Clinical Disease Research Articles

Advanced Quantitative MRI Unveils Microstructural Thalamic Changes Reflecting Disease Progression in Multiple Sclerosis.

In patients with multiple sclerosis (PwMS), thalamic atrophy occurs during the disease course. However, there is little understanding of the mechanisms leading to volume loss and of the relationship between microstructural thalamic pathology and disease progression. This cross-sectional and longitudinal study aimed to comprehensively characterize in vivo pathologic changes within thalamic microstructure in PwMS using advanced multiparametric quantitative MRI (qMRI). Thalamic microstructural integrity was evaluated using quantitative T1, magnetization transfer saturation, multishell diffusion, and quantitative susceptibility mapping (QSM) in 183 PwMS and 105 healthy controls (HCs). The same qMRI protocol was available for 127 PwMS and 73 HCs after a 2-year follow-up period. Inclusion criteria for PwMS encompassed either an active relapsing-remitting MS (RRMS) or inactive progressive MS (PMS) disease course. Thalamic alterations were compared between PwMS and HCs and among disease phenotypes. In addition, the study investigated the relationship between thalamic damage and clinical and conventional MRI measures of disease severity. Compared with HCs, PwMS exhibited substantial thalamic alterations, indicative of microstructural and macrostructural damage, demyelination, and disruption in iron homeostasis. These alterations extended beyond focal thalamic lesions, affecting normal-appearing thalamic tissue diffusely. Over the follow-up period, PwMS displayed an accelerated decrease in myelin volume fraction [mean difference in annualized percentage change (MD-ApC) = -1.50; p = 0.041] and increase in quantitative T1 (MD-ApC = 0.92; p < 0.0001) values, indicating heightened demyelinating and neurodegenerative processes. The observed differences between PwMS and HCs were substantially driven by the subgroup with PMS, wherein thalamic degeneration was significantly accelerated, even in comparison with patients with RRMS. Thalamic qMRI alterations showed extensive correlations with conventional MRI, clinical, and cognitive disease burden measures. Disability progression over follow-up was associated with accelerated thalamic degeneration, as reflected by enhanced diffusion (β = -0.067; p = 0.039) and QSM (β = -0.077; p = 0.027) changes. Thalamic qMRI metrics emerged as significant predictors of neurologic and cognitive disability even when accounting for other established markers including white matter lesion load and brain and thalamic atrophy. These findings offer deeper insights into thalamic pathology in PwMS, emphasizing the clinical relevance of thalamic damage and its link to disease progression. Advanced qMRI biomarkers show promising potential in guiding interventions aimed at mitigating thalamic neurodegenerative processes.

Endothelial dysfunction markers syndecan-1 and thrombomodulin are associated with higher albuminuria levels in type 2 diabetes with no history of clinical cardiovascular disease

IntroductionIndividuals with type 2 diabetes and increased albuminuria, a well-established marker of microvascular complications, are at a higher risk for cardiovascular disease (CVD) and premature mortality. Therefore, a better understanding of the underlying pathophysiology is needed to improve risk stratification and tailor prevention and intervention. MethodsWe conducted a cross-sectional study including 463 individuals with type 2 diabetes, various degrees of albuminuria and without CVD. We analysed the association between albuminuria and markers of endothelial function (thrombomodulin and syndecan-1), thrombin generation (thrombin-antithrombin complex, prothrombin fragment 1 + 2), fibrinogen, platelet function (activation using soluble plasma selectin and aggregation using Multiplate® Analyzer) using regression models. ResultsIn the study cohort 33 % were women, the mean ± SD age was 65 ± 9 years, and median [IQR] diabetes duration was 15 [9–20] years. In total, 344 (74 %) individuals had normal albuminuria, 87 (19 %) moderately- and 32 (7 %) severely increased albuminuria levels. Higher markers of endothelial function and fibrinogen were independently associated with higher albuminuria levels (p < 0.01). No association between albuminuria and markers of thrombin generation and platelet was demonstrated. ConclusionWe demonstrated an independent association between albuminuria and markers of endothelial function and fibrinogen in individuals with type 2 diabetes and no history of CVD.

Uterine cancer among Asian Americans: Disparities & clinical characteristics and disease presentations

Uterine cancer among Asian Americans: Disparities & clinical characteristics and disease presentations

Content validation of the nursing diagnosis “ineffective protection” in the context of adolescents with cancer

ObjectiveTo analyze the relevance of a set of clinical elements to represent the content domain of the nursing diagnosis Ineffective Protection. Design and methodsThis study employed content validation, using expert judgment to assess the appropriateness of clinical indicators, etiological factors, and conceptual and operational definitions, integrating the collective wisdom framework, the theory of predictive diversity, and the determination of rater skill level. ResultsFrom the middle range theory, 28 clinical indicators and 17 etiological factors were identified, which were rated by 34 raters. The analysis showed that the clinical indicators restlessness and insomnia and the etiological factors ambient temperature and humidity were not considered relevant for the nursing diagnosis of Ineffective Protection, because the median content validity index was lower than 0.9. ConclusionsContent validation verified that most of the components of the nursing diagnosis of Ineffective Protection were considered relevant by judges. Practical implicationsIt is believed that the data obtained can help nurses to more easily evaluate the related factors and clinical indicators of Ineffective Protection presented by adolescents with cancer, which favors the process of diagnostic inference.

Application of superb microvascular imaging technology in clinical disease activity of rheumatoid arthritis.

Detection of synovitis is essential for assessing the activity and predicting the prognosis of rheumatoid arthritis (RA). The aim of this study was to investigate the diagnostic performance of superb microvascular imaging (SMI) in RA patients with high, moderate, and low activity. One hundred four patients with active RA were selected from the hospital between May 2022 and August 2023. The study observed the correlation between bone erosion of the carpal joint, joint cavity effusion, thickness of synovial hyperplasia of the carpal joint, positivity rate of synovial blood vessels, and their semiquantitative scores with the clinical disease activity of RA using SMI examination. The detection of synovial hyperplasia thickness and joint effusion in the high-activity group was higher than that in the low-activity group, and the difference was statistically significant (P < 0.05). The quantitative SMI test demonstrated that the synovial blood flow grading and semiquantitative grade increased gradually with activity level (P<0.05). During the high, moderate, and low-activity groups, the vascular index (VI) value of the hyperplastic synovial membrane decreased gradually, showing statistical significance both between and within the groups (P<0.05). SMI technology exhibited high sensitivity and accuracy in assessing disease activity in RA. It holds significant clinical application value as a reliable auxiliary tool for assessing disease activity in RA and treatment. Key Points • Super micro-vascular imaging (SMI) demonstrated higher detection rates of microvesselsin RA patients with high disease activity compared to those with low activity, showing statistical significance. • The quantitative SMI test revealed a clear correlation between synovial blood flow grading and disease activity levels in RA patients, highlighting the potential of SMI as a valuable tool for disease activity and treatment of rheumatoid arthritis.

Effect of single parenteral administration of marbofloxacin on bacterial load and selection of resistant Enterobacteriaceae in the fecal microbiota of healthy pigs

BackgroundAntimicrobial resistance (AMR) is a global concern impacting both humans, animals and their environment. The use of oral antimicrobials in livestock, particularly in pigs, has been identified as a driver in the selection of AMR bacteria. The aim of the present study was to evaluate the effects of a single intramuscular (IM) dose of marbofloxacin (8 mg/kg) on Enterobacteriaceae and E. coli populations, as well as on fluoroquinolone resistance within the fecal microbiota of pigs. Twenty healthy pigs, 60-days old, were divided into two groups: a treated group (n = 13) and a control group (n = 7) and were monitored over a 28-day experimental period. Fecal samples were collected from all animals for the isolation of E. coli and Salmonella strains. The minimum inhibitory concentration (MIC) of marbofloxacin for the isolates recovered on MacConkey agar supplemented with 1 or 4 µg/mL of marbofloxacin and for some generic E. coli isolates (recovered from MacConkey agar not supplemented with marbofloxacin) was determined using the broth microdilution method. Genomic DNA was extracted from the confirmed bacterial strains and sequenced using the Sanger method to identify mutations in the quinolone resistance determining regions (QRDRs) of the gyrA and parC genes.ResultsThe single IM administration of marbofloxacin resulted in a significant decrease in Enterobacteriaceae and E. coli fecal populations from days 1 to 3 post- treatment. No Salmonella isolates were detected in either group, and no marbofloxacin-resistant E. coli isolates were identified. The MIC of the selected generic E. coli strains (n = 100) showed an increase to up to 0.5 µg/mL between days 1 and 3 post-treatment but remained below the clinical breakpoint of marbofloxacin resistance (4 µg/mL). Sequencing of these isolates revealed no mutations in gyrA and parC genes.ConclusionsThe present study showed that this dosing regimen of marbofloxacin significantly decreases the fecal shedding of Enterobacteriaceae and E. coli populations in pigs, while limiting the selection of marbofloxacin-resistant E. coli isolates. These findings warrant validation in sick pigs to support the selective use of this antibiotic solely in cases of clinical disease, thereby minimizing the reliance on conventional (metaphylactic) group treatments in pigs.

The data layer: the importance of sources critical appraisal

Abstract One of the main purposes of public health institute is to tracking the health status of its citizens and understanding its evolution over time. Given the absence of a singular, comprehensive data source, we developed a framework to select databases specific to each disease and outcome of interest. This process includes a thorough evaluation of the operational case definitions, as well as the strengths and weaknesses of each database, with a particular focus on their sensitivity and specificity. These qualities are appraised following a dedicated scoring form into different categories (i.e., high, medium, low). The selection criteria for data sources hinge on several key questions: Is the database exhaustive or merely a sample? Does the case definition rely on direct medical diagnoses or proxies? Does the source capture all cases? Is the data collected at regional or national level? Are there mechanisms for yearly or periodic updates? To establish the most accurate national prevalence estimates for each outcome, we often need to adjust for data misclassification-applying corrections for biases such as self-reported data and interpolating for missing entries. In some instances, a pooled estimate from multiple data sources is developed. A specific case will be presented to illustrate our approach in practice. This critical evaluation is pivotal, as the quality of data underpins the entire health information pyramid. The integrity of our data directly influences our ability to convert data into actionable health wisdom, ultimately affecting public health decision-making and policy formulation.

Investigation of a Norovirus GII.4Sydney[P16] outbreak in a care facility in Portugal, 2022

Abstract Background On the 29th of April 2022 the local Public Health unit was notified of 12 cases of acute gastroenteritis in residents of a long-term care facility (LTCF). A joint epidemiological investigation team was established and initiated an outbreak investigation to characterize the outbreak and implement infection control measures. Methods Epidemiological questionnaires were administered to staff (n = 44) and residents (n = 60). Case definition was LTCF residents or staff members with at least one of the following symptoms: diarrhoea, vomiting, nausea, between April 25th and May 14th, 2022. Stool or vomit samples were collected for 11 individuals. To assess environmental contamination fifteen food samples from previous meals and six surface samples from toilet faucets, wash tubs, and cutting boards were collected. Spatial distribution of cases within the LTCF was performed to guide infection control implementation. Results A total of 43 people met the case definition. Attack rates in residents and staff were 37% (23/63) and 42% (20/48), respectively. Of the total tested specimens, six (6/8) from residents and two (2/3) from staff were positive for the Norovirus (NoV) GII.4 Sydney [P16] variant by genotyping. Two (2/6) samples from surface swabs from the toilet faucet in the resident’s living room were also positive for NoV GII. Food samples were negative for major bacterial agents implicated in gastrointestinal outbreaks. Cases were distributed throughout the LTCF wards with no clear clustering. Four residents required hospital admission. Conclusions Results suggest person-to-person as well as environmental transmission of NoV. Identification of behavioural and spatial patterns of residents and staff and subsequent enactment of infection control strategies mitigated the outbreak. These findings reinforce the need for public health to maintain continuous technical support to LTCF on the implementation of infection control best practices. Key messages • Outbreak investigation in LTCF confirms Norovirus transmission, emphasizing the importance of infection control measures in long-term care facilities. • Study reveals Norovirus outbreak in LTCF, underscores the role of person-to-person and environmental transmission, highlighting the need for robust infection control protocols.

Characterizing the progression of subclinical cardiac amyloidosis through artificial intelligence applied to electrocardiographic images and echocardiograms

Abstract Background Transthyretin amyloid cardiomyopathy (ATTR-CM) follows an indolent course and may remain undiagnosed for many years before resulting in clinical disease. Purpose To assess the utility of scalable artificial intelligence (AI) methods applied to electrocardiographic (ECG) images and echocardiograms in detecting longitudinal changes that precede the clinical diagnosis of ATTR-CM. Methods Across 5 hospitals of a large U.S.-based hospital system, we identified a total of 234 patients (age 79 [IQR:70-85] years, n=56 (23.9%) women) with ATTR-CM, defined by the presence of a positive bone scintigraphy scan (or pharmacotherapy with an approved transthyretin stabilizer) between 2015 and 2023. Using 10:1 age- and sex-matched controls, we independently trained convolutional neural network algorithms to discriminate ATTR-CM from controls using i) ECG images (AUROC 0.915) or ii) echocardiographic studies by incorporating all available views (AUROC 0.93). In a leave-out testing set of n=82 individuals with serial ECGs and n=49 individuals with serial echocardiograms we characterized longitudinal patterns in the evolution of the AI ECG and echo-based scores, and estimated the percentage of individuals that would have screened positive across distinct time intervals. Results In the leave-out testing set 52.4% and 34.7% of all individuals who went on to receive a diagnosis of ATTR-CM would have screened positive by AI deployed to ECGs and echocardiograms, respectively, 1 to 3 years before their confirmatory testing, with the percentage increasing to 75.6% and 69.4% in the 12 months before their eventual diagnosis (A). Across both modalities, there was a longitudinal increase in AI predictions when comparing the median of all studies performed more than a year before diagnosis versus the median of any studies performed within 12 months of diagnosis (AI-Echo: 0.20 [IQR: 0.04-0.35] to 0.49 [0.24-0.59] &amp; AI-ECG: 0.07 [0.02-0.20] to 0.32 [0.11-0.49], p&amp;lt;0.001 for both) (B), consistent with evolution in the ECG and echocardiographic signature of ATTR-CM before its clinical diagnosis. Conclusions We demonstrate that AI applied directly to ECG images and echocardiography may enable scalable monitoring of subclinical ATTR-CM progression.

Tiktok as a Source of Education and Misinformation in Lichen Sclerosus.

The purpose of this study is to evaluate the content, delivery, and quality of medical information for vulvar lichen sclerosus on the social media platform TikTok. This is a descriptive, cross-sectional study. Using the third-party data scraping tool Apify, TikTok videos tagged with #lichensclerosus or "lichen sclerosus" were identified and sorted by view count. A sample of 100 videos was reviewed by 2 independent reviewers, excluding those not discussing lichen sclerosus. Videos were assessed using a coding document, the Patient Educational Materials Assessment Tool, and the DISCERN instrument. Interrater reliability was measured, and statistical analyses included Fleiss' kappa, intraclass correlation coefficient, t tests, and Wilcoxon rank sum test with Holm-Bonferroni correction. Content creators included patients (46%), health care professionals (30%), and others. Topics focused on clinical disease (52%) and treatment (48%). Evidence-based medicine was discussed in 71.7% of treatment-related videos, while 51.7% included nonevidence-based approaches, with a neutral or positive sentiment. Videos discussing topical steroids often had negative sentiments. Quality assessment revealed 61% of videos were understandable, 27% actionable, and 46% contained misinformation. Videos by health care professionals had less misinformation and higher quality scores compared to patient-generated content. Commercially biased videos were more understandable but contained more misinformation. TikTok serves as a significant platform for sharing information on lichen sclerosus, but nearly half of the content contains misinformation. Health care professionals need to engage in social media to provide accurate information and counteract misinformation. Enhanced collaboration with patient advocates and careful resource sharing can improve the quality and reliability of medical information available online.

Utilizing unsupervised machine learning to uncover novel phenogroups within the broad QRS complex

Abstract Background Conduction disease can manifest as a broad QRS complex on the ECG. Broad QRS is conventionally categorised as left bundle branch block (LBBB) and right bundle branch block (RBBB) or non-specific intraventricular conduction delay (IVCD), based on QRS morphology. These subgroups were coined over a century ago and have been relevant for heart failure with reduced ejection fraction and cardiac resynchronization therapy (CRT). However, there may be more precise phenogroups underlying broad QRS complexes. Purpose Using unsupervised machine learning to define novel broad QRS phenogroups and characterise them using clinical variables and disease outcomes. Methods We extracted 51 relevant features using a Variational Autoencoder from 47,456 median-beat ECGs with broad QRS intervals (QRS ≥ 130ms) from a secondary care cohort. These were input into Discriminative Dimensionality Reduction via Learning a Tree (DDRTree), a clustering method that models the continuum of heterogeneity by projecting the underlying distribution as a tree structure in a low-dimensional space, while assigning distinct branch/cluster labels. Results Six distinct phenogroups were identified within broad QRS morphologies (Figure-1). Two branches were RBBB dominant (Branch 1: more males, high-comorbidity; Branch 6: low-comorbidity/healthy-RBBB). Two branches were LBBB dominant (Branch 4: mixed IVCD with CHB burden; Branch 5: more females, CRT responders). Two branches were IVCD/mixed-phenotype (Branch 2: IVCD-dominant, high risk of future cardiovascular events; Branch 3: average/core branch). Within LBBB, Branch 4 and 5 showed similar trends with improving echocardiography profiles and CRT response when adjusted for covariates, each compared against the core branch. Branch 5 was distinct due its high risk of future HF (HR 1.19 [1.07-1.33] p &amp;lt; 0.01), cardiovascular death (HR 1.35 [1.20-1.50] p &amp;lt; 0.0001), all-cause mortality (HR 1.08 [1.01-1.16] p &amp;lt; 0.05) and CHB (HR 1.35 [1.16-1.56] p &amp;lt; 0.0001) (Figure-2). Conversely within RBBB, Branch 1 and 6 showed stark differences across various traits. Branch 1 captured a high-risk profile associated to higher risk of cardiovascular death (HR 1.37 [1.24-1.52] p &amp;lt; 0.0001), all-cause mortality (HR 1.20 [1.12-1.29] p &amp;lt; 0.0001) and CHB (HR 1.15 [1.01-1.32] p &amp;lt; 0.05) (Figure-2), while Branch 6 retained a low-risk phenotype. The tree dimensions also revealed relevant trends in cardiac anatomy and valvular dysfunction; the top-left region in Figure-1 associated with higher left ventricular ejection fraction and lower left ventricular end-diastolic dimension, lower left ventricular end-systolic dimension and a greater CRT response. Conclusion Through unsupervised methods we have identified conduction disease phenogroups with additive value for disease prognosis and CRT response prediction beyond traditional LBBB and RBBB labels. These novel phenogroups may help guide precision care for patients with a broad QRS complex.Figure-1Figure-2

Invasive validation of central blood pressure measurements using a suprasystolic monitor

Abstract Interest in the assessment of Central Blood Pressure (cBP) is steadily growing since it is a better predictor of myocardial infarction, stroke, or death than Peripheral Blood Pressure (pBP). However, pBP remains the first line for the diagnosis of hypertension (HTN) due to the ease and speed of the measurement. We sought to validate a new method to estimate cBP from brachial sphygmomanometer measurements. We estimated cBP using a sphygmomanometer that can record, after conventional pBP measurements, the pressure in the cuff maintained at a constant suprasystolic pressure. cBP is calculated using a method based on applying a physics-based model of the left subclavian artery to the brachial arterial branch to the suprasystolic brachial artery pressure waveforms. We compared this noninvasive estimated cBP to an invasive gold-standard measurement during cardiac catheterization. After clinically indicated cardiac catheterization requiring a haemodynamic assessment of a moderate coronary artery stenosis by Fractional Flow Reserve (FFR), the wire that incorporates a high fidelity electronic pressure transducer was positioned into the guiding catheter left in the ascending aorta. Simultaneous measurements were performed with a cuff placed on the patient's left arm. The output signals were recorded in a custom-based acquisition system. The comparison was obtained on the same 10 seconds recorded by the cuff and the pressure wire. The goal will be to reach 85 patients as recommended by the ARTERY Society Task Force. It recommends as an accuracy criterion to achieve a mean difference ≤ 5 mmHg with a standard deviation (SD) ≤ 8 mmHg, which are the standards adopted for this study. Patients with aortic stenosis, atrial fibrillation, or frequent (supra)ventricular extrasystoles were excluded. A total of 197 pairs of measured-estimated cBP were analysed in 78 patients with a mean age of 63 ± 8 yo, 75% of whom were men, 70% had hypertension, 26% fdiabetes, 93% dyslipidemia, 41% were tobacco users and 14% suffered from clinical peripheral artery diseases without history of revascularization. The median (InterQuartiles 25-75%) pBP was 123 [112 134] / 70 [64 77] mmHg. Measured cBP was 102 [92 11] / 78 [70 84] mmHg with a central augmentation index of 34 [23 44] %. The mean difference between estimated and measured systolic cBP was 4.9 ± 6.5 mmHg, while it was -3.9 ± 5.8 mmHg for diastolic cBP, meeting the prespecified accuracy criteria. In conclusion, our approach based on an exact matching and comparison of non-invasive suprasystolic arm cuff measurements and high-fidelity aortic BP validates that an estimation of central aortic blood pressure that can be easily carried out in daily practice and might improve HTN management. It remains to be demonstrated that more cardiovascular complications will be avoided by guiding the antihypertensive therapy with cBP instead of pBP measurements.Bland-Altman of estimated - measured cBP

The Network of Expertise on Long COVID as a means to synthesise intelligence and improve our response to long COVID at EU level

Abstract To promote international collaboration and strengthen EU and national-level responses to Long COVID, the Commission set up the Network of Expertise on Long COVID (NELC) in 2023. It brings together national institutions involved in Long COVID work, nominated by the Public Health Expert Group (PHEG) representatives of each Member State. The network provides a platform for exchanges of national experiences on diagnosis, treatment, and management of long COVID. The Commission and the NELC agreed on eight specific actions to be implemented to manage Long COVID. The development of a Long COVID definition is complex due to the diverse range of symptoms experienced by patients, and so working towards a unified EU case definition is the first action proposal. This will allow the development and implementation of a surveillance system on national and EU level to foster the knowledge on the actual scale and the symptomatology of Long COVID across the EU leading to a better comparability of health data at Union level. The proposal to develop and implement a training programme for healthcare professionals at EU level will allow for the exchange of expertise/training on Long COVID across Member States. The provision of clinical guidelines based on evidence to Member States will help manage Long COVID, and international collaboration will allow for the sharing of valuable information and data with third countries that have experience with Long COVID. The Commission will use the EU Health Policy Platform to create an open stakeholder group. This group will allow stakeholders and patient groups to express their point of view, and to share experiences. Assessing the far-reaching social and economic consequences of Long COVID across the EU will allow for more targeted social and economic policy responses from Member States. It is important that priority is given to research responding to the most urgent needs of health care systems, which is why the Commission aims to identify research needs.

Evaluating XGBoost’s predictive accuracy on surgical site Infections in cardiac surgery

Abstract Background Surgical site infections (SSIs) pose a significant threat in cardiac surgery (CS), profoundly impacting patient prognosis. SSI incidence varies widely, reported between 3.5% and 26.8%. The study used a decade-long dataset from SSI surveillance in a specialized hospital in Italy, applying machine learning (ML) techniques to predict the SSI incidence among CS patients. Methods Data collected from 2013-2023 through the surveillance system of SSI in patients undergoing CS were used to train a predictive ML algorithm (XGBoost). Data included information on demographics, risk factors, surgery variables (incision site, prophylaxis, etc.), and the infection outcome derived from follow-up interviews at 30 days post-surgery, or 90 days for patients with prosthetic materials, according to the ECDC case definition of SSI. We used the R libraries “caret”, “smotefamily” and “xgboost” to train the algorithm. A train-test split of 70-30 was applied. Both downsampling of the majority class (no SSI) and oversampling of SSI cases with SMOTE were used in the training set to address class imbalance. Results A total of 10,534 subjects (65.9% males, mean age 68.3 years) who underwent CS (64.3% with prosthetic materials) were included, among which 533 SSIs were identified (mean incidence of 5.06%), with 430 cases (80.7%) occurring after discharge (38.7% deep SSI) and 103 (19.3%) before discharge (55.5% deep SSI). The trained XGBoost algorithm achieved an AUC of 0.62, sensitivity of 69%, and specificity of 50% in the prediction of SSI on the test dataset. Conclusions These findings suggest that while the XGBoost model provides a fair predictive capability, there is significant room for improvement in sensitivity and specificity. The use of artificial intelligence offers a promising opportunity to identify patients at risk of SSI. However, further research and comprehensive data are needed to refine the predictive model and effectively improve prevention measures. Key messages • Predominantly occurring post-discharge, SSIs in cardiac surgery necessitate enhanced prevention strategies, highlighting the critical phase after hospital discharge where surveillance is paramount. • Artificial intelligence may enhance post-discharge SSI surveillance, promising to identify patients at increased risk. Further research is needed to refine these AI tools for optimal sensitivity.

Investigation of a Norovirus GII outbreak in a primary school in Portugal,2023

Abstract Background The onset of acute gastroenteritis cases among students in a primary school class on September 19, 2023, prompted an immediate response from the local Public Health unit. A collaborative effort was initiated to investigate and contain the outbreak. Methods Epidemiological questionnaires were distributed to 166 students and 8 staff members, defining cases as individuals exhibiting symptoms including diarrhoea, vomiting, or nausea between September 19th and September 24th, 2023. Additionally, stool samples were collected from three individuals. Results Out of 166 students and 8 staff members, 39 individuals met the case definition, resulting in attack rates of 22% (37/166) and 25% (2/8) among students and staff, respectively. Laboratory analysis confirmed two cases of Norovirus GII among the tested specimens, with five students requiring medical attention. Conclusions Our investigation underscores the significance of continuous epidemiological surveillance and swift implementation of infection control measures in school settings. The detection of Norovirus transmission emphasizes the necessity for rigorous adherence to infection control best practices. Our findings advocate for sustained technical support from public health authorities to prevent and manage similar outbreaks effectively. Key messages • Study on Norovirus outbreak in a primary school highlights the imperative of infection control measures, emphasizing the importance of ongoing support from public health authorities. • The Norovirus outbreak investigation underscores the vital role of surveillance and swift response in containing infectious diseases within educational settings safeguarding all.

Machine learning to improve the understanding of rabies epidemiology in low surveillance settings

In low and middle-income countries, a large proportion of animal rabies investigations end without a conclusive diagnosis leading to epidemiologic interpretations informed by clinical, rather than laboratory data. We compared Extreme Gradient Boosting (XGB) with Logistic Regression (LR) for their ability to estimate the probability of rabies in animals investigated as part of an Integrated Bite Case Management program (IBCM). To balance our training data, we used Random Oversampling (ROS) and Synthetic Minority Oversampling Technique. We developed a risk stratification framework based on predicted rabies probabilities. XGB performed better at predicting rabies cases than LR. Oversampling strategies enhanced the model sensitivity making them the preferred technique to predict rare events like rabies in a biting animal. XGB-ROS classified most of the confirmed rabies cases and only a small proportion of non-cases as either high (confirmed cases = 85.2%, non-cases = 0.01%) or moderate (confirmed cases = 8.4%, non-cases = 4.0%) risk. Model-based risk stratification led to a 3.2-fold increase in epidemiologically useful data compared to a routine surveillance strategy using IBCM case definitions. Our study demonstrates the application of machine learning to strengthen zoonotic disease surveillance under resource-limited settings.

Serbia multidisciplinary approach for surveillance and risk identification – The “One Health” information for action

Abstract Issue/problem To date, Serbia has not detected locally acquired Dengue cases. Since a competent Dengue virus vector Aedes albopictus (Ae. albopictus) has been detected since 2017, imported cases have the potential to trigger local transmission. Description of the problem To ensure preparedness and timely response in the event of an epidemic signal in Serbia, we described the imported Dengue cases and analysed the geographical distribution and density of the vector. Probable and confirmed imported cases meeting the 2018 EU case definition were reported via the National Notifiable System between January 2019 and December 2023. We monitored the density and geographical spread of mosquitos, including Ae. albopictus, which were collected during May-October 2022 and 2023. Mosquito genera were determined according to morphological criteria and DNA barcoding. Results During the investigation period, physicians reported three probable and four confirmed imported Dengue cases; the mean age was 28.4 (standard deviation (SD)=11.5) years and 57% were male. Cases had travelled in Southeast Asia (n = 6) and the Caribbean (n = 1). The mean time interval from symptom onset to seeking medical care was 3.6 (SD = 2.1) days and from symptom onset to laboratory confirmation 7.4 (SD = 6.3) days. We collected 1994 Ae. albopictus mosquitoes in 308 sampling sites across 12 Serbian regions. We observed the highest number of mosquitoes in September (38%, p &amp;lt; 0.001) and in the Belgrade region (81%, p &amp;lt; 0.001). In 2022, we detected Ae. albopictus mosquitos in seven regions and in 2023 in nine. Lessons Ae. albopictus mosquitoes were widely distributed in Serbia, with the highest presence during September and in the capital region. The importation of Dengue cases from affected countries underscores the need for enhanced integrated and “real-time” surveillance linked with vector control activities.

Prevalence of depression, anxiety and post-traumatic stress disorder (PTSD) after acute myocardial infarction: a systematic review and meta-analysis

Abstract Background There is increasing recognition that patients experience a greater risk of mental illnesses after an acute myocardial infarction (AMI), with the former being linked to worse post-AMI outcomes. However, the prevalence of these conditions is largely unknown as most studies focus on depression and few on other illnesses such as anxiety and post-traumatic stress disorder (PTSD). Additionally, existing studies mostly involved diagnoses of mental illnesses through patient-reported questionnaires which may carry subjectivity (1). Therefore, we conducted a systematic review and meta-analysis to estimate the prevalence and risk factors of developing depression, anxiety and PTSD after an AMI with the inclusion of only studies with official diagnoses of the mental illnesses. Methods Searches in MEDLINE, EMBASE, and PsycINFO up to January 23, 2023, identified 25 qualifying studies that examined the risk of depression, anxiety and PTSD after AMI, with case definitions based strictly on psychiatrist-administered structured interviews according to the Diagnostic and Statistical Manual for Mental Disorders (DSM) criteria. Meta-analyses of proportions using random-effects models estimated the pooled prevalence of each outcome at the &amp;lt;3-month and &amp;gt;3-month time-points. Heterogeneity was tested using I-squared statistics, if significant heterogeneity was found, subgroup analyses and meta-regression analyses were performed to identify the source of heterogeneity. Study quality was assessed using the Newcastle-Ottawa Scale (NOS) and Risk of Bias 2 (RoB2) Tool, and publication bias using the funnel plot and verified by the Egger’s and Begg’s tests. Results A total of 25 studies were included in the meta-analysis. The pooled prevalence of depression post-AMI (20 studies) was 16.70% (95% CI: 12.40%; 22.11%), with pooled prevalence &amp;lt;3-month and &amp;gt;3-month post-AMI at 19.46% (95% CI: 15.47%; 24.19%) and 14.87% (95% CI: 9.55%; 22.43%) respectively. Pooled prevalence of anxiety (7 studies) and PTSD (3 studies) were 11.96% (95% CI: 6.15; 21.96%) and 10.26% (95% CI:5.49;18.36%) respectively. Subgroup analysis showed that the pooled prevalence of both depression and anxiety are significantly higher in the female gender, in those with hypertension, diabetes or hyperlipidemia, and in smokers, while the pooled prevalence of depression is higher in unmarried than married individuals and in patients with a history of depression. Meta regression indicates that history of depression is a significant predictor of prevalence of depression (p= 0.0035, regression coefficient 1.54). Conclusion The prevalence of mental illnesses is high after AMI. Risk factors identified included female gender, hypertension, diabetes, hyperlipidemia, smoking, depression history, as well as one’s social set-up. These findings highlight the importance of screening at-risk patients and early intervention to improve long-term outcomes after AMI.Forest plot of depression prevalenceSubgroup analysis for depression

Effectiveness of Implant Therapy in Patients With and Without a History of Periodontitis: A Systematic Review With Meta-Analysis of Prospective Cohort Studies.

This systematic review investigates the effectiveness of implant therapy in patients with and without a history of periodontitis in terms of implant loss, peri-implant marginal bone loss (MBL), and occurrence of peri-implant diseases. The protocol of the present meta-analysis was registered on PROSPERO (CRD42021264980). An electronic search was conducted up to April 2024. All prospective cohort studies reporting implant loss, MBL, and occurrence of peri-implant diseases in both patients with a history of periodontitis (HP) and patients with no history of periodontitis (NHP) after at least 36-month follow-up were included. The risk of bias was evaluated using the Newcastle-Ottawa Scale and the quality of the evidence was also assessed. A meta-analysis was performed on the selected outcomes at the available follow-up time points. Subgroup analyses were conducted based on follow-up time, rate of progression and severity of periodontitis, and implant surface characteristics. Publication bias was evaluated using the Funnel plot and Egger's test. From 13 761 initial records, 14 studies (17 articles) were finally included. Eight studies had a low risk of bias level, and six had a medium risk of bias level. Meta-analysis showed that HP patients had a significantly greater risk for implant loss (HR: 1.75; 95% CI: 1.28-2.40; p = 0.0005; I2 = 0%), MBL (MD: 0.41 mm; 95% CI 0.19, 0.63; p = 0.0002; I2 = 54%), and peri-implantitis (3.24; 95% CI: 1.58-6.64; p = 0.001; I2 = 57%) compared to NHP, whereas no significant intergroup difference for peri-implant mucositis was found. Subgroup analyses revealed a particularly greater risk for implant loss for HP patients over a ≥ 10-year follow-up (HR: 2.02; 95% CI: 1.06-3.85; p = 0.03; I2 = 0%) and for patients with a history of grade C (formerly aggressive) periodontitis (HR: 6.16; 95% CI: 2.53-15.01; p < 0.0001; I2 = 0%). A greater risk for implant loss for stages III-IV (severe) periodontitis, and implants with rough surfaces was also found. Within the limits of heterogeneous case definitions and methods of assessment, a history of periodontitis has been proved to significantly increase the risk for implant loss, particularly at long follow-up (≥ 10 years) and in case of rapidly progressive forms (grade C), and for MBL and peri-implantitis.

Fibroblast activation in cardio-oncology

Abstract Introduction Carcinoid heart disease is a rare disease affecting the right sided heart valves (1) while anthracycline cardiotoxicity is a dreaded sequelae of a common chemotherapeutic agent that can occur early or even years after exposure (2). Activated fibroblasts, a key factor in these diseases, can be imaged with 68Gallium-fibroblast activation protein inhibitor (68Ga-FAPI). Method 12 patients with carcinoid syndrome, 12 patients with previous anthracycline exposure and 10 healthy volunteers underwent hybrid 68Ga-FAPI positron emission tomography and magnetic resonance imaging. Areas of fibroblast activation were quantified as mean and maximum target-to-background ratios (TBRmean and TBRmax). Results Carcinoid syndrome: 2 of the 12 patients had carcinoid heart disease [mean age 70, 50% female] (CHD) (Figure 1A). 68Ga-FAPI uptake was seen in the liver lesions of all patients with known carcinoid liver tumours. Of the 10 patients without cardiac involvement, 6 had significant tricuspid valve 68Ga-FAPI uptake (CHD- FAPI+) (Figure 1B) and 4 did not (CHD- FAPI-). Median tricuspid TBRmax was significantly higher in CHD + [2.38 (IQR 2.35-2.42)], than CHD- patients [CHD- FAPI+: 1.68 (IQR 1.65-1.73), CHD- FAPI-: 1.55 (IQR 1.53-1.65)], although this was higher than healthy volunteers [1.45 (IQR 1.43- 1.61; p&amp;lt;0.05). CHD- FAPI+ patients had significantly elevated urinary 5-HIAA levels compared to CHD- FAPI- patients [Median =188 mg/24hr (IQR 151-196) in CHD- FAPI+ vs 32mg/24hr ( IQR 12-73); p=0.03]. Anthracycline chemotherapy: 3 of the 12 patients had cardiotoxicity [mean age 61, 67% female]. Anthracycline patients had higher left ventricular myocardial 68Ga-FAPI uptake than healthy volunteers with cardiotoxicity patients having the highest. [TBRmean: Cardiotoxicity 1.46 (IQR 1.36- 1.53), No cardiotoxicity 1.37 (IQR 1.19- 1.49), Healthy volunteers 0.73 (IQR 0.66 - 0.81); p&amp;lt;0.01 (Figure 1E). Across the cohort a moderate negative correlation was observed between Left ventricular ejection fraction and 68Ga-FAPI activity (LV TBRmean r =-0.46 and TBRmax (r= -0.66) Discussion 68 Ga-FAPI provides us the ability to assess fibroblast activation and for the first time demonstrated the key role of these cells in both these cardio-oncology conditions. Increased fibroblast activation is observed around the tricuspid valve in patients with carcinoid syndrome both in those with and without overt clinical disease. Similarly increased myocardial fibroblast activation is observed in patients exposed to anthracyclines even many years after exposure and where there is no overt evidence of cardiotoxicity. Conclusion 68Ga-FAPI imaging holds promise in evaluating the role of activated fibroblasts in the pathology of both carcinoid heart disease and cardiotoxicity, providing information beyond the current resolution of current clinical approaches.