Actus Santé

Background: The effect of using intravascular ultrasound (IVUS) during percutaneous coronary intervention (PCI) on short-term mortality is not well established. The goal of this study was to evaluate any association between the use of IVUS during PCI on mortality vs no ICUC in a large inpatient database. Method: We used the National Inpatient Sample (NIS) database for available ICD-10 codes from 2016-2020 for IVUS and PCIs. Results: A total of 10,059,56 PCIs were performed. 206,910 underwent IVUS-guided PCI vs 9,852,359 without IVUS use. Mortality did not differ between the two groups with 2.52% mortality in the IVUS arm vs 2.59% in no IVUS cohort, p=0.4. The mean age of patients with ICUS use was 65.5 vs 70.1 years without IVUS. Total in-hospital cost in the IVUS group was double that without IVUS (141,920$ vs 71,568$). Furthermore, IVUS utilization was significantly higher in patients with private HMO patients (28.3% vs 17.2%). Conclusion: In-patient all-cause mortality using IVUS during PCI was similar to those patients without IVUS utilization but doubled the cost with higher utilization in privately insured patients

Objective: To study the impact of group II pulmonary hypertension (PH) on the outcomes of patients admitted with ST-elevation Myocardial Infarction (STEMI), we conducted a nationwide retrospective cohort study. Patients and Methods: Using the National Inpatient Sample (NIS) Database from 2017 to 2020, a retrospective study of adult patients with a principal diagnosis of STEMI with a secondary diagnosis with or without group II PH according to ICD-10 codes. Several demographics, including age, race, and gender, were analyzed. The primary endpoint was mortality, while the secondary endpoints included cardiogenic shock, mechanical intubation, length of stay in days, and patient charge in dollars. Multivariate logistic regression model analysis was used to adjust for confounders, with a p-value less than 0.05 considered statistically significant. Results: The study included 27,020 patients admitted with a STEMI, 95 of whom had group II PH. The mean age for patients with and without PH was 66 and 67, respectively. In the PH group, 37% were females compared to 34% in the non-PH group. The in-hospital mortality rate was higher in the PH group (31.5% vs. 9.5%, P <.001, aOR 3.25, P <.023). The rates and adjusted odds of cardiogenic shock and mechanical ventilation were higher in the PH groups (aOR 1.12 aOR 2.16, respectively) but not statistically significant. Patients with PH had a longer length of stay and a higher total charge. Conclusion: Group II PH was associated with worse clinical and economic outcomes in heart failure patients admitted with STEMI.

Objectives: Substance use disorder has been associated with increased morbidity in COVID-19 infection. However, less is known about the impact of active substance use and medications for opioid use disorder (MOUD) on COVID-19 outcomes. We conducted a retrospective cohort study to evaluate the impact of substance use, namely cannabis, cocaine, alcohol, sedative and opioid use as well as buprenorphine or methadone = on COVID-19 morbidity and mortality. Methods: Using electronic-health record data at a large urban hospital system, patients who tested positive for COVID-19 between January 1, 2020 to December 31, 2021 were included. Substance use was identified from urine toxicology and MOUD prescriptions within 90 days prior to admission. COVID-19 outcomes included mortality, ICU admission, need for ventilatory support, number and duration of hospitalizations. Multivariable logistic regression was performed controlling for variables such as age, sex, medical comorbidity, tobacco use, and social disadvantage. Results: Among COVID-19 positive patients (n=17,423), sedative, cannabis, cocaine, and opioid use was associated with statistically significant increases in need for ICU care, need for ventilatory support, number of hospitalizations and duration of hospitalization. Substance use was not associated with an increase in all-cause mortality. There were no statistically significant differences between methadone, buprenorphine and other opioids on COVID-19 outcomes. Conclusions: Active substance use were associated with increased morbidity in COVID-19 infection. MOUD was not associated with worse COVID-19 outcomes compared to OUD. Future studies focused on MOUD treatments that reduce morbidity may help improve clinical outcomes in COVID-19.

Incompatible insect technique coupled with sterile insect technique (IIT-SIT) via releases of sterile male Wolbachia-infected mosquitoes is a promising tool for dengue control. In a six-year trial from 2016 to 2022, comprising 10.35 km2 of high-rise housing estates and 607,872 residents, we designed a synthetic control study methodology to assess the efficacy of IIT-SIT in reducing adult female Aedes aegypti populations, using data from a large, routinely collected, nationwide surveillance system of 57,990 unique mosquito traps in public housing estates. We demonstrated that Wolbachia-based IIT-SIT dramatically reduces wildtype Aedes aegypti populations by an average of 60.64% (95% CI: 59.59%-61.44%) and 79.37% (95% CI: 78.85%-79.87%) in 3, 6 months of releases and eventually 90.17% (95% CI: 89.92%-90.42%) in 12 and more months of releases. We further found a smaller but non-negligible suppression effect which gradually increased over time (47.91%, 95% CI: 47.29%-48.52%) in adjacent, non-intervention sites. Our results demonstrate the potential of IIT-SIT for strengthening dengue control in tropical cities, where dengue burden is the greatest.

Viral sequencing has been critical in the COVID-19 pandemic response, but sequencing and bioinformatics capacity remain inconsistent. To examine the utility of a cloud-based sequencing analysis platform for SARS-CoV-2 sequencing, we conducted a cross-sectional study incorporating seven countries in July 2022. Sites submitted sequential SARS-CoV-2 sequences over two weeks to the Global Pathogen Analysis Service (GPAS). The GPAS bioinformatics cloud platform performs sequence assembly plus lineage and related sample identification. Users can share information with collaborators while retaining data ownership. Seven sites contributed sequencing reads from 5,346 clinical samples, of which 4,799/5,346 (89.8%) had a lineage identified. Omicron lineages dominated, with the vast majority being BA.5, BA.4 and BA.2, commensurate with contemporary genomic epidemiological observations. Phylogenetic analysis demonstrated low within-lineage diversity, and highly similar sequences present in globally disparate sites. A cloud-based analysis platform like GPAS addresses bioinformatics bottlenecks and facilitates collaboration in pathogen surveillance, enhancing epidemic and pandemic preparedness.

Omicron subvariants of SARS-CoV-2 may resist vaccine- or infection-induced immunity thereby increasing the risk of reinfections in previously infected persons. This study aimed to investigate the clinical severity and the average time to the onset of Omicron reinfection. This survey study collected clinical data on Omicron reinfection. Information on time of infection, reinfection interval, overall clinical presentation, and severity of infection was reported. The total prevalence of symptoms among 201 participants was significantly higher in the first infection (risk difference (RD), 9.86%; 95% CI, 7.54-12.19]) compared to the second infection, and the hospitalization rate among all participants was significantly lower for the second infection than the primary infection (odds ratio (OR), 6.25; 95% CI, 2.158-24.71). The prevalence of symptoms compared with the first infection with pre-Omicron variants was similar to that of the first infection with the Omicron variant (RD, 2.56%; 95% CI, -6.14-1.01). However, the hospitalization rate for pre-Omicron primary infection was significantly higher (OR, 6.76; 95% CI, 2.87-15.87]) than that observed with Omicron variants. The severity of the primary infection and of a pre-Omicron variant was greater than that of a secondary infection or with an Omicron variant.

In a randomized, pre-post intervention study, we evaluated the influence of a large language model (LLM) generative AI system on accuracy of physician decision-making and bias in healthcare. 50 US-licensed physicians reviewed a video clinical vignette, featuring actors representing different demographics (a White male or a Black female) with chest pain. Participants were asked to answer clinical questions around triage, risk, and treatment based on these vignettes, then asked to reconsider after receiving advice generated by ChatGPT+ (GPT4). The primary outcome was the accuracy of clinical decisions based on pre-established evidence-based guidelines. Results showed that physicians are willing to change their initial clinical impressions given AI assistance, and that this led to a significant improvement in clinical decision-making accuracy in a chest pain evaluation scenario without introducing or exacerbating existing race or gender biases. A survey of physician participants indicates that the majority expect LLM tools to play a significant role in clinical decision making.

Background: Syndromic surveillance utilising primary health care (PHC) data is a valuable tool for early outbreak detection, as demonstrated in the potential to identify COVID-19 outbreaks. However, the potential of such an early warning system in the post-COVID-19 era remains largely unexplored. Methods: We analysed PHC encounter counts due to respiratory complaints registered in the Brazilian database of the Universal Health System between January and July 2023. We applied EARS (variation C1-C2-C3) and EVI to estimate the weekly thresholds. An alarm was determined when the number of encounters exceeded the week-specific threshold. We used data on hospitalisation due to respiratory disease to classify weeks in which the number of cases surpassed predetermined thresholds as anomalies. We compared EARS and EVI's efficacy in anticipating anomalies. Findings: A total of 119 anomalies were identified across 116 immediate regions during the study period. The EARS-C2 presented the highest early alarm rate, with 81/119 (68%) early alarms, and C1 the lowest, with 71 (60%) early alarms. The lowest true positivity was the EARS-C1 118/1354 (8.7%) and the highest EARS-C3 99/856 (11.6%). Conclusion: Routinely collected PHC data can be successfully used to detect respiratory disease outbreaks in Brazil. Syndromic surveillance enhances timeliness in surveillance strategies, albeit with lower specificity. A combined approach with other strategies is essential to strengthen accuracy, offering a proactive and effective public health response against future outbreaks.

The biological mechanisms through which most non-protein-coding genetic variants affect disease risk are unknown. To investigate the gene-regulatory cascades that ensue from these variants, we mapped blood gene expression and splicing quantitative trait loci (QTLs) through bulk RNA-sequencing in 4,732 participants, and integrated these data with protein, metabolite and lipid QTLs in the same individuals. We identified cis-QTLs for the expression of 17,233 genes and 29,514 splicing events (in 6,853 genes). Using colocalization analysis, we identified 3,430 proteomic and metabolomic traits with a shared association signal with either gene expression or splicing. We quantified the relative contribution of the genetic effects at loci with shared etiology through statistical mediation, observing 222 molecular phenotypes significantly mediated by gene expression or splicing. We uncovered gene-regulatory mechanisms at GWAS disease loci with therapeutic implications, such as WARS1 in hypertension, IL7R in dermatitis and IFNAR2 in COVID-19. Our study provides an open-access and interactive resource of the shared genetic etiology across transcriptional phenotypes, molecular traits and health outcomes in humans (https://IntervalRNA.org.uk).

Predicting distant recurrence of endometrial cancer (EC) is crucial for personalized adjuvant treatment. The current gold standard of combined pathological and molecular profiling is costly, hampering implementation. We developed HECTOR (Histopathology-based Endometrial Cancer Tailored Outcome Risk), a multimodal deep learning prognostic model using hematoxylin-and-eosin-stained whole-slide-images and tumor stage as input, on 1,912 patients from seven EC cohorts including the PORTEC-1/-2/-3 randomized trials. HECTOR demonstrated C-indices in internal (n = 353) and external (n = 151) test sets of 0.788 and 0.816 respectively, outperforming the current gold-standard, and identified patients with markedly different outcomes (10-year distant recurrence-free probabilities of 97.0%, 77.7% and 58.1% for HECTOR low, intermediate and high risk groups). HECTOR also predicted adjuvant chemotherapy benefit better than current methods. Morphological and genomic feature extraction identified correlates of HECTOR risk groups, some with therapeutic potential. HECTOR improves on the current gold-standard and may help delivery of personalized treatment in EC.

Colorectal adenomas (CRA) are precursor lesions of the colon that may progress to adenocarcinomas, with patients currently categorized into risk groups by morphological features. We aimed to establish a molecular feature-based risk allocation framework towards improved patient stratification. Deep Visual Proteomics (DVP) is a novel approach that combines image-based artificial intelligence with automated microdissection and ultra-high sensitive mass spectrometry. Here we used DVP on formalin-fixed, paraffin-embedded (FFPE) CRA tissues from nine patients, immunohistologically stained for Caudal-type homeobox 2 (CDX2), a protein implicated in colorectal cancer, enabling the characterization of cellular heterogeneity within distinct tissue regions and across patients. DVP seamlessly integrated with current pathology workflows and equipment, identifying DMBT1, MARCKS and CD99 as correlated with disease recurrence history, making them potential markers of risk stratification. DVP uncovered a metabolic switch towards anaerobic glycolysis in areas of high dysplasia, which was specific for cells with high CDX2 expression. Our findings underscore the potential of spatial proteomics to refine early-stage detection and contribute to personalized patient management strategies and provided novel insights into metabolic reprogramming.

Congenital heart disease (CHD) is the most common congenital anomaly. Non-canonical splice-disrupting variants are not routinely evaluated by clinical tests. Algorithms including SpliceAI predict such variants, but are not specific to cardiac-expressed genes. Whole genome (WGS) (n=1083) and myocardial RNA-Sequencing (RNA-Seq) (n=114) of CHD cases was used to identify splice-disrupting variants. Using features of variants confirmed to affect splicing in myocardial RNA, we trained a machine learning model that outperformed SpliceAI for predicting cardiac-specific splice-disrupting variants (AUC 0.92 vs 0.66), and was independently validated in 43 cardiomyopathy probands (AUC 0.88 vs 0.64). Application of this model to 971 CHD WGS samples identified 9% patients with splice-disrupting variants in CHD genes. Forty-one% of predicted splice-disrupting variants were deeply intronic. The burden of variants in CHD genes was higher in cases compared with 2,570 controls. Our model improved genetic yield by identifying splice-disrupting variants that are not evaluated by routine tests.

How can one study a criminal organisation that, as one of its most basic principles, denies its own existence? To this end, the political anthropologist Deborah Puccio-Den has developed a new paradigm: the anthropology of silence.

Alors que le développement de l’intelligence artificielle (IA) va réclamer toujours plus d’énergie, comment limiter son impact sur le changement climatique ?

Menée au Japon à partir des données d'une enquête réalisée auprès de 1 084 professionnels de santé, cette étude analyse l’association entre les connaissances des médecins en matière de vaccination et l’administration ou la recommandation du vaccin contre le papillomavirus humain (HPV) en l’absence de recommandations gouvernementales

Menée à l'aide de lignées cellulaires d'adénocarcinome colorectal et d'adénocarcinome du poumon, cette étude démontre que, selon les mutations présentent sur les gènes KRAS et/ou PIK3CA des cellules cancéreuses, l'inhibition de la protéine SOS1 et la délétion de KSR1 peuvent augmenter l'efficacité des inhibiteurs de MEK et prévenir le risque de résistance thérapeutique

Menée à partir de données portant sur 107 patients atteints d'un carcinome urothélial HER2+ de stade localement avancé ou métastatique et inclus dans deux essais de phase II, cette étude évalue l'efficacité, du point de vue du taux de réponse objective, et la toxicité du disitamab védotin (un conjugué anticorps-médicament ciblant HER2) après l'échec d'au moins une ligne de chimiothérapie

Mené sur 41 patients atteints d'un cancer métastatique de la prostate résistant à la castration, cet essai de phase IB détermine la dose maximale tolérée de CC-115 (un inhibiteur de mTORC1/2 et de l'ADN-PK) en combinaison avec l'enzalutamide