bluuebunny/crossref_metadata_2025 huggingface dataset:
Use of Ayush measures and advocacies by Ayush practitioners and health seekers for the prevention of coronavirus disease-19: Cross-sectional analysis of an application-based data
Authors: Srikanth Narayanam , Rana Rakesh Kumar , Jameela Sophia , Singhal Richa , Tripathi Arunabh , Khanduri Shruti , Rao Bhogavalli Chandrasekhara , Chhatre Leena , Singh Rajeshwari , Goel Sumeet , Chiluveri Ashwin Chandra , Ota Sarda , Sharma Madan Mohan , Yadav Babita , Singh Renu , Thrigulla Saketh Ram , Londhe Deepak Jagannath , Dhiman Kartar Singh
Published: June 2024

Introduction:

Ayush Sanjivani is a mobile application launched by the Ministry of Ayush to gather information regarding the acceptability and extent of utilization of Ayurveda, Yoga, Unani, Siddha, Sowa-Rigpa, and Homoeopathy (Ayush) advocacies for the prevention of coronavirus disease-19 (COVID-19). The mobile application has different modules to garner the desired information regarding the trends of use of Ayush measures by the Indian public and practitioners.

Objectives:

The objectives of this study were to determine the trends of the utilization of Ayush measures by the beneficiaries for the prevention of COVID-19 and to determine the benefit obtained in terms of self-reported parameters of general well-being, the overall impact on general health, and in preventing the onset of flu or COVID-19 like symptoms such as fever, chills, headache, muscle or body aches, cough, sore throat, and runny nose.

Methods:

A cross-sectional study was undertaken to analyze the data generated through the “Ayush Sanjivani mobile application” from May to July 2020. The responses generated in terms of demographic profile, utilization pattern, benefits obtained, the interventions used, and the data of beneficiaries in terms of geographic location and the interventions prescribed were analyzed statistically to assess the trends of the utilization of Ayush measures for prophylaxis as reported by the Ayush practitioners.

Results:

Data of 74,568 Ayush physicians and 13,521,245 beneficiaries/health seekers were used for the analysis. Ayush advocacies/measures were utilized by 69,195 (92.8%) physicians for prophylaxis. Samshamani vati, Chyavanprasha, and Arsenicum album-30C were the most commonly used Ayush interventions. Improvement in terms of appetite, bowel movements, sleep, mental well-being, stamina, preexisting disease, and disposition was reported by 42,400 (61.3%) physicians. Maximum beneficiaries were from the state of Gujarat followed by Madhya Pradesh. Arsenicum album 30°C was the most commonly prescribed/distributed intervention among the beneficiaries/health seekers.

Conclusion:

Maximum physicians reported utilization of Ayush prophylactic measures for the prevention of COVID-19. A large number of health seekers were provided Ayush prophylactic measures across various geographical locations in India.
Qualitative phytochemical characterization and free radical scavenging activity of Talapotaka churna
Authors: Nille Guruprasad C. , Mishra Shardendu Kumar , Reddy K. R. C.
Published: June 2024

Background:

Bioactive compounds from medicinal plants play a crucial role in treating various ailments. Talapotaka churna, a polyherbal formulation, is reported in Ayurveda for its therapeutic excellence. Although clinical and animal experimental studies are available, no work has yet been reported on the preliminary phytochemical and analytical profile of Talapotaka churna.

Aim:

To report the preliminary phytochemical, analytical profile, and antioxidative potential of Talapotaka churna.

Materials and Methods:

Talapotaka churna was prepared by following standard methods of preparations. Its organoleptic, physicochemical evaluation, thin-layer chromatography, phytochemical screening, and antioxidative activity have been evaluated following the available guidelines.

Results:

Preliminary phytochemical evaluation of Talapotaka churna showed the presence of alkaloids, phenolic compounds, glycosides, and saponins. The presence of polyphenolic compounds attributes to the antioxidant properties of Talapotaka churna.

Conclusion:

The antioxidant phytochemicals confirmed by the chromatographic characterization of Talapotaka churna support its therapeutic potential. Further studies are warranted to explore the mechanistic pathways of phytochemicals of Talapotaka churna to establish the therapeutic implication in diabetes mellitus.
Quantifying the progress of ayurgenomics research: A bibliometric review of publications
Authors: Singh S. B. , Mansoria Poornima
Published: June 2024

A new area of research known as ayurgenomics was established by integrating the Tridosha and Prakriti principles with genomics. Throughout the past few years, various studies have been undertaken and published. In order to determine the research hotspots and trends, we retrieved the published literature of ayurgenomics from the dimension data base and performed a bibliometric analysis using VOSviewer to examine keywords, authors, nations, and organizations. A total of 32 suitable publications were examined between the years of 2011 and January 2023, with the most publications occurring in the year 2022. The analysis revealed an increasing trend in the number of publications. Mitali Mukerji and Bhavna Parashar were found as most active researchers in ayurgenomics. Publications came from four nations: India, China, the United States, and Denmark, with India having the highest number (18) of publications. The keywords with the highest occurrences were medicine (54) Ayurveda (53) and Prakriti (50). This bibliometric study revealed that there are limited numbers of publications on ayurgenomics. It is still a relatively new field and more research is needed to fully understand its potential benefits and limitations.
Preliminary analytical study of Bhallatakadi kshara (herbomineral preparation)
Authors: Jawanjal Pravin M. , Bedarkar Prashant B. , Patgiri Biswa Jyoti , Savrikar Shriram S.
Published: June 2024

Introduction:

Bhallatakadi kshara is described in Charaka samhita Grahani chikista adhyaya. Bhallatakadi kshara consists of ten ingredients and is indicated in Hridaroga, (~disease of heart), Pandu (~pallor/anemia), Grahanidosha (~diseases due to malfunctioning of gastrointestinal tract dealing with digestion), Gulma (~a type of lump), Udavarta (~upward movement of Vayu with retention of stool and urine), and Shula (colicky pain in the abdomen).

Objective:

The objective of the study is to develop analytical standards for Bhallatakadi kshara by preparing and testing three different batches using the same method of preparation.

Materials and Methods:

Bhallatakadi kshara is prepared by putapaka (~heating of herbomineral preparation covered in various substances at a desired temperature) method. It is subjected to physicochemical analysis, scanning electron microscopy, Energy Dispersive X-Ray Spectroscopy (EDAX), and Wavelength Dispersive X-Ray Fluorescence (WD-XRF).

Results:

In the WD-XRF study, major contents are Cl (76.929%) and Na (16.952%), and minor are (K 2.0%), S (1.693%), Ca (0.581%), Si (0.543%), P (0.288%), Mg (0.353%), and Fe (0.213%).

Conclusion:

By using the same method of preparation, the three different batches of Bhallatakadi kshara were showing particle size and other parameters very close to each other. The average particle size of Bhallatakadi kshara is found to be 33.67 mm (volumetric median diameter) and 9.01 mm (Sauter mean diameter) and contains activated carbon and other elements such as Cl, Na, K, and Mg.
A comprehensive review of Pāṭhabheda (variant readings) in Carakasaṁhitā
Authors: Panja Asit Kumar
Published: June 2024

Carakasaṁhitā (1500 BCE) is the most important and widely popular classical compendium of Ayurveda written by Ācārya Agniveśa based on the preaching of Lord Ātreya. The text underwent various forms of metamorphosis at the various points of time over the period of three and half millennium years. Various portions of the texts were added and some other alterations have been done to the text. Pāṭhabheda or variant readings refer to differences in the text that appear in multiple copies of a manuscript. This helps to reconstruct the history of a text and gain a deeper understanding of the cultural and historical context in which it was produced and transmitted. Four commentaries were taken into consideration for the current study. The total number of variants of readings found was 3656, which were categorized into six subgroups namely Pañcanidāna (related to diagnosis), Dravya (related to drugs of different sources like minerals, animals, and plants), Siddhānta (related to principles), Cikitsā (modality, methods of treatment), Auṣadha yoga (related to formulations), and Samanya (general terms). The Pāṭhabheda (variant readings) found in Carakasaṁhitā should be analyzed scientifically and those are to be considered as a part to enrich the wisdom and as tools to understand the wide range of practical implementations of all aspects and clinical practice in a better way.
Ayurveda compound formulations “Panchatikta ghrita” and “Gandhakadya malahara” in the management of Vicharchika (atopic eczema): A prospective open-label clinical trial
Authors: Avhad Anil D. , Sharma Bhagwan Sahay , Paikrao Sumedh N. , Mahajon Bidhan , Khanduri Shruti , Tripathi Arunabha , Rana Rakesh , Singhal Richa , Kale Kiran V. , Rao B.C.S , Srikanth Narayanam
Published: June 2024

Background:

Eczema or atopic dermatitis is one of the significant public health concerns worldwide. Its prevalence is estimated to be 15–20% in children and 1–3% in adults. Moreover, the incidence of eczema has increased by 2–3-folds during the past decades in industrialized countries. The condition can considerably impact the quality of life of the affected individual by causing physical discomfort, emotional distress, sleep disturbance, and restriction of domestic and social activities.

Objectives:

The present study was intended to assess the efficacy of Panchatikta Ghrita (PTG) as Shamana sneha (~internal medication for unctuous therapy) and the external application of Gandhakadya Malahara (GKM) in Vicharchika vis-à-vis eczema.

Materials and Methods:

A prospective open-label clinical trial was conducted in 101 participants of aged between 18 and 60 years with atopic eczema. PTG was given a dose of 10 gm twice daily before food with lukewarm water. GKM was advised for external application twice a day for 12 weeks. The participants were assessed based on cardinal symptoms, Eczema Area and Severity Index scores (EASI), Patient-Oriented Eczema Measure (POEM), and Dermatology Life Quality Index (DLQI) questionnaire scores.

Results:

The symptoms such as itching, popular eruption, hyperpigmentation, hypopigmentation, and exudation gradually decreased and showed a significant improvement at the end of the study. The EASI, POEM, and DLQI showed statistically significant improvement.

Conclusion:

Ayurveda compound formulations, PTG and GKM, were found clinically safe and effective in the management of Vicharchika (atopic eczema).
Mindfulness and epigenetics as factors of human health transformation
Authors: Fonseca Mauricio Arley
Published: June 2024

The pandemic context has reproduced a lot of information about health regulations, strongly oriented by useful scientific schemes. However, there are other humanitarian ways to take care of health affectations, beyond biologically measured facts, but an emotional component with transformational potential in the organism, which requires listening to the wisdom of the body's nature, as an expression of spirituality. In fact, mindfulness and epigenetics focus on the wisdom of the body's nature. As a consequence, in the next paragraphs, several academic works have been reviewed related to mindfulness and body, and epigenetics not just in humans, but also in animals and trees. This approach is based on the idea that an inclusive project requires to transcends the human being and paying attention to the integration of natural beings. As a methodical approach, the bases come from sociocritical paradigms and depth-hermeneutics. The aim is to create a dialectical social health discussion by considering different ideological constructions. This communication is a contribution to health educational projects, which implies criticizing the practices that have been reproduced for years, with their strong intercultural and unconscious connections.
Preparation and preliminary physicochemical profile of Kaphaketu rasa
Authors: Yadav Pooja , Kumar Sanjay , Vaidya Meghna , Choudhary Anita , Prajapat Shyama
Published: June 2024

Introduction:

Kaphaketu Rasa (KKR) is a classical herbomineral formulation mentioned for the treatment of deranged Kapha (~Dosha responsible for regulating body fluids and keeping the body constituents cohesive). It is made-up of Shuddha tankana (processed Borax), Pippali (Piper longum Linn.), Shankha bhasma (incinerated conch shell), Shuddha vatsanabha (Aconitum chasmanthum Stapf ex Holmes). Though, an important formulation, no published data is available till date. Herein, an attempt has been made to develop the preliminary profiles by following standard methods.

Materials and Methods:

KKR was manufactured by following the methods mentioned at Ayurvedic Formulary of India. The individual ingredients were processed and mixed thoroughly, levigated with the juice of ginger (Zingiber officinale Rosc). The preliminary analytical profile was developed by following the standard methods mentioned in respective volumes of Ayurvedic Pharmacopoeia of India.

Results:

About 41.9% increase in the yield was noticed in the manufacturing of KKR. The High-Performance Thin-Layer Chromatography profile of KKR revealed eight bands at 254 nm. X-ray diffraction showed calcite (CaCO3) as a major compound with an amorphous shape and structure. Inductive coupled plasmaoptical emission spectrometry analysis revealed the presence of mercury (1.05 mg/kg), lead (2.17 mg/kg), arsenic (3.43 mg/kg), calcium (9549.75 mg/kg), and cadmium (0.03 mg/kg).

Conclusion:

The preliminary profile developed can be considered as baseline data for future studies.
Experimental evidence to the untapped potential of Ayurvedic herb, Ashwagandha: Bench-to-Bedside
Authors: Wadhwa Renu , Kaul Sunil C.
Published: June 2024

The last century has witnessed a major transition in every aspect of human life. Advancement in science and technologies, health, agriculture and medical sectors have tremendously improved food and living standards. A significant surge in human life expectancy has resulted in an increase in aging society triggering alters in global population demographics, social, and health-care supporting systems. Industrialization of lifestyle with excessive use of chemicals has sparked another negative feedback loop, threatening quality of life (QOL), and increasing sense of stress and anxiety. Together, these scenarios have posed new challenges to manage age- and stress-related ailments and maintain good QOL. Traditional home medicine systems, in contrast to use of chemicals/drugs, depending on the use of natural resources/ways to boost our built-in defense mechanisms. Ayurveda (Ayu means life and Veda means knowledge) is the world’s oldest home medicine system of Indian origin that continues to be a living tradition with a history of about ~5000 years. Ayurvedic medicine, with its deeply trusted concept of holistic approach, is based on maintaining the harmonious balance of different life-elements to treat/prevent diseases. Ayurvedic system involves the use of variety of herbs/plants, yoga, and relaxation techniques. Among a large number of plants described to enhance QOL in Ayurveda, Ashwagandha (Withania somnifera (L.) Dunal) categorized as Rasayana (a rejuvenating herb) is also appraised as “Queen of Ayurveda”. In this review, we discuss the experimental evidence of the therapeutic activities of Ashwagandha and its untapped potential for the treatment of stress, brain ailments, cancer and COVID-19.
Giant Left Atrial Myxoma with Mitral Valve Obstruction
Authors: Bahloul Amine , Sarray Hela , Kammoun Yassmine , Charfeddine Selma , Gueldich Majdi , Dammak Aymen , Frikha Imed , Abid Leila , Hammami Rania , Kammoun Samir
Published: June 2024

Cardiac myxomas are the most common primary intracardiac tumors in adults. Although benign from a histopathological point of view, they can be life-threatening for the patient. We present a case of an unusually giant left atrial myxoma causing mitral valve obstruction and pulmonary hypertension successfully treated with surgical resection. Our patient was a 54-year-old woman who presented to our emergency complaining of progressive dyspnea of about 1 month duration. On cardiovascular examination, we found crackling rales at both lung bases and a diastolic murmur in the mitral focus. Transthoracic echocardiography revealed a giant mass in the left atrium connected to the interatrial septum and extended into the left ventricle during diastole which caused obstruction of the left ventricular inflow tract and a pulmonary hypertension. The patient underwent a median sternotomy with the removal of left atrial mass and patch closure of the interatrial septum. Histopathological examination confirmed the diagnosis of myxoma. One week later, the patient was discharged without any complications. Giant left atrial myxoma although a benign mass, can induce dramatic symptoms and be life-threatening. In case of suspicion, it must be diagnosed early by transthoracic echocardiography and urgently managed by surgical removal.
Nephroblastoma with Right Atrial Extension
Authors: Umuerri Ejiroghene Martha , Odion-Obomhense Helen Kesiena
Published: June 2024

Two-dimensional echocardiography is useful in the diagnosis of cardiac masses, including tumors. Cardiac metastasis of nephroblastoma heralds a worse prognosis. This 4-year-old child presented with clinical and radiological features suggestive of nephroblastoma. She had intracaval spread of the tumor to the right atrium. The cardiac metastasis was initially missed as echocardiography was not part of the routine workup for the patient as she had no clinical features suggestive of cardiac disease. Although cardiac metastasis of nephroblastoma is rare, we recommend routine transthoracic echocardiography for all patients irrespective of the presence of cardiac symptoms and signs.
A Mediastinal Hematoma after the Bentall Operation Detected by Transthoracic Echocardiography
Authors: Hosseinsabet Ali , Bagheri Jamshid , Shirani Shapoor
Published: June 2024

A round, well-defined mass was incidentally detected at follow-up transthoracic echocardiography in an asymptomatic 36-year-old man with a history of Bentall operation 8 months earlier. Computed tomography angiography of the aorta demonstrated a mediastinal hematoma below the pulmonary artery in the mid-mediastinum. Although mediastinal hematomas are hard to detect after cardiac surgery via transthoracic echocardiography, the probable presence of this complication should be kept in mind during echocardiography.
Effects of Sacubitril/Valsartan Treatment on Left Ventricular Myocardial Torsion Mechanics in Patients with Heart Failure Reduced Ejection Fraction 2D Speckle Tracking Echocardiography
Authors: Elshafey Wassam Eldin Hadad , Al Khoufi Emad Ali , Elmelegy Ehab Kamal
Published: June 2024

Background:

Left ventricular ejection fraction (LVEF) is calculated from volumetric change without representing true myocardial properties. Strain echocardiography has been used to objectively measure myocardial deformation. Myocardial strain can give accurate information about intrinsic myocardial function, and it can be used to detect early-stage cardiovascular diseases, monitor myocardial changes with specific therapies, differentiate cardiomyopathies, and predict the prognosis of several cardiovascular diseases. Sacubitril/valsartan has been shown to improve mortality and reduce hospitalizations in patients with heart failure with reduced ejection fraction (HFrEF). The effect of sacubitril/valsartan angiotensin receptor neprilysin inhibitor (ARNI) on left ventricular (LV) ejection fraction (EF) and torsion dynamics in HFrEF patients has not been previously described.

Methods:

The study involved 73 patients with HFrEF, for all patients Full history was taken, full clinical examination was done. Baseline vital signs, ECG, NYHA classification, conventional echocardiography and STE were done at baseline study and after 6 and 11 months. Basal and apical LV short-axis images were acquired for further off-line analysis. Using commercially available two-dimensional strain software, apical, basal rotation, and LV torsion were calculated.

Results:

ARNI group of patients showed improvement of symptoms, LV global longitudinal strain (LVGLS)% and diastolic parameters including, E/A, E/e', TV, untwist onset and rate after 6 months of therapy in comparison to the traditionally treated patients. The improvement continued for 11 months with in additional significant improvement of systolic parameters in the form of LVGLS%, EF%, Twist, Apical and basal rotations, main dependent parameters for improvement of EF% was LVGLS% and Apical rotation.

Conclusion:

To the best of our knowledge, this is the first study to demonstrate that therapy with sacubitril/valsartan in HFrEF patients could create a state of gradual and chronic LV deloading which cause relieving of myocardial wall tensions and decreasing the LV end diastolic pressure this state could cause cardiac reverse remodeling and reestablishment of starling forces proprieties of LV myocardium, which lead to increase of LV EF.
Effect of Percutaneous Coronary Intervention on Diastolic Function in Coronary Artery Disease
Authors: Aggarwal Puneet , Sinha Santosh Kumar , Marwah Rishabh , Nath Ranjit Kumar , Pandit Bhagya Narayan , Singh Ajay Pratap
Published: June 2024

Background:

Left ventricle (LV) diastolic dysfunction is often present in patients with significant coronary artery disease (CAD), even in the absence of regional or global LV systolic dysfunction. It has been suggested that abnormalities in LV diastolic function may actually precede LV systolic dysfunction, and therefore, serve as an early and sensitive marker of ischemia. This study aims to find improvement of diastolic function after percutaneous coronary intervention (PCI) in patients with stable or unstable angina.

Methods:

In this single-center hospital-based study, we enrolled 309 patients with either stable or unstable CAD and with normal systolic function who underwent successful PCI. Two-dimensional transthoracic echocardiography was performed at baseline (before PCI) and repeated 48 h after PCI. LV diastolic parameters were compared before and after PCI using paired samples t-test results.

Results:

Mean age of study population was 56.65 ± 9.65 years. Majority of patients were male (63%). There was significant increase in mitral E-wave velocity (68.39 ± 17.52 cm/s vs. 71.64 ± 18.23 cm/s), E/A ratio (0.85 ± 0.29 vs. 0.89 ± 0.32), and early diastolic mitral annular motion (e') (7.02 ± 0.89 cm/s vs. 8.45 ± 0.86 cm/s) following PCI (P < 0.0001). Left atrial volume index (22.53 ± 4.43 vs. 20.81 ± 4.14), tricuspid jet velocity (0.91 ± 0.57 m/s vs. 0.76 ± 0.67 m/s), and E/e' ratio (10.03 ± 3.5 vs. 8.62 ± 2.61) decreased significantly following PCI (P < 0.001).

Conclusion:

This study suggests that LV diastolic filling pattern is modified significantly as early as 48 h after successful PCI. Improvement in impaired relaxation appears to be most likely explanation for these changes. PCI may be potential therapeutic target to improve diastolic function in patients with CAD.
Transcatheter Mitral Valve Repair to Treat Postmyocardial Infarction Papillary Muscle Rupture
Authors: Hayek Ahmad , Grinberg Daniel , Derimay François , Bochaton Thomas
Published: June 2024

A 75-year-old man was admitted to the emergency department for a late-presenting myocardial infarction. The coronary angiography revealed a thrombotic occlusion of the circumflex artery. He presented a rapid hemodynamic and respiratory deterioration as a result of a severe mitral regurgitation with a flail anterior leaflet due to a partial tear of the medial papillary muscle (PM). Given the patient's comorbidities, a percutaneous mitral valve repair with two-dimensional (2D)/3D transesophageal echocardiography was performed, deploying two MitraClips. MitraClip implantation may be considered in an acute setting of PM tear as an alternative for surgical treatment in selected patients.
Prognostic Value of Modified Haller Index in Patients with Suspected Coronary Artery Disease Referred for Exercise Stress Echocardiography
Authors: Sonaglioni Andrea , Rigamonti Elisabetta , Nicolosi Gian Luigi , Lombardo Michele
Published: June 2024

Background:

The influence of chest conformation on outcome of patients with suspected coronary artery disease (CAD) is actually unknown.

Materials and Methods:

This retrospective study included all consecutive patients who underwent exercise stress echocardiography (ESE) for suspected CAD at our institution between February 2011 and September 2019. Modified Haller index (MHI; chest transverse diameter over the distance between sternum and spine) was assessed in all patients. Obstructive CAD was diagnosed by ≥70% stenosis in any epicardial coronary artery. During the follow-up time, we evaluated the occurrence of any of the following: (1) cardiovascular (CV) hospitalizations and (2) cardiac death or sudden death.

Results:

A total of 1091 consecutive patients (62.4 ± 12.6 years, 57.2% of men) were included in the study. Patients with normal chest shape (MHI ≤2.5) and those with concave-shaped chest wall (MHI >2.5) were separately analyzed. A positive ESE was diagnosed in 171 patients of which 80.7% had an obstructive CAD (true positive), while 19.3 not (false positive [FP]). Majority of FP ESE (70.9%) derived from concave-shaped chest wall group. During follow-up time (2.5 ± 1.9 years), 9 patients died and 281 were hospitalized because of heart failure (163), acute coronary syndromes (39), and arrhythmias (79). At the multivariate Cox regression analysis, age (heart rate [HR]: 1.02, 95% confidence interval [CI]: 1.01–1.03), MHI >2.5 (HR: 0.39, 95% CI: 0.26–0.56), diabetes mellitus (HR: 4.89, 95% CI: 3.78–6.32), horizontal ST depression ≥1 mm (HR: 2.86, 95% CI: 1.98–4.15), peak exercise average E/e' ratio (HR: 1.08, 95% CI: 1.06–1.10), and peak exercise wall motion score index (HR: 1.79, 95% CI: 1.36–2.35) were independently correlated with outcome.

Conclusions:

Patients with concave-shaped chest wall (MHI >2.5) have a significantly lower probability of CV events than those with normal chest shape (MHI ≤2.5) over a medium-term follow-up. A noninvasive chest shape assessment could identify subjects at lower risk of CV events.
Feasibility and Role of Right Ventricular Stress Echocardiography in Adult Patients
Authors: Pergola Valeria , Previtero Marco , Lorenzoni Giulia , Ocagli Honoria , Simeti Giuseppe , Aruta Patrizia , Baritussio Anna , Cecchetto Antonella , Leoni Loira , Mancuso Daniela , Gregori Dario , Salvo Giovanni Di , Iliceto Sabino , Mele Donato
Published: June 2024

Background:

The great technological advancements in the field of echocardiography have led to applications of stress echocardiography (SE) in almost all diagnostic fields of cardiology, from ischemic heart disease to valvular heart disease and diastolic function. However, the assessment of the right ventricle (RV) in general, and in particular in regard to the contractile reserve of the RV, is an area that has not been previously explored. We, therefore, propose a study to investigate the potential use of SE for the assessment of RV function in adult patients.

Aims and objectives:

The primary aim is to evaluate the feasibility of right ventricular SE. The secondary aim is to assess right ventricular contractile reserve.

Matherials and Methods:

Eighty-one patients undergoing a physical or dobutamine stress echocardiogram for cardiovascular risk stratification or chest pain were the subject of the study. An exercise leg cycle using a standard WHO protocol was used to simultaneously assess the right and left ventricular global and regional function as well as acquiring Doppler data. Whereas the patient had limitations in mobility, a dobutamine SE was be performed. We evaluated the average values of tricuspid annular plane systolic excursion (TAPSE), fractional area change (FAC), S-wave, systolic pulmonary artery pressure (sPAP), and right ventricle global longitudinal (free wall) strain (RVGLS) during baseline and at the peak of the effort. RV contractile reserve was defined as the change in RVGLS from rest to peak exercise. We also assessed the reproducibility of these measurements between two different expert operators (blind analysis).

Results:

At least 3 over 5 RV function parameters were measurable both during baseline and at the peak of the effort in 95% of patients, while all 5 parameters in 65% of our population, demonstrating an excellent feasibility. All RV-studied variables showed a statistically significant increase (P < 0.001) at peak compared to the baseline. The average percentage increases at peak were 31.1% for TAPSE, 24.8% for FAC, 50.6% for S-wave, 55.2% for PAPS, and 39.8% for RV strain. The reproducibility between operators at baseline and peak was excellent. Our study demonstrates that TAPSE, FAC, and S-wave are highly feasible at rest and at peak, while TAPSE, S-wave, and sPAP are the most reliable measurements during RV stress echo.

Conclusion:

RVGLS is useful in the assessment of RV contractile reserve in patients with good acoustic window. Further studies are needed to evaluate the impact of contrast echocardiography in improving RV contractile reserve assessment during SE.
"Pac-Man Heart" and Mitral Valve Prolapse
Authors: Peluso Angela Pamela , Iesu Ivana , Provenza Gennaro , Citro Rodolfo
Published: June 2024

A 50-year-old man accessed the echo laboratory for dyspnea. His medical history was unremarkable. Transthoracic two-dimensional echocardiogram showed a posterior leaflet of the mitral valve prolapse associated with eccentric regurgitant jet. An excavation of the medium interventricular septum, in the absence of left–right interventricular shunt, was detected as an incidental finding and considered as partial ventricular septum defect. Owing to the absence of acute myocardial infarction and thrombolysis in patient's medical history, this finding has been considered “pac-man heart” of the congenital origin. Of note, the association of this deformity with mitral valve prolapse is reported for the first time.
Diagnostic Efficacy of Chest Computed Tomography for Coronavirus Disease 2019
Authors: Zakariaee Seyed Salman , Salmanipour Hossein , Kaffashian Mohammad Reza
Published: June 2024

Background:

A significant discrepancy between the results of previous studies is identified regarding the diagnostic efficacy of chest computed tomography (CT) for coronavirus disease 2019 (COVID-19). We aimed to evaluate the diagnostic efficacy of chest CT for COVID-19.

Methods:

Suspected cases of COVID-19 with fever, cough, dyspnea, and evidence of pneumonia on chest CT scan were enrolled in the study. The accuracy, sensitivity, and specificity of chest CT were determined according to real-time reverse transcriptase-polymerase chain reaction (RT-PCR) results as the gold standard method.

Results:

The study population comprised 356 suspected cases of COVID-19 (174 men and 182 women; age range 3–96 years; mean age ± standard deviation, 55.21 ± 18.38 years). COVID-19 patients were diagnosed using chest CT with 89.8% sensitivity, 78.1% accuracy, 21.3% specificity, 84.7% positive predictive value, and 30.23% negative predictive value. The odds ratio was 2.39 (95% confidence interval, 1.16–4.91). Typical CT manifestations of COVID-19 were observed in 48 (13.5%) patients with negative RT-PCR results and 30 (8.4%) patients with confirmed positive RT-PCR results had no radiological manifestations. Kappa coefficient of chest CT for diagnosis of COVID-19 was 0.78.

Conclusion:

The results show that when RT-PCR results are negative, chest CT could be considered as a complementary diagnostic method for the diagnosis of COVID-19 patients. A more comprehensive diagnostic method could be established by combining the chest CT examination, clinical symptoms, and RT-PCR assay.
Early Detection of Alzheimer's Disease Based on Clinical Trials, Three-Dimensional Imaging Data, and Personal Information Using Autoencoders
Authors: Akramifard Hamid , Balafar Mohammad Ali , Razavi Seyed Naser , Ramli Abd Rahman
Published: June 2024

Background:

A timely diagnosis of Alzheimer's disease (AD) is crucial to obtain more practical treatments. In this article, a novel approach using Auto-Encoder Neural Networks (AENN) for early detection of AD was proposed.

Method:

The proposed method mainly deals with the classification of multimodal data and the imputation of missing data. The data under study involve the MiniMental State Examination, magnetic resonance imaging, positron emission tomography, cerebrospinal fluid data, and personal information. Natural logarithm was used for normalizing the data. The Auto-Encoder Neural Networks was used for imputing missing data. Principal component analysis algorithm was used for reducing dimensionality of data. Support Vector Machine (SVM) was used as classifier. The proposed method was evaluated using Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Then, 10fold crossvalidation was used to audit the detection accuracy of the method.

Results:

The effectiveness of the proposed approach was studied under several scenarios considering 705 cases of ADNI database. In three binary classification problems, that is AD vs. normal controls (NCs), mild cognitive impairment (MCI) vs. NC, and MCI vs. AD, we obtained the accuracies of 95.57%, 83.01%, and 78.67%, respectively.

Conclusion:

Experimental results revealed that the proposed method significantly outperformed most of the stateoftheart methods.
Evaluating Morphological Features of Electrocardiogram Signals for Diagnosing of Myocardial Infarction Using Classification-Based Feature Selection
Authors: Mahmoudinejad Seyed Ataddin , Safdarian Naser
Published: June 2024

Background:

Cardiovascular disease (CVD) is the first cause of world death, and myocardial infarction (MI) is one of the five primary disorders of CVDs which the patient electrocardiogram (ECG) analysis plays a dominant role in MI diagnosis. This research aims to evaluate some extracted features of ECG data to diagnose MI.

Methods:

In this paper, we used the Physikalisch-Technische Bundesanstalt database and extracted some morphological features, such as total integral of ECG, integral of the T-wave section, integral of the QRS complex, and J-point elevation from a cycle of normal and abnormal ECG waveforms. Since the morphology of healthy and abnormal ECG signals is different, we applied integral to different ECG cycles and intervals. We executed 100 of iterations on a 10-fold and 5-fold cross-validation method and calculated the average of statistical parameters to show the performance and stability of four classifiers, namely logistic regression (LR), simple decision tree, weighted K-nearest neighbor, and linear support vector machine. Furthermore, different combinations of proposed features were employed as a feature selection procedure based on classifier's performance using the aforementioned trained classifiers.

Results:

The results of our proposed method to diagnose MI utilizing all the proposed features with an LR classifier include 90.37%, 94.87%, and 86.44% for accuracy, sensitivity, specificity, respectively. Also, we calculated the standard deviation value for the accuracy of 0.006.

Conclusion:

Our proposed classification-based method successfully classified and diagnosed MI using different combinations of presented features. Consequently, all proposed features are valuable in MI diagnosis and are praiseworthy for future works.
Signal Processing Framework for the Detection of Ventricular Ectopic Beat Episodes
Authors: Srinivasulu Avvaru , Sriraam Natarajan
Published: June 2024

The Holter monitor captures the electrocardiogram (ECG) and detects abnormal episodes, but physicians still use manual cross-checking. It takes a considerable time to annotate a long-term ECG record. As a result, research continues to be conducted to produce an effective automatic cardiac episode detection technique that will reduce the manual burden. The current study presents a signal processing framework to detect ventricular ectopic beat (VEB) episodes in long-term ECG signals of cross-database. The proposed study has experimented with the cross-database of open-source and proprietary databases. The ECG signals were preprocessed and extracted the features such as pre-RR interval, post-RR interval, QRS complex duration, QR slope, and RS slope from each beat. In the proposed work, four models such as support vector machine, k-means nearest neighbor, nearest mean classifier, and nearest RMS (NRMS) classifiers were used to classify the data into normal and VEB episodes. Further, the trained models were used to predict the VEB episodes from the proprietary database. NRMS has reported better performance among four classification models. NRMS has shown the classification accuracy of 98.68% and F1-score of 94.12%, recall rate of 100%, specificity of 98.53%, and precision of 88.89% with an open-source database. In addition, it showed an accuracy of 99.97%, F1-score of 94.54%, recall rate of 98.62%, specificity of 99.98%, and precision of 90.79% to detect the VEB cardiac episodes from the proprietary database. Therefore, it is concluded that the proposed framework can be used in the automatic diagnosis system to detect VEB cardiac episodes.
Use of Internet of Things for Chronic Disease Management
Authors: Dadkhah Mehdi , Mehraeen Mohammad , Rahimnia Fariborz , Kimiafar Khalil
Published: June 2024

Most of the countries with elderly populations are currently facing with chronic diseases. In this regard, Internet of Things (IoT) technology offers promising tools for reducing the chronic disease burdens. Despite the presence of fruitful works on the use of IoT for chronic disease management in literature, these are rarely overviewed consistently. The present study provides an overview on the use of IoT for chronic disease management, followed by ranking different chronic diseases based on their priority for using IoT in the developing countries. For this purpose, a structural coding was used to provide a list of technologies adopted so far, and then latent Dirichlet allocation algorithm was applied to find major topics in literature. In order to rank chronic diseases based on their priority for using IoT, a list of common categories of chronic diseases was subjected to fuzzy analytic hierarchy process. The research findings include lists of IoT technologies for chronic disease management and the most-discussed chronic diseases. In addition, with the help of text mining, a total of 18 major topics were extracted from the relevant pieces of literature. The results indicated that the cardiovascular disease and to a slightly lesser extent, diabetes mellitus are of the highest priorities for using IoT in the context of developing countries.
Automatic Choroidal Segmentation in Optical Coherence Tomography Images Based on Curvelet Transform and Graph Theory
Authors: Eghtedar Reza Alizadeh , Esmaeili Mahdad , Peyman Alireza , Akhlaghi Mohammadreza , Rasta Seyed Hossein
Published: June 2024

Background:

Automatic segmentation of the choroid on optical coherence tomography (OCT) images helps ophthalmologists in diagnosing eye pathologies. Compared to manual segmentations, it is faster and is not affected by human errors. The presence of the large speckle noise in the OCT images limits the automatic segmentation and interpretation of them. To solve this problem, a new curvelet transform-based K-SVD method is proposed in this study. Furthermore, the dataset was manually segmented by a retinal ophthalmologist to draw a comparison with the proposed automatic segmentation technique.

Methods:

In this study, curvelet transform-based K-SVD dictionary learning and Lucy-Richardson algorithm were used to remove the speckle noise from OCT images. The Outer/Inner Choroidal Boundaries (O/ICB) were determined utilizing graph theory. The area between ICB and outer choroidal boundary was considered as the choroidal region.

Results:

The proposed method was evaluated on our dataset and the average dice similarity coefficient (DSC) was calculated to be 92.14% ± 3.30% between automatic and manual segmented regions. Moreover, by applying the latest presented open-source algorithm by Mazzaferri et al. on our dataset, the mean DSC was calculated to be 55.75% ± 14.54%.

Conclusions:

A significant similarity was observed between automatic and manual segmentations. Automatic segmentation of the choroidal layer could be also utilized in large-scale quantitative studies of the choroid.
Nonlinear Feature Extraction Methods Based on Dual-Tree Complex Wavelet Transform Subimages of Brain Magnetic Resonance Imaging for the Classification of Multiple Diseases
Authors: Bazdar Amir , Hatamian Amir , Ostadieh Javad , Nourinia Javad , Ghobadi Changiz , Mostafapour Ehsan
Published: June 2024

It has been a long time since we use magnetic resonance imaging (MRI) to detect brain diseases and many useful techniques have been developed for this task. However, there is still a potential for further improvement of classification of brain diseases in order to be sure of the results. In this research we presented, for the first time, a non-linear feature extraction method from the MRI sub-images that are obtained from the three levels of the two-dimensional Dual tree complex wavelet transform (2D DT-CWT) in order to classify multiple brain disease. After extracting the non-linear features from the sub-images, we used the spectral regression discriminant analysis (SRDA) algorithm to reduce the classifying features. Instead of using the deep neural networks that are computationally expensive, we proposed the Hybrid RBF network that uses the k-means and recursive least squares (RLS) algorithm simultaneously in its structure for classification. To evaluate the performance of RBF networks with hybrid learning algorithms, we classify nine brain diseases based on MRI processing using these networks, and compare the results with the previously presented classifiers including, supporting vector machines (SVM) and K-nearest neighbour (KNN). Comprehensive comparisons are made with the recently proposed cases by extracting various types and numbers of features. Our aim in this paper is to reduce the complexity and improve the classifying results with the hybrid RBF classifier and the results showed 100 percent classification accuracy in both the two class and the multiple classification of brain diseases in 8 and 10 classes. In this paper, we provided a low computational and precise method for brain MRI disease classification. the results show that the proposed method is not only accurate but also computationally reasonable.
Automatic Diagnosis of COVID-19 Pneumonia using Artificial Intelligence Deep Learning Algorithm Based on Lung Computed Tomography Images
Authors: Amiri Mohammad , Ranjbar Manizheh , Mohammadi Gholamreza Fallah
Published: June 2024

Background:

The lung computed tomography (CT) scan contains valuable information and patterns that provide the possibility of early diagnosis of COVID-19 disease as a global pandemic by the image processing software. In this research, based on deep learning of artificial intelligence, the software has been designed that is used clinically to diagnose COVID-19 disease with high accuracy.

Methods:

Convolutional neural network architecture developed based on Inception-V3 for deep learning of lung image patterns, feature extraction, and image classification. The theory of transfer learning was utilized to increase the learning power of the system. Changes applied in the network layers to increase the detection power. The process of learning was repeated 30 times. All diagnostic statistical parameters of the diagnostic were analyzed to validate the software.

Results:

Based on the data of Imam Khomeini Hospital in Sari, the validity, sensitivity, and accuracy of the software in diagnosing of affected to COVID-19 and nonaffected to it were obtained 98%, 98%, and 98%, respectively. Diagnostic statistical parameters on some data were 100%. The modified algorithm of Inception-V3 applied to heterogeneous data also had acceptable precision.

Conclusion:

The proposed basic architecture of Inception-v3 utilized for this research has an admissible speed and exactness in learning CT scan images of patients' lungs, and diagnosis of COVID-19 pneumonia, which can be utilized clinically as a powerful diagnostic tool.
Sensitivity Analysis of a 6 MeV Photon Beam Monte Carlo Model
Authors: Shami Nahid , Atarod Maryam , Shokrani Parvaneh , Najafizade Nadia
Published: June 2024

Background:

This study aimed to optimize efficiency in Monte Carlo (MC) simulation using sensitivity analysis of a beam model.

Methods:

The BEAMnrc-based model of 6 MV beam of a Siemens Primus linac was developed. For sensitivity analysis, the effect of the electron source, treatment head, and virtual phantom specifications on calculated percent depth dose (PDD) and lateral dose profiles was evaluated.

Results:

The optimum mean energy (E) and the full width at half maximum (FWHM) of the intensity distribution of the electron beam were calculated as 6.7 MeV and 3 mm, respectively. Increasing E from 6.1 to 6.7 MeV, increased the PDD in the fall-off region by 4.70% and decreased the lateral profile by 8.76%. Changing the FWHM had a significant effect on the buildup region of PDD and the horns and out-of-field regions of the lateral profile. Increasing the collimators opening by 0.5 mm, PDD increased by 2.13% and the central and penumbra regions of profiles decreased by 1.98% and 11.40% respectively. Collimator properties such as thickness and density were effective in changing the penumbra (11.32% for 0.25 cm increment) and the out-of-field (22.82% for 3 g/cm3) regions of the lateral profiles.

Conclusion:

Analysis of a 6 MV model showed that PDD profiles were more sensitive to changes in energy than to FWHM of the electron source. The lateral profiles were sensitive to E, FWHM, and collimator opening. The density of the collimator affected only the out-of-field region of lateral profiles. The findings of this study may be used to make benchmarking of an MC beam model more efficient.
Automatic Diagnosis of Stage of COVID-19 Patients using an Ensemble of Transfer Learning with Convolutional Neural Networks Based on Computed Tomography Images
Authors: Gifani Parisa , Vafaeezadeh Majid , Ghorbani Mahdi , Mehri-Kakavand Ghazal , Pursamimi Mohamad , Shalbaf Ahmad , Davanloo Amirhossein Abbaskhani
Published: June 2024

Background:

Diagnosis of the stage of COVID-19 patients using the chest computed tomography (CT) can help the physician in making decisions on the length of time required for hospitalization and adequate selection of patient care. This diagnosis requires very expert radiologists who are not available everywhere and is also tedious and subjective. The aim of this study is to propose an advanced machine learning system to diagnose the stages of COVID-19 patients including normal, early, progressive, peak, and absorption stages based on lung CT images, using an automatic deep transfer learning ensemble.

Methods:

Different strategies of deep transfer learning were used which were based on pretrained convolutional neural networks (CNNs). Pretrained CNNs were fine-tuned on the chest CT images, and then, the extracted features were classified by a softmax layer. Finally, we built an ensemble method based on majority voting of the best deep transfer learning outputs to further improve the recognition performance.

Results:

The experimental results from 689 cases indicate that the ensemble of three deep transfer learning outputs based on EfficientNetB4, InceptionResV3, and NasNetlarge has the highest results in diagnosing the stage of COVID-19 with an accuracy of 91.66%.

Conclusion:

The proposed method can be used for the classification of the stage of COVID-19 disease with good accuracy to help the physician in making decisions on patient care.