among 962 plaques and 25 normal arteries, inter-modality agreement for overall Plaque-RADS was moderate to substantial (κ, 0.578–0.758). Agreement was almost perfect for RADS 1-2 (κ, 0.814–0.883) but lower for RADS 3-4 (κ, 0.427–0.709). US, CTA, and MRI demonstrated substantial to almost perfect agreement in assessing plaque presence and maximum wall thickness (κ/ICC, 0.697–0.878). CTA and MRI experts demonstrated substantial to almost perfect agreement in ulcer detection (κ, 0.880) and intraluminal thrombus (κ, 0.787), but moderate agreement in intraplaque hemorrhage (κ, 0.578). Regarding reader experience, all intermediate and expert readers across US, CTA, and MRI achieved substantial to almost perfect agreement in overall and different categories of RADS scoring (κ/ICC, 0.624–0.954). Learning curve analysis confirmed that all readers improved with training, with the most pronounced gains observed in US beginners. Plaque-RADS is reliable for low-risk plaques across modalities, whereas accurate categorization of high‑risk plaques requires experienced readers and advanced imaging. These findings may help inform stratified imaging decisions.
