Impact of atherosclerosis imaging-quantitative computed tomography on diagnostic certainty, downstream testing, coronary revascularization, and medical therapy: the CERTAIN study.

AIMS: The incremental impact of atherosclerosis imaging-quantitative computed tomography (AI-QCT) on diagnostic certainty and downstream patient management is not yet known. The aim of this study was to compare the clinical utility of the routine implementation of AI-QCT versus conventional visual coronary CT angiography (CCTA) interpretation. METHODS AND RESULTS: In this multi-centre cross-over study in 5 expert CCTA sites, 750 consecutive adult patients referred for CCTA were prospectively recruited. Blinded to the AI-QCT analysis, site physicians established patient diagnoses and plans for downstream non-invasive testing, coronary intervention, and medication management based on the conventional site assessment. Next, physicians were asked to repeat their assessments based upon AI-QCT results. The included patients had an age of 63.8 ± 12.2 years; 433 (57.7%) were male. Compared with the conventional site CCTA evaluation, AI-QCT analysis improved physician's confidence two- to five-fold at every step of the care pathway and was associated with change in diagnosis or management in the majority of patients (428; 57.1%; P < 0.001), including for measures such as Coronary Artery Disease-Reporting and Data System (CAD-RADS) (295; 39.3%; P < 0.001) and plaque burden (197; 26.3%; P < 0.001). After AI-QCT including ischaemia assessment, the need for downstream non-invasive and invasive testing was reduced by 37.1% (P < 0.001), compared with the conventional site CCTA evaluation. Incremental to the site CCTA evaluation alone, AI-QCT resulted in statin initiation/increase an aspirin initiation in an additional 28.1% (P < 0.001) and 23.0% (P < 0.001) of patients, respectively. CONCLUSION: The use of AI-QCT improves diagnostic certainty and may result in reduced downstream need for non-invasive testing and increased rates of preventive medical therapy.

Association between red blood cell distribution width and the prognosis of brain death in patients with a Glasgow Coma Scale < 6.

Red blood cell distribution width (RDW) has been reported as a meaningful prognostic factor in various diseases. Our study compared patients' RDW levels and prognosis at admission and discharge time. A total of 128 patients 77 patients who suffered brain death (subject group), and 51 patients who were discharged from the hospital (control group) with GCS ≤ 6 were recruited from 60 hospitals for this study. Demographical data and RDW measurements in these patients at admission time and brain death/discharge time were extracted into two groups. 46 (35.9%) patients were females and 82 patients (64.1%) were males with a median age of 36 years old. A significant difference in baseline characteristics of GCS (P < 0.001), RDW at admission time (P < 0.001), and RDW at discharge or brain death time (P < 0.001) were noted between the two groups. In the overall population, RDW at admission time had a median value of 13.75% and was positively correlated with gender (P < 0.04, rs = 0.582) and age (P < 0.023, rs = - 0.201). Initially, there were no significant differences in RDW upon admission. However, upon discharge, although the RDW in the control group was not significant (P < 0. 1), the RDW level at the time of brain death was notably 0.45 fold higher (P = 0.001) compared to the time of admission. The standardized residuals at the two-time points showed an approximately normal distribution. The most effective RDW cut-off in Brain death was determined as 14.55. Based on the findings, using RDW as a prognostic factor has a sensitivity of 0.468 and a specificity of 0.137 in diagnosing brain death. RDW biomarker is a simple and inexpensive laboratory test that may be seen as a valuable perspective for initial patient evaluation. RDW is a powerful marker for the prognosis of brain death in patients with a GCS ≤ 6 at admission time, in order to identify a subset of patients who may require more aggressive management in the trauma center.

The Impact of Heparin Therapy in Deceased Donors on Early Graft Survival for Kidney and Liver Recipients: A Clinical Trial Study.

BACKGROUND: Significant hemodynamic, hormonal, and metabolic impairment of a brain-dead organ donor is often associated with the deterioration of graft viability. This study aimed to compare the effect of heparin therapy as a therapeutic dose after brain death confirmation on early graft survival in kidney and liver recipients. METHOD AND MATERIALS: The deceased donors were sorted into two groups based on their D-dimer level. After confirming brain death, one group was given a heparin injection (case group), while the other group did not receive any heparin (control group). A total of 71 brain death donors and matched kidney and liver transplants were included in the case group. A total of 43 brain death donors and matched kidney and liver transplants were included in the control group. A total of 5000 units of heparin were administered every 6 hours to the deceased donor case group. RESULTS: The mean age of the case and control groups were 36.27 ± 16.13 and 36.15 ± 18.45, respectively. An independent t test showed that there were no differences between the number of procured organs in both groups (p = 0.29). There was no significant difference between the graft survival rate and the doses of heparin injection to the liver recipients (p = 0.06). However, a significant difference was revealed between the graft survival rate and the dose of heparin injection (p = 0.004) in kidney recipients. CONCLUSIONS: The data suggest that administering low therapeutic doses of heparin to donors before organ donation may potentially prevent thrombosis and provide a protective benefit. We showed that heparin therapy had no significant effect on the number of donated organs and graft survival.

Trends in organ donation and transplantation over the past eighteen years in Iran.

BACKGROUND: This article will review the trends in organ donation over the past 18 years in Iran. MATERIAL AND METHODS: All donation and transplantation statistics were extracted by reviewing the Organ Procurement and Transplantation database of the Ministry of Health of Iran from 2002 to 2019. RESULTS: Iran's national deceased donation rate from 2002 to 2019 increased 19.06-fold from .75 to 14.3 per million population (PMP). After the beginning of the COVID-19 pandemic, the rate of organ donation in Iran decreased significantly. Although 1 year after the onset of the pandemic, due to the widespread adoption of COVID19 vaccination, the rate of organ donation began to increase again, this system is still under performing. During the years under examination, the rate of deceased kidney donation increased significantly compared to living kidney donation and reached up to 2001 kidney transplantations in 2021. From 2002 to 2019, the rate of liver transplants increased to 12.8. Likewise, the rate of heart transplants increased 8.4-fold, from 15 to 126 cases during the same time. CONCLUSSION: Although a personal choice, the process of organ donation involves medical, legal, ethical, organizational, and social aspects. The trend in increasing donation rates over the past years can be attributed to multiple influences, which include rigorous team efforts in the organ donation and transplantation systems, in addition to creating a donation culture and promoting donation through media platforms. Moreover, we can say that the rising rates of deceased donor transplantation also can drive down rates of commercial living donor transplantation.

Outpatient Cardiovascular Rehabilitation Registry in Iran: The First Rehabilitation Registry Experience at EMR.

INTRODUCTION: The collected information includes demographic profile, medical history, physical examination, patient risk factors, anthropometric evaluation, medications, echocardiographic results, and exercise testing of all patients who participated in the outpatient cardiac rehabilitation program in Cardiac Rehabilitation Department since 1996 until now. Each patient was assigned an electronic code by which the patient's information could be identified. Subsequently, standard questionnaires were used, such as International physical activity questionnaire (IPAQ) to assess physical activity, MAC NEW to assess the quality of life, Spielberg to measure anxiety, Beck to assess depression, and nutritional questionnaires. RESULTS: The findings were recorded, and the data were analyzed by the web and SPSS software. For all patients, the forms were filled based on a number of variables including backgrounds, registration components, type of referral, diagnosis of underlying heart disease, methods of data collection and entry, details of the educational program, return to work, psychiatric condition, drug regimen, clinical condition, echocardiography findings, functional capacity and exercise test response, smoking status, nutritional habits, and finally their 5-year follow-up for events and re-hospitalization. CONCLUSION: It is necessary for the authors to establish a cardiac rehabilitation registration that can properly display care quality indicators and collect and report standard data from different nations to improve the quality of cardiac rehabilitation services and identify weaknesses.

Association of fruits, vegetables, and fiber intake with COVID-19 severity and symptoms in hospitalized patients: A cross-sectional study.

Background and aims: Fruits and vegetables are rich in fiber and a good source of anti-inflammatory and immune-boosting vitamins, minerals, and antioxidants. We investigated the association between fruits, vegetables, and fiber intake and severity of COVID-19 and related symptoms in hospitalized patients. Methods: A total of 250 COVID-19 hospitalized patients aged 18 to 65 years were recruited for this cross-sectional study in Kashan, Iran, between June and September of 2021. Dietary intakes were assessed using an online validated 168-item food frequency questionnaire (FFQ). COVID-19 severity and symptoms were evaluated using the National Institutes of Health (NIH) COVID-19 Treatment Guidelines. Moreover, we examined COVID-19 symptoms, inflammatory biomarkers, and additional factors. Results: The mean age of participants was 44.2 ± 12.1 years, and 46% had severe COVID-19. Patients with higher consumption of fruits (OR: 0.28; 95% CI: 0.14-0.58, P-trend <0.001), vegetables (OR: 0.33; 95% CI: 0.16-0.69, P-trend <0.001), and dietary fiber (OR: 0.25; 95% CI: 0.12-0.53, P-trend <0.001) had lower odds of having severe COVID-19. In addition, they had shorter hospitalization and convalescence periods, lower serum C-reactive protein (CRP), and a reduced risk of developing COVID-19 symptoms such as sore throat, nausea and vomiting, dyspnea, myalgia, cough, weakness, fever, and chills. Conclusion: Higher consumption of fruits, vegetables, and fiber was inversely linked with COVID-19 severity, clinical symptoms, hospitalization and convalescence duration, and CRP concentrations. The results should be interpreted with caution in light of the limitations, and prospective cohort studies are required to further evaluate these findings.

Interobserver variability among expert readers quantifying plaque volume and plaque characteristics on coronary CT angiography: a CLARIFY trial sub-study.

BACKGROUND: The difference between expert level (L3) reader and artificial intelligence (AI) performance for quantifying coronary plaque and plaque components is unknown. OBJECTIVE: This study evaluates the interobserver variability among expert readers for quantifying the volume of coronary plaque and plaque components on coronary computed tomographic angiography (CCTA) using an artificial intelligence enabled quantitative CCTA analysis software as a reference (AI-QCT). METHODS: This study uses CCTA imaging obtained from 232 patients enrolled in the CLARIFY (CT EvaLuation by ARtificial Intelligence For Atherosclerosis, Stenosis and Vascular MorphologY) study. Readers quantified overall plaque volume and the % breakdown of noncalcified plaque (NCP) and calcified plaque (CP) on a per vessel basis. Readers categorized high risk plaque (HRP) based on the presence of low-attenuation-noncalcified plaque (LA-NCP) and positive remodeling (PR; ≥1.10). All CCTAs were analyzed by an FDA-cleared software service that performs AI-driven plaque characterization and quantification (AI-QCT) for comparison to L3 readers. Reader generated analyses were compared among readers and to AI-QCT generated analyses. RESULTS: When evaluating plaque volume on a per vessel basis, expert readers achieved moderate to high interobserver consistency with an intra-class correlation coefficient of 0.78 for a single reader score and 0.91 for mean scores. There was a moderate trend between readers 1, 2, and 3 and AI with spearman coefficients of 0.70, 0.68 and 0.74, respectively. There was high discordance between readers and AI plaque component analyses. When quantifying %NCP v. %CP, readers 1, 2, and 3 achieved a weighted kappa coefficient of 0.23, 0.34 and 0.24, respectively, compared to AI with a spearman coefficient of 0.38, 0.51, and 0.60, respectively. The intra-class correlation coefficient among readers for plaque composition assessment was 0.68. With respect to HRP, readers 1, 2, and 3 achieved a weighted kappa coefficient of 0.22, 0.26, and 0.17, respectively, and a spearman coefficient of 0.36, 0.35, and 0.44, respectively. CONCLUSION: Expert readers performed moderately well quantifying total plaque volumes with high consistency. However, there was both significant interobserver variability and high discordance with AI-QCT when quantifying plaque composition.

CT ​Evaluation ​by ​Artificial ​Intelligence ​for ​Atherosclerosis, Stenosis and Vascular ​Morphology ​(CLARIFY): ​A ​Multi-center, international study.

BACKGROUND: Atherosclerosis evaluation by coronary computed tomography angiography (CCTA) is promising for coronary artery disease (CAD) risk stratification, but time consuming and requires high expertise. Artificial Intelligence (AI) applied to CCTA for comprehensive CAD assessment may overcome these limitations. We hypothesized AI aided analysis allows for rapid, accurate evaluation of vessel morphology and stenosis. METHODS: This was a multi-site study of 232 patients undergoing CCTA. Studies were analyzed by FDA-cleared software service that performs AI-driven coronary artery segmentation and labeling, lumen and vessel wall determination, plaque quantification and characterization with comparison to ground truth of consensus by three L3 readers. CCTAs were analyzed for: % maximal diameter stenosis, plaque volume and composition, presence of high-risk plaque and Coronary Artery Disease Reporting & Data System (CAD-RADS) category. RESULTS: AI performance was excellent for accuracy, sensitivity, specificity, positive predictive value and negative predictive value as follows: >70% stenosis: 99.7%, 90.9%, 99.8%, 93.3%, 99.9%, respectively; >50% stenosis: 94.8%, 80.0%, 97.0, 80.0%, 97.0%, respectively. Bland-Altman plots depict agreement between expert reader and AI determined maximal diameter stenosis for per-vessel (mean difference -0.8%; 95% CI 13.8% to -15.3%) and per-patient (mean difference -2.3%; 95% CI 15.8% to -20.4%). L3 and AI agreed within one CAD-RADS category in 228/232 (98.3%) exams per-patient and 923/924 (99.9%) vessels on a per-vessel basis. There was a wide range of atherosclerosis in the coronary artery territories assessed by AI when stratified by CAD-RADS distribution. CONCLUSIONS: AI-aided approach to CCTA interpretation determines coronary stenosis and CAD-RADS category in close agreement with consensus of L3 expert readers. There was a wide range of atherosclerosis identified through AI.