Risultati per: Passo 12. Ripulire in modo mirato le cartelle cliniche degli assisiti

Circulation, Volume 148, Issue Suppl_1, Page A16682-A16682, November 6, 2023. Introduction:Electrocardiography (ECG) can be easily obtained at a low cost and includes voltage and time interval representing heart conditions. We hypothesized that artificial intelligence (AI) detects a subtle abnormality in 12-lead ECG and may predict individual mortality.Methods:Among 502,411 population in UK Biobank, 42,096 individuals had 12-lead ECG from 2013 to 2022. Among 41,572 survival group, after adjusting the following inclusion criteria; normal sinus rhythm, age under 60 years, PR interval 120~200ms, QTc interval 350~460ms, and QRS duration 70~100ms, 4,512 individuals were enrolled in this study. We developed and tested convolutional neural network (CNN) model to predict all cause death, cardiovascular (CV) death, or sudden cardiac arrest (SCA). The study population were divided into train (80%), validation (10%), and test (20%) set.Results:Among 4,512 patients with median 3.7 years [IQR; 2.7-5.1] of follow-up, the rate of all-cause mortality was 11.6% (524). In overall study population, median age was 55.5 years and proportion of male sex was 42.2%. The patients with all-cause death were older (p

Circulation, Volume 148, Issue Suppl_1, Page A12401-A12401, November 6, 2023. Background:Anticoagulant RCTs are thought to have enrolled younger and less comorbid patients with atrial fibrillation (AF) compared to the general population. We developed a representation score summarizing patient characteristics to describe how well RCT participants with AF reflect a nationally representative cohort.Methods:We studied adults >=65 years old with AF by harmonizing two data sources: (1) patient-level data from 12 landmark RCTs testing anticoagulants vs. placebo or antiplatelets from the Atrial Fibrillation Investigators (AFI) consortium and (2) the Health and Retirement Study AF cohort (HRS-AF), a representative cohort of older adults with AF in the U.S. We fit a logistic regression model to estimate the probability of inclusion in the HRS-AF cohort in the pooled sample using age, height, weight, gender, heart failure, hypertension, diabetes, prior stroke, and prior myocardial infarction. This estimate, the Trial Benchmark Score, reflected the probability of belonging to the HRS-AF cohort and ranged from 0 to 1, with higher scores reflecting a greater likelihood of belonging to the HRS-AF cohort. We plotted the distribution of scores for HRS-AF and AFI participants and compared the mean scores using a t-test.Results:Compared to the HRS-AF cohort (n=3542), AFI participants (n=7933) were younger (72 vs. 76yrs, standardized mean difference [SMD] -0.7), more frequently male (64% vs. 46%, SMD 0.3), and had a lower likelihood of prior stroke (19% vs. 23%, SMD -0.4). The mean Trial Benchmark Score differed significantly between the two cohorts (HRS-AF mean 0.47 vs. AFI mean 0.23, p0.47 (the HRS-AF mean score).Conclusion:Differences in the Trial Benchmark Scores distributions indicate a substantial difference in the distribution of observable characteristics and that RCT participants were not fully representative of the benchmark population.

Circulation, Volume 148, Issue Suppl_1, Page A17094-A17094, November 6, 2023. Introduction:As echocardiographic screening is limited by access to technology, structural heart disease (SHD) is often diagnosed after the development of clinical symptoms. To enable automated and accessible screening of SHD, we developed and validated a deep-learning model for 12-lead electrocardiograms (ECGs) for various screening populations.Methods:We used 12-lead ECGs with paired TTEs at the Yale New Haven Hospital (2015-2021) to develop convolutional neural networks for detecting SHD. SHD was defined as the presence of any one of the following on a transthoracic echocardiogram (TTE) performed within 30 days of the ECG: hypertrophic cardiomyopathy (IVSd > 1.5cm and diastolic dysfunction), LV ejection fraction < 40%, or severe left-sided valvular disease (aortic/mitral stenosis or regurgitation). We developed an ensemble XGBoost model based on predictions for individual SHDs and patient age and sex as a single screen across all SHDs. We also simulated the model performance across cohorts with varying disease prevalence.Results:The model was developed in 456,927 ECGs/118,623 individuals (66.5±16.0 years, 45.6% women, 16.5% Black) and validated in 13,181 ECGs/13,181 individuals (65.1±17.3 years, 49.5% women, 14.5% Black). In the held-out validation set, the ensemble XGBoost model achieved an AUROC of 0.92 (95% CI: 0.91-0.94) and an AUPRC of 0.64 (95% CI: 0.57-0.70), with a sensitivity of 85% and specificity of 88%. The AUROCs for the individual disease models ranged from 0.72-0.95. (Panel A) In the test set with 10% disease prevalence, the ensemble model had a PPV 44% and an NPV of 98%. (Panel B) In simulated cohorts with 5% and 20% disease prevalence, the model had reached NPV & PPV of 99% & 27%, and 98% & 64%, respectively. (Panel C)Conclusion:We developed a novel ensemble deep-learning model for detecting several SHDs directly from ECGs with high PPV and NPV. This approach represents a robust, scalable, and accessible modality for automated SHD screening.

Circulation, Volume 148, Issue Suppl_1, Page A13690-A13690, November 6, 2023. Introduction:Diagnostic criterion of left ventricular hypertrophy (LVH) on 12-leads electrocardiogram (ECG) were established. We verified them comparing with artificial intelligence (AI) method.Hypothesis:Machine learning on 12-leads ECG show higher diagnostic performance comparing with historical criterion.Methods:First, consecutive 60 patients with LVH were recruited, and one to one matching with age and sex to patients with normal cardiac function was performed. Finally, 120 patients (69.6 ± 12.6years, 38men per group) were enrolled. LVH was defined as at least one LV wall (septum, posterior wall, apex) showed thickness over 15mm on ultrasound echocardiography. No sinus rhythm, and wide QRS cases were excluded.Results:By logistic regression analysis, 77 significant predictors were extracted. Among historical criterion, Cornell voltage showed high accuracy (0.783) and area under receiver operating characteristics curve analysis (AUROC; 0.808). Conversely, among AI methods, light gradient boosting machine demonstrated higher accuracy (0.843) and random forest method higher AUROC (0.882). V2/V2 S-wave amplitude and I/V5 T-wave amplitude played essential roles to build the AI models.Conclusions:AI diagnosis on ECG for LVH showed powerful diagnostic performance comparing historical criterion.

Circulation, Volume 148, Issue Suppl_1, Page A16503-A16503, November 6, 2023. Introduction:Left coronary dominance is associated with worse clinical outcomes in the setting of coronary artery disease (CAD). Little is known about the determinants of dominance, including whether it is solidified in utero or sometime after birth.Hypothesis:Investigating the genetic determinants of dominance will identify new arteriogenesis pathways targetable for enhancing coronary artery growth and collateralization in humans.Methods:We conducted a stratified multi-population genome-wide association study of dominance using REGENIE and TopMed-imputed genotypes available in 43813 White, 9532 Black, and 3550 Hispanic participants of the Million Veteran Program (MVP) who had undergone a cardiac catheterization. We modelled left and co-dominant combined vs. right, as well as left vs. right dominance, adjusting for sex and 10 genetic principal components. We also explored whether dominance and CAD were genetically correlated using LD score regression. Lastly, we sought to validate compelling population genetic signals in mice using whole organ imaging of the heart, which allows for the quantification of coronary anatomy and variation.Results:Thirteen loci reached genome wide significance (GWS). The most intriguing was a top hit located downstream of C-X-C Motif Chemokine Ligand 12 (CXCL12) which, remarkably, reached GWS in both White and Black Veterans. While the CXCL12 signal robustly colocalized with the signal in this region for CAD (COLOC PPH4: 87.1%), the genome wide genetic correlation of dominance with CAD was otherwise modest in both MVP (rg=-0.18, p=0.007) and CardiogramplusC4D (rg=-0.16, p=0.018). To gain evidence for causality, we modeled dominance in Cxcl12-deficient mice (n=64 wildtype; n=62 heterozygous). Murine coronary arteries develop in a field of Cxcl12 expression and choose right or left dominance during embryogenesis, a time when we found human dominance to also be evident. Reminiscent of our human GWAS, dominance was skewed away from the common phenotype in Cxcl12 heterozygous mice (p=0.038).Conclusions:CXCL12 is a primary determinant of coronary artery dominance in humans and mice. The modest negative genetic correlation between CAD and dominance supports a developmental component to CAD susceptibility.

Objective
To examine the use of CT, emergency department (ED)-presentation and hospitalisation and in 12 months before and after a diagnosis of cancer.

Design
Population-based retrospective cohort study.

Setting
West Australian linked administrative records at individual level.

Participants
104 009 adults newly diagnosed with cancer in 2004–2014.

Main outcome measures
CT use, ED presentations, hospitalisations.

Results
As compared with the rates in the 12th month before diagnosis, the rate of CT scans started to increase from 2 months before diagnosis with an increase in both ED presentations and hospitalisation from 1 month before the diagnosis. These rates peaked in the month of diagnosis for CT scans (477 (95% CI 471 to 482) per 1000 patients), and for hospitalisations (910 (95% CI 902 to 919) per 1000 patients), and the month prior to diagnosis for ED (181 (95% CI 178 to 184) per 1000 patients) then rapidly reduced after diagnosis but remained high for the next 12 months. While the patterns of the health services used were similar between 2004 and 2014, the rate of the health services used during after diagnosis was higher in 2014 versus 2004 except for CT use in patients with lymphohaematopoietic cancer with a significant reduction.

Conclusion
Our results showed an increase in demand for health services from 2 months before diagnosis of cancer. Increasing use of health services during and post cancer diagnosis may warrant further investigation to identify factors driving this change.

Virus H5N1 riscontrato nelle isole Falkland

Dall’inizio dell’anno sono 11 i morti confermati per la malattia

This study compares data on the symptoms of posttraumatic stress disorder (PTSD) among family members of patients with acute respiratory distress syndrome (ARDS) caused by COVID-19 vs non–COVID-19 ARDS.

Sono 7,4 milioni le famiglie che ne fanno il pieno nel carrello

Grazie a diagnosi tempestiva e accesso alla profilassi Prep

Annals of Internal Medicine, Ahead of Print.

Annals of Internal Medicine, Ahead of Print.

San Raffaele Roma, Italia prima al mondo per pazienti coinvolti

Annals of Internal Medicine, Ahead of Print.