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Background: Clinically important perioperative atrial fibrillation (POAF) is a common cardiac complication after noncardiac surgery. Little is known about how patients with POAF are managed acutely and whether practices have changed over time. Methods: We conducted an observational substudy of patients who had POAF, were at elevated cardiovascular risk, and were enrolled in the PeriOperative Ischemic Evaluation (POISE)-1, 2 and 3 trials between 2002 and 2021. POAF was defined as new, clinically important atrial fibrillation occurring within 30 days after surgery. We assessed the use of rhythm-control and anticoagulation treatment in response to POAF, at hospital discharge and at 30 days after surgery. We assessed for temporal trends using multivariable logistic regression. Results: Of the 27,896 patients included, 545 (1.9%) developed clinically important POAF. Patients received rhythm-control treatment in 48.6% of cases. The level of use of rhythm-control treatment increased over the course of the trials (POISE-1 vs POISE-2 vs POISE-3; 40.9% vs 49.5% vs 59.1%). A later randomization date was associated independently with use of rhythm-control treatment (odds ratio, 1.05 per year; 95% confidence interval, 1.01-1.09). Anticoagulation treatment was prescribed in 21% of POAF cases. The level of anticoagulation treatement use was higher in POISE-3, compared to that in the 2 previous trials (POISE-1 vs POISE-2 vs POISE-3—16.4% vs 16.5% vs 33.6%). A later randomization date was associated independently with use of anticoagulation treatment (odds ratio, 1.06 per year; 95% confidence interval, 1.02-1.11). Conclusions: Despite the absence of randomized controlled trials, the level of use of rhythm-control and anticoagulation treatment for POAF is rising. High-quality trials are needed urgently to determine whether these interventions are safe and effective in this population. Résumé: Contexte: En chirurgie non cardiaque, la fibrillation auriculaire postopératoire (FAPO) d’importance clinique est une complication cardiaque fréquente. La prise en charge ponctuelle des patients présentant une FAPO est mal connue et on ne sait pas précisément si les pratiques ont évolué au fil du temps. Méthodologie: Nous avons mené une sous-étude d’observation auprès de patients ayant présenté une FAPO et dont le risque cardiovasculaire était élevé, et qui avaient participé aux études 1, 2 ou 3 du programme d’essais cliniques POISE (PeriOperative Ischemic Evaluation) entre 2002 et 2021. La FAPO était définie comme un nouvel épisode de fibrillation auriculaire (FA) d’importance clinique au cours des 30 jours suivant une intervention chirurgicale. Nous avons évalué l’utilisation d’un traitement visant à régulariser le rythme cardiaque et de l’anticoagulothérapie dans la prise en charge d’une FAPO, au moment du congé de l’hôpital, puis 30 jours après l’intervention chirurgicale. Nous avons procédé à l’évaluation des tendances temporelles par régression logistique multivariée. Résultats: Sur les 27 896 patients inclus dans l’analyse, 545 (1,9 %) ont présenté une FAPO d’importance clinique. Dans 48,6 % des cas, les patients ont reçu un traitement visant à régulariser le rythme cardiaque. Le taux d’utilisation d’un traitement visant à régulariser le rythme cardiaque a augmenté d’une étude à l’autre (étude POISE-1 vs étude POISE-2 vs étude POISE-3; 40,9 % vs 49,5 % vs 59,1 %, respectivement). Une date plus tardive de la répartition aléatoire était un facteur indépendant de l’utilisation d’un traitement visant à régulariser le rythme cardiaque (rapport de cotes = 1,05 par an; intervalle de confiance [IC] à 95 % : 1,01-1,09). Une anticoagulothérapie a été prescrite à 21 % des patients ayant présenté une FAPO. Le taux d’utilisation d’une anticoagulothérapie était plus élevé dans l’étude POISE-3, comparativement aux deux essais précédents (étude POISE-1 vs étude POISE-2 vs étude POISE-3; – 16,4 % vs 16,5 % vs 33,6 %, respectivement). Une date plus tardive de la répartition aléatoire était un facteur indépendant d’utilisation d’une anticoagulothérapie (rapport de cotes = 1,06 par an; IC à 95 % : 1,02-1,11). Conclusions: Malgré l’absence d’essais comparatifs avec répartition aléatoire, le taux d’utilisation d’un traitement visant à régulariser le rythme cardiaque ou d’une anticoagulothérapie chez les patients présentant une FAPO est en augmentation. Il existe un besoin urgent de réaliser des études cliniques de grande qualité afin de déterminer si ces interventions sont sûres et efficaces dans cette population de patients.

Background: Individuals with inborn errors of immunity (IEI) have an increased risk of developing malignancies compared to their peers. We report a case of Hodgkin lymphoma in an adolescent with CD27 deficiency. Case report: A 15-year-old girl presented with cervical swelling and breathlessness for 3 days. Her past history was remarkable, with a history of recurrent respiratory infections. On examination, she had grade 2 clubbing, bilateral cervical lymphadenopathy, hepatosplenomegaly, and bilateral coarse crepitations. Biopsy showed overlapping immunomorphological features of classic Hodgkin lymphoma (HL), with features intermediate between diffuse large B-cell lymphoma and HL. A staging PET-CT revealed a stage III disease and bronchiectatic changes in bilateral lungs. The serum immunoglobulin levels showed hypogammaglobulinemia. Next generation sequencing demonstrated a homozygous missense variant in the CD27 gene (c.319C>T; p.Arg107Cys). She was treated with ABVD/COPDac chemotherapy along with supportive care. She is currently 16 months post-treatment. Conclusion: CD 27 deficiency is a rare IEI with a common variable immunodeficiency phenotype and a high propensity to develop lymphomas. Clinical suspicion, early detection, and management are warranted to prevent complications and mortality.

In India, poor health insurance coverage and high out-of-pocket expenditure especially for chronic and rare genetic/life-threatening diseases is a reality. People who use medical crowdfunding as an option to meet medical expenditures and the sudden growth of new fundraising platforms are significant developments in healthcare. The digital platforms in fundraising and the multitude of transactions they perform are increasing in the country and have a significant impact on the health sector and the rights of the patients which points toward the need for more effective regulation. In the absence of sector-specific legislation and government guidelines, the paper summarizes the growth of medical crowdfunding in India, identifies the challenges, and reiterates the need for effective legal enforcement systems.

Background: The prevalence of myopia in the 5–15-year age group in India has been 7.5% over the past four decades. While ocular growth and physical growth occur simultaneously during early life, the existence of a common regulatory system for both is still debated. Aims and Objectives: This study aims to analyze the ocular biometry and anthropometric values of young myopes and emmetropes aged 18–25 years. Materials and Methods: This case–control study involved a sample size of 86 participants. Corneal curvature was measured using keratometry, while A-scan ultrasonography was utilized to measure axial length, lens thickness, anterior chamber depth, and vitreous chamber depth. Results: The results indicated that there were no significant differences in ocular biometry and anthropometric values between the case and control groups, except for corneal thickness and axial length. The mean corneal thickness was found to be 549.64 μm in the case group and 566.05 μm in the control group, while the mean axial length was 24.70 mm in the case group and 23.41 mm in the control group. An increase in height was correlated with longer axial length in myopes. Conclusion: There was no difference in anthropometry and ocular biometry in emmetropes and myopes in the age group of 18–25 years of age. Myopes tend to have thinner corneas, which should be taken into consideration before performing refractive surgeries. The presence of thin corneas in individuals with myopia can result in inaccurately low measurements of intraocular pressure, potentially hampering the early detection of glaucoma within this high-risk demographic.

Study region: The Ailaoshan National Nature Reserve forest is a mountainous water catchment area for the Lancang River basin and a subtropical ecological conservation area in southwest China. Study focus: The study aimed to understand how water fluxes in a subtropical forest responds to extreme weather disturbances and their recoveries in the post-damage years. We used eddy covariance data (2010–2019) to investigate the evapotranspiration (ET), transpiration (T), evaporation (E), and canopy conductance (Gc) before and after an extreme snow event in 2015. New Hydrological Insights: In the snow damage year, the leaf area index (LAI) decreased by 49 % compared to the pre-damage levels. The severe vegetation damage caused a significant decrease in ET, T, E, and Gc by 35 %, 36 %, 23 %, and 33 %, respectively, compared to the pre-damage levels. T returned to its pre-damage level in 2016, one year after the snow damage. In contrast, LAI, ET, E and Gc recovered to their pre-damage levels in 2018, four years after the initial damage. Reduced ET caused a strong positive RFET, which diminished forest evaporative cooling and resilience. Our results suggest that the delayed E recovery enables water reserves in the ecosystems to be used through T to support rapid understory vegetation growth. This mechanism plays critical in bolstering ecosystem resilience as it facilitates swift recovery following disturbances in subtropical forests.

A multi-band antenna is proposed for terrestrial applications above 5 GHz. The design includes one director element, three split ring resonators (SRR), and a printed patch antenna on a FR4 substrate to make the miniature structure. The novelty is the addition of “C” split rings and one identical stub linked to the partial ground into the radiating element, which improves impedance matching and radiation characteristics across the target bands. The prototype is designed with five distinct resonance frequencies and radiation patterns compared to those produced by the patch, the director and resonators are added. Return loss simulation results and measured radiation pattern findings are validated and analyzed. The antenna produces a gain of 7.84 dB, overall efficiency of 84.76 %, and a VSWR of 1.8 at 7 GHz frequency, which is achieved due to the peculiar features of the FR4 and it is highly suitable for traditional communication. VSWR, gain, and radiation efficiency are all higher on this antenna than they are on a typical multiband antenna. At 20 GHz, the designed antenna band is efficient to operate with five dissimilar resonant frequency bands, pinpointed at 7.224 GHz, 10.723 GHz, 13.808 GHz, 17.014 GHz and 19.549 GHz through different impedance bandwidths.

Introduction: The appendix, once considered a vestigial structure, is now recognised as a site of diverse pathologies beyond simple appendicitis through a systematic analysis of published literature and case studies. The diagnosis of appendiceal lesions is still a clinical phenomenon and a constant struggle. The gold standard for diagnosing appendiceal lesions, however, is meticulous histopathological examination. Aim: To determine the histopathological distribution of all the appendiceal lesions and to identify the rare and unusual histopathological findings in appendectomy specimens received at a tertiary care Centre. Materials and Methods: A cross-sectional study was conducted in the Department of Pathology at Karpaga Vinayaga Institute of Medical Sciences and Research Centre, Chengalpattu, Tamil Nadu, India for a duration of 10 years, from August 2013 to August 2023. From the histopathological records of 832 appendectomies, 40 specimens with unusual histopathological findings were identified and analysed in this study. Relevant recorded data from all the appendiceal specimens reported during the study period, with special reference to age, sex, and histopathological findings, were retrieved and evaluated retrospectively. Corresponding slides and specimens were reviewed. The data were presented in the form of frequency tables and percentages. The analysis was done using Statistical Package for Social Sciences (SPSS) software version 20.0. Results: Out of 832 appendectomy specimens, there were 485 (58.29%) cases of acute appendicitis, 244 (29.33%) cases of chronic appendicitis, 59 (7.09%) cases of subacute appendicitis, and 4 (0.48%) cases of gangrenous appendicitis. Unusual histopathology findings were noted in 40 cases (4.81%). These include 17 cases of appendiceal neuroma, eight cases of Xanthogranulomatous appendicitis, seven cases of Enterobius vermicularis, three cases of Low-grade Appendiceal Mucinous Neoplasm (LAMN), one case of appendiceal Neuroendocrine Tumour (NET), one case of Goblet Cell Adenocarcinoma (GCA), one case of metastatic squamous cell carcinomatous deposit in the appendix, one case of urothelial rests in the appendix, and one case of appendiceal lipoma. Conclusion: In this study, 4.81% of patients had atypical appendiceal lesions. A complete histopathological examination of appendectomy specimens increases the chances of discovering unusual lesions of the appendix. Ultimately, this comprehensive analysis will contribute to future improvements in clinical management and prognostication, fostering better patient outcomes.

Purpose: individuals with intellectual disability (ID) often experience challenges related to low levels of physical fitness, impacting both their physical and mental well-being. This study aims to evaluate the pulmonary function of children with ID and explore the effect of yoga practices on pulmonary function among the participants with ID. Material & Methods: the study was an assessor-blinded, randomised, controlled study. Participants clinically diagnosed with intellectual disability (ID) were randomly assigned to either yoga intervention or no intervention for a duration of 6 months. Pulmonary function test was assessed at baseline and after 6 months of intervention using a Helios 401 device. Results: in this study, a total of 56 adult participants of both sexes with intellectual disabilities (ID) were initially enrolled (n=56). Following the intervention, the final sample size was 48 participants. Notably, the participants in the yoga group demonstrated a statistically significant (p

The diagnosis of Multiple Myeloma (MM) is made by demonstration clonal plasma cells in Bone Marrow (BM) aspiration/biopsy, in addition to assessing serum biochemical parameters, conducting radiological examinations, and considering the clinical presentation. In most cases, predominantly mature plasma cells are observed, along with scattered immature forms in the BM. Several morphological variants of plasma cells have been reported, including Auer rod-like inclusions, small lymphocyte-like cells, hairy cell-like cells, anaplastic variants, promonocyte-like cells, crystal-storing histiocytes, Burkitt-like cells, and blastoid cells. In this series of five cases, most showed a typical clinical presentation and laboratory findings suggestive of plasma cell dyscrasia. However, the morphology of each case exhibited unusual morphological variants, posing diagnostic challenges. These variants included Auer rod-like inclusions, small lymphocytes/lymph-plasmacytoid cells, hairy-like cells, multilobulated nuclei, and anaplastic variants mimicking dysplastic megakaryocytes, leading to various differential diagnoses. The age range of these cases was 57-76 years. Most of the cases presented with generalised dull aching body pain. Imaging studies revealed lytic lesions involving various parts of the bone, including the skull, ribs, vertebrae, and femur. Biochemical assays suggested the possibility of plasma cell dyscrasia. Two of the cases had primary Plasma Cell Leukaemia (PCL), which is a rare and highly aggressive plasma cell neoplasm. The anaplastic variant is associated with a poor prognosis, aiding in predicting treatment responses. However, due to the unusual morphological presentation, the diagnosis of MM or PCL was made after conducting ancillary studies such as Serum Protein Electrophoresis (SPEP), serum free light chain assay, Immunofixation Electrophoresis (IFE), and immunophenotyping through Immunohistochemistry (IHC) or flow cytometry.

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.

Background Human Resource for Health (HRH) migration is an emerging concern in the development paradigm due to the critical importance to sustainability of health system in India. Being the largest human resource supplier to the world, it is important to analyze the consequences of the migration of HRH in the delivery of healthcare services to the country’s population. The study evidences limited to examine the size, distribution of the existing human resources or trends or patterns in migration. The consequences of migration have its implications to the healthcare delivery mechanism which needed to be critically analyzed. Review Methodology The methodology adopted in the paper is descriptive design. The critical review used to evaluate the existing evidence and to develop conceptual framework. The process involved the setting of the inclusion and exclusion criteria to select the articles. It included wide range of articles from the world development reports to specific studies oriented on the HRH scenario of the country. The search strategy comprised both form of studies qualitative and quantitative. The study utilizes the official data set published as report form. Main Findings The data on the migration in context of India, not systematically updated in the existing evidences. The availability of data on migration limits to few reports i.e.(World Health Organization) WHO’s Joint Learning Initiatives and studies which combines census data of Organization for Economic Cooperation and Development (OECD) and results in the number of foreign born health professionals. 1. A major proportion of the research studies reviewed describes the disparity in distribution of HRH between rural-urban and public-private. Few researches focused towards the policy environment of the source and destination country for the migration. 2. There is pool of literature explaining the factors of migration but it margins when to analyze the significant implications to healthcare delivery mechanism and health outcomes for the source country. GJMEDPH 2015; Vol. 4, issue 3 1 Assistant Professor, Department of Social Work, (UGC Centre of Advanced Study), Faculty of Social Sciences, Jamia Millia Islamia (A Central University), New Delhi and Visiting Research Professor, School of Public Health, University of Minnesota, USA 2 Assistanr Professor, Department of Social Work, Aditi Mahavidyalaya, University of Delhi and Doctoral Fellow, Department of Social Work, (UGC Centre of Advanced Study), Faculty of Social Sciences, Jamia Millia Islamia (A Central University), New Delhi *Corresponding Author: Panneer Sigamani Assistant Professor, Department of Social Work, (UGC Centre of Advanced Study), Faculty of Social Sciences, Jamia Millia Islamia (A Central University), New Delhi and Visiting Research Professor, School of Public Health, University of Minnesota, USA sigamanip@jmi.ac.in Conflict of Interest—none Funding—none 2 www.gjmedph.org Vol. 4, No. 3 2015 ISSN#- 2277-9604 Reviews Recommendations The paper recommends with the strategic initiative requisition for the live data records to update the HRH situation in the country. The imperative need of additional HRH training, retaining and recruiting is essential for the health system. The country specific human resource policy is vital for the strengthening of the healthcare services and regularizing of movement of health professional within and out of the country. The study gives an insight on emerging concern towards the HRH movement and considers the consequences rationally on the public health system of the country. Conclusion The research paper results into giving an idea to understand the present scenario of HRH in India. Though the present HRH information system is generalized description of the number of health professionals registered with the respective councils. It does not explain the exact quantification of the extent of the HRH migration, even though it is common among the health professionals. It is important to establish relation among the variables of migration and its consequence to the health system. The need for developing greater understanding for the long term consequences of migration on the source country is essential factors to be analyzed. The study limited to the secondary data analysis on HRH migration.

SignificanceConvolutional 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.AimDevelop 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.ApproachWe 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.ResultsThe 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.ConclusionsWe demonstrate the effectiveness of our approach for more interpretable and reliable oral potentially malignant lesion and malignant lesion 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.

SignificanceEarly 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.AimTo reduce the class bias caused by data imbalance.ApproachWe 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.ResultsBy 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.ConclusionsExperimental 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.

SignificanceOral 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.AimTo develop a mobile-based dual-mode image classification method and customized Android application for point-of-care oral cancer detection.ApproachThe 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.ResultsWe 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.ConclusionsOur study demonstrates the effectiveness of a mobile-based approach for oral cancer screening in low-resource settings.