Mortality and major postoperative complications within 1 year after vascular surgery: a prospective cohort study.

INTRODUCTION: Patients undergoing vascular procedures are prone to developing postoperative complications affecting their short­term mortality. Prospective reports describing the incidence of long­term complications after vascular surgery are lacking. OBJECTIVES: We aimed to describe the incidence of complications 1 year after vascular surgery and to evaluate an association between myocardial injury after noncardiac surgery (MINS) and 1­year mortality. PATIENTS AND METHODS: This is a substudy of a large prospective cohort study Vascular Events in Noncardiac Surgery Patients Cohort Evaluation (VISION). Recruitment took place in 28 centers across 14 countries from August 2007 to November 2013. We enrolled patients aged 45 years or older undergoing vascular surgery, receiving general or regional anesthesia, and hospitalized for at least 1 night postoperatively. Plasma cardiac troponin T concentration was measured before the surgery and on the first, second, and third postoperative day. The patients or their relatives were contacted 1 year after the procedure to assess the incidence of major postoperative complications. RESULTS: We enrolled 2641 patients who underwent vascular surgery, 2534 (95.9%) of whom completed 1­year follow­up. Their mean (SD) age was 68.2 (9.8) years, and the cohort was predominantly male (77.5%). The most frequent 1­year complications were myocardial infarction (224/2534, 8.8%), amputation (187/2534, 7.4%), and congestive heart failure (67/2534, 2.6%). The 1­year mortality rate was 8.8% (223/2534). MINS occurred in 633 patients (24%) and was associated with an increased 1­year mortality (hazard ratio, 2.82; 95% CI, 2.14-3.72; P <0.001). CONCLUSIONS: The incidence of major postoperative complications after vascular surgery is high. The occurrence of MINS is associated with a nearly 3­fold increase in 1­year mortality.

One-year Outcomes after Discharge from Noncardiac Surgery and Association between Predischarge Complications and Death after Discharge: Analysis of the VISION Prospective Cohort Study.

BACKGROUND: In previous analyses, myocardial injury after noncardiac surgery, major bleeding, and sepsis were independently associated with most deaths in the 30 days after noncardiac surgery, but most of these deaths occurred during the index hospitalization for surgery. The authors set out to describe outcomes after discharge from hospital up to 1 yr after inpatient noncardiac surgery and associations between predischarge complications and postdischarge death up to 1 yr after surgery. METHODS: This study was an analysis of patients discharged after inpatient noncardiac surgery in a large international prospective cohort study across 28 centers from 2007 to 2013 of patients aged 45 yr or older followed to 1 yr after surgery. The study estimated (1) the cumulative postdischarge incidence of death and other outcomes up to a year after surgery and (2) the adjusted time-varying associations between postdischarge death and predischarge complications including myocardial injury after noncardiac surgery, major bleeding, sepsis, infection without sepsis, stroke, congestive heart failure, clinically important atrial fibrillation or flutter, amputation, venous thromboembolism, and acute kidney injury managed with dialysis. RESULTS: Among 38,898 patients discharged after surgery, the cumulative 1-yr incidence was 5.8% (95% CI, 5.5 to 6.0%) for all-cause death and 24.7% (95% CI, 24.2 to 25.1%) for all-cause hospital readmission. Predischarge complications were associated with 33.7% (95% CI, 27.2 to 40.2%) of deaths up to 30 days after discharge and 15.0% (95% CI, 12.0 to 17.9%) up to 1 yr. Most of the association with death was due to myocardial injury after noncardiac surgery (15.6% [95% CI, 9.3 to 21.9%] of deaths within 30 days, 6.4% [95% CI, 4.1 to 8.7%] within 1 yr), major bleeding (15.0% [95% CI, 8.3 to 21.7%] within 30 days, 4.7% [95% CI, 2.2 to 7.2%] within 1 yr), and sepsis (5.4% [95% CI, 2.2 to 8.6%] within 30 days, 2.1% [95% CI, 1.0 to 3.1%] within 1 yr). CONCLUSIONS: One in 18 patients 45 yr old or older discharged after inpatient noncardiac surgery died within 1 yr, and one quarter were readmitted to the hospital. The risk of death associated with predischarge perioperative complications persists for weeks to months after discharge.

Epidemiology of Motoric Cognitive Risk Syndrome in the Kerala Einstein Study: Protocol for a Prospective Cohort Study.

BACKGROUND: The southern India state of Kerala has among the highest proportion of older adults in its population in the country. An increase in chronic age-related diseases such as dementia is expected in the older Kerala population. Identifying older individuals early in the course of cognitive decline offers the best hope of introducing preventive measures early and planning management. However, the epidemiology and pathogenesis of predementia syndromes at the early stages of cognitive decline in older adults are not well established in India. OBJECTIVE: The Kerala Einstein Study (KES) is a community-based cohort study that was established in 2008 and is based in the Kozhikode district in Kerala state. KES aims to establish risk factors and brain substrates of motoric cognitive risk syndrome (MCR), a predementia syndrome characterized by the presence of slow gait and subjective cognitive concerns in individuals without dementia or disability. This protocol describes the study design and procedures for this KES project. METHODS: KES is proposing to enroll a sample of 1000 adults ≥60 years old from urban and rural areas in the Kozhikode district of Kerala state: 200 recruited in the previous phase of KES and 800 new participants to be recruited in this project. MCR is the cognitive phenotype of primary interest. The associations between previously established risk factors for dementia as well as novel risk factors (apathy and traumatic brain injury) and MCR will be examined in KES. Risk factor profiles for MCR will be compared between urban and rural residents as well as with individuals who meet the criteria for mild cognitive impairment (MCI). Cognitive and physical function, medical history and medications, sociodemographic characteristics, lifestyle patterns, and activities of daily living will be evaluated. Participants will also undergo magnetic resonance imaging and electrocardiogram investigations. Longitudinal follow-up is planned in a subset of participants as a prelude to future longitudinal studies. RESULTS: KES (2R01AG039330-07) was funded by the US National Institutes of Health in September 2019 and received approval from the Indian Medical Council of Research to start the study in June 2021. We had recruited 433 new participants from urban and rural sites in Kozhikode as of May 2023: 41.1% (178/433) women, 67.7% (293/433) rural residents, and 13.4% (58/433) MCR cases. Enrollment is actively ongoing at all the KES recruitment sites. CONCLUSIONS: KES will provide new insights into risk factors and brain substrates associated with MCR in India and will help guide future development of regionally specific preventive interventions for dementia. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/49933.

An Oral Galectin Inhibitor in COVID-19-A Phase II Randomized Controlled Trial.

BACKGROUND: SARS-CoV-2 vaccines play an important role in reducing disease severity, hospitalization, and death, although they failed to prevent the transmission of SARS-CoV-2 variants. Therefore, an effective inhibitor of galectin-3 (Gal-3) could be used to treat and prevent the transmission of COVID-19. ProLectin-M (PL-M), a Gal-3 antagonist, was shown to interact with Gal-3 and thereby prevent cellular entry of SARS-CoV-2 in previous studies. AIM: The present study aimed to further evaluate the therapeutic effect of PL-M tablets in 34 subjects with COVID-19. METHODS: The efficacy of PL-M was evaluated in a randomized, double-blind, placebo-controlled clinical study in patients with mild to moderately severe COVID-19. Primary endpoints included changes in the absolute RT-PCR Ct values of the nucleocapsid and open reading frame (ORF) genes from baseline to days 3 and 7. The incidence of adverse events, changes in blood biochemistry, inflammatory biomarkers, and levels of antibodies against COVID-19 were also evaluated as part of the safety evaluation. RESULTS: PL-M treatment significantly (p = 0.001) increased RT-PCR cycle counts for N and ORF genes on days 3 (Ct values 32.09 ± 2.39 and 30.69 ± 3.38, respectively) and 7 (Ct values 34.91 ± 0.39 and 34.85 ± 0.61, respectively) compared to a placebo treatment. On day 3, 14 subjects in the PL-M group had cycle counts for the N gene above the cut-off value of 29 (target cycle count 29), whereas on day 7, all subjects had cycle counts above the cut-off value. Ct values in placebo subjects were consistently less than 29, and no placebo subjects were RT-PCR-negative until day 7. Most of the symptoms disappeared completely after receiving PL-M treatment for 7 days in more patients compared to the placebo group. CONCLUSION: PL-M is safe and effective for clinical use in reducing viral loads and promoting rapid viral clearance in COVID-19 patients by inhibiting SARS-CoV-2 entry into cells through the inhibition of Gal-3.

Revisiting secondary prevention in coronary heart disease.

Secondary prevention in coronary heart disease is the prevention of occurrence of recurrent coronary events after clinical diagnosis. High level of adherence to secondary prevention interventions, especially aggressive lifestyle changes and pharmacotherapy can lead to significant decline in recurrent coronary events. Both international and Indian studies have reported low adherence to such therapies. Evidence-based useful interventions include regular physical activity, yoga, intake of healthy diet, smoking and tobacco use cessation and weight management. Pharmacotherapeutic interventions useful are anti-platelet therapy, target oriented lipid lowering therapy with statins, beta blockers and angiotensin converting enzyme inhibitors in patients with impaired left ventricular function. Hypertension and diabetes management with control to targets is important. Novel strategies include use of anticoagulants, anti-inflammatory drugs, and triglyceride lowering for residual risk. Physician and patient level interventions using multifaceted educational, socioeconomic and technological innovations are important to promote life-long adherence to these strategies.

'Quality of life at 90 days after stroke and its correlation to activities of daily living': A prospective cohort study.

BACKGROUND: The main goal of stroke rehabilitation is to improve the health-related quality of life (HRQoL). In developed countries, several studies evaluating the HRQoL among stroke survivors have been conducted. In India, HRQoL related to stroke as an important health care issue has not received sufficient attention. The study was conducted to encourage the professionals to use stroke-specific HRQoL scales in clinical practice as one of the measures of stroke outcome. OBJECTIVES: To study the correlation between activities of daily living (ADLs) and HRQoL at 90 days following an acute stroke. METHODS: In this prospective study, functional independence of patients admitted with stroke were measured using Barthel Index (BI). At 90 days post-stroke patients were assessed using two questionnaires. RESULTS: Significant improvement in BI total and domains scores at 90 days (p < .001) were seen. At follow-up, Stroke Specific Quality of Life Scale-12 (SS-QoL-12) score for 59 patients was 48 (high QoL). Individuals scored lowest for psychosocial subscale of HRQoL compared to physical subscale. All items and the total score of the BI showed a significant positive partial correlation (p< .001) with the HRQoL total score. The self-care domain of BI showed the highest correlation with QoL total score at 0.88. CONCLUSIONS: Patient dependent in ADL constantly scored less in all QoL domains. The psychosocial QoL was found to be most affected even in the presence of complete functional independence paving way for further studies on factors that impact psychosocial QoL of stroke survivors.

Field validation of deep learning based Point-of-Care device for early detection of oral malignant and potentially malignant disorders.

Early detection of oral cancer in low-resource settings necessitates a Point-of-Care screening tool that empowers Frontline-Health-Workers (FHW). This study was conducted to validate the accuracy of Convolutional-Neural-Network (CNN) enabled m(mobile)-Health device deployed with FHWs for delineation of suspicious oral lesions (malignant/potentially-malignant disorders). The effectiveness of the device was tested in tertiary-care hospitals and low-resource settings in India. The subjects were screened independently, either by FHWs alone or along with specialists. All the subjects were also remotely evaluated by oral cancer specialist/s. The program screened 5025 subjects (Images: 32,128) with 95% (n = 4728) having telediagnosis. Among the 16% (n = 752) assessed by onsite specialists, 20% (n = 102) underwent biopsy. Simple and complex CNN were integrated into the mobile phone and cloud respectively. The onsite specialist diagnosis showed a high sensitivity (94%), when compared to histology, while telediagnosis showed high accuracy in comparison with onsite specialists (sensitivity: 95%; specificity: 84%). FHWs, however, when compared with telediagnosis, identified suspicious lesions with less sensitivity (60%). Phone integrated, CNN (MobileNet) accurately delineated lesions (n = 1416; sensitivity: 82%) and Cloud-based CNN (VGG19) had higher accuracy (sensitivity: 87%) with tele-diagnosis as reference standard. The results of the study suggest that an automated mHealth-enabled, dual-image system is a useful triaging tool and empowers FHWs for oral cancer screening in low-resource settings.

Inflammatory bowel disease-related colorectal cancer: Past, present and future perspectives.

Inflammatory bowel disease-related colorectal cancer (IBD-CRC) is one of the most serious complications of IBD contributing to significant mortality in this cohort of patients. IBD is often associated with diet and lifestyle-related gut microbial dysbiosis, the interaction of genetic and environmental factors, leading to chronic gut inflammation. According to the "common ground hypothesis", microbial dysbiosis and intestinal barrier impairment are at the core of the chronic inflammatory process associated with IBD-CRC. Among the many underlying factors known to increase the risk of IBD-CRC, perhaps the most important factor is chronic persistent inflammation. The persistent inflammation in the colon results in increased proliferation of cells necessary for repair but this also increases the risk of dysplastic changes due to chromosomal and microsatellite instability. Multiple pathways have been identified, regulated by many positive and negative factors involved in the development of cancer, which in this case follows the 'inflammation-dysplasia-carcinoma' sequence. Strategies to lower this risk are extremely important to reduce morbidity and mortality due to IBD-CRC, among which colonoscopic surveillance is the most widely accepted and implemented modality, forming part of many national and international guidelines. However, the effectiveness of surveillance in IBD has been a topic of much debate in recent years for multiple reasons - cost-benefit to health systems, resource requirements, and also because of studies showing conflicting long-term data. Our review provides a comprehensive overview of past, present, and future perspectives of IBD-CRC. We explore and analyse evidence from studies over decades and current best practices followed globally. In the future directions section, we cover emerging novel endoscopic techniques and artificial intelligence that could play an important role in managing the risk of IBD-CRC.

Interpretable deep learning approach for oral cancer classification using guided attention inference network.

SIGNIFICANCE: Convolutional neural networks (CNNs) show the potential for automated classification of different cancer lesions. However, their lack of interpretability and explainability makes CNNs less than understandable. Furthermore, CNNs may incorrectly concentrate on other areas surrounding the salient object, rather than the network's attention focusing directly on the object to be recognized, as the network has no incentive to focus solely on the correct subjects to be detected. This inhibits the reliability of CNNs, especially for biomedical applications. AIM: Develop a deep learning training approach that could provide understandability to its predictions and directly guide the network to concentrate its attention and accurately delineate cancerous regions of the image. APPROACH: We utilized Selvaraju et al.'s gradient-weighted class activation mapping to inject interpretability and explainability into CNNs. We adopted a two-stage training process with data augmentation techniques and Li et al.'s guided attention inference network (GAIN) to train images captured using our customized mobile oral screening devices. The GAIN architecture consists of three streams of network training: classification stream, attention mining stream, and bounding box stream. By adopting the GAIN training architecture, we jointly optimized the classification and segmentation accuracy of our CNN by treating these attention maps as reliable priors to develop attention maps with more complete and accurate segmentation. RESULTS: The network's attention map will help us to actively understand what the network is focusing on and looking at during its decision-making process. The results also show that the proposed method could guide the trained neural network to highlight and focus its attention on the correct lesion areas in the images when making a decision, rather than focusing its attention on relevant yet incorrect regions. CONCLUSIONS: We demonstrate the effectiveness of our approach for more interpretable and reliable oral potentially malignant lesion and malignant lesion classification.

Bayesian deep learning for reliable oral cancer image classification.

In medical imaging, deep learning-based solutions have achieved state-of-the-art performance. However, reliability restricts the integration of deep learning into practical medical workflows since conventional deep learning frameworks cannot quantitatively assess model uncertainty. In this work, we propose to address this shortcoming by utilizing a Bayesian deep network capable of estimating uncertainty to assess oral cancer image classification reliability. We evaluate the model using a large intraoral cheek mucosa image dataset captured using our customized device from high-risk population to show that meaningful uncertainty information can be produced. In addition, our experiments show improved accuracy by uncertainty-informed referral. The accuracy of retained data reaches roughly 90% when referring either 10% of all cases or referring cases whose uncertainty value is greater than 0.3. The performance can be further improved by referring more patients. The experiments show the model is capable of identifying difficult cases needing further inspection.

Diabetes and COVID-19: Role of insulin resistance as a risk factor for COVID-19 severity.

Patients with diabetes are more susceptible to coronavirus disease 2019 (COVID-19), and as a consequence, develop more severe form of disease. This is partly due to a systemic inflammatory state and pro thrombotic milieu seen in metabolic syndrome. In this review, we attempt to explore the pathogenetic links between insulin resistance and COVID-19 disease severity. Insulin resistance is an underlying condition for metabolic syndromes, including type 2 diabetes, which impairs insulin signaling pathways affecting metabolic and cardiovascular homeostasis. A high concentration of circulating insulin shifts the balance to mitogen activated protein kinase (MAPK)-dependent signaling and causes endothelial cell damage. The phosphatidylinositol 3 kinase and MAPK dependent signaling pathways maintain a balance between nitric oxide-dependent vasodilator and endothelin-1 dependent vasoconstriction actions of insulin. Vascular smooth muscle cell dysfunction is responsible for inflammation and blood coagulation leading to microvascular and macrovascular complications in diabetes. Hyperactivity in renin-angiotensin system is implicated in development of islet oxidative stress and subsequent ß-cell dysfunction, as it alters the islet blood flow. These deleterious effects of insulin resistance involving altered blood pressure, vascular dysfunction, and inflammation could be associated with increased severity in COVID-19 patients. We conclude that clinical and/or biochemical markers of insulin resistance should be included as prognostic markers in assessment of acute COVID-19 disease.

Multicentric study to evaluate the effectiveness of Thermalytix as compared with standard screening modalities in subjects who show possible symptoms of suspected breast cancer.

INTRODUCTION: Machine learning in computer-assisted diagnostics improves sensitivity of image analysis and reduces time and effort for interpretation. Compared to standard mammograms, a thermal scan is easily scalable and is a safer screening tool. We evaluate the performance of Thermalytix (an automated thermographic screening algorithm) compared with other standard breast cancer screening modalities. METHODS: A prospective multicentre study was conducted to assess the non-inferiority of sensitivity of Thermalytix (test device) to that of standard modalities in detecting malignancy in subjects who show possible symptoms of suspected breast cancer. Standard screening modalities and Thermalytix were obtained and interpreted independently in a blinded fashion. A receiver operating characteristic (ROC) curve was constructed to identify the best cut-off point, non-inferiority margin of ≥10% to demonstrate the non-inferiority. RESULTS: We recruited 258 symptomatic women who first underwent a thermal scan, followed by mammogram and/or ultrasound. At Youden's Index of ROC curve, the test device had a sensitivity of 82.5% (95% CI 73.2 to 91.9) and specificity of 80.5% (95% CI 75.0 to 86.1) as compared with diagnostic mammogram, which had sensitivity of 92% (95% CI 80.7 to 97.8) and specificity of 45.9% (95% CI 34.3 to 57.9) when BI-RADS 3 (Breast Imaging-Reporting and Data System) was considered as test-positive. The overall area under the curve (AUC) was 0.845. For women aged <45 years, the test device had a sensitivity and specificity of 87.0% (95% CI 66.4 to 97.2) and 80.6% (95% CI 72.9 to 86.9), respectively. For women aged ≥45 years, the sensitivity and specificity were 80.5% (95% CI 65.1 to 91.2) and 86.5% (95% CI 78.0 to 92.6, respectively). CONCLUSION: We evaluated Thermalytix, a new AI-based modality for detecting breast cancer. The high AUC in both women under 45 years and above 45 years shows the potential of Thermalytix to be a supplemental diagnostic modality for all ages. Further evaluation on larger sample size is needed. TRIAL REGISTRATION NUMBER: CTRI/2017/10/0 10 115.

Classification of imbalanced oral cancer image data from high-risk population.

SIGNIFICANCE: Early detection of oral cancer is vital for high-risk patients, and machine learning-based automatic classification is ideal for disease screening. However, current datasets collected from high-risk populations are unbalanced and often have detrimental effects on the performance of classification. AIM: To reduce the class bias caused by data imbalance. APPROACH: We collected 3851 polarized white light cheek mucosa images using our customized oral cancer screening device. We use weight balancing, data augmentation, undersampling, focal loss, and ensemble methods to improve the neural network performance of oral cancer image classification with the imbalanced multi-class datasets captured from high-risk populations during oral cancer screening in low-resource settings. RESULTS: By applying both data-level and algorithm-level approaches to the deep learning training process, the performance of the minority classes, which were difficult to distinguish at the beginning, has been improved. The accuracy of "premalignancy" class is also increased, which is ideal for screening applications. CONCLUSIONS: Experimental results show that the class bias induced by imbalanced oral cancer image datasets could be reduced using both data- and algorithm-level methods. Our study may provide an important basis for helping understand the influence of unbalanced datasets on oral cancer deep learning classifiers and how to mitigate.

Mobile-based oral cancer classification for point-of-care screening.

SIGNIFICANCE: Oral cancer is among the most common cancers globally, especially in low- and middle-income countries. Early detection is the most effective way to reduce the mortality rate. Deep learning-based cancer image classification models usually need to be hosted on a computing server. However, internet connection is unreliable for screening in low-resource settings. AIM: To develop a mobile-based dual-mode image classification method and customized Android application for point-of-care oral cancer detection. APPROACH: The dataset used in our study was captured among 5025 patients with our customized dual-modality mobile oral screening devices. We trained an efficient network MobileNet with focal loss and converted the model into TensorFlow Lite format. The finalized lite format model is ∼16.3 MB and ideal for smartphone platform operation. We have developed an Android smartphone application in an easy-to-use format that implements the mobile-based dual-modality image classification approach to distinguish oral potentially malignant and malignant images from normal/benign images. RESULTS: We investigated the accuracy and running speed on a cost-effective smartphone computing platform. It takes ∼300 ms to process one image pair with the Moto G5 Android smartphone. We tested the proposed method on a standalone dataset and achieved 81% accuracy for distinguishing normal/benign lesions from clinically suspicious lesions, using a gold standard of clinical impression based on the review of images by oral specialists. CONCLUSIONS: Our study demonstrates the effectiveness of a mobile-based approach for oral cancer screening in low-resource settings.

Validation of an Isothermal Amplification Platform for Microbial Identification and Antimicrobial Resistance Detection in Blood: A Prospective Study.

Background: Recent advances in nucleic acid amplification technique (NAAT)-based identification of pathogens in blood stream infections (BSI) have revolutionized molecular diagnostics in comparison to traditional clinical microbiology practice of blood culture. Rapid pathogen detection with point-of-care diagnostic-applicable platform is prerequisite for efficient patient management. The aim of the study is to evaluate an in-house developed, lyophilized OmiX-AMP pathogen test for the detection of top six BSI-causing bacteria along with two major antimicrobial resistance (AMR) markers of carbapenem and compare it to the traditional blood culture-based detection. Materials and methods: One hundred forty-three patients admitted to the Medical Intensive Care Unit, Narayana Hrudayalaya, Bangalore, with either suspected or proven sepsis, of either gender, of age ≥18 years were enrolled for the study. Pathogen DNA extracted from blood culture sample using OmiX pReP method was amplified at isothermal conditions and analyzed in real time using OmiX Analysis software. Results: Among the processed 143 samples, 54 were true negative, 83 were true positive, 3 were false negative, and 2 were false positive as analyzed by OmiX READ software. Gram-negative bacteria (91.3%) and gram-positive bacteria (75%) were detected with 100% specificity and 95.6% sensitivity along with the AMR marker pattern with a turnaround time of 4 hours from sample collection to results. Conclusion: OmiX-AMP pathogen test detected pathogens with 96.5% concordance in comparison to traditional blood culture. Henceforth, OmiX-AMP pathogen test could be used as a readily deployable diagnostic kit even in low-resource settings. How to cite this article: Maheshwarappa HM, Guru P, Mundre RS, Lawrence N, Majumder S, Sigamani A, et al. Validation of an Isothermal Amplification Platform for Microbial Identification and Antimicrobial Resistance Detection in Blood: A Prospective Study. Indian J Crit Care Med 2021;25(3):299-304.

T1 mapping and conditional survival in paediatric dilated cardiomyopathy with advanced heart failure.

Myocardial fibrosis is associated with adverse events in idiopathic dilated cardiomyopathy. Cardiac MRI with late gadolinium enhancement can detect myocardial fibrosis. We evaluated the conditional survival of children and adolescents based on native T1 mapping (combined proton signal from myocytes and interstitium prior to contrast administration by the measurement of myocardial and blood relaxation time) as a means to assess myocardial fibrosis. This retrospective case-cohort over a 3-year period included all consecutive patients (aged ≤ 21 years) with advanced heart failure from dilated cardiomyopathy (echocardiographic left ventricular ejection fraction ≤ 45% and NYHA class ≥ 2) who underwent cardiac MRI.Conditional survival (follow-up ≥ 6 months after cardiac MRI) was assessed to include NYHA functional class and time to event (death or heart transplantation). A total of 57 patients (mean age 11.7 ± 6.1 years; 58% male) had a median NYHA Class III (31/57) and median left ventricular ejection fraction 25% (20-38%). Survival data were available in 82% patients (46/57) and the crude mortality rate was 24% (11/46) and one patient (2%) underwent heart transplantation. The median native T1 was elevated at 1351 ms (95% CI 1332, 1394) and it showed no difference between the groups who survived to those who died. Performing a multilevel regression analysis on prognosis failed to predict 6-month conditional survival.

Biobanking for Translational Diabetes Research in India.

India is declared as the diabetic capital of the world. Clinically well-annotated blood samples will advance diabetes research for better diagnostic and treatment methods. Building a disease-specific biobank with high-quality peripheral blood mononuclear cells (PBMCs) and clinical follow-up data system will serve as a good platform for clinical research in diabetes. Processing and storage of high-quality biospecimen for translational research in diabetes demand the implementation of good clinical laboratory practices. "Certification or accreditation programs" that improve biorepository processes and frameworks are lacking in Indian context. To sustain and translate the research into clinical practice, good governance of the biobank and financial resources is required. For ethical issues related to health needs of the people and participants in the research, issues related to research process, translational research, and commercialization, data sharing should be addressed. For India to be an innovation and sustainable country Indian government is supporting translational research facilities, including biobanks. India has developed biobanks for various diseases; however, diabetes-specific research biorepository is lacking. Given the dangers of diabetic burden, India should set up a diabetes disease-specific repository learning from the global organizations and customize to the needs of Indian context. It is important to have private agencies get involved to develop biobanks and future research as there are commercial goals to translate research into practice. New technologies of specimen storing and preservation, data management, and data sharing should be adopted for developing cost-effective long-standing disease-specific population biobank in India.

Validation of a Genome-Wide Polygenic Score for Coronary Artery Disease in South Asians.

BACKGROUND: Genome-wide polygenic scores (GPS) integrate information from many common DNA variants into a single number. Because rates of coronary artery disease (CAD) are substantially higher among South Asians, a GPS to identify high-risk individuals may be particularly useful in this population. OBJECTIVES: This analysis used summary statistics from a prior genome-wide association study to derive a new GPSCAD for South Asians. METHODS: This GPSCAD was validated in 7,244 South Asian UK Biobank participants and tested in 491 individuals from a case-control study in Bangladesh. Next, a static ancestry and GPSCAD reference distribution was built using whole-genome sequencing from 1,522 Indian individuals, and a framework was tested for projecting individuals onto this static ancestry and GPSCAD reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India. RESULTS: The GPSCAD, containing 6,630,150 common DNA variants, had an odds ratio (OR) per SD of 1.58 in South Asian UK Biobank participants and 1.60 in the Bangladeshi study (p < 0.001 for each). Next, individuals of the Indian case-control study were projected onto static reference distributions, observing an OR/SD of 1.66 (p < 0.001). Compared with the middle quintile, risk for CAD was most pronounced for those in the top 5% of the GPSCAD distribution-ORs of 4.16, 2.46, and 3.22 in the South Asian UK Biobank, Bangladeshi, and Indian studies, respectively (p < 0.05 for each). CONCLUSIONS: The new GPSCAD has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment.

One-year Results of a Factorial Randomized Trial of Aspirin versus Placebo and Clonidine versus Placebo in Patients Having Noncardiac Surgery.

BACKGROUND: The authors previously reported that perioperative aspirin and/or clonidine does not prevent a composite of death or myocardial infarction 30 days after noncardiac surgery. Moreover, aspirin increased the risk of major bleeding and clonidine caused hypotension and bradycardia. Whether these complications produce harm at 1 yr remains unknown. METHODS: The authors randomized 10,010 patients with or at risk of atherosclerosis and scheduled for noncardiac surgery in a 1:1:1:1 ratio to clonidine/aspirin, clonidine/aspirin placebo, clonidine placebo/aspirin, or clonidine placebo/aspirin placebo. Patients started taking aspirin or placebo just before surgery; those not previously taking aspirin continued daily for 30 days, and those taking aspirin previously continued for 7 days. Patients were also randomly assigned to receive clonidine or placebo just before surgery, with the study drug continued for 72 h. RESULTS: Neither aspirin nor clonidine had a significant effect on the primary 1-yr outcome, a composite of death or nonfatal myocardial infarction, with a 1-yr hazard ratio for aspirin of 1.00 (95% CI, 0.89 to 1.12; P = 0.948; 586 patients [11.8%] vs. 589 patients [11.8%]) and a hazard ratio for clonidine of 1.07 (95% CI, 0.96 to 1.20; P = 0.218; 608 patients [12.1%] vs. 567 patients [11.3%]), with effect on death or nonfatal infarction. Reduction in death and nonfatal myocardial infarction from aspirin in patients who previously had percutaneous coronary intervention at 30 days persisted at 1 yr. Specifically, the hazard ratio was 0.58 (95% CI, 0.35 to 0.95) in those with previous percutaneous coronary intervention and 1.03 (95% CI, 0.91to 1.16) in those without (interaction P = 0.033). There was no significant effect of either drug on death, cardiovascular complications, cancer, or chronic incisional pain at 1 yr (all P > 0.1). CONCLUSIONS: Neither perioperative aspirin nor clonidine have significant long-term effects after noncardiac surgery. Perioperative aspirin in patients with previous percutaneous coronary intervention showed persistent benefit at 1 yr, a plausible sub-group effect.