ObjectiveTo evaluate the real-life use of a modified Gillmore algorithm with a "one-stop-shop” approach, bone scintigraphy (BS), a monoclonal gammopathy test (GT), a salivary gland biopsy (SGB), and genetic testing performed at the same time for the diagnosis of cardiac amyloidosis at the French National Reference Centre for Cardiac Amyloidosis (Henri Mondor Hospital, Créteil, France).MethodsThis retrospective cohort study included a total of 1222 patients with suspected amyloidosis who underwent BS and GT between June 2008 and May 2019.ResultsOf 1222 patients, 349 had no cardiac uptake on BS and negative GT (BS?/GT?), 276 were BS?/GT positive (GT+), 420 patients were BS+/GT?, and 177 were BS+/GT+. Our one-stop-shop check-up enabled us to diagnose 892 (72.9%) patients; 330 (27.0%) patients required additional examinations, such as mass spectrometry and/or a cardiac biopsy. This subset notably included 112 patients with amyloid light chain amyloidosis. More than 64% of the patients with transthyretin amyloidosis or another type of amyloidosis were diagnosed during the one-stop shop visit. Sensitivity and specificity of BS for transthyretin amyloidosis diagnosis was 99% and 96%, respectively. For amyloid light chain diagnosis, sensitivity and specificity were 100% and 76%, respectively, for GT and 54% and 100%, respectively, for SGB. Of 910 transthyretin genetic tests, 205 (17%) detected mutations.ConclusionThe results of our real-life cohort study confirmed the ability of a one-stop-shop approach with a modified Gillmore algorithm to diagnose cardiac amyloidosis and the interest of simultaneous testing for earlier diagnosis. The SGB has diagnostic value because it is easy, quick, and less invasive than a cardiac biopsy. 相似文献
Whether diagnostic timing in transthyretin (TTR) cardiac amyloidosis (CA) predisposes patients to worse outcomes is unresolved. We aimed to describe the long-term association of diagnostic timing (time from first onset of symptoms consistent with CA leading to medical contact to definitive diagnosis) with mortality in patients with wild-type TTR-CA (ATTRwt-CA). Overall, we reviewed the medical records of 160 patients seen at a tertiary care amyloidosis unit from January 1, 2016, to January 1, 2020 (median [interquartile range] follow-up, 21 [10 to 34] months), and compared them by survival. Median diagnostic timing was 4 (2 to 12) months and was longer in nonsurvivors (9 [3 to 15] vs 3 [1 to 7] months; P<.001). Patients diagnosed 6 or more months after symptom onset had higher mortality, with a median survival of 30 months (95% CI, 22 to 37 months). On Cox multivariable analysis, timing was independently associated with all-cause mortality (hazard ratio per month increase, 1.049 [95% CI, 1.017 to 1.083]) together with age at diagnosis, disease stage, New York Heart Association class, and coronary artery disease. In conclusion, diagnostic timing of ATTRwt-CA is associated with mortality. Timely diagnosis is warranted whenever “red flags” are present. 相似文献
Better association of 3D echocardiography–derived RVEF versus conventional metrics of RV systolic function with adverse clinical outcomes: a meta-analysis of 10 studies.
Patients with stage 3 and stage 4 CKD demonstrate alterations in LV GLS, LVMI, E/e′, LAVI, and LASr but had normal LVEF. Each of these parameters was evaluated using reported normal values as a cutoff (normal indicated as green) in the figure. Left atrial reservoir strain was the strongest predictor of death and MACE and the only echocardiographic parameter that predicted adverse events.
Graphical Abstract Prognostic value of RA strain in patients with PH. Left panels show two examples RA strain from patients with PH. Top left shows a survivor with RA peak strain of 49%; bottom left shows a nonsurvivor with peak RA strain of 22%. Right panel shows Kaplan-Meier plots of patients with PH grouped by RA strain above and below 25%, demonstrating a significant association with survival.
ObjectiveTo develop an artificial intelligence (AI)–based tool to detect cardiac amyloidosis (CA) from a standard 12-lead electrocardiogram (ECG).MethodsWe collected 12-lead ECG data from 2541 patients with light chain or transthyretin CA seen at Mayo Clinic between 2000 and 2019. Cases were nearest neighbor matched for age and sex, with 2454 controls. A subset of 2997 (60%) cases and controls were used to train a deep neural network to predict the presence of CA with an internal validation set (n=999; 20%) and a randomly selected holdout testing set (n=999; 20%). We performed experiments using single-lead and 6-lead ECG subsets.ResultsThe area under the receiver operating characteristic curve (AUC) was 0.91 (CI, 0.90 to 0.93), with a positive predictive value for detecting either type of CA of 0.86. By use of a cutoff probability of 0.485 determined by the Youden index, 426 (84%) of the holdout patients with CA were detected by the model. Of the patients with CA and prediagnosis electrocardiographic studies, the AI model successfully predicted the presence of CA more than 6 months before the clinical diagnosis in 59%. The best single-lead model was V5 with an AUC of 0.86 and a precision of 0.78, with other single leads performing similarly. The 6-lead (bipolar leads) model had an AUC of 0.90 and a precision of 0.85.ConclusionAn AI-driven ECG model effectively detects CA and may promote early diagnosis of this life-threatening disease. 相似文献
